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Long before the gut microbiome was even a thing, humans knew that it is very important to be conscious of what we put in our bodies. 2,000 years ago, Greek philosopher Hippocrates proclaimed that, “All disease begins in the gut.

Many traditional cuisines and medical practices reflect that depending on geography, climate, and genetics of the people in the region, but it wasn’t until recently that their impacts on gut and general health was appreciated. Now, mainstream conversations by people like Dr. Rhonda Patrick and the countless new research initiatives in the field of the gut microbiome are examining the variables at play in dictating overall health.

But can it really control chronic health conditions like Type 2 Diabetes. Or more?

The Gut Microbiome: Unlocking the Secrets of Our Inner Ecosystem

In the last decade, our understanding of the gut microbiome—an intricate community of trillions of microorganisms residing in the human digestive system—has grown exponentially. Previously thought of as a passive player in digestion, researchers now recognize the microbiome as a pivotal factor influencing many aspects of human health, including metabolism, immune function, and even neurological health. As scientific advancements continue to shed light on the microbiome’s influence, the potential for personalized medicine and health interventions based on microbiome data becomes increasingly clear.

What is the Gut Microbiome?

The human gut microbiome consists of a variety of bacteria, fungi, archaea, and viruses that live symbiotically within the intestines. These microorganisms perform a wide array of functions crucial to human health, from breaking down complex carbohydrates and synthesizing essential vitamins to modulating immune responses and protecting against harmful pathogens.

The balance within this ecosystem, known as microbiota balance or homeostasis, is essential. Disruptions to this equilibrium, referred to as dysbiosis, have been linked to a wide array of diseases. For instance, dysbiosis is increasingly recognized as a key factor in metabolic diseases like type 2 diabetes and obesity, as well as in neurological conditions such as autism spectrum disorder (ASD).

The human gut microbiome is a complex ecosystem, and imbalances or dysfunctions in specific bacteria or enzymes can contribute to a wide range of health issues. Below are the top 10 bacteria and/or enzymes in the gut that are commonly associated with health problems:

1. Firmicutes (phylum of bacteria)

Role: Firmicutes are a major group of bacteria in the human gut microbiome, involved in the fermentation of dietary fibers and the production of short-chain fatty acids (SCFAs), which are beneficial for gut health.

Issues: An overgrowth of Firmicutes has been linked to obesity and metabolic disorders, as they may be more efficient at extracting energy from food, leading to increased fat storage.

2. Bacteroides (phylum of bacteria)

Role: Bacteroides help break down complex molecules like proteins and polysaccharides, contributing to digestion and the regulation of inflammation.

Issues: An imbalance between Bacteroides and other gut microbes can contribute to conditions like inflammatory bowel disease (IBD) and irritable bowel syndrome (IBS). A reduction in Bacteroides has also been associated with obesity.

3. Lactobacillus (phylum of bacteria)

Role: Lactobacillus species are known for their role in fermenting lactose into lactic acid, maintaining an acidic environment in the gut, and inhibiting pathogenic bacteria.

Issues: A deficiency in Lactobacillus can lead to digestive disturbances, like bloating and diarrhea, and may increase susceptibility to infections, particularly in individuals with compromised immune systems.

4. Clostridium difficile (species of bacteria)

Role: Clostridium difficile is a gut bacterium that can be beneficial when in balance with other microbes.

Issues: Overgrowth, often due to antibiotic use, can lead to severe gastrointestinal diseases such as antibiotic-associated diarrhea and colitis. It is responsible for causing inflammation and damage to the colon.

5. Escherichia coli (E. coli; species of bacteria)

Role: E. coli is normally found in small amounts in the gut, where it plays a role in digesting food and producing certain vitamins.

Issues: Certain pathogenic strains of E. coli, especially E. coli O157:H7, can cause severe infections, leading to food poisoning, diarrhea, and even kidney failure.

6. Enterococcus faecalis (species of bacteria)

Role: Enterococcus faecalis is part of the normal microbiome and plays a role in the breakdown of food.

Issues: When in excess, this bacterium can contribute to gut inflammation, and it has been associated with infections in the gut, urinary tract, and bloodstream, especially in people with compromised immunity.

7. Faecalibacterium prausnitzii (species of bacteria)

Role: This bacterium is a producer of butyrate, an SCFA that supports gut health by providing energy to colon cells and reducing inflammation.

Issues: A reduction in Faecalibacterium prausnitzii has been linked to inflammatory bowel diseases like Crohn’s disease and ulcerative colitis.

8. Ruminococcus (phylum of bacteria)

Role: Ruminococcus species are involved in the breakdown of complex fibers into simple sugars, playing a vital role in digesting plant material.

Issues: A lack of Ruminococcus can lead to digestive problems and impaired gut health. Imbalances in this group are often linked with conditions like IBS and obesity.

9. Methanobrevibacter smithii (species of Archaea)

Role: This microorganism is an archaeon that contributes to methane production in the gut by fermenting carbohydrates.

Issues: Excessive methane production has been associated with constipation and bloating. Elevated methane levels can slow intestinal transit, leading to symptoms such as abdominal pain, bloating, and irregular bowel movements.

10. Digestive Enzymes (e.g., Amylase, Lactase, Lipase)

Role: These enzymes are crucial for the digestion of carbohydrates (amylase), lactose (lactase), and fats (lipase).

Issues: Deficiencies in specific digestive enzymes can cause issues like lactose intolerance (lack of lactase), difficulty digesting starches (insufficient amylase), and fat malabsorption (low lipase). These deficiencies lead to bloating, gas, diarrhea, and other digestive disturbances.

[H4] Additional Notable Enzyme and Microbe Issues

Protease Deficiencies: Insufficient protease enzymes can lead to incomplete protein digestion, causing bloating, discomfort, and malabsorption of nutrients.

The Microbiome and Disease Correlations

Recent studies have revealed how the gut microbiome influences both metabolic and neurological health.

One of the most significant findings comes from the relationship between the microbiome and type 2 diabetes. A number of microbial species have been found to be more prevalent in people with diabetes, while others may protect against it by improving insulin sensitivity and metabolic function. Research shows that these microbes can influence inflammation, insulin resistance, and the gut-brain axis—highlighting the microbiome's pivotal role in regulating metabolism.

Similarly, the gut microbiome has also been implicated in autism spectrum disorder (ASD). Studies have shown that children with ASD tend to have distinct microbiome profiles compared to neurotypical children. Specific imbalances in gut bacteria may contribute to the gastrointestinal issues commonly seen in individuals with ASD, as well as affect behavior and cognitive development. Though more research is needed, the connection between gut health and neurodevelopment is becoming increasingly evident.

The Rise of Microbiome Testing and Personalized Dietsl

As understanding of the gut microbiome grows, so too does the demand for personalized health approaches. The boom in microbiome testing services, which provide individuals with insights into the composition of their gut flora, is a direct response to this increased awareness. These at-home testing kits collect stool samples, which are then analyzed for microbial composition. Companies like Viome and Tiny Health offer insights not only into the diversity of an individual’s microbiome but also provide tailored dietary and lifestyle recommendations aimed at restoring balance and improving overall health. For instance, Tiny Health focuses on optimizing infant gut health, while Viome provides personalized meal plans based on microbiome analysis, promising improved digestion and immune function.

This rise in microbiome testing has opened the door to personalized nutrition, where interventions are based not on generic dietary advice, but on the individual’s unique microbiome profile. Such customization has the potential to shift the approach from generalized treatment to more specific, data-driven strategies.

Gut microbiome-based supplements are becoming increasingly popular as people seek to improve digestion, immune function, and overall health. Many of these supplements are designed to support or restore the balance of beneficial bacteria in the gut. So much so that podcasts with large audiences, include The Joe Rogan Experience and Huberman Lab are getting sponsored by those, with a strong message of preventing illness, rather than treating it.

Here’s a list of some of the top gut microbiome-based supplements that are commonly used, including AG1, and a few others:

1. AG1 (formerly Athletic Greens)

Overview: AG1 is a popular all-in-one green powder supplement that includes probiotics, prebiotics, digestive enzymes, and other nutrients aimed at supporting gut health. It contains a mix of vitamins, minerals, antioxidants, and adaptogens.

Gut Health Benefits: The probiotics and prebiotics in AG1 help promote a healthy balance of gut bacteria, improve digestion, and boost the immune system. The blend of digestive enzymes also helps break down food more efficiently, supporting overall gut function.

2. Seed Daily Synbiotic

Overview: This supplement combines both probiotics and prebiotics, designed to promote digestive health, reduce inflammation, and improve gut microbiota balance.

Gut Health Benefits: Seed’s Daily Synbiotic contains 24 clinically studied probiotic strains and organic prebiotics, which support gut flora diversity and overall digestion. It has also been shown to promote a healthy gut lining, reduce bloating, and improve immune function.

3. Culturelle Daily Probiotic

Overview: Culturelle is a well-known brand that offers probiotics for general digestive health and immune support. It includes the strain Lactobacillus rhamnosus GG, one of the most widely researched probiotic strains.

Gut Health Benefits: This supplement is designed to balance gut bacteria, reduce symptoms of IBS, and support immune function. It also helps alleviate digestive discomfort such as bloating, diarrhea, and constipation.

4. Bio-K+ Probiotics

Overview: Bio-K+ offers a range of probiotic supplements, including capsules, powders, and fermented drinks. Their products contain a blend of three strains of probiotics (Lactobacillus acidophilus, Lactobacillus casei, and Lactobacillus rhamnosus).

Gut Health Benefits: Bio-K+ is designed to help restore the balance of gut microbiota after antibiotics, reduce inflammation, and improve gut health overall. It’s particularly effective for individuals experiencing digestive issues or antibiotic-induced dysbiosis.

5. Align Probiotics

Overview: Align is a popular probiotic supplement known for its use of the strain Bifidobacterium 35624. It is one of the most studied probiotic strains for digestive health.

Gut Health Benefits: Align helps to balance the gut microbiome, reduce bloating, and support overall gut health. It is particularly known for helping with IBS symptoms and has been shown to improve digestive regularity.

6. VSL#3

Overview: VSL#3 is a high-potency probiotic supplement that contains 8 different strains of bacteria, including Lactobacillus, Bifidobacterium, and Streptococcus species.

Gut Health Benefits: VSL#3 is often used in clinical settings for the management of IBS, IBD (inflammatory bowel disease), and ulcerative colitis. Its high concentration of probiotics helps to restore balance in the gut and reduces symptoms of digestive disorders.

7. Klean Probiotics (Klean Athlete)

Overview: Klean Athlete is a brand that offers supplements for athletes, including probiotics aimed at improving gut health and digestion.

Gut Health Benefits: Their probiotic supplement contains several strains that support digestion, reduce bloating, and enhance nutrient absorption. It is also designed to promote a healthy immune system, which is critical for athletes’ performance and recovery.

8. Renew Life Ultimate Flora Probiotic

Overview: This probiotic supplement contains 50 billion CFUs (colony-forming units) per capsule, including multiple strains such as Lactobacillus and Bifidobacterium.

Gut Health Benefits: Ultimate Flora is designed to support digestive health, reduce bloating, and improve regularity. The high CFU count makes it a potent option for addressing more severe gut issues like constipation and irregular bowel movements.

9. Dr. Formulated Probiotics by Garden of Life

Overview: Dr. Formulated Probiotics offers a wide variety of probiotic supplements, including those aimed at promoting gut health, digestive comfort, and immunity.

Gut Health Benefits: These probiotics contain a mix of strains like Bifidobacterium and Lactobacillus, as well as prebiotics to support the growth of beneficial bacteria. They help restore gut flora balance and improve digestive issues like gas, bloating, and irregularity.

10. Hyperbiotics Pro-15

Overview: Hyperbiotics Pro-15 is a high-potency probiotic supplement that contains 15 different strains of probiotics to support gut health and improve digestive function.

Gut Health Benefits: This supplement is designed to support a healthy gut microbiome, improve nutrient absorption, and reduce bloating and discomfort. It is often recommended for people with digestive imbalances or those looking to improve their overall gut health.

Other Notable Supplements

Prebiotics: In addition to probiotics, prebiotic supplements like Inulin and FOS (fructooligosaccharides) are designed to nourish beneficial gut bacteria and promote gut health.

Digestive Enzymes: Supplements containing enzymes like amylase, protease, lipase, and lactase can assist with the digestion of carbohydrates, proteins, and fats, helping to alleviate bloating, gas, and digestive discomfort.

Supplements, Biotech, and the Future of Metabolic Health

The growing field of microbiome-based therapies extends beyond testing to a burgeoning market in probiotics, prebiotics, and other supplements designed to optimize gut health. These supplements aim to improve microbiome diversity, which, in turn, can impact metabolic processes. For example, specific strains of probiotics are now being investigated for their potential to alleviate insulin resistance and improve metabolic health, which may help address the growing prevalence of type 2 diabetes and obesity.

The biotech industry is poised to reap significant rewards from this shift in focus from symptom treatment to addressing metabolic imbalances at their root. Companies like Seed Health, which manufactures probiotics for metabolic and gut health, are positioning themselves as key players in a multibillion-dollar industry. With their recent exploration of a potential $1 billion sale, they highlight the profitability of microbiome-related products.

This new focus on metabolic issues has sparked debates, particularly surrounding the categorization of obesity. For years, obesity was predominantly treated as a genetic disorder, but emerging research is pushing for a reframing and recognition that metabolic dysfunction, particularly driven by gut health, plays a crucial role. The approval and growing use of GLP-1 agonists, such as Ozempic, have further solidified the importance of metabolic health as a key factor in weight management.

The global gut health supplement industry has experienced significant growth in recent years, driven by increasing consumer awareness of the importance of gut health and its impact on overall well-being.

Market Size and Growth Projections

2023 Estimates: The global gut health supplement market was valued at approximately USD 12.3 billion in 2023.

2030 Projections: By 2030, the market is projected to reach around USD 22.6 billion, reflecting a compound annual growth rate (CAGR) of 8.9% from 2023 to 2030.

2032 Projections: Another analysis estimates the market will grow to USD 3.6 billion by 2032, with a CAGR of 22.5% during the forecast period from 2024 to 2032.

The growth of the gut health supplement market is influenced by several factors:

Consumer Awareness: There is a growing recognition of the gut microbiome's role in overall health, leading to increased demand for supplements that support digestive health.

Health Trends: Rising incidences of digestive disorders and gastrointestinal issues have prompted consumers to seek preventive healthcare solutions, including gut health supplements.

Product Innovation: Advancements in supplement formulations, such as personalized probiotics and prebiotics, are attracting consumers interested in tailored health solutions.

How Gut Microbiome Research Is Conducted

The complexity of the microbiome and its diverse interactions with human health has made research in this field challenging. However, a variety of sample types, sophisticated laboratory methods, protocols , and digital tools are being used to uncover the mysteries of the gut ecosystem.

Sample Types: Stool samples remain the most commonly used sample type for microbiome analysis, as they directly reflect the composition of gut bacteria. However, saliva, urine, and even breath tests are also being explored as potential sources of microbial information.

Methodology: Advanced techniques, such as 16S rRNA gene sequencing and shotgun metagenomics, are essential tools for identifying and cataloging the various microorganisms in a sample. These techniques enable researchers to map the microbial communities and gain a better understanding of their genetic and functional profiles. Adherence to standard operating procedures (SOPs) ensures that data is reproducible and reliable, a key aspect of microbiome research.

Environmental Health and Safety (EHS): Rigorous EHS protocols are critical when handling any biological samples. In the laboratory, strict guidelines are followed to prevent contamination, ensure researcher safety, and maintain sample integrity.

Digital Tools: The use of electronic lab notebooks (ELNs) or all-in-one Scientific Management Platforms (SMPs) is integral in microbiome research, as they allow for accurate and accessible documentation of experimental procedures, observations, and results. These digital tools streamline data management, enhance collaboration, and improve the overall efficiency of research.

Centralizing Research Data and AI’s Role in Microbiome Studies

As microbiome research grows in scope and complexity, centralizing research data is becoming increasingly important. Platforms like the Human Microbiome Project have paved the way for large-scale data collection and integration, facilitating collaboration and the sharing of findings across the scientific community.

The application of artificial intelligence (AI) in microbiome research is a game-changer. AI-powered tools can analyze vast amounts of data quickly, uncover hidden patterns, and generate predictive models for how different microbial populations influence human health. This has the potential to revolutionize personalized medicine, enabling tailored therapies based on an individual’s microbiome profile.

AI and ML in Gut Microbiome Research

AI, machine learning (ML), and large language models (LLMs) are playing an increasingly important role in the field of gut microbiome research. These technologies help process and analyze large, complex datasets, which is essential in microbiome research due to the vast diversity of microbial communities and the complexity of interactions within the gut. Below is an overview of how these technologies are being used, and some key tools and platforms to watch out for in this space.

1. Data Analysis and Pattern Recognition

Role: AI and ML algorithms are particularly useful in identifying patterns and correlations in large datasets generated from microbiome sequencing, metabolomics, and clinical data. The ability to quickly process and analyze thousands or millions of microbial data points allows researchers to identify specific microbes or microbial community structures associated with health conditions like obesity, diabetes, or autism.

Techniques Used: Common ML techniques applied in microbiome research include supervised learning (e.g., classification algorithms to identify microbial markers for disease), unsupervised learning (e.g., clustering to identify patterns in microbial communities), and deep learning (e.g., convolutional neural networks for image-based microbiome data like microscopy images).

Example: ML can be used to predict which microbial strains are most beneficial for a given patient based on their microbiome profile, clinical history, and environmental factors.

2. Predicting Health Outcomes

Role: AI-driven predictive models are being developed to predict health outcomes based on gut microbiome profiles. By analyzing large datasets from clinical trials and patient cohorts, AI can identify biomarkers (specific bacteria, genes, or metabolites) that correlate with the onset or progression of diseases, including gastrointestinal disorders, metabolic conditions, and even neurological diseases like autism.

Example: Machine learning algorithms can predict the risk of developing conditions like Type 2 diabetes or Crohn’s disease based on the microbial composition of the gut, helping with early diagnosis or preventive measures.

3. Personalized Medicine and Microbiome-Based Therapeutics

Role: AI models are being used to design personalized microbiome-based therapies. This can involve creating targeted probiotics, prebiotics, or even dietary recommendations based on an individual’s microbiome profile. By analyzing the gut microbiome data and considering genetic and environmental factors, AI can help tailor interventions to the individual, offering a more effective and personalized approach to treating conditions related to gut health.

Example: Personalized recommendations for microbiome-modulating interventions (like probiotics or dietary changes) are being designed using AI models that analyze a patient’s unique gut microbiome and lifestyle factors.

Large Language Models (LLMs) in Microbiome Research

LLMs, such as OpenAI’s GPT models and others like BERT, have found applications in microbiome research, particularly in processing scientific literature and generating insights from vast amounts of data.

1. Literature Mining and Data Extraction

Role: LLMs are particularly adept at sifting through vast amounts of scientific literature and extracting relevant insights. In microbiome research, these models can help identify emerging trends, summarize key findings from thousands of papers, and generate hypotheses by analyzing published studies on microbiome-disease relationships.

Example: LLMs can be used to scan academic databases for new microbiome-related studies, identify novel links between gut microbiota and diseases, and suggest potential new areas for investigation.

2. Natural Language Processing (NLP) for Data Interpretation

Role: LLMs can process and interpret clinical notes, survey data, or patient interviews, extracting relevant microbiome-related insights. This is especially helpful when combining qualitative data from different sources (e.g., patient-reported outcomes and microbiome data).

Example: In clinical trials, LLMs can help interpret subjective data (e.g., patient surveys on gut symptoms) and correlate it with objective microbiome data to improve understanding of how specific microbial communities affect disease symptoms.

Key AI, ML, and LLM Tools for Gut Microbiome Research

Several (though not all) computational tools and platforms leverage AI, ML, and LLMs to advance microbiome research. If you’re doing microbiology research, here are a few you’ve likely heard of.

1. QIIME 2

Overview: QIIME 2 is a powerful, open-source bioinformatics platform that uses machine learning to analyze microbiome data. It helps researchers identify microbial species, track changes in microbiome composition over time, and correlate these changes with health outcomes.

AI/ML Role: QIIME 2 supports various ML techniques for microbial community analysis, including clustering, dimensionality reduction, and taxonomic classification.

2. MetaPhlAn

Overview: MetaPhlAn (Metagenomic Phylogenetic Analysis) is a tool used for profiling microbial communities based on metagenomic sequencing. It helps identify microbial taxa within a sample, providing valuable insights into the composition of the microbiome.

4. Fungal Community Analysis (FUNGuild)

Overview: FUNGuild is a Python-based tool used to analyze fungal communities in the microbiome.

5. DeepMicro

Overview: DeepMicro uses deep learning (specifically, autoencoders) to turn high-dimensional microbiome profiles into simpler, more useful forms. These simplified versions are then used to build accurate disease prediction models..

• AI/ML Role: By using deep learning techniques, DeepMicro can uncover complex relationships between microbiome profiles and diseases, providing predictive analytics and actionable insights.

Occupational Hazards in the Gut Microbiome Field

In the field of gut microbiome research, there are several occupational hazards that researchers and laboratory personnel may encounter due to the nature of the work involved. These hazards can be physical, biological, or related to the management of large volumes of data and complex experimental workflows.

Take a look at the primary risks and how digital tools like eLabNext, an Electronic Lab Notebook (ELN) platform, and SciSure, the first Scientific Management Platform (SMP) can mitigate these risks and enhance lab safety and efficiency.

1. Biological Hazards

Risk: Microbiome research often involves the handling of human or animal biological samples, including stool, saliva, or blood. These samples may contain pathogens such as viruses, bacteria, and fungi, which pose a potential health risk to laboratory staff if not handled correctly.

Mitigation: Proper containment and sterilization protocols must be in place to prevent exposure to infectious agents. Lab personnel should also wear appropriate personal protective equipment (PPE), such as gloves, lab coats, and face shields.

2. Chemical Hazards

Risk: Gut microbiome research frequently uses chemicals in experimental procedures, including reagents for DNA extraction, PCR, and sequencing. Many of these chemicals, such as ethanol, formaldehyde, and solvents, can be hazardous to health if they are not handled with care.

Mitigation: Clear labeling of chemicals, safe storage practices, and the use of fume hoods and proper PPE can help prevent chemical exposures.

3. Ergonomic Hazards

Risk: Laboratory work can often involve repetitive tasks such as pipetting, handling small instruments, and sitting for extended periods during data analysis. These tasks can lead to musculoskeletal disorders like carpal tunnel syndrome or back pain.

Mitigation: Ergonomic workstations, adjustable chairs, and tools designed to reduce repetitive strain are essential for minimizing physical stress in the lab.

4. Cross-Contamination of Samples

Risk: In microbiome research, the risk of cross-contamination between samples is a significant concern, especially when working with cultures, DNA extraction, and sequencing. Cross-contamination can result in inaccurate data and misinterpretation of results.

Mitigation: Rigorous lab protocols, such as using separate workstations for different stages of sample preparation, and regular cleaning of equipment, can help minimize contamination risks.

5. Data Management and Accuracy

Risk: As microbiome research generates massive amounts of data, managing, organizing, and ensuring the accuracy of this data is a key challenge. Poor data management can lead to errors, inconsistencies, and data loss, which can derail important research and lead to inaccurate conclusions.

Mitigation: Proper digital tools are essential for managing large datasets, tracking experiments, and ensuring data integrity.

How SciSure, the First Scientific Management Platform, Can Fix These Issues

1. Enhancing Data Management and Accuracy

• eLabNext and SciShield’s platform, SciSure provides a digital platform for researchers to record and track all experimental details in real time, from sample collection and preparation to data analysis. By eliminating the reliance on paper-based records, SciSure reduces the risk of data loss, human error, and illegibility.

Feature Benefit: Researchers can access a fully centralized, searchable, and organized digital record of their experiments, ensuring that all data is consistent, accurate, and easily retrievable for future analysis or reporting.

2. Minimizing Cross-Contamination Risks

• By integrating standardized workflows and SOPs (Standard Operating Procedures), SciSure ensures that the handling of samples is done according to the best practices, reducing the chances of contamination. Researchers can input and track protocol details, such as equipment cleaning and sterilization steps, directly into the system, which helps maintain a clean and safe work environment.

Feature Benefit: The system allows for the integration of safety checklists and automated reminders, so lab personnel follow correct procedures at every step of the experiment.

3. Ensuring Compliance and Safety

SciSure integrates EHS (Environmental, Health, and Safety) protocols into its digital workflows. It helps ensure that labs comply with regulatory guidelines for biological and chemical hazards. Researchers can log safety measures such as PPE use, waste disposal protocols, and equipment sterilization directly into the ELN.

Feature Benefit: These digital tools reduce the risk of accidental exposure and ensure that researchers are always adhering to safety procedures. eLabNext also keeps a record of compliance to facilitate audits and inspections.

4. Improving Ergonomics and Work Efficiency

• By digitizing the process of experimental design, sample tracking, and data collection, SciSure reduces the time spent on manual tasks such as paperwork and data entry. This allows researchers to focus more on the scientific aspects of their work and less on administrative duties, potentially reducing stress and strain from repetitive tasks.

Feature Benefit: eLabNext's platform is accessible from any device, allowing researchers to input data directly from the lab bench or work remotely. This flexibility can help alleviate the physical demands on lab personnel.

5. Supporting Collaboration and Communication

• SciSure provides a platform for real-time collaboration among research teams, both within the laboratory and across different locations. Researchers can share data, protocols, and notes instantly, helping to streamline communication and avoid delays caused by physical meetings or paper records.

Feature Benefit: Improved collaboration not only accelerates research but also enables more accurate and efficient problem-solving in the event of unexpected issues, such as sample contamination or data inconsistencies.

6. Data Security and Backup

• With SciSure, all experimental data is stored securely in the cloud, offering reliable data backup and minimizing the risk of data loss. Since microbiome research generates large amounts of high-value data, ensuring its safety is critical for long-term research progress.

Feature Benefit: Automated data backups and encryption ensure the protection of sensitive research data, reducing the likelihood of security breaches or accidental deletions.

Conclusion

The rise of microbiome research presents a new frontier in understanding and managing human health. As more is understood about the gut microbiome’s influence on diseases like type 2 diabetes, autism, and obesity, the potential for personalized therapies and interventions grows exponentially. With the support of cutting-edge research tools, centralized data systems, and AI, the future of microbiome-based health interventions promises not only to treat symptoms but to address the root causes of metabolic dysfunctions, offering hope for more effective, long-term solutions to some of the most pressing health challenges of our time.

To learn how SMPs can accelerate your research, lab operations, and safety, contact us here.

ELN screenshot
Digitalization

The Future of Gut Health: How Digital Tools Are Leading the Way

With the support of digital tools and AI, the future of microbiome-based health interventions promises to be bright. Learn more.

eLabNext Team
Zareh Zurabyan
|
5 min read

This is not a game... People's lives are on the line.

In labs around the world, risk management is still too often treated as a checkbox—a compliance form, a safety poster, a door sign, or a training module that may or may not have been completed. But from where I sit, and especially within context of the most significant pandemic in modern history, the traditional definition of ‘risk management’ is dangerously narrow. And dangerously outdated.

Risk starts with quite simply a lack of a digital record of what experiments are being performed, which samples are used, and what protocols were followed. Imagine if a physician treating you was unable to locate your medical history, was unable to produce digital clinical notes, and could not look up what medications were prescribed?  In modern labs, the ability to reproduce research findings is critical, and the risk of losing research is a major reason why drugs on average take 10-15 years to develop with an up to 90% failure rate1.

Far beyond reproducible research, risk in scientific environments is extremely high stakes. The consequences of a single misstep can be severe, far-reaching, and permanent. It’s not just about whether your audits are in order or if your chemicals are correctly labeled. Misunderstanding and mishandling of organizational risk management can yield costly lawsuits. Equipment failures could halt critical research; a piece of equipment left unmonitored could spoil samples and put the health and safety of scientists and the quality of experiments at risk. A single inventory error (especially with hazardous chemicals) can lead to an uncontained fire at worst or a citation from a local fire department at best. And it’s about the regulatory and reputational fallout that follows, jeopardizing not just the science, but the scientists and the population depending on it.

The reality, unfortunately, is that most scientific research organizations are underprepared to address organizational risk, holistically. But it’s not due to carelessness—it’s because they’re relying on a patchwork of poorly integrated point solutions that do not connect with one another. Systems and data become fragmented, oversight slips, and risk multiplies. And when something does go wrong, organizations lack the capabilities to respond.  

At SciSure, we believe that needs to change. And fast. Because when your infrastructure can’t support safe, connected, and reproducible science, it’s not just a person in a lab that is at risk. It can and will impact entire organizations.

The expanding definition of organizational risk in the lab

For many institutions, “risk management” still begins and ends with compliance—making sure safety data sheets are filed, audits are passed, and training is up to date. All important. But that narrow view misses the wider scope of organizational risk that organizations face every day.

Organizational risk can result in not only regulatory fines or failed inspections, but operational breakdowns, reputational damage, intellectual property loss, and even legal liability. These aren’t abstract threats—they’re real consequences that emerge when your systems can’t keep up with scientific complexity.

Imagine a promising discovery lost inside of a paper notebook that leaves with a departing researcher. A mislabeled chemical triggering a safety incident. A training lapse that results in an unqualified person operating high-risk equipment or mishandling hazardous chemicals.  Imagine a safety eye wash or shower in a lab that is not turned on for years or inspected regularly? These scenarios are common failure points in labs running on disconnected systems that are not focused on holistic organizational risk management.

In labs around the world, risk management is still too often treated as a checkbox—a compliance form, a safety poster, a door sign, or a training module that may or may not have been completed. But from where I sit, and especially within context of the most significant pandemic in modern history, the traditional definition of ‘risk management’ is dangerously narrow. And dangerously outdated.

  • Wasted research effort, when poor systems prevent illumination of the research occurring in real time, informing speedy go/no-go decisions on unviable projects.
  • Lawsuits stemming from irreproducible research, missing digital records, or IP ownership disputes.
  • Fines for inadequate reporting or noncompliance with fire codes, biosafety rules, and local regulations.
  • Audit failures that stall funding, delay research, or expose gaps in oversight.
  • Fire hazards, from mislabeled or misplaced chemicals and incompatible storage.
  • Inventory risks, including missing samples, spoiled materials, and even the disappearance of dangerous substances.
  • Untrained personnel using high-risk equipment or performing hazardous protocols.
  • Equipment breakdowns due to missed maintenance or poor oversight.
  • Biosafety incidents—as the world was reminded during COVID—that can escalate into public health emergencies.
  • Delayed lab permits due to poor documentation or lack of operational readiness.
  • Manual data errors in spreadsheets that compromise data integrity—or worse, result in lost discoveries.
  • Paper-based records that vanish with staff turnover, or are literally recycled with critical insight inside.

These are not rare edge cases. They’re common, costly, and often preventable failures that emerge when labs operate without centralized, integrated systems, focused on delivering results while minimizing risk.

Beyond passing inspections, organizational risk management is about protecting your science, your people, and your future. In a world where a single mistake can lead to reputational damage, legal exposure, or public health consequences, scientific organizations must think bigger—and act sooner—when it comes to mitigating organizational risk.

Why your systems are your first line of defense

You can’t manage what you can’t see. And when your lab’s infrastructure is built on disconnected systems, what you can’t see can hurt you.

Risk often takes root in operational blind spots, such as missed equipment checks, untracked chemicals, expired certifications, mislabeled samples, and out-of-date inspections. These aren’t caused by carelessness, but by architecture: the fractured, bolt-on infrastructure that’s become the norm in too many labs fail to illuminate the precise data required to assess and mitigate organizational risk.

That’s why we built something fundamentally different: the SciSure Scientific Management Platform (SMP). It brings together every critical layer of lab operations—health and safety, inventory, training, equipment, and research data—into a single, integrated ecosystem. No more bouncing between disconnected systems or relying on workarounds. With the SMP, labs operate from one central source of truth: a shared home base where scientists, safety officers, and leadership stay aligned, informed, and in control.

This connected infrastructure mitigates organizational risk in three powerful ways:

  1. It improves visibility. Lab managers, Principal Investigators, EHS teams, Lab Operations, and Senior Leadership can see what’s happening across every lab in real time. Whether it's a flagged inspection, a chemical storage issue, a missed training deadline, or simply an inventory of people, places, and hazards, nothing is hidden.
  2. It strengthens traceability. From procurement through to publication, every item and action is digitally logged and re-producible. Inventory is auto-classified. Experiments are linked to protocols. Data is preserved, and accountability is built in.
  3. It standardizes safety and compliance. Training is recorded in-platform, tied directly to user roles and workflows. Chemical inventory management is not buried but automated instead. Reporting and audit readiness becomes part of the daily routine, not a last-minute scramble.

Because no two organizations or labs are exactly alike, the SMP is built to evolve with your organization’s needs. With open application programming interfaces (APIs) and seamless custom integration capabilities, it connects with your existing tools and infrastructure, maximizing flexibility making your organization future-proof and responsive as new technologies emerge.

Intelligence only works if the infrastructure does

Centralizing your tools and data lays the groundwork for what comes next. As artificial intelligence (AI) and machine learning become practical realities in scientific labs, systems need more than connectivity—they need clarity. And that starts with clean, consistent, centralized data to combat data fragmentation and siloed systems.

Without clean data, even the most sophisticated AI-powered systems are limited, and can introduce new risks instead of solving them. That’s why integrated digital lab infrastructure isn’t just a technical upgrade, it’s a critical enabler of intelligent, risk-aware operations.

The SciSure Scientific Management Platform delivers that foundation. All operational data—from inventory to inspections, training records to equipment logs—flows through a single platform. That means labs can maintain visibility into research and experiments, enforce safety protocols, trace activity across the research lifecycle, and stay audit-ready by default.

With that foundation in place, your lab can be future-ready for AI integration, unlocking the potential to:

  • Spot patterns in compliance issues across locations or teams
  • Predict safety risks based on historical incident trends
  • Assist with faster classification and inventory management using image recognition
  • Prioritize alerts based on pattern recognition and historical incident data

These aren’t just productivity wins—they’re risk mitigators. AI has the potential to be a proactive partner in lab safety, reproducibility, and decision-making—but only if the infrastructure is ready for it.

From reactive compliance to proactive stewardship

Many labs treat compliance as a periodic task—something to prepare for in advance of an audit, not something embedded in day-to-day operations. But that mindset is changing fast.

Regulatory scrutiny is intensifying across the globe. In May 2025, an executive order in the United States, “Restoring Gold Standard Science”, expanded federal oversight of research labs, public and private alike. Local agencies are also stepping up: fire departments now routinely require up-to-date chemical inventories, and biosafety protocols are under sharper review in the wake of COVID-era lessons.

In this climate, ticking boxes isn’t enough. Labs are expected to demonstrate continuous oversight, enforceable safeguards, and digital traceability. This is where the conversation shifts from compliance to stewardship. Because the real question isn’t “can we pass an audit?” It’s “can we guarantee the integrity of our science—and the safety of those doing it?”.

Stewardship means knowing your risks before an inspector points them out. It means building infrastructure that protects your science as carefully as you pursue it. And it means recognizing that organizational risk doesn’t just threaten lab operations, it also threatens public trust.

Resilient science starts with the right systems

Organizational risk isn’t theoretical. It’s operational, financial, and sometimes existential. And in today’s labs, it’s growing.

Labs can’t afford to be reactive. The risks are too great, and the consequences too far-reaching. Whether it’s a safety incident, a lost dataset, or a delayed approval, every gap in oversight undermines not just your research but the trust that research depends on.

The answer isn’t more tools. It’s better infrastructure.

At SciSure, we believe the future of science depends on systems that do more than capture data—they protect it. Systems that don’t just enable research, but safeguard it. That’s why we built the SciSure Scientific Management Platform from the ground up for the people who need it—to give labs the foundation they need to work smarter, move faster, and reduce risk at every level.

Because when the stakes are this high, the infrastructure behind your science matters as much as the science itself.

Ready to take a proactive approach to organizational risk?

Let’s talk. SciSure is here to help you build a lab environment that’s safer, smarter, and built for the future.

1 Sun, D., Gao, W., Hu, H., & Zhou, S. (2022). Why 90% of clinical drug development fails and how to improve it? Acta Pharmaceutica Sinica B, 12(7), 3049–3062. https://doi.org/10.1016/j.apsb.2022.02.002

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Security & Compliance

Organizational Risk in Scientific Research: It’s Bigger Than You Think

Learn how SciSure's SMP delivers reproducible research and reduces organizational risk through technology built specifically for practicing safe and compliant science.

eLabNext Team
Philip Meer
|
5 min read

What if your digital lab actually made your life easier?

Digital transformation is supposed to make labs more efficient. More compliant. More connected. But too often, it ends up doing the opposite.

Instead of solving problems, it adds complexity—another login, another workflow, another tool that doesn’t quite fit. Scientists are burdened by additional admin. Lab managers lose visibility. Safety is treated as an afterthought. The promise of digitalization gets lost in a maze of disjointed systems.

But it doesn’t have to be that way.

Done right, a digital lab delivers not just operational excellence, but operational simplicity. It’s a space where science, safety and operational oversight work in sync—where systems support your scientists, not slow them down. That’s the kind of lab we’re building at SciSure: one that’s not just digital for digital’s sake, but genuinely easier to run, manage, and grow.

That’s what this article is about: how to get digital lab transformation right. Read on for some practical tips to help you avoid the common pitfalls, build buy-in, and create a platform your entire team actually wants to use.

Start with people, not platforms

Digital transformation isn’t just a tech decision—it’s a culture shift. And the success of any new system depends on how well it fits the people expected to use it. That’s why the smartest digital lab projects don’t start with a software demo. They start with a conversation.

If your scientists are already juggling ten systems, another tool won’t feel like help. If lab managers don’t see how change will simplify compliance or increase visibility, adoption stalls. And if EHS teams feel excluded, safety is destined to remain an afterthought.

Before anything is rolled out, get in the room with your scientists, lab ops, lab managers, and EHS teams. Ask where things are breaking down. Where are they duplicating effort? What slows them down or stresses them out? What would “better” actually look like in their day-to-day? These are the insights that should shape your implementation—not just a list of features, but a real-world map of needs, workflows and frustrations.

At SciSure, this is exactly how we approach transformation. Our Scientific Management Platform (SMP) is designed to adapt to the way labs already work. Whether it’s scientists logging experiments, EHS teams tracking compliance, or managers overseeing resources, everything lives in a shared environment, tailored to each user’s role.

Because when your system reflects your team’s reality, adoption isn’t something you have to push—it’s something that just makes sense.

Start small, prove fast

One of the most common mistakes in digital lab transformation is trying to roll out everything too fast.

Eager to modernize, labs often aim for full rollout from day one—digitizing every workflow, onboarding every team, and expecting instant adoption across the board. But when everything changes at once, even the best system can feel like disruption.

A more effective approach is to start with a single, meaningful use case. Something high-friction but high-impact: maybe it’s streamlining sample traceability, tracking chemical inventory, or embedding safety training into daily workflows. Pick a problem your team cares about. Solve it well. Then show the results. Crawl. Walk. Jog. Run.  

Define your success measures up front: e.g., reducing errors by 50% or cutting approval time by 30%. Roll out early to a target group, celebrate that win, measure impact, then use it to fuel the next phase. This approach builds confidence. It gives scientists and lab managers a reason to engage. And it creates space for feedback before scaling further.

At SciSure, we’ve built our Scientific Management Platform to support this phased approach. Labs can begin with targeted capabilities—whether it’s ELN, LIMS, or EHS—and add others as needs evolve. Every success story becomes a stepping stone, not a silo.

Choose tools that fit the way you work

No two labs are alike. Yet too often, software treats them as if they are.

Rigid systems expect labs to fit their mold—forcing teams to follow workflows that don’t match their reality and use disconnected tools that were never built to work together. That’s when the friction starts: duplicated data, clunky workarounds, and mounting frustration.

The right digital lab platform should do the opposite. It should meet your team where they are, then evolve with you over time.

That’s why the SciSure SMP brings together ELN, LIMS, EHS, and integrations into one unified environment—while staying flexible enough to adapt to your lab’s reality. You can configure workflows, define access by role, and phase in capabilities at your own pace.

And when it comes to integration, we don’t believe in locking you into a closed ecosystem. Through our developer hub and connected vendor marketplace, SciSure supports custom integrations via open Application Programming Interfaces (API) and Software Development Kits—so your instruments, software, and third-party services can all connect natively. Whether it’s environmental sensors, procurement platforms, or freezer monitoring tools, data flows directly into the system, no copying, pasting, or reformatting required.

Because transformation doesn’t mean disruption. It means making your digital lab feel like home—familiar, connected, and designed around the way you work.

Don’t add safety later—build it in from the start

In too many labs, safety still feels like something you do at the end—like buckling your seatbelt after you’ve arrived. It’s treated as a compliance chore, not a core part of scientific work. And EHS professionals are often seen as the enforcers, not the enablers. That mindset has to change.

In a truly modern digital lab, safety isn’t something you remember at the last minute. It’s already there—woven into daily workflows, embedded in routine actions, and visible to every stakeholder without extra effort.

That’s the shift SciSure enables. Our platform integrates EHS directly into the systems scientists already use—no jumping between tabs, no hunting for forms, no more disconnected checklists. Risk assessments are linked to protocols. Safety training is automatically assigned, tracked, and renewed. Chemical usage is logged in real time. SDS records are accessible in a click.

Inspections, audits, and incident reporting are no longer isolated events—they’re ongoing processes made simple through automation and role-based visibility. Every task completed contributes to a safer, more compliant environment, without adding extra steps.

Because when safety is part of the flow, it’s not something you chase. It’s something you sustain.

Plan for change—not just rollout

Digital transformation isn’t a one-time switch. It’s a shift in how your lab works, and that shift needs to be nurtured.  

Too many projects stumble after launch because change management was an afterthought. Teams weren’t trained. Ownership wasn’t clear. Feedback wasn’t captured. And what started as innovation became just another system people work around. To avoid that fate, build change into your plan from the start.

Assign internal champions. Define who owns which workflows. Create space for training—not just upfront, but ongoing. And choose a platform that grows with you, not one that locks you into rigid workflows.

At SciSure, we designed our platform to evolve alongside the labs that use it. That means in-product guidance, dedicated onboarding support, and capabilities that can be phased in as your needs change. From our developer hub to our vendor marketplace, everything is built to support connection and continuous improvement—not complexity for complexity’s sake.

Change is only hard when you’re going it alone. With SciSure, you’re not.

Build the lab your team deserves

Most scientists didn’t choose this career to spend their days clicking through disconnected systems, chasing down compliance records, or copying data between spreadsheets. But somewhere along the way, that became the norm. It doesn’t have to stay that way.

A successful digital lab isn’t defined by how many point solutions it has—it’s defined by how well its systems work for the people inside it. When your systems are connected, your workflows are clear, and your safety processes are seamless, everything changes. Scientists get time back. Lab managers get real visibility. EHS teams stop chasing problems and start preventing them.

That’s what transformation looks like when it’s done right. And that’s the kind of lab SciSure’s SMP was built to support.

Because at the end of the day, digital tools should help you do what you set out to do in the first place: focus on the science, move faster with confidence, and build something that lasts.

Ready to unlock operational simplicity in your lab?

Let’s talk. SciSure’s Scientific Management Platform is built to simplify operations, unite your teams, and bring safety, science, and oversight into one connected system.

Get in touch to see how we can help you build a digital lab that actually works for your people.

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Digitalization

Digital Lab Transformation Done Right

Explore how to build a successful digital lab, without the pitfalls. Practical tips on rollout, adoption, integration, and making transformation stick.

eLabNext Team
Jon Zibell
|
5 min read

Most modern labs assume their lab data is in good shape. After all, they’re using digital systems—LIMS, ELNs, instrument software, cloud storage. Surely that means data integrity is covered?

In reality, most labs are handling an array of point solutions and digital tools that don’t connect. Data gets siloed. Workflows get fragmented. And what looks like a digital lab on the surface often hides serious gaps underneath—gaps that can lead to inconsistencies, errors and missing audit trails.

That’s a big issue. Because in science, trust means everything. Whether you’re publishing results, sharing data with collaborators, or building evidence for a regulatory submission, everything rests on confidence in your lab data.

If you’re still juggling disconnected digital solutions, your data might be at risk—not because your team is doing anything wrong, but because your systems can’t keep up. In this article, we’ll unpack five often-overlooked threats to data integrity, and offer practical steps any lab can take to tighten control, reduce risk and protect the reliability of its science.

1. Disconnected tools, fragmented lab data

Many labs are running on a patchwork of digital systems: a LIMS for sample tracking, an ELN for experiment notes, an instrument interface for results, and a separate system for approvals or QC. Individually, these tools do their job. But together? They often don’t.

Without integration, lab data ends up split across platforms. Teams copy and paste between systems, re-enter the same information multiple times, or rely on offline workarounds to bridge the gaps. That’s when the cracks start to show.

Inconsistent records. Misaligned timestamps. A missing version of a file just when an auditor needs it. These issues aren’t the result of poor practice—they’re symptoms of poor connectivity. When your tools don’t talk to each other, your data doesn’t flow. And when data doesn’t flow, it’s difficult to trust.

Our recommendation:

Invest in a connected platform that unifies your core systems—LIMS, ELN, EHS and integrations—into a single system where data flows seamlessly. SciSure’s Scientific Management Platform (SMP) is built to do exactly that, helping labs close data gaps and maintain full oversight of their data from end to end.

2. Uncontrolled access undermines accountability

In many labs, access control is still an afterthought. Shared logins. Generic passwords. Local files saved to desktops or emailed between colleagues. It’s workable—but it’s risky.

Without proper user permissions and audit trails, you can’t see who changed what, when, or why. And when something goes wrong—a result looks off, a file is missing, or two versions conflict—you have no reliable way to trace the issue. It’s not just inconvenient. It undermines confidence in your lab data and creates real risk during audits, QA reviews or disputes.

This isn’t just a security issue. It’s a data integrity issue. And it can catch even well-run labs off guard during audits or investigations.

Our recommendation:

Implement role-based access controls across your entire lab environment. Ensure every user action is logged and traceable, with clear audit trails for edits, approvals and data handovers. SciSure’s SMP is designed with granular permission layers and built-in traceability—so your lab data tells a clear story, from creation to completion.

3. Audit trails that fall apart under pressure

It’s easy to assume your lab is audit-ready—until someone asks for proof. Too often, audit trails are partial, scattered, or dependent on individual knowledge. Files saved under ambiguous names. Data approvals managed via email. A key document sitting on someone’s desktop who left months ago.

When auditor, collaborators, or QA teams ask to see how or when a decision was made, your lab data should speak for itself. If you can’t produce a clear trail, you risk non-compliance, project delays, or even the loss of regulatory approval.

Audit gaps aren’t always obvious. They creep in through informal processes, disconnected tools, and the assumption that someone else has the record.

Our recommendation:

Build audit-readiness into your daily workflows—not as an afterthought, but as a default. With SciSure’s SMP, every data point, action and approval is automatically logged and versioned—so your lab data is always ready to defend itself.

4. Lab data living outside the system

You’d be surprised how much data still lives off-grid.

Files tucked away on personal drives. USBs passed between team members. Screenshots of results emailed for convenience. Even when a lab uses digital systems, there’s often a shadow layer of untracked data that exists outside any controlled environment.

The risks are huge. When data isn’t captured within your core systems, it can’t be secured, audited, or versioned. That leaves labs vulnerable to loss, duplication, or misinterpretation—especially when key team members move on or regulators come knocking.

Worse, it creates a false sense of confidence. You think your lab data is centralized and complete—until someone needs a file that never made it into the system.

Our recommendation:

Make it effortless for your team to keep lab data where it belongs: in a secure, connected platform. SciSure’s SMP supports direct instrument integrations, centralized data capture and easy upload mechanisms—so valuable data doesn’t slip through the cracks.

5. Version confusion and the illusion of control

Not all data risks come from missing records. Sometimes the problem is having too many versions, stored across email threads, shared folders, or downloaded from different platforms. Without strong lifecycle controls, labs lose sight of which version is the final, approved, or most accurate one.

You might have an SOP in place. But when five people edit five copies of the same file—and no system records who did what, or when—it’s only a matter of time before errors creep in. Critical decisions get made using outdated or incomplete information. And no one notices until results are questioned or workflows break down.

This kind of version drift doesn’t just slow things down—it undermines trust in your lab data and weakens your ability to stand behind it.

Not necessarily.

Treat data versioning and review as core parts of your lab infrastructure—not side processes. SciSure’s SMP enforces single-source data management with full version history, approval workflows and audit logs—so you always know which file is the right one, and why.

Data integrity doesn’t fail loudly… until it does

Most integrity failures don’t come from a single dramatic mistake. They build up slowly, through small oversights, disconnected systems, and assumptions that everything is “under control”.

But when the moment comes—an audit, a submission, a collaboration—your lab data needs to hold up. It needs to be complete, connected and defensible.

That only happens when your systems are designed for integrity from the ground up.

SciSure’s Scientific Management Platform helps labs do just that—by unifying your LIMS, ELN, instrument integrations and compliance workflows into one connected environment. No more silos. No more shadow data. Just visible, reproducible data you can trust.

Ready to take control of your data?

Let’s talk. SciSure’s Scientific Management Platform is built to close integrity gaps and give you complete visibility across your lab.

Get in touch to see how we can help you protect your data—and the science behind it.

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Security & Compliance

5 Hidden Threats Putting Your Lab Data at Risk

Hidden risks threaten lab data integrity—even in digital labs. Discover 5 overlooked threats and how to protect your lab data from inconsistency and error.

eLabNext Team
Philip Meer
|
5 min read

What made you get into science?

You probably didn’t imagine a future spent buried in spreadsheets, logging into ten different tools, or chasing inventory approvals. You didn’t think about hours spent formatting compliance reports, chasing different departments, or spending half your time trying to find missing data.

Let’s face it—you didn’t get into science for the admin. But somehow, that’s where the journey led. Somewhere along the way, science became paperwork. Discovery turned into red tape. Curiosity took a backseat to compliance.

At SciSure, we believe it’s time to change that.

Science has a workflow problem

Today’s labs are bursting with digital tools—ELNs, LIMS, inventory management software, EHS platforms, procurement systems—but most of them don’t talk to each other. These single-point solutions were designed to address one aspect of the puzzle, not the entire picture.

If a scientist needs to run an experiment, they might need to check three siloed databases, coordinate with two departments, and track down someone in procurement—all before they even pick up a pipette.

Lab operations and EHS teams are equally overwhelmed. They’re working tirelessly to support the science, but with little visibility into what’s happening across the labs, and little time to chase down missing data or out-of-date records. Instead of being proactive, they’re stuck in a constant cycle of reactive problem-solving.

It’s chaotic. It’s inefficient. But most of all, it’s not what the Scientist Experience should feel like.

As I said to a room full of scientists at a recent event:

“Close your eyes and think back to the moment you decided to become a scientist. Did you picture spending half your time on admin work?” 

The room responded with an odd kind of laughter, not because it was funny. Because it was real. Because every person there felt the pain. And the worst part? We’ve all accepted it as usual. But normal doesn’t mean acceptable—and at SciSure, we’re here to challenge that.

Introducing SciSure’s Scientific Management Platform

We’re not here to add another tool to the pile. We’re here to replace the pile with something new. Something comprehensive. Something built from the ground up for the people who actually use it.

SciSure is the result of a bold, deliberate merger between two established names in digital lab technology: eLabNext, long respected for its ELN and LIMS capabilities, and SciShield, a trusted leader in EHS, compliance, and lab safety. By combining our offerings, we have become the first platform to connect the whole triangle of scientists, lab operations, and EHS in one unified system. No silos. No disconnects. No handoffs between incompatible tools.

Welcome to the Scientific Management Platform (SMP): a true home base for the modern lab. A place where every part of your day—from experiment planning to procurement to training reminders—is connected, visible, and easy to manage.

Most of us can still remember. It wasn’t just a subject at school—it was a spark. A moment. You saw something under a microscope that made the invisible visible, read about a medical breakthrough, or started asking questions that nobody had the answers to. And you thought: “I want to do this. I want to change the world.”
As a result, lab staff today spend hours toggling between platforms, re-entering the same data multiple times, or emailing colleagues for updates that are buried in someone else’s system. Compliance logs reside in one system, while inventory records are stored in another. Safety training records might be tracked in spreadsheets that only one person knows how to access. 

  • One login instead of ten.
  • One interface instead of half a dozen.
  • One continuous experience, where your experiment, your materials, your inventory, your compliance, and your safety are all part of the same workflows.
  • A digital marketplace of pre-built integrations and add-ons for the tools you trust.

At the heart of SciSure is something we call the Scientist Experience (SX). While most platforms focus on generic “user experience (UX)”, we’ve gone further. SciSure is purpose-built for science, with workflows, functionality, and connectivity that feel intuitive to researchers, not retrofitted for them. This isn’t consumer-grade UX repackaged for the lab—it’s a purpose-built experience designed to support the way scientists actually work.

No more jumping between disconnected systems. No more missing data, miscommunications, or duplicative admin.

Just science. Streamlined and reproducible.

We’ve brought ELN, LIMS, EHS, inventory, procurement, and safety into one system to create the first truly end-to-end SMP because scientists deserve better. Because the science itself depends on it.

Operational simplicity, not complexity

In the biopharma world, you hear a lot about “operational excellence.” But let’s be honest—too often, that “excellence” looks like a long and complex roadmap, a multi-year digital transformation strategy, and a small army of consultants and resources just to get started. 

I, for one, prefer the term operational simplicity. Improving your lab shouldn’t be overwhelming. It shouldn’t require ripping everything out and starting from scratch. And it definitely shouldn’t mean waiting years to see value.

You should be able to start today. Start with what matters most—maybe that’s digitalizing your protocols, automating your inventory management, bolstering your safety workflows, or getting a grip on training compliance. Start where the pain is loudest. And then build from there. 

With SciSure, you don’t need to onboard everything at once. Our platform is modular, scalable, and flexible, so you adopt what you need, when you need it. You grow at your own pace, with solutions that you will never outgrow as you scale. 

You control the pace. You control the priorities. You control the controllables.

That last line is something I’m always saying to our team—and to our customers. Because in an industry that’s dealing with economic pressure, regulatory uncertainty, and tightening budgets, you can’t control the chaos out there.

But you can control how your lab operates. You can build a system that’s efficient, compliant, and delivers proven ROI—without needing a complete overhaul every time something shifts. Simplicity isn’t a shortcut. It’s a strategy, and it’s one I’m proud to stand for.

Safety that’s built in—not bolted on

Too often, lab safety is treated like an afterthought. It’s like buckling your seatbelt when you’ve already arrived at your destination—performative, reactive, and, frankly, too late. It’s a bit of a “check the box” exercise.

In many labs, safety is something scientists ‘remember’ to do right before someone checks in. Training reminders get lost in junk email inboxes. Chemical inventories get updated days after the work is done. Compliance audits spark frantic document hunts. Meanwhile, EHS teams, instead of being proactive partners, become the bad guys chasing people down.

That’s not a people problem. That’s a system problem. And I’ve seen the consequences firsthand.

An early part of my career was in protective apparel, where I designed lab coat safety programs for complex research centers. I learned of a heartbreaking story of a young researcher who never made it home after a lab accident. It felt like we could have done so much more to protect her and others. I remember asking, “Why aren’t we fixing this?” The answer shocked me: “Because it’s research. We can’t always make scientists follow the rules.”

But instead of blaming the scientists, I asked a different question: “Why aren't they following the rules?” 
What I found changed everything for me. The PPE wasn’t built for them. It was uncomfortable, impractical, and designed without their input. So my team and I redesigned it from the ground up and made it readily accessible, including a special fit for women. Today, that flame-resistant lab coat is widely used in labs all over the world. Not because we mandated safety, but because we built it for people who needed to wear it. Built by scientists, for scientists.

That experience shaped everything I do. At SciSure, we’ve taken the same approach.

We asked:

  • Why are scientists overwhelmed?
  • Why does EHS feel like a nuisance instead of a partner?
  • Why is lab ops always chasing problems instead of preventing them?

Now we are building the platform to fix it. With the Scientific Management Platform, safety and compliance are no longer bolted on at the end—they’re built in from the start: Training alerts live in your home base, right where you log your experiments. Hazards drive requirements for safety procedures and training. EHS gets visibility without needing to micromanage and nag scientists for updates. 

With our SMP, lab operations, EHS, and scientists aren’t on separate teams anymore. They’re part of one connected system, supporting each other in real time. We’re not perfect, and we won’t pretend to be. But we’re listening. We’re building. And we’re solving a problem that no one else has had the guts to take on. 

Because true safety shouldn’t slow science down. It should set it free.

The future of the Scientist Experience (SX)

Imagine a lab where scientists don’t dread admin days. EHS isn’t the bad guy. Ops isn’t stuck chasing down updates, and every part of your research journey is connected, compliant, and reproducible. Imagine a system that offers pre-built integrations and add-ons with tools you already use and trust.

That’s what we’re building.

Not because it’s easy. But because it’s necessary. Because great science deserves to be scalable and reproducible. Because patients are waiting, and because somewhere, a young scientist believes she can change the world.

Let’s help her achieve it. 

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Digitalization

Dear scientists: You deserve better.

Labs are drowning in admin and disconnected tools. SciSure’s Scientific Management Platform puts science first, streamlining workflows, safety, and compliance.

eLabNext Team
Jon Zibell
|
5 min read

Trust is the currency of science.

Whether you’re publishing results, submitting regulatory data, or developing new therapeutics, the confidence others have in your data determines how far it can go. And that confidence—research integrity—doesn’t just come from good intentions. It comes from robust systems.

Too often, we treat integrity as a people issue. We focus on protocols, training, or maybe ethics. All important. But after decades working with labs of every size and discipline, I’ve seen something else at play: when your systems are fragmented, your integrity is at risk—even when your people do everything right.

In many labs, data still lives across a messy patchwork of systems—an ELN here, a spreadsheet there, paper records in a binder. Teams copy and paste data across platforms, version control becomes guesswork, and no one’s quite sure what the “final” version is.

When an auditor asks for proof of compliance or a collaborator needs to validate results, you realize how much depends on assumed knowledge and goodwill. And when people move on, or mistakes surface, the fragility of those systems becomes painfully clear.

That’s why I believe system integrity is the backbone of research integrity—and why connected lab platforms are no longer a nice-to-have, but a scientific necessity.

When systems undermine science

Research integrity doesn’t fail all at once. It erodes quietly, through disconnected point solutions, manual data transfer and systems that were never designed to work together.

I’ve walked into labs with world-class researchers using cutting-edge instrumentation—only to find their data pipelines held together with nothing more than good intentions. It’s not because they don’t care. It’s because the systems around them haven’t kept pace with the demands of modern science.

Disconnected platforms; siloed ELNs, standalone LIMS, inventory tools that don’t talk to safety systems—all create invisible fault lines. Data gets duplicated or lost. Metadata goes missing. It becomes impossible to trace the full lifecycle of a sample or reconstruct the context behind a result.

And when that happens, the consequences are real. Reproducibility suffers. Internal reviews stall. Regulatory submissions take longer and carry more risk. Worse still, you lose confidence—not just in your systems, but in the science itself.

For organizations working in regulated environments, the stakes are even higher. Incomplete audit trails, missing version histories, or informal approvals can mean non-compliance, rejected submissions, or reputational damage.

These aren’t edge cases. They’re everyday realities in labs that haven’t yet joined up their data infrastructure. And they represent a quiet threat to the very thing science depends on most: trust.

What research integrity actually looks like

Too often, research integrity gets framed as either a matter of ethics or a matter of compliance—something enforced through training or checked off in audits. But in real-world lab environments, it comes down to something more fundamental: can your infrastructure support consistent, trustworthy science?

That infrastructure isn’t just software. It’s the entire operational system that governs how data is generated, recorded, shared, and reviewed. It includes your ELN, LIMS, EHS system, instrument integrations, user permissions, approval chains, and how all of those components interact.

In labs with strong system integrity, research integrity is built-in. You don’t have to rely on memory, trust, or double-checking a spreadsheet—because the process itself ensures traceability, reproducibility and control at every step.

Here’s what it looks like in practice:

• Protocols are version-controlled and digitally signed by authorized users

• Sample records are automatically linked to test results, instruments, and reagents used

• Every action is timestamped and traceable across users and systems

• Permissions and role-based access prevent accidental edits or data leaks

• Metadata—like experiment conditions or instrument settings—is captured automatically, not added after the fact

It’s about more than preventing fraud. It’s about preventing drift—those subtle gaps between what was planned, what was done, and what gets reported. When those gaps widen, reproducibility breaks down. When they close, trust scales.

And this matters whether you’re running a small academic group or a global R&D program. Because sooner or later, someone outside your team—an auditor, a collaborator, a regulator—will ask: can we rely on this data?

Research integrity means being able to say “yes”, and being able to show it, systemically. That’s exactly what we’re building at SciSure: a connected home base for the lab where trust, traceability, and transparency aren’t bolted on—they’re built in.

The value of system integrity

Research integrity is often treated as an outcome—as something measured by reproducibility, accuracy or audit success. But behind all those metrics is a more foundational truth: you can’t deliver research integrity unless your systems are built to support it.

This is where system integrity comes in. It’s not about individual tools. It’s about how your tools work together to preserve the full lifecycle of your data: generation, approval, storage, access and re-use.

Labs with strong system integrity can trace every data point back to its origin—who captured it, how it was reviewed, and where it’s stored. Their workflows don’t rely on individuals to go the extra mile; they’re embedded in the platform. And when regulations evolve or new technologies are introduced, those systems adapt, because they were designed with change in mind.

System integrity isn’t an add-on—it’s the architecture. And in our experience, when you get that right, research integrity stops being a problem you fix—and starts being something you can trust.

Turning risky into resilient

Disconnected systems don’t just slow things down—they erode confidence. When your ELN, LIMS, EHS system and instrument data all live in separate silos, the gaps between them become places where integrity fails: a missing sample ID, an overwritten protocol, a spreadsheet with no owner.

That’s why connected platforms are so essential—not just for operational efficiency, but for resilience. When systems are joined up, workflows become transparent. Data becomes trustworthy. Compliance becomes routine, not reactive.

At SciSure, we’ve built our Scientific Management Platform (SMP) around that principle. It brings together the critical building blocks of research management—ELN, LIMS, EHS, inventory, sample tracking, regulatory workflows and audit logs—into one coherent, cloud-native environment.

Within the SMP, system integrity is more than a principle—it’s a set of connected capabilities designed to make compliance and reproducibility seamless. That includes:

• Automated sample lineage tracking across collection, processing, and storage

• Embedded compliance checkpoints aligned with 21 CFR Part 11, GxP, and ISO 17025

• Configurable approval chains with full digital audit trails

• A unified environment where ELN, LIMS, and EHS modules speak the same language

• Scalable SDK-based integration, allowing labs to evolve without losing traceability

But just as importantly, the SMP isn’t rigid. Every lab works differently. That’s why we offer both a growing library of ready-to-use integrations and a developer Software Development Toolkit that supports custom workflows, instrument integrations and data pipelines. You’re not stuck working around the platform—you shape it around how your lab already works.

And when your systems are this connected, integrity becomes effortless. You’re no longer relying on tribal knowledge to chase down files or verify data lineage. It’s all there—verifiable, reproducible and ready to stand up to scrutiny.

Research resilience starts here. Not with good intentions or paper-based processes, but with infrastructure that’s designed to make trust scalable.

Research integrity is in your hands

Research integrity isn’t just about what happens at the bench—it’s about what happens behind the scenes. The tools, the workflows, the handoffs, the audit trails. If those systems are fragile, no amount of rigor at the surface can compensate for what’s missing underneath.

That’s why integrity has to start at the system level. When your infrastructure supports consistency, traceability and compliance by default, research integrity becomes scalable. Defensible. Repeatable. It becomes a property of your lab—not just the people in it.

At SciSure, we believe that good science needs good systems. And we’ve built our platform to help labs create the kind of environment where integrity thrives—now and in the future.

If you’re serious about protecting the trustworthiness of your research, start by asking: do your systems support the science you stand behind?

Ready to future-proof your lab’s integrity? Contact us to see how SciSure can help you unlock the system your science deserves.

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Lab Data Management

Research Integrity Starts with System Integrity

Research integrity depends on system integrity. Explore how SciSure helps labs protect data, ensure compliance, and scale reproducibility

eLabNext Team
Philip Meer
|
5 min read

Lab operations is a job of countless moving parts. You’re the one who gets the 6 a.m. message about a broken freezer. The one answering late emails about missing reagents. The one tracking down overdue chemical inventory reports. It’s you that’s stuck in the middle—trying to keep scientists on-track, keep EHS happy, and still hit the goals set from administration.

And here’s the truth: your job isn’t one job. It’s twenty. You’re part scientist, part problem solver, part safety officer, equipment coordinator, procurement specialist, compliance tracker—and yes, firefighter. Every day. All the time.

I’ve talked with enough LabOps leaders to know that “multitasking” doesn’t even begin to cover it. One of the first questions I ask when I meet someone in LabOps is: How many hats do you wear? And without fail, they just laugh—or roll their eyes. Because they already know the answer: Too many.

One person recently told me, “If I could just take off one hat—just one—I’d be so much more valuable to my scientists.” That stuck with me. Because it speaks to a deeper truth about your role: you’re the operational engine behind the lab, the one keeping the science moving, the one making sure research doesn’t stall. And yet? You’re often unable to get to the work that moves the needle. 

You’re expected to be the glue—to bind together scientists, EHS, vendors, facilities, IT, and more—but no one’s provided you the tools to actually hold it all together. That’s not your fault. That’s the system’s fault.

We’ve normalized the dysfunction

Most labs I walk into are juggling an eye-watering number of systems: There’s an app for inspections. A training matrix spreadsheet. A cloud drive for ordering. A digital binder for SDS sheets that hasn’t been updated in months. Someone’s still logging chemicals in an Excel sheet. And yet—everyone’s expected to operate like a high-performance team.

Scientists are in their own zone, focused on getting experiments done. EHS is off in theirs, trying to ensure safety and regulatory coverage without full visibility into the data they need to be audit ready. LabOps are often the one caught in the middle, expected to make all of it work. We’ve been sold the idea that this fragmented ecosystem is normal. That cobbling together ten tools and calling it “digital transformation” is just the cost of doing science.

But it’s not normal. It’s just the status quo—and it’s broken.

We don’t need more complexity. We need operational simplicity.

In biopharma, there’s a buzzword that’s been floating around for years: “operational excellence”. You see it in slide decks. Hear it in strategy meetings. Entire departments are built around chasing it.

But I’ll be honest—when I see the typical roadmap for getting there, my eyes glaze over. Not because it isn’t well-intentioned. But because it’s built for a world where you’ve got unlimited time, a dozen project managers, and years to transform your systems. 

That’s not the world LabOps lives in. Most labs don’t need “excellence”, they need something that works today. That’s why, at SciSure, we’re championing something new: operational simplicity. And we’ve created the first platform that actually delivers it—end to end. We’re not here to add another tool to the pile. We’re here to replace the pile with something built from the ground up for the people who actually use it.

The Scientific Management Platform (SMP) is a first-of-its-kind system that unites scientists, LabOps, and EHS under one roof. Not as users of the same tool, but as collaborators inside a shared ecosystem. Forged from a strategic merger between two trusted leaders—eLabNext, known for its ELN and LIMS software, and SciShield, respected for EHS, biosafety, and chemical safety solutions—we’re working hard to deliver something no one else had the conviction to do:

A true end-to-end solution. A home base for the entire scientific organization.

  • One login. One interface. One system that links research, inventory, safety, compliance, and regulatory reporting.
  • Intuitive dashboards for scientists, EHS, and LabOps—tailored to what they need.
  • Built-in safety and compliance workflows—no chasing, no bolt-ons, no “oops, we forgot to do the training”.
  • A modular design that lets you adopt what you need today—and expand when you're ready.

With the SMP, you're not logging in and out of 10 tools. You're not re-entering data or transcribing between systems that can’t talk to each other. You’re not cobbling together workarounds just to make your lab function. You're simply working. Confidently. Transparently. Collaboratively.

And that’s the power of operational simplicity: it gives you control. Control over your workflows. Control over your data. Control over your time. In a world that’s constantly changing—funding shifts, regulatory updates, staffing turnover—you can’t control the chaos. But you can control the controllables. That’s what SciSure is here to help you do.

Our goal at SciSure isn’t to force everyone into the same workflow. It’s to connect their silos in a way that makes sense—so that LabOps doesn’t have to be the translator, or the buffer, or the one who copies data from one system to another.

Scientists want to work in their environment. EHS needs reliable data. LabOps needs visibility across both. We’re building SciSure to make that possible—to let everyone do their job well, while ensuring they’re connected in the background where it counts.

From chasing problems to preventing them

I’ve heard it time and time again: LabOps lives in reactive mode. You’re running from one task to the next, never quite catching up, always reacting. There’s no space to think ahead—let alone optimize, strategize, or innovate. But when you give LabOps the right tools, everything changes.

Suddenly, you’ve got real-time dashboards that tell you what’s overdue, what’s at risk, and what’s just around the corner. You get automatic reminders for training, inspections, and compliance updates—not frantic emails the day before something’s due. Instead of cross-checking three systems to figure out who’s behind on chemical inventory, you can see the status in a single view. You stop wondering if your data is current. You know it is.

Reporting becomes fast and confident. MAQs, CFATS, flammables—the kind of documentation that used to take hours now takes minutes, because it’s all built in. No more guesswork. No more copy-paste. And with threshold-based alerts tied to real hazard data, you're not just catching problems. You're preventing them.

But here’s the part I love the most—it changes how you think. Instead of dreading the next audit, you’re ready for it. Instead of catching issues downstream, you’re preventing them upstream. Instead of getting pulled in every direction, you’re setting the direction. That’s the shift we’re creating with SciSure. And it’s not hypothetical—it’s happening right now in labs just like yours.

Time to rethink chemical inventory

Ask anyone in LabOps what drains the most time, and chemical inventory will be near the top. Not because it’s difficult—but because it’s disconnected. Updates get lost. SDSs live in silos. Reports are always a scramble. We’ve built SciSure to turn that burden into a strategic lever.

With SciSure, chemical inventory tasks that used to take hours now take minutes. As soon as a chemical is added to inventory, you know which hazards apply and what regulations are relevant, even going as far as automatically adding it to your regulatory reports. One team we worked with used to spend nearly three full days reconciling chemical inventory across their site. After switching to SciSure, they were done in thirty minutes. Another cut data correction time from seventeen hours per month down to under two minutes. When you scale these time savings across dozens of people, across hundreds of tasks, those minutes and costs add up fast.

We recently looked at data from 32 customer sites to understand the real impact of transforming chemical inventory workflows. Here’s a snapshot of what LabOps and EHS teams are actually gaining back:

Activity Before SciSure With SciSure
Adding a container to inventory 6.5 minutes 1.7 minutes
Finding/viewing chemical inventory 10.5 minutes 1.3 minute
Viewing inventory by space/location 17.2 minutes 1.4 minute
Updating multiple containers at once 22.8 minutes 3.4 minutes
Correcting monthly chemical data 17.3 hours/month 1.7 minutes/month
Supporting labs with inventory updates 13.5 hours/month 1.6 minutes/month
Generating complex chemical reports (e.g. MAQs, CFATS) 21.4 hours 7 minutes
Lab members updating their inventory 11.9 hours 15 minutes
Reconciling inventory for a location 19.8 hours—3 days 30 minutes
Finding an SDS for a chemical 6.7 minutes 3.2 minutes

Table 1: Time savings reported across 32 SciSure customer sites

But the real value isn’t just speed. It’s confidence. When inventory connects to hazard profiles, to training requirements, to reporting and procurement—you’re not just checking boxes. You’re running a safer, more accountable lab. And you’re giving scientists and EHS teams shared data they can trust.

Flexibility and extendibility built around you. 

SciSure doesn’t pretend to be everything for everyone. We know labs are complex. We know preferences vary. That’s why we built our SciSure Marketplace of integrations to be open and extensible.

Let’s say you already have a scheduling tool your scientists love. Great. Don’t toss it—integrate it. Or maybe your team uses a specific vendor for procurement or equipment monitoring. Perfect—bring them in.

Our Marketplace is designed to let you work the way you want. It’s an open ecosystem where trusted third parties—including some of our own competitors—can plug directly into the SciSure platform. Why? Because we believe that as a scientific community, we are “better together”. Because if it makes your workflow smoother, if it saves your team time, and if it helps scientists get back to the work that matters, then we’ll make room. That’s how serious we are about interoperability.

As one of our Marketplace Partners put it:

“Our integration with SciSure allows scientists, LabOps, and EHS to view critical data in one seamless place. It means labs can proactively monitor environmental conditions and respond instantly to deviations that could compromise valuable samples.”
- Sridhar Iyengar, Founder and CSTO, Elemental Machines

Some of our customers have even started building their own integrations. One group created a fully custom equipment scheduler inside SciSure using our developer tools. No vendor lock-in. No workarounds. Just functionality that fits the way they operate.

That’s what flexibility should look like. Because you’re not here to serve the system. The system should serve you.

Let’s stop fixing what’s broken. Let’s build what works.

The truth is, LabOps shouldn’t have to hustle this hard just to hold the lab together. Scientists shouldn’t be buried in admin. EHS shouldn’t have to chase compliance.

And you? You shouldn’t be the translator between teams and tools that were never built to align in the first place.

That’s why we created SciSure. Not as a patch, but as a true home base. A unified foundation for modern labs—one that connects your people, your processes, and your purpose. Because the science matters. And so do the people and patients behind it.

Let’s make it easier to do the work that matters most. Let’s give LabOps their time, their tools, and their voice back. You’re not the problem. The system is.

Let’s fix it--together.

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Digitalization

Lab Managers: You’re Not the Problem. Your Systems Are.

LabOps isn’t broken--you’re just stuck with broken systems. Discover how SciSure simplifies lab operations, connects teams, and gives control back to you.

eLabNext Team
Jon Zibell
|
5 min read

Cambridge, MA — July 10, 2025 — SciSure, formerly SciShield and eLabNext, is proud to announce the formal sponsorship of The Engine, a nonprofit founded by MIT to  incubate and accelerate early-stage Tough Tech companies from idea to impact. This sponsorship marks the next step in a partnership rooted in a shared mission: helping startups accelerate the development of life-changing technologies, treatments, and healthcare solutions.

SciSure was recently formed from the merger of SciShield and eLabNext. Both companies were longtime partners of The Engine: For years, SciShield supported The Engine with environmental health and safety (EHS) and compliance infrastructure, while eLabNext powered the digital backbone of many resident companies. Now, by joining forces, SciShield and eLabNext are expanding their support—giving Tough Tech entrepreneurs connected access to the critical digital tools, compliance frameworks, and operational resources they need to scale and succeed.

"We’ve seen firsthand how important the right infrastructure is for Tough Tech startups to reach the market," said Jon Zibell, VP of Global Alliances and Marketing for SciSure "By deepening our partnership with The Engine, we’re making it easier for innovators to focus on what matters most—delivering breakthroughs that have a lasting impact on society."

“Given the fact that science is moving more and more towards Tough Tech and Tech Bio (as in technology-first, using advanced computational tools like AI, ML, cloud, and data engineering), it is so important to be able to create an API/SDK-Powered ecosystem for scientists that know that we can support their platforms, automation, and scalability.” said Zareh Zurabyan, VP of Commercial, Americas for SciSure. 

Through this enhanced partnership, The Engine’s resident companies will gain:

  • Integrated Digital Operations: Access to eLabNext’s Digital Lab Platform (DLP), combining ELN, LIMS, lab automation, and compliance tracking into one connected system.
  • Built-in EHS and Compliance Support: SciShield’s platform ensures startups meet regulatory standards from day one, reducing risk and saving time.
  • Early Access Incentives: Special access to tailored onboarding, incentives, and ongoing support for adopting SciShield and eLabNext solutions. 
  • Best-in-Class Software: A full suite of software solutions for Scientists, LabOps, and EHS to ensure the highest probability of achieving commercial success and making a lasting impact.
  • Education and Collaboration: New opportunities for startups to participate in co-hosted workshops, hands-on training, and knowledge-sharing sessions on lab digitalization, safety, and compliance.

“For years, SciSchield and eLabNext have provided critical infrastructure and resources to fuel the growth of our residents,” said Alexa Monti, Vice President of Business Development and Strategic Partnerships at The Engine. “We are now thrilled to welcome their sponsorship as SciSure. Partnerships like this are essential to building a resilient innovation ecosystem that enables founders to transform breakthrough ideas into world-changing impact.”

About The Engine:

The Engine is a nonprofit incubator and accelerator dedicated to supporting early-stage Tough Tech companies tackling the world's greatest challenges. Founded by MIT in 2016, The Engine provides critical support for Tough Tech companies in the form of specialized lab and fabrication infrastructure, programming and mentorship, and an ecosystem of experts and investors. By bridging the gap between groundbreaking ideas and real-world impact, The Engine plays a crucial role in advancing solutions to complex global issues. For more information, visit engine.xyz

Media Contact: 

press@engine.xyz

Media Contact:

Jon Zibell
Vice President of Global Alliances & Marketing
J.Zibell@scisure.com

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News

SciSure Sponsors The Engine to Deepen Commitment to Tough Tech Startups

The partnership will provide The Engine’s resident companies with critical digital infrastructure for EHS, LabOps, and compliance tracking.

eLabNext Team
|
5 min read

Over the past decade, the life sciences industry has undergone a foundational transformation, one that redefines how biology is explored, understood, and scaled. 

Traditional, wet-lab-driven biotechnology has shifted toward TechBio, a new model grounded in software engineering, data architecture, and AI-native platforms. This transition replaces linear, hypothesis-driven experimentation with computationally designed, automated, and feedback-driven discovery systems.

Whereas classical biotech workflows revolved around physical assays and post-hoc data interpretation, TechBio organizations prioritize upstream data infrastructure, machine learning (ML)-ready outputs, and modular technology stacks from the outset. 

Bioinformaticians have transitioned from support roles to strategic leadership, while wet lab execution has become programmable. Digital platforms, such as ELN/LIMS ecosystems, have become mission-critical infrastructure. Interdisciplinary teams spanning biology, data science, and software engineering collaborate in product-oriented models, similar to those found in SaaS companies. AI tools also augment decision-making at every stage, from target identification to manufacturing.

This guide outlines what TechBio is and ten defining pillars, providing detailed examples. It explores how TechBio organizations engineer not only therapies, but the digital systems that discover, refine, and validate them. 

As the boundary between biology and computation dissolves, TechBio positions itself as the operating system of 21st-century life sciences, offering a blueprint for faster, more scalable, and reproducible scientific innovation.

Welcome to TechBio, where biology meets software engineering, and the future is being coded before it's cultured.

What is TechBio?

TechBio is the convergence of biology, software engineering, and AI, replacing traditional wet-lab workflows with computationally driven, programmable discovery systems. It reimagines life sciences as a scalable, data-centric platform where interdisciplinary teams and digital infrastructure power faster, more reproducible innovation.

10 Pillars Defining the TechBio Transition

1. Data Architecture Before Wet Work

Traditional biotech began with the bench: Run experiments, generate data, and interpret the results later. 

In TechBio, the inverse is true. Teams now design the data schema, ontology, and analysis pipeline first, enabling smart experiment design, ML-ready outputs, and scalable platforms that can adapt over time.

If your data isn't structured for insight on Day 1, you're already behind. Here are some examples:


This inversion – starting with data design before experimentation – has reoriented R&D pipelines around long-term scalability. As structured data becomes a strategic asset, TechBio companies are increasingly valued not just for their scientific breakthroughs but for the reusability of their data layers. This has profound implications for platform business models, partnerships, and cross-study insights.

2. AI-First vs. Hypothesis-First

Biotech works in a sequential logic: form a hypothesis, test it in an in vitro model, and iterate. 

TechBio builds AI-native systems that surface insights and correlations before human hypotheses even form, accelerating discovery.

The AI isn't replacing the scientist; it's augmenting their intuition at scale. Examples include:

  • Insitro and Inceptive are generating drug candidates with ML from genetic/phenotypic data, especially in diseases like ALS and obesity.
  • CRISPR screening now uses AI to predict essential gene targets before experiments, significantly reducing the time-to-lead.


The shift from hypothesis-driven to AI-augmented discovery marks a turning point in biological research. Rather than replacing scientists, AI now operates as a collaborative engine that surfaces new dimensions of correlation and causation. The competitive edge is shifting toward organizations that can orchestrate this human–machine loop efficiently, striking a balance between statistical signals and biological plausibility.

3. Platform Engineering as a Core Competency

In TechBio, companies aren’t just developing drugs; they're developing software platforms that standardize workflows, integrate third-party tools, and turn fragmented research into reproducible systems. 

Internal data platforms, LIMS/ELN integrations, and ML pipelines are essential baseline technologies for competitiveness. Some real-world examples include:


The rise of internal engineering teams and reusable software platforms in the life sciences mirrors the evolution of the tech industry. Platformization allows TechBio companies to rapidly launch programs across therapeutic areas, onboard partners, and generate real-time feedback loops. The result is a higher innovation velocity and better capital efficiency, traits that investors and pharmaceutical partners increasingly favor.

4. Bioinformaticians Are the New Bench Scientists

In a TechBio org, the bioinformatician is no longer “behind the scenes;” they're core to strategy, productization, and decision-making. Teams prioritize hires who can extract signal from noise, build predictive models, and interface with both biologists and back-end engineers. Bioinformaticians are now tasked with defining the experiment design, not just analyzing results after the fact.
As the bottleneck in modern biology moves from experimentation to interpretation, bioinformaticians have emerged as essential architects of discovery. Organizations that empower computational biology as a front-line discipline – not a downstream service – are demonstrating faster time-to-insight, better target validation, and smarter trial design. Talent acquisition in this field is now a core strategic priority.

5. Composable Lab Tech Stacks

Gone are the days of rigid, siloed lab systems. TechBio demands modular, API-connected ecosystems that allow seamless integration between ELN, LIMS, data lakes, assay instruments, and cloud analysis tools. 

Composability – the ability to select, assemble, and reconfigure components, such as services, modules, or APIs – is the new competitive advantage.

Top TechBio orgs are building integrated ecosystems where ELN, LIMS, and assay data sync in real-time, reducing batch errors and improving reproducibility. Composable architecture transforms labs from siloed environments into interoperable, cloud-connected ecosystems. 

This flexibility enables rapid tool swapping, real-time data syncing, and scalable digital operations. As composability becomes a prerequisite, the market is shifting toward vendors and platforms that emphasize integration, standardization, and cross-domain orchestration.

6. Experimental Automation as Software

Wet lab automation has evolved beyond the use of robotic arms. Now it’s programmable. TechBio teams treat lab execution as code: Experiments are version-controlled and modularized, making them reproducible across different geographical locations. Strateos and Emerald Cloud Lab are commercial examples of how this can work, letting scientists run remote assays, QC, and sample processing with code.
By treating lab execution as programmable infrastructure, TechBio closes the loop between in silico design and in vitro execution. Automation not only accelerates throughput but also unlocks a new paradigm of version-controlled science, where reproducibility and traceability become codified. The winners in this space will be those who can abstract biology into code without sacrificing fidelity.

7. Interdisciplinary Product Teams

TechBio orgs are structured like SaaS companies. Product managers, software engineers, data scientists, and bench biologists all contribute to the strategic path for products. Product-market fit isn’t just about efficacy; it’s about workflow usability, data interoperability, and analytical scalability. 

Dyno Therapeutics, a company using AI to discover and optimize better delivery of gene therapies, employs product managers and ML leads alongside virologists to design AAV capsid platforms with specific tropisms.
The productization of science, where multi-disciplinary teams own features, roadmaps, and outcomes, blurs the lines between R&D and product development. TechBio teams now operate like agile startups, iterating on therapeutic designs with the same velocity and feedback mechanisms as SaaS companies. This accelerates both discovery and market alignment, reducing the translational lag between R&D and impact.

8. Open Science Meets IP-Protected Infrastructure

Rather than hoarding findings in PDFs or publications, TechBio companies publish datasets, APIs, and tools while protecting their insights via proprietary ML models and data platforms. It's not just about the molecule or target; it's about the ecosystem that discovers it.

TechBio is redefining the balance between openness and defensibility. By releasing tools and datasets while protecting the infrastructure that operationalizes them, companies can build communities, accelerate adoption, and establish defensible moats around proprietary layers. This hybrid approach to IP strategy mirrors the open-core model in software and is fast becoming the norm in science-forward organizations.

9. AI-Augmented Decision-Making in R&D

From target identification to trial design, AI is infused across the R&D lifecycle. NLP models extract insights from literature, generative models design protein structures, and predictive models flag risks before they manifest. For example:

  • GLP-1 and incretin research is being accelerated by multimodal AI models that predict cardiometabolic response based on genetic and dietary data.
  • CRISPR off-target prediction tools, such as DeepCRISPR and CRISPR-Net, minimize risk before editing begins.


From discovery to development to manufacturing, TechBio companies are using predictive models to make faster, more informed decisions. This transition lowers risk, reduces cost, and improves outcomes, positioning AI-augmented pipelines as the gold standard for next-generation therapeutics.

10. Speed, Scale, and Signal

TechBio companies operate on startup timelines, not scientific timelines. They use cloud infrastructure, continuous data streaming, and rapid feedback loops to compress cycle times from months to days. Signal extraction and throughput are the key metrics. What used to take 18 months in a wet lab now happens in 6 weeks via computational modeling and robotic execution.

By adopting cloud infrastructure, continuous experimentation, and agile pipelines, companies can reduce the cycle time from question to answer and from idea to impact. As signal extraction becomes the metric that defines productivity, organizations are now judged by how efficiently they can learn, not just how much they can test.

The Venture Capital (VC) & Private Equity (PE) Outlook: Why TechBio Is the New Investor Mandate

The TechBio transition has fundamentally reshaped investor psychology in life sciences. Where traditional biotech relied on long timelines, binary risk, and molecule-centric valuations, today’s VC and PE firms are seeking software-first, platform-oriented, and AI-native biology companies that exhibit repeatable innovation, scalability, and enterprise value beyond a single therapeutic asset.

Key Investment Trends Driving Capital Deployment in TechBio

The biotech investment landscape is shifting, with VC deployment accelerating in late 2025 and favoring AI-native, TechBio firms modeled after high-growth SaaS companies. Private equity is moving away from traditional biotech roll-ups toward digital-first infrastructure plays, such as LIMS and automation platforms. Valuations are compressing for single-asset biotech firms but expanding for multi-modal platforms with in-house AI/ML capabilities. IPO and exit readiness now require both clinical and tech maturity, while firms lacking digital infrastructure face the greatest funding risk.

With TechBio firmly entrenched, here’s what the not-too-distant future looks like:

  • Prioritizing Platform over Pipeline: Investors are favoring companies with data platforms or AI discovery engines that can generate multiple assets, rather than a single-drug pipeline. Look at Flagship and Andreessen Horowitz (a16z) continuing to back repeatable discovery systems, such as Generate Biomedicines and Inceptive, instead of molecule-first approaches.
  • Computational Biology at a Premium: Companies with ML-native workflows, structured data ontologies, and in silico design capabilities are commanding higher valuations. Recursion Pharmaceuticals’ IPO and valuation, for example, were tied more to its image-based AI infrastructure than its lead program.
  • Cross-Disciplinary Teams as a Signal of Quality: Interdisciplinary founding teams that blend machine learning, systems biology, and engineering are seen as higher-execution risk mitigators. PE firms are increasingly conducting technical due diligence not just on pipelines, but also on the infrastructure stack, data operations, and software engineering.
  • Shift Toward B2B and SaaS Models in Life Sciences: A wave of investment is flowing into companies that serve the TechBio ecosystem, including cloud-native LIMS/ELN platforms, computational CROs, and automated lab systems. These provide recurring revenue, faster sales cycles, and infrastructure lock-in, metrics that closely align with the tech sector's investment benchmarks.
  • AI as a Defensibility Layer: VCs are heavily weighing proprietary AI models as part of the IP moat. It's no longer enough to own a sequence; firms must own the system that designs or predicts the sequence. Investors now look at data exclusivity, model performance, API extensibility, partner integrations, and model improvement over time.

TechBio: Redefining the Future of the Life Sciences

The life sciences funding environment is undergoing the same disruption that has reshaped fintech, media, and cybersecurity: from asset-centric investing to platform- and systems-centric investing. As biology becomes programmable, investors no longer seek the best drug; they seek the best engine for discovering, designing, and optimizing drugs.

The overarching implications of this include a shift to:

  • Hiring more software engineers and ML experts than lab techs
  • VCs seeking platform-first models with recurring data assets
  • Companies prioritizing cloud-native, ML-enabled workflows.
  • Faster, reproducible, and AI-augmented discoveries.

For companies, this means:

  • Building infrastructure before pipelines
  • Valuing reproducibility as a product
  • Prioritizing software engineers and bioinformaticians as co-founders
  • Designing business models around feedback loops, not just endpoints

The leaders of this next chapter won’t just discover, they’ll design biology as an engineered system, built on platforms, powered by data, and scaled with AI.

While Biotech commercialized biology, TechBio will make biology computational.

ELN screenshot
Digitalization

Digital Transformation in Biology: The Ultimate Guide to TechBio

Discover how TechBio is transforming life sciences by merging biology with AI, data architecture, and software engineering.

eLabNext Team
Zareh Zurabyan
|
5 min read

If you manage environmental health and/or safety (EHS) in a life science laboratory, you can set up safety protocols, and put up eye-spray stations that you test daily, but building a culture of compliance is a whole other can of worms. Furthermore, the link between EHS and sustainability efforts are not always top-of-mind for lab personnel.

So, how can you educate and compel researchers to be more sustainable?

In the modern lab, where digitalization continues to make research more efficient and streamlined, leveraging software platforms that centralize lab operations – including EHS and sustainability efforts – can help you avoid safety and sustainability mistakes that can cost millions of dollars and could lead to personnel injuries.

In this article, we’ll cover EHS in the life sciences, its link to sustainability,  how to enforce compliance digitally, leveraging tools such as ELN/LIMS, and the best practices for achieving this. Using a decentralized platform for EHS and other lab operations is a mistake you do not want to make, so we also introduce a new type of software tool for laboratories called a Scientific Management Platform (SMP), that combines EHS (especially Exposure Control), with your day-to-day ELN/LIMS.

Environment, Health, and Safety (EHS) in Life Sciences and Biotech

What is EHS?

EHS in life sciences and biotech involves policies and procedures designed to:

  • Protect the environment from biohazards and chemical pollutants.
  • Ensure employee health through safe practices and exposure controls.
  • Maintain workplace safety in laboratories, manufacturing, and research facilities.

EHS Areas of Focus

Environmental Protection

  • Waste Management: Disposal of biohazardous and chemical waste following strict guidelines.
  • Energy Efficiency: Implementation of green lab initiatives to reduce energy use.
  • Sustainable Practices: Incorporating biodegradable materials and reducing water use in lab operations.

Occupational Health

  • Exposure Control: Limiting exposure to pathogens, hazardous chemicals, and radiation.
  • Health Monitoring: Regular health screenings for employees working with toxic substances.
  • Mental Well-being: Programs addressing stress in high-pressure research environments.

Workplace Safety

  • Equipment Safety: Regular maintenance of autoclaves, centrifuges, and lab machinery.
  • PPE Compliance: Ensuring the use of lab coats, gloves, goggles, and respirators where necessary.
  • Emergency Readiness: Spill response training and protocols for accidents involving biological or chemical agents.

Top 10 EHS Examples in Life Sciences and Biotech

Academic and industry labs handle hazardous materials, dangerous equipment, and harmful biological agents. Effective EHS programs ensure compliance to mitigate the risks of these activities. Below are ten examples that highlight essential safety measures in these high-risk settings.

  1. Biowaste Management: Segregation and sterilization of biological waste.
  2. Fume Hood Usage: Safe handling of volatile chemicals and reagents.
  3. Pathogen Containment: Use of biosafety cabinets for handling infectious agents.
  4. Radiation Safety: Monitoring and control for radiological materials in research.
  5. Chemical Inventory Systems: Tracking and proper storage of hazardous substances
  6. Ventilation Systems: Preventing air contamination in laboratories.
  7. Incident Reporting: Documenting and analyzing lab accidents and near misses.
  8. Ergonomic Lab Design: Preventing repetitive strain injuries among researchers.
  9. Hazard Communication: Clear labeling and documentation of chemical and biological hazards.
  10. Training Programs: Regular EHS training tailored to biotech-specific risks.

Real-World Applications of EHS

The examples above apply to various sectors within the industry, from R&D to large-scale manufacturing.

  • Pharmaceutical R&D: Safely handling toxic reagents and ensuring GMP compliance.
  • Biomanufacturing: Managing emissions and waste from large-scale bioreactors.
  • Clinical Trials: Protecting researchers from potential pathogen exposure during specimen handling.
  • Gene Therapy Labs: Strict protocols for handling genetically modified organisms (GMOs).

Benefits of EHS in Life Sciences and Biotech

By tailoring EHS practices to the unique challenges of life sciences and biotech, organizations can achieve safer and more compliant operations while driving innovation. The benefits of EHS compliance include:

  • Ensures regulatory compliance (e.g., OSHA, WHO, IFC).
  • Reduces environmental impact of high-tech lab activities.
  • Enhances employee safety and operational efficiency.
  • Builds public trust by prioritizing ethical and sustainable practices.

What is the Link Between EHS and Sustainability?

EHS provides a foundation for a laboratory or organizations sustainability practices, by mitigating the environmental impacts of research, ensuring worker safety, and promoting efficient use of resources. In this context, sustainability refers to the adoption of business practices that meet present needs without compromising the ability of future generations to meet theirs. It involves integrating environmental stewardship, social responsibility, and economic viability to achieve long-term success.

EHS Integration with Sustainability:

  • Energy Use Reduction: Transitioning to energy-efficient lab equipment.
  • Carbon Neutral Labs: Offsetting carbon emissions from lab processes.
  • Water Recycling: Using closed-loop systems in biomanufacturing.

Sustainability Through Digitization: The Role of a Scientific Management Platform (SMP) in Labs and Institutions

Introduction to Lab Sustainability through Digitization

Sustainability in labs and research institutions extends beyond environmental conservation; it encompasses efficient resource use, minimizing waste, and adopting practices that ensure long-term viability.

Digitization, particularly through the adoption of Electronic Lab Notebooks (ELNs), Laboratory Information Management Systems (LIMS), or all-in-one SMPs plays a pivotal role in driving sustainability by reducing physical resource dependence and enhancing operational efficiency.

What is an SMP?

An SMP is a digital ecosystem that unifies lab operations, digital research, and EHS. It’s distinguished from other ELN and LIMS platforms in that it is a single platform that serves the needs of an entire life science organization, including scientists, lab operations professionals, EHS and compliance personnel, and leadership.

Impact of an SMP on Lab Sustainability

1. Reduction of Paper and Physical Resource Use

  • Traditional Practices: Labs have historically relied on paper-based lab notebooks, forms, and records, leading to significant paper waste.
  • Digitized Solution: SMPs, as well as ELNs and LIMS, eliminate the need for physical notebooks and documentation, significantly reducing paper usage. A large institution can save thousands of sheets of paper annually by transitioning to digital systems.

2. Streamlining Data Management

  • Resource Optimization: SMPs, ELNs, and LIMS centralize data storage, eliminating redundancies and enhancing accessibility, thereby reducing the energy costs associated with manual data retrieval and storage.
  • Cloud Integration: Many systems operate on energy-efficient cloud platforms, further reducing on-site energy consumption.

3. Decreasing Redundancy and Waste

  • Inventory Control: SMPs and LIMS improve inventory management, ensuring efficient use of reagents and consumables, reducing overstocking, and minimizing expired materials.
  • Experimentation Efficiency: SMPs and ELNs support accurate experiment tracking, preventing redundant trials and saving time and resources.

4. Energy Efficiency in Lab Operations

  • Digitally Monitored Systems: SMPs and LIMS can integrate with lab equipment to optimize energy usage, such as monitoring freezers, incubators, and other devices.
  • Scheduling and Maintenance: These platforms help schedule equipment usage and maintenance, reducing unnecessary energy consumption.

5. Waste Management and Compliance

  • Traceability: LIMS and SMPs enhance the traceability of samples and reagents, ensuring proper disposal of hazardous materials and compliance with environmental regulations.
  • Analytics: The analytics modules in these systems can identify wasteful practices and recommend more sustainable workflows.

6. Remote Collaboration and Access

  • Virtual Collaboration: SMPs and ELNs enable remote data sharing and collaboration, reducing the need for physical presence and associated travel, contributing to lower carbon footprints.
  • Global Integration: Institutions can collaborate globally without duplicating experiments or resources.

Impact of an SMP on Institutional Sustainability

1. Institution-Wide Standardization

Digital systems promote uniformity across labs, ensuring sustainable practices are maintained at every level. Standardization also enables new personnel to quickly and easily adopt standardized practices during onboarding.

2. Educational and Training Benefits

Digital platforms make sustainability training more effective by integrating real-time data tracking and eco-conscious decision-making.

3. Long-Term Cost Efficiency

Though initial implementation costs are high, digitization reduces operational costs in the long term by minimizing resource wastage and improving process efficiency.

4. Scalability and Growth

Digitized labs are better equipped to scale sustainably as they require fewer physical expansions and utilize resources more efficiently.

Impact of an SMP on Global Sustainability

1. Alignment with SDGs

Digitized labs contribute to the United Nations’ Sustainable Development Goals (SDGs) by promoting responsible consumption and production (Goal 12) and climate action (Goal 13).

2. Carbon Footprint Reduction

Digitally driven labs contribute to global carbon reduction efforts through energy efficiency, reduced paper use, and waste minimization.

3. Circular Economy Participation

By optimizing resources and ensuring traceability, labs using ELNs and LIMS align with the principles of a circular economy.

Driving Safety and Sustainability Through Lab Digitalization

Digital tools, like SMPs, are transforming life science labs and organizations by enhancing safety, sustainability, and efficiency. As EHS initiatives align with sustainability goals, platforms like ELNs, LIMS, and SMPs streamline compliance, reduce waste, and optimize operations.

SMPs, in particular, centralize lab management, ensuring resource efficiency, data traceability, and proactive safety measures. By embracing digital transformation, labs can foster a culture of sustainability, minimize environmental impact, and enhance operational excellence, positioning themselves for long-term success in an evolving scientific landscape.

To learn more about SMPs and their role in lab safety and sustainability, contact us.

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Security & Compliance

Digital Tools for Safer and More Sustainable Life Science Labs

Learn how digital tools, like Scientific Management Platforms (SMPs) enhance safety, sustainability, and efficiency in life science labs.

eLabNext Team
Zareh Zurabyan
|
5 min read

There’s a quiet crisis going on in the life sciences.

Not one of discovery, but of trust.

For decades, researchers have pushed the boundaries of what we can cure, engineer, and sequence. But underneath the innovation lies a foundation that's worryingly fragile.

The uncomfortable truth?

Most published studies in biology can’t be reproduced, even by the original authors.

The cost?

Billions in lost R&D, failed drug programs, and an erosion of confidence in the scientific process itself.

This isn’t a story of bad actors or malicious data fabrication (though those certainly happen). It’s a story of fragmentation, friction, and foundational dysfunction.

Problems with Reproducibility: The Facts

In the last two decades, several hard truths about scientific reproducibility have come to light:

These numbers aren’t just headlines; they’re a mirror held up to the industry. These reports come from companies with billion-dollar drug pipelines, published in reputable journals. The data cannot be ignored and the implications ripple far beyond the lab bench.

From Pen & Paper Problems to Digital Chaos

Reproducibility issues aren’t new.

In the era of paper lab notebooks, the culprits were often simple: illegible notes, missing details, inconsistent materials, and poor documentation. But now, the scientific community faces a different kind of problem; one created by digital overload and systemic fragmentation.

Today’s labs are full of digital tools – electronic lab notebooks (ELNs), laboratory information management systems (LIMSs), etc. –  that streamline a number of day-to-day tasks.

However, there’s a lack of infrastructure to integrate these various tools and their users:

  • Protocols may live in one of several ELNs, often not standardized across teams.
  • Sample data and experimental results are siloed across spreadsheets, cloud folders, or aging LIMS platforms.
  • APIs, if they exist at all, are brittle and rarely support real-time data harmonization.
  • Automation platforms create structured data that cannot be easily integrated or analyzed alongside other tools.
  • Contextual data, including decisions, anomalies, tribal knowledge, isn’t formally documented from digital communication tools, like Slack and email threads.  

We moved away from notebooks, in favor of “more organized” digital record-keeping, only to land in a more complex, distributed lab environment. The reproducibility crisis isn’t the result of carelessness; it comes from an inefficient digital lab ecosystem.

The Franken-stack: How We Got Here

Most labs didn’t build for scale, they patched.

A spreadsheet here.

An ELN over there.

A homegrown LIMS no one dares touch.

As science became more complex, so did the software stack, but without a plan for how all of these technologies would integrate.

What we’re left with is a "Frankenstack": Dozens of disconnected systems, none of which talk to each other cleanly.

  • ELNs exist in silos, with no connection to sample registries.
  • LIMS are often bespoke and inflexible, designed for QC workflows, not R&D experimentation.
  • Data analysis tools require manual data cleaning before use.
  • Inventory systems are either Excel-based or completely disconnected from experiment design.
  • Communication about experimental context lives outside these systems — in email, Slack, or memory.

This patchwork stack fragments context, introduces human error, and makes knowledge non-portable.

The consequence?

Reproducibility is impossible to guarantee because the inputs, conditions, and decision points are scattered and ephemeral.

Why Infrastructure Matters More Than Ever

Reproducibility doesn’t fail at the point of analysis, it fails in the moment data is captured, recorded, and stored. If scientific outputs are generated without structure, traceability, or context, the ability to replicate them becomes hopeless.

The solution isn’t more tools.

It’s better infrastructure:

  • Centralized platforms that unify sample tracking, data entry, protocol versioning, and results in one workflow.
  • APIs that do more than connect systems; they standardize data across them.
  • Audit trails that are automatic, comprehensive, and human-readable.
  • Tools that don’t just collect information, but turn it into structured, mineable insight.

These aren’t "nice-to-haves." They’re the foundation for building modern, resilient scientific organizations.

Why Infrastructure is Everything

It’s easy to think of infrastructure as “the pipes behind the walls.” But in life sciences, your infrastructure is your science.

Whether you’re managing molecular assays, CRISPR edits, sample transfers, or regulatory data, your tech stack shapes what’s possible, what’s traceable, and ultimately what’s reproducible.

Right now, too many organizations are building high-stakes science on low-integrity digital foundations.

What Does Infrastructure in Life Sciences Actually Mean?

It’s more than software. True digital infrastructure for scientific R&D means:

  • Standardized Data Models: Consistent formatting, structure, and taxonomy across experiments, instruments, and departments.
  • Workflow-Driven Systems: Tools that reflect how real scientific work happens, not just generic data entry forms.
  • Interoperability by Design: APIs and integrations that are robust, real-time, and allow seamless data flow between systems.
  • User Accountability & Audit Trails: Every action tracked and contextualized, automatically.
  • Scalable Configuration: The ability to evolve as science evolves, without technical debt or vendor lock-in.
  • Searchable, Structured Data Lakes: Not just storage, but queryable knowledge for retrospective analysis, meta-studies, and ML readiness.

This infrastructure is what separates scientific documentation from scientific intelligence.

What Good Infrastructure Looks Like

To get reproducibility right, we need to think like systems architects, not just scientists.

A reproducibility-ready infrastructure is:

1. Unified

All core experimental functions, including sample tracking, protocol execution, data capture, and result analysis,  live in a single connected platform or are interoperable by design.

2. Context-Rich

Every result is linked to its experimental conditions, sample lineage, protocol version, and user interaction history automatically.

3. API-first

The system is built to push and pull data in real time, enabling automation, dashboards, and analytics without data silos.

4. Flexible

You shouldn’t need a full migration every time your sample type, equipment, experimental workflow, or reagents change. Good infrastructure is modular, configurable, and adaptable to evolving workflows.

5. Designed for Discovery

Data doesn’t just sit in silos. It’s structured and indexed so teams can learn from it. AI and ML can only add value if the data is consistent and queryable.

This Isn’t Just IT’s Job; It’s a Strategic Priority

Behind every workflow is an infrastructure decision, made intentionally, or by default.

If the goal is to accelerate drug development, pass regulatory audits, or scale teams globally, infrastructure isn’t a backend function, it’s a core driver of scientific velocity.

The difference between a lab that consistently innovates and one that drowns in its own data often comes down to this:

Do you control your infrastructure, or does your infrastructure control you?

Elevating the User Experience (UX)

Ask any scientist how they spend their day, and you won’t hear “pushing the boundaries of molecular innovation.”

You’ll hear something more like: “I was digging through old ELN entries, chasing down a protocol version, cross-checking a spreadsheet, and trying to remember what that weird sample label meant.”

This is not a software problem.

This is a user experience (UX) problem.

The Solution: A Unified Lab Platform That Prioritizes SX

The future of scientific work will not be defined by feature lists or flashy dashboards; it will be defined by how easy it is to find, trust, and act on critical data.

This is where a unified platform becomes essential; particularly one that:

  • Brings experiments, samples, protocols, and results into a single, connected workspace
  • Lets scientists move seamlessly from planning to execution to analysis, without leaving the system
  • Embeds communication, approvals, and auditability into the workflow itself
  • Surfaces contextual insights, not just files, when they’re needed most
  • Is designed with the actual scientist in mind, not just IT admins or regulatory reviewers

This is what it means to prioritize UX.

What UX-Driven Lab Platforms Enable: Reproducibility and More

When the platform is unified and intuitive, the benefits are immediate and exponential:

  • More reproducible results because all actions and data are captured in context
  • Faster onboarding for new scientists who no longer need to learn six tools to get started
  • Better collaboration between bench scientists, computational teams, QA, and leadership
  • Clearer handoffs between professional services, customer success, and commercial teams
  • Stronger data integrity across the entire lifecycle of a project

UX is not a luxury; it’s the critical layer that enables science to scale, safely and intelligently.

You Can’t Fix Science Without Fixing the Scientific Experience

If we care about speed, reproducibility, and collaboration, we have to care about experience. Because scientists don’t just need better tools, they need better systems that align with how they think, work, and share knowledge.

And that system needs to be unified, intuitive, and built for the realities of modern R&D.

UX must become central to how we build the next generation of scientific platforms.

Because when scientists are empowered to focus, to find clarity, and to trust their systems, they don’t just work better — they discover faster.

To learn more about how to optimize your lab, contact us for a free 30-minute consultation.

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Digitalization

Repairing Reproducibility: Fixing Digital Chaos with Better Infrastructure

Learn how digital chaos and Franken-stack’s are making the reproducibility crisis in the life sciences worse and how a unified platform can change everything.

eLabNext Team
Zareh Zurabyan
|
5 min read

Boston, MA--SciSure, the Scientific Management Platform (SMP) designed to unify scientific research, safety, operations, and compliance, today announced a strategic partnership with US Lab Partners, a leader in lab and facility operations and EHS (Environmental Health &Safety) consulting. Together, the organizations are launching a transformative “Virtual Incubator Model” that gives emerging and scaling life science organizations affordable access to world-class digital lab infrastructure and operational support.

Unlocking Modern Lab Management for Scientific Entrepreneurs

Emerging life science organizations have long faced a costly challenge: accessing high-quality EHS, lab operations, and compliance infrastructure before they have the resources or scale to support large software investments. The new SciSure and US Lab Partners collaboration eliminates this barrier. By combining SciSure’s comprehensive, scalable software suite with US Lab Partners’ expert consulting and implementation services, these organizations can now operate efficient, safe, and compliant labs from day one.

“Our customers have often told us they needed digital infrastructure long before they had the budget or internal resources to manage it,” said Philip Meer, CEO of SciSure. “This partnership ensures they no longer have to choose between premium software or on-the-ground expert services—they get both, seamlessly integrated.”

Better Together: A Complete Solution for Emerging Labs

US Lab Partners provides deep, hands-on expertise in lab setup, operations, and EHS compliance. They become an extension of the customer's internal team, guiding labs through complex requirements and day-to-day operations. SciSure complements this with an industry-leading platform encompassing Electronic Lab Notebooks (ELN), Laboratory Information Management Systems (LIMS), inventory tracking, and EHS workflows—all in one secure and scalable environment.

“Too often, emerging scientific companies are forced to rely on underpowered tools—systems that create data silos and are little more than glorified spreadsheets,” said Jon Zibell, Vice President of Global Alliances and Marketing at SciSure. “This partnership is designed to change that. We are delivering a seamless digital experience from day one, without sacrificing safety, compliance, or data integrity.”

“Digitizing lab operations is no longer optional—it’s critical for continuity, safety, and scientific integrity,” said Demet Aybar, CEO and Founder of US Lab Partners. “Together with SciSure, we’re delivering world-class software and hands-on expertise that have traditionally been reserved for Big Pharma, now accessible to startups and academic innovators.”

Impacting the Future of Scientific Innovation

This partnership marks a pivotal shift in how scientific organizations can launch and operate. By eliminating the traditional burden of high costs, fragmented systems, and lack of technical resources, the Virtual Incubator Model accelerates innovation while reducing overhead and risk.

Customers now gain access to:

  • A fully digital and seamlessly integrated record-keeping system from day one
  • End-to-end EHS and inventory management software and services
  • A robust LMS with training content library
  • Trusted partners who bring both software and service to manage lab setup, safety, and compliance
  • ELN, LIMS, SOP’s, and Sample Management built-in

“This model reflects our shared mission: to help brilliant science thrive without operational bottlenecks,” Aybar added. “We’re here to make world-class lab infrastructure available without compromise.”

About SciSure

SciSure is the world’s first Scientific Management Platform (SMP), combining eLabNext’s Digital Lab Platform and SciShield’s trusted LabOps and EHS software into a unified solution designed by scientists, for scientists. SciSure supports over 550,000 Scientists, over 40,000 labs, and over 800 scientific organizations worldwide.

About US Lab Partners

US Lab Partners is a trusted leader in lab and facility operations and EHS consulting, helping life sciences companies and academic institutions design, launch, and operate scalable, compliant lab environments. Their experts help customers navigate regulatory landscapes, ensure compliance, and build lab environments that scale with scientific ambition.

Media Contact:

Jon Zibell
Vice President of Global Alliances & Marketing
j.zibell@scisure.com

Kyrie Stevens
Chief Business Officer, US Lab Partners, LLC
kyrie@uslabpartners.com

ELN screenshot
News

US Lab Partners and SciSure Launch Strategic Partnership to Transform EHS Services and Lab Operations

SciSure and US Lab Partners launch a Virtual Incubator Model to bring top-tier lab software and EHS support to emerging life science labs.

eLabNext Team
SciSure Team
|
5 min read

Let’s be honest—lab data is everywhere… just not where you need it, how you need it or when you need it.

You finish an experiment, type up your notes, log your samples, maybe even update a spreadsheet. Then weeks later, someone needs that same dataset—and suddenly you’re trawling through five different systems to piece it all back together. Sound familiar?

This is where the FAIR data principles come in. An acrynym for Findable, Accessible, Interoperable and Reusable, FAIR has become the gold standard for scientific data management and stewardship—but in most labs, they’re still more of an aspiration than reality. And the biggest hurdle? Fragmentation.

When your core digital lab systems—from Electronic Lab Notebooks (ELNs) to Lab Information Management Systems (LIMS)—don’t talk to each other, even the best science ends up buried in silos. It’s harder to share, harder to track, and almost impossible to reuse meaningfully without substantial manual effort or starting from scratch.

But things are changing. As more labs move toward integrated digital systems, interoperability and reusability are no longer pipe dreams—they’re becoming the new baseline. With the right platform in place, FAIR data can stop being a headache and start being a superpower.

The cost of fragmented systems and teams

Most labs don’t suffer from a lack of data—they suffer from a lack of framework.

One team logs experimental details in an ELN. Another updates sample records in a LIMS. Safety teams track hazardous materials and proceedures in four different standalone HSE systems. Procurement runs two different punch-out systems. IT tries to hold it all together with a few brittle integrations and a lot of crossed fingers.

This fragmentation isn’t just inconvenient—it’s corrosive. When systems don’t talk to each other, data can get duplicated, mislabeled or lost entirely. Scientists waste time chasing missing context, trying to validate results they didn’t generate, or re-running experiments that should’ve been reusable. Compliance becomes a nightmare. Audit trails break down. And collaboration slows to a crawl.

Worse still, disconnected systems foster disconnected teams. Everyone works hard—but in isolation. When every department has its own tools, its own workflows, its own naming conventions, even rudimentary questions can be complex. Which version is the latest? Who owns this dataset? Is it safe to reuse? Can we trust it?

It’s a heavy cost, paid in wasted hours, delayed results, missed insights and sometimes, preventable errors. And in a research landscape where funding is tightening, timelines are short, and patients are waiting, labs simply can’t afford to be this inefficient.

Rethinking the digital lab

So, what happens when systems start working together?

When your ELN, LIMS, HSE and other key tools don’t just coexist, but connect—you unlock something far greater than the sum of their parts. You get a lab where data flows freely, where processes are standardized, and where every team pulls in the same direction.

That’s what a Scientific Management Platform (SMP), like the one we’re building at SciSure, delivers. It unifies the once disconnected digital point solutions into a true home base for the lab. By embedding interoperability across your lab’s ecosystem, it turns isolated databases into a shared, transparent operational backbone.

The result? A single source of truth. Experiments logged in the ELN are automatically linked to sample records in the LIMS. Safety data and records update in real time across both EHS HSE and inventory logs. Procurement knows what’s in stock without needing to ask. Everyone sees the same data, in the right context, without manual data transfer, syncing or version control nightmares.

But what about your lab’s specific needs? A truly comprehensive platform should let you integrate the tools you rely on, whatever your research focus. That’s why we've put Custom Software Integrations and Software Development Kits (SDKs) at the heart of the SMP. Whether you're connecting a barcode reader, a microscopy suite or want to onboard your own in-silico modelling engine, the SDK lets you customize workflows and build extensions that work your way.

SciSure is built for that kind of flexibility. With 40+ (and growing) ready-to-use integrations and a developer toolkit that empowers labs to connect just about any system, it ensures your digital infrastructure is future-proof – ready to scale and adapt alongside your science.

And the impact goes far beyond convenience. Unified systems mean fewer errors, faster decisions, richer audit trails and reproducibility by default. Instead of bending your processes to fit the software, you can finally make the software fit your science.

How the Scientific Management Platform supports FAIR data

FAIR data is more than a framework—it’s the foundation for faster research, easier collaboration, and insights that don’t get lost in the shuffle. But achieving it takes more than good intentions. It takes systems that are connected, consistent, and built for scale.

Here’s how SciSure’s SMP helps labs turn the FAIR principles into everyday practice:

Findable

Disconnected systems bury information. SciSure makes it easy to find what you need—instantly and in context.

  • All data entries (samples, protocols, experiment records) are fully searchable.
  • Standardized metadata and tagging improves indexing and retrieval.
  • Centralized dashboards help users locate resources across ELN, LIMS and inventory in seconds.
  • Audit trails track who created what and when—so nothing is lost in handover.

Accessible

Data locked away in silos slows everything down. SciSure ensures authorized users can access the data they need without risking compliance.

  • Role-based permissions control who sees what across departments.
  • Cloud-based access from any device ensures data is never location-locked.
  • Real-time collaboration allows multiple users to contribute without duplication.
  • Historical data remains readable and structured—no more out-of-date formats or software dependencies.

Interoperable

When systems don’t speak the same language, you’re stuck with manual workarounds. SciSure connects the dots—automatically.

  • Integrates ELN, LIMS, instruments and data sources into one ecosystem.
  • Open API (Application Programming Interface) enables seamless communication between systems.
  • Software Developer Kit empowers custom integrations tailored to your lab’s tools and workflows.
  • Harmonized data formats make downstream sharing, analytics and AI integration easy.

Reusable

Data reusability means more than just accessing old data—it means being able to rely on it, repurpose it, and build on it without starting from scratch. SciSure makes reusability the default, not the exception.

  • Embedded protocol versions, annotations and user history ensure traceability.
  • Structured data formats make it easy to rerun analyses or replicate experiments.
  • Data from past projects can be re-applied, modelled or scaled—without starting from scratch.
  • AI tools can ingest structured data directly, unlocking new insights from old experiments.

FAIR data for successful AI integration

AI is no longer a future possibility; it’s already being embedded into lab workflows to accelerate discoveries and optimize workflows. But for AI to work effectively, it needs fuel. And not just more data—structured data.  

Machine learning models depend on clean, consistent, structured datasets to do their job. That means the way data is collected, labelled, and stored has a direct impact on what AI can achieve. This is where the SMP’s FAIR data becomes essential. Standardized formats. Clear metadata. Full experimental context. All indexed and accessible in real time.

Instead of spending months cleaning up legacy datasets, researchers can build AI-ready data by default. Whether you’re training a toxicity model, scaling high-throughput screening, or feeding historic assay data into a predictive engine, the infrastructure is already in place.

Better still, the system evolves with you. As models generate insights, those results can be looped back into the platform—tagged, timestamped and ready for re-analysis or verification.

AI can’t thrive in a data swamp. But with a FAIR data foundation and the right digital architecture, it becomes a powerful partner in discovery.

Make FAIR data work for You

FAIR data is much more than a buzzword. It’s becoming the baseline for credible, collaborative, future-ready science. But getting there means more than aligning with principles on paper. It means rethinking how your lab works—how data is created, shared, and used.

Connected platforms like SciSure’s Scientific Management Platform give labs the tools to make that shift. By unifying ELN, LIMS, HSE and more—while enabling deep custom integration—they turn FAIR into something practical, powerful and future-proof.

The result? Research that moves faster, teams that work better together and data that keeps on delivering long after the experiment is completed. If you’re ready to unlock the full value of your lab’s data—findable, accessible, interoperable and reusable by design—it’s time to get connected.

Contact us today to unlock the power of FAIR data in your lab!

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Security & Compliance

FAIR Data, Better Science: Why Connected Labs Are the Future

FAIR data means better science. Learn how unifying ELN, LIMS and HSE into a central SMP supports reproducible results, data reuse and AI readiness in labs.

eLabNext Team
Nathan Watson
|
5 min read

Streamlining Chemical Inventory Reporting for Fire Safety

Managing chemical inventory can be a daunting task for laboratories of all sizes.

From tracking quantities toward building fire codes and MAQ limits to staying on top of regulatory reporting requirements, the complexities can quickly overwhelm even the most organized teams.

But with the advent of chemical inventory reporting solutions like SciSure for Health & Safety (formerly SciShield), labs are experiencing a revolution in efficiency, organization, and safety.

Now we will explore the benefits of accurate, real-time reporting tied to your chemical inventory and dive into how these systems are transforming chemical inventory reporting, one click at a time:

Stay organized and eliminate storage chaos by digitizing your chemical inventory with container level tracking in real-time.

Efficiency

Chemical inventory reporting solutions make your team more efficient by reducing the time spent on common tasks by up to 80% — meaning that a task that normally takes you an afternoon to complete will take just a few minutes.

Instead of manually calculating totals toward MAQ limits, for instance, chemical inventory reporting software can do this for you. Not only does this save you time, it also reduces the chance of human errors.

What’s more, chemical inventory reporting software will make managing your chemical inventory easier. You can track containers, view storage recommendations and expiration dates, and complete audits on the go from any mobile device. This frees up scientists' time to focus their core work like applying for grants and conducting research while keeping your labs safe and compliant.

Organization

Chemical inventory reporting software provides a centralized platform for managing your chemical inventory data. Users can easily input, store, and update information about the chemicals they have on-site, including details like quantities, locations, and expiration dates.

The best chemical inventory solutions don’t stop there, though. They also offer real-time monitoring capabilities, allowing you to track changes in your chemical inventory as they occur. This helps you stay up-to-date with your reporting obligations and proactively manage chemical hazards.

Hazard Identification

With potentially hundreds of chemicals on hand, identifying the hazard profile of each one is a time-consuming task. But with a chemical inventory reporting software, it doesn't have to be.

Your software should allow you to instantly see the hazards associated with any chemical in your inventory. You don’t have to go searching for an SDS online or in a binder because that information is readily available at your fingertips.

Additionally, chemical inventory reporting software should give you a “big picture” view of chemicals and high-hazard materials in your labs. Which chemicals count toward your flammable solvents limit? How many peroxide formers are set to expire by the end of this month? With chemical inventory reporting software, these questions are easy to answer.

Accurate Reporting

With effective chemical inventory software, there’s no need for Excel spreadsheets full of complicated formulas and calculations. By pulling relevant data from the centralized database, chemical inventory reporting software automates the process of generating regulatory reports, such as Tier II/Right-to-Know (RTK) reports, streamlining reporting processes, meaning you won’t be scrambling to get it done before the deadline.

As we mentioned above, one of the key features of chemical inventory software is its ability to track containers in real-time. This means that as changes are made to the chemical inventory, such as additions, deletions, or updates, the software automatically reflects these changes in your regulatory reports. This real-time synchronization ensures that reports are always up-to-date and accurate.

Compliance

Chemical reporting software empowers labs to efficiently manage their chemical inventory, enhancing accuracy and streamlining reporting – achieving compliance with fire codes and MAQs is simplified.

As fire code regulations evolve chemical inventory software will help you to maintain compliance. By storing all your chemical data in a single place, you'll have instant access to the information you need to adapt to changes. You'll never have to worry about the unknown of fire code compliance and MAQs because you can easily compare your current inventory with the new regulations.

Scalability

With more time to focus on research and funding opportunities thanks to your chemical inventory software, you might find your lab operations growing. The good news is that a robust software system like SciSure will scale with you as you grow.

As your operations expand, SciSure can accommodate increasing amounts of chemical inventory data and support additional users without sacrificing accuracy or efficiency. You can even manage permissions for different users or groups based on their job description (e.g., lab member, PI, etc.). This ensures that individuals throughout your organization are only able to view or change information that is relevant to their role.

Safety

At the end of the day, chemical inventory software makes your labs safer by helping you manage hazardous materials more effectively. It enables precise tracking of chemicals throughout their lifecycle, from purchase to disposal, so you can proactively address fire hazards such as expired chemicals or incompatible storage.

And, in the event of a fire, chemical inventory software is — quite literally — a lifesaver. Having access to an accurate chemical inventory, complete with the quantities and locations of chemicals, enables emergency responders to quickly assess the situation, identify potential hazards, and take appropriate measures to protect personnel and property.

Take control of your chemical inventory

Chemical inventory software solves the headache of fire code compliance and regulatory reporting by giving you control over your chemical inventory once and for all, organized and in compliance — with regulatory reporting in real-time, in just a few clicks. Next, learn about the key features to look for in chemical inventory software.

The power of accurate, real-time chemical reporting is the key to mitigating risks and enhancing fire safety.

Your takeaway

With the right software solution, you can save hours and days of complex report pulling for your regulatory reporting, MAQ's, TierII/RTK, and Fire Code compliance.

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Environmental, Health & Safety

Streamlining Chemical Inventory Reporting for Fire Safety

Chemical inventory software solves the headache of fire code compliance and regulatory reporting by giving you control over your chemical inventory.

eLabNext Team
Mark Esposito
|
5 min read

BOSTON, MA (April 2, 2025)GA International, a global leader in laboratory identification solutions, under its LabTAG brand, announced today that its DYMO® LabelWriter™ 5-Series Printing Kits are now compatible with SciSure (formerly eLabNext)—an intuitive and flexible system for collecting, managing, and analyzing laboratory information. The integration is available in the eLabMarketplace through an Add-on, and provides researchers with a reliable, precise, and user-friendly solution for labeling in critical laboratory workflows.

“We’re excited to expand our partnership with SciSure by introducing this Dymo® LabelWriter™ 550 Add-On,” comments George Ambartsoumian, Founder and CEO of GA International. “This tool allows researchers to print labels directly from the eLabNext interface, making sample identification faster, easier, and more reliable. It’s another step forward in our shared mission to streamline lab workflows and improve sample and data management in laboratories.” 

The Add-on allows users access to pre-designed label templates tailored for LabTAG’s specialized DYMO-Branded CryoSTUCK® Labels directly within SciSure. These templates are optimized for the Dymo® LabelWriter™ 5-series printers, ensuring perfect formatting, dimensions, and layout alignment. This eliminates the need for manual adjustments and enables effortless label printing in just a few clicks. By combining the affordability of the Dymo® LabelWriter™5-Series (550, 550 Turbo, and 5XL) with LabTAG's durable cryogenic labels, the Add-on also offers a cost-effective labeling solution, particularly beneficial for labs working on a tight budget.

“We jump on every opportunity to enhance our platform by integrating tools that simplify workflows, collaborating with companies that share our passion for sample and data management, and streamlining lab operations for our users,” says Zareh Zurabyan, VP of Commercial, Americas. “This recent collaboration with LabTAG is a win for everyone and ensures that labs can focus on their research with confidence, knowing their labeling needs are met with innovative and reliable technology.” 

To learn more about SciSure and how to connect with LabTAG’s Dymo® LabelWriter™ 550 Printer Add-on, visit the Marketplace.

About LabTAG

GA International has over 25 years of experience as a leading manufacturer of specialty labels, supplying laboratory identification solutions to biomedical research labs, biobanks, hospitals, and other healthcare institutions. Since its inception, GA International has become a worldwide leader in cryogenic and chemical-resistant labels, strongly dedicated to R&D and customer service. 

For more information about GA International, please visit www.labtag.com

Press contacts

For Media & Communication Inquiries

Ishan Wadi, Marketing Leader
ishan.wadi@ga-international.com

For Technical Inquiries Related to the Add-On

Alexandre Beaudoin Gagne, IT Director
alexandre.beaudoin@ga-international.com

ELN screenshot
News

New LabTAG Add-On Streamlines Laboratory Labeling with Dymo® LabelWriter™ 5-Series and SciSure Integration

LabTAG’s DYMO® LabelWriter™ 5-Series Printing Kits now integrate with SciSure, offering labs a reliable and user-friendly labeling solution via the Marketplace.

eLabNext Team
|
5 min read
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