Your go-to blog for modern lab management

This article was originally published by eLabNext prior to its integration into SciSure. SciSure was formed in 2025 through the merger of eLabNext and SciShield.

Gone are the days of manual stocktaking and juggling spreadsheets in many laboratories. With the natural evolution of laboratory digitalization, over 60,000 scientists now rely on eLabNext to manage their complete lab inventory in their daily operations. As the use of the eLabNext platform has grown, we’ve received a tremendous amount of feedback and suggestions from our customers on how to enhance and extend the usability and functionality of eLabNext's inventory management system. After an extensive development phase, during which we completely overhauled the inventory system, we rolled out a beta version to our customers in 2023. This pivotal step has allowed us to gather invaluable insights, paving the way for a broader release aimed at elevating the industry's leading inventory management system to even greater heights of excellence.

In this blog post, we're diving into the key features and improvements we've incorporated into our new inventory management system. We’ll also share our plans for future updates and refinements to enhance its functionality even further.

Breaking Down the Features and Enhancements

This new inventory system incorporates some of the most highly requested features, improvements, and enhancements submitted by our customers. Here are the top 10 new features:

1. Enhanced Overall User Interface and Usability

The new inventory system has been fully reworked based on our new UX/UI standards to enhance the overall look, feel, and usability of the module. These changes also align with expectations set for modern software accessibility compliance, according to the Web Content Accessibility Guidelines (WCAG).

2. Flexible Three-column Panels

Among the most requested improvements was the ability to visualize compartment and sample information on the same page. To address this, we've introduced a third panel that opens next to the compartment view, allowing users to easily view information on any sample within a compartment. Users can now also expand and collapse panels and customise the width of each panel according to their preferences.

3. Enhanced Usability for Moving Samples

In line with the modernization of software tools, we've introduced a more intuitive way to organize your sample boxes. We've incorporated options for selecting multiple samples at once, allowing users to move samples through drag-and-drop to a different position within the box.

4. Collapsible Sample Series

Sample series can now be expanded within the sample list to easily visualise and manage the sample stocks that are part of a series. This functionality enables users to perform bulk actions on parts of the sample stocks within a series.

5. Group-shared and Customizable Views

Throughout the inventory, users can choose which data columns to display by adjusting the view. The width of columns can easily be adjusted to customize the table view according to the user's content and preferences.  Once a custom view is saved, it can be shared across all sample lists throughout the inventory. Additionally, these saved views can now also be shared with other users in the group, enhancing collaboration and consistency.

6. Improved Visualization of Compartments and Bulk Actions Support

We have enhanced the overall visualization of compartments and their properties. Users can now view compartment properties directly from the inventory browser, including limits, storage capacity, and the status of compartments when assigned to users or shared. Furthermore, users can perform bulk actions, such as printing labels or moving compartments, on multiple compartments at a time.

7. New Export Options for Samples

New extended options for exporting samples have been introduced. Users can now directly export lists of samples based on their selected list view. Supported export formats include PDF, Excel, and CSV, making it easier to share and analyze data outside the platform.

8. Sample and Location Selection

Addressing feedback about inefficiencies, we've improved the process of linking samples to experiments or other samples by allowing users to search for and select multiple samples before linking. Location selection has been enhanced for adding samples as sample series, through batch import, or when cloning, by enabling the selection of multiple locations if the created sample batch size exceeds available space in a compartment.

9. Full Compatibility with Our API and SDK

The inventory system is fully based on our API and compatible with our Software Development Kit (SDK). Most add-ons have been adjusted to ensure full compatibility with the new inventory system. This allows users and partners to more easily utilise eLabNext Developer, our API, and SDK to build, test, and release add-ons to the marketplace.

10. Other Improvements and Enhancements

• Enabled the option to enter a reason when archiving samples.
• Added the option to display the full location path in sample lists.
• Introduced the option to add a sample to the created series when cloning into a sample series.
• Reworked reservations as Assignments for Storage Units and Bookings for Equipment.
• Change owner function is now available as a sample action button.
• Tasks linked to samples are now displayed in a separate tab.
• Status icons for assigned, shared, and validation required on equipment and storage units.
• The number of samples that can be imported has increased to 400.
• Improved flow for adding samples to multiple locations when adding a sample series, either through cloning or regular addition.

Continued Development on Inventory Management

The major updates to the inventory system lay the foundation for further enhancements that we have planned for eLabNext in the coming years. We will continue to refine and improve our other existing inventory-related functionalities, including the Sample Archive, Advanced Search, Storage Units and Equipment, and our Supplies and Ordering System. Our goal is to ensure a fully seamless, consolidated, and flexible sample and inventory management experience for any R&D laboratory. Additionally, we are committed to delivering some of the most requested features by our customers, such as:

• Integration of equipment into the Electronic Lab Notebook (ELN).
• Email notifications for expired samples or equipment requiring validation.
• Support for setting multiple parents for a sample.
• Cloning samples to a different sample type.
• Changing the sample type for an existing sample.
• Bulk cloning of samples.
• Enhanced stock tracking and reordering.
• Improved inventory searchability, filtering, and reporting.
• Sharing of samples across groups and limiting access to samples within those groups.

If you have any questions about the feature improvements, please don't hesitate to contact us.

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Creating a biotech start-up comes with many tasks and challenges, along with the excitement of building out your company and business model. As you work in the early stages of hiring, fundraising, and meeting with investors, you also have a major operational focus on driving the science forward and building the laboratory infrastructure for your team.

Whether you are set up in a co-working/incubator space or opening a lab at a university, you’ll need to start managing inventory, equipment service schedules, ordering consumables and supplies, and, more importantly, handling new samples. Typically, many fall back on old habits from previous lab environments, including spreadsheets for tracking inventory, word processors for protocols, and physical notebooks for experimental recording and calculations. With the current AI/ML-enabled world of biotech, this is analogous to using a Polaroid to (unironically!) take photos or a landline to make phone calls.

Conversely, Digital Lab Platforms (DLPs) are the “smartphones” of your lab, an all-in-one solution that can manage samples, protocol, lab data, and files or automate data analysis, report generation, and submission to your manager. As you start your lab, consider the benefits of using a digital lab platform from the very beginning. Creating this standardization is key as you scale and require a more collaborative and organized environment.

Below, we look at some common start-up tasks and how DLPs can help them run more efficiently.

Onboarding and Processes Training

To avoid training new team members on multiple systems and showing the complex and unique ways your company manages data and other information, you can show them one system and train them on it. For SciSure for Research (formerly eLabNext), our user guides are great references for new and experienced users of the system.* The guides have visuals and links to assist you in your SciSure journey. 

*Pro tip: Create an SciSure training protocol in your Protocols module to help manage the training process!

User Permissions and Auditing

As you grow your team and hire, you can use your Digital Lab Platform to manage who has control over certain functions in the lab. Whether it is signing off on an experiment or archiving samples from your inventory, you can organize these permissions in our permissions settings. You can control these functions anytime, make changes or updates when necessary, and standardize who is responsible for what is in your lab.

You can utilize SciSure’s logs and audit trail features to keep track of all changes and updates in your lab. You can see what updates were made to a protocol or sample information. You can also view the equipment validation history. Even the most minor changes, like updating a user from “scientist” to “administrator” in your permission settings, are captured and logged in the permission change log.

Inventory Management

Digitizing lab assets from the start of your lab is important for maintaining a well-organized environment. With SciSure, you can begin setting up all your new equipment, like freezers, centrifuges, tubes, pipettes, and more, as you build out your lab. To keep organized with service maintenance and calibrations, assign locations and log the service tech’s contact information for each piece of equipment to make scheduling service simpler. Your team can utilize the equipment booking calendar to reserve equipment while using it or to view when the equipment is in service.

As you start receiving and managing samples, you can easily track where the sample is being stored and create custom data fields to track things like quantity, collection date, sample type, and other metadata. Utilizing pre-barcoded tubes or containers from the start simplifies your sample management process. With our barcode scanning feature, your team can attach barcodes to sample tubes or utilize pre-barcoded tubes and easily scan them using our Mobile App (or any 2D scanner), enabling quick viewing/editing of all sample information.

Protocol Creation and Management

Digital Lab Platforms also enable you to manage all your protocols and SOPs with platforms. As you continue building your lab, standardize the team’s protocols by creating them directly in SciSure, which enables you to generate formulas that make calculations easier and minimize any calculation mistakes. 

Starting a lab and building out all new protocols may seem overwhelming, but our AI Protocol Generator has made it much less daunting by facilitating the import of standard lab protocols (like Western Blotting, PCR, or buffer protocols).

ELN and Reporting

Managing and monitoring project progress is critical for ensuring your research is on track and under budget. Digital Lab Platforms, can help you standardize experiments and reporting and visually track which tasks have been completed. 

It also allows you to collaborate very effectively with your team, assign tasks, tag users in comments, and collaborate on different projects within your team. SciSure is where your inventory and protocols come together; you can capture what samples were used in an experiment, the samples generated from the experiment, and what protocols were used. 

Other experiment section types in SciSure include file and image sections, where you can add files and images from your experiments, and Microsoft Office sections, which allow you to upload and/or work directly with programs like Word, PowerPoint, and Excel for data reporting.

Get Started on Digitizing

As I’ve highlighted above, standardizing your operations to one multi-functional system (rather than many monofunctional systems) makes it much easier as you grow your team. SciSure allows users to customize the platform to their workflow and utilize the tool however it works for them. You get to define what information is captured within the system and how you want your team to use it. 

If you’d like to see how SciSure can benefit your new lab, schedule a free demo here!

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Lab Communication and collaboration are the lifeblood of any successful laboratory environment. In a setting where precision, accuracy, and efficiency are paramount, the methods by which team members interact and share information can significantly impact the overall effectiveness of lab operations. Whether it's through emails, shared digital platforms, or in-person meetings, maintaining clear and open lines of communication ensures that everyone is on the same page and can work together seamlessly to achieve common goals. 

Effective collaboration in the lab not only fosters a more cohesive team but also drives innovation and problem-solving, combining diverse perspectives and expertise to tackle complex challenges. By adopting strategies to enhance communication and teamwork, laboratories can optimize their operations, improve research outcomes, and accelerate discoveries.

In this blog, we'll explore various ways to enhance communication and collaboration in the lab. Read on to discover our top tips for improving lab communication, from leveraging digital lab solutions to building a strong team culture.

In this blog, we will cover:

• What is lab communication and collaboration?
• Common challenges in lab communication
• Improving lab communications with digital lab solutions
• Five tips to improve your lab's communication and collaboration
• Time to get connected

What is lab communication and collaboration?

Lab communication encompasses all the various methods by which information is exchanged within the laboratory environment. These methods include meetings, emails, reports, and documentation. Clear and effective communication is critical for ensuring that lab operations run smoothly and that all team members are on the same page, minimizing misunderstandings and errors. 

Collaboration refers to the cooperative efforts between team members and collaborators on projects, documentation, and data. Effective collaboration is vital for scientific research, as it fosters new ideas and drives innovation. Leveraging collaborative tools such as shared digital workspaces and project management software can help streamline these efforts. 

Implementing effective lab communication and collaboration strategies can bring a host of benefits:

• Improved operational efficiency: Effective communication and collaboration streamline lab processes, reducing errors and redundancies. When team members can easily share information and coordinate their efforts, operations become more efficient.
• Enhancement of research quality: Teamwork plays a crucial role in producing high-quality, reliable research outcomes. Collaborative efforts ensure that multiple perspectives are considered, leading to more robust and credible results.
• Fostering innovation: Collaboration is a powerful driver of innovation. When team members work together, they can combine their expertise and insights to discover new solutions and advancements in scientific research.
• Resource optimization: Collaboration allows for better allocation and utilization of resources. By sharing equipment, knowledge, and skills, teams can optimize the use of available resources, reducing waste and improving overall efficiency.
• Regulatory compliance: Clear communication is essential for meeting regulatory and compliance standards. Proper documentation and information sharing ensure that all lab activities adhere to necessary guidelines and regulations.

Common challenges in lab communication

Effective communication and collaboration in the lab don't come without their hurdles. From misunderstandings and miscommunications to variability in working styles and approaches, these challenges can hinder progress and create friction among team members. Outlined below are some of the most common challenges faced by labs seeking to improve communication and collaboration processes:

Fragmented communication channels

Using multiple, non-integrated communication methods can lead to fragmented communication. Information gets lost, and team members may struggle to stay informed. For instance, using separate tools for emails, messaging, and project management without integration can cause vital updates to be missed.

Data silos

Isolated data storage and lack of accessibility create data silos, which hinder effective collaboration. Team members need easy access to shared data to work efficiently. An example is when different departments use distinct databases without a centralized system, making it difficult to share and combine critical information.

Lack of coordination in complex tasks

Managing projects and tasks with multiple team members can be challenging. Without proper coordination, tasks may overlap or be neglected, leading to delays and errors. For example, uncoordinated schedules and unclear task responsibilities often result in duplicated efforts or missed deadlines.

Inconsistent documentation

Inconsistent or inadequate documentation can cause confusion and inefficiencies. Proper documentation ensures that all team members are on the same page. An example is when project details are recorded inconsistently across different platforms, making it hard to track progress and accountability.

Lack of real-time updates

Without real-time updates, teams may work with outdated information, leading to mistakes. For instance, if stock levels or task statuses are not updated immediately, team members might make decisions based on incorrect data, affecting overall productivity.

Inadequate resource allocation

Inadequate resource allocation is another symptom of poor communication in the lab and can lead to bottlenecks and inefficiencies. Ensuring that resources are distributed based on priority and need is crucial. For example, if one project has too many resources while another critical task is understaffed, it can slow down overall project progress.

Addressing these challenges is crucial to maintaining a productive and harmonious working environment and ensuring the success of research projects. 

Improving lab communications with digital lab solutions

In modern research environments, effective communication and collaboration are paramount to achieving successful outcomes. Adopting digital lab solutions can be a sure way to transform your lab's communication capabilities, bringing streamlined processes, enhanced data sharing plus improved operational efficiency. From streamlined project management to more robust documentation processes, digital tools bring numerous advantages for improving communication and collaboration in any lab setting.

Digital lab platforms, including Electronic Lab Notebooks (ELNs) and Laboratory Information Management Systems (LIMS), offer numerous benefits and features that significantly improve lab communication and collaboration. Here are the main advantages and capabilities:

Centralized communication

• Centralized digital platform: Both ELNs and LIMS centralize all lab communications, providing a single conduit for sharing information, updates, and data.
• Real-time collaboration: Digital lab platforms allow team members to collaborate in real-time, reducing delays in communication and enhancing the efficiency of information exchange.

Enhanced data sharing and accessibility

• Instant data access: Digital platforms allow quick access to all relevant lab data and documentation, enabling team members to retrieve and review information effortlessly.

Improved project management

• Task coordination: Built-in project management tools help streamline task assignment, coordination, and tracking, ensuring that projects progress smoothly.
• Progress tracking: Digital lab platforms provide tools to monitor the status of ongoing tasks and projects, helping teams stay on schedule and meet deadlines.

Secure communication

• Data security: Features like encryption and access controls protect sensitive information, ensuring that only authorized personnel can access critical data.
• Regulatory compliance: Digital lab platforms help maintain regulatory compliance by providing secure data handling, detailed audit trails and long-term data preservation.

Better resource management: 

• Lab resources: Digital lab solutions help in better management of lab resources, including equipment, reagents and consumables. ELN platforms track the usage of these resources, while LIMS platforms can monitor inventory levels and usage patterns, helping labs optimise resource use, reduce waste and ensure that essential items are always available when needed.

Long-term data preservation and accountability

• Data preservation: Digital platforms ensure long-term data storage, safeguarding valuable research data and making it easily retrievable in the future.
• Audit trails: Detailed audit trails enhance transparency and accountability, providing a clear record of data access and modifications.

By incorporating advanced digital lab solutions like ELN and LIMS platforms, research facilities can significantly enhance their communication, collaboration, and overall operational efficiency. SciSure for Research (formerly eLabNext) provides the best of both worlds by integrating the comprehensive features of ELN and LIMS platforms, offering a robust, flexible, and convenient tool to improve communication in modern research environments.

Five tips to improve your lab's communication and collaboration

Effective communication and collaboration are pivotal for the success of any research lab. These factors not only enhance the efficiency of working processes but also foster a culture of transparency and innovation. By implementing strategic approaches and leveraging modern digital tools, labs can transform the way team members interact and share information, ultimately driving more accurate and reproducible results. Here are some top tips to improve your lab's communication and collaboration.

1. Assess your lab's needs

Begin by thoroughly evaluating your lab's specific communication and collaboration needs. This involves understanding the unique requirements of your projects, the workflow of team members, and any existing gaps in communication. Understanding these needs will help you choose the right tools and tailor them to fit your lab's structure.

2. Choose the right digital tools

Carefully select digital solutions that best meet your lab's requirements. Consider factors such as ease of use to ensure all team members can quickly adapt, integration capabilities with existing systems, and robust security features to protect sensitive data. Additionally, look for tools that offer flexibility and customization options to suit varying project needs.

3. Provide training and support

Provide comprehensive training for lab personnel on new tools and offer ongoing support to address any issues that arise. This includes initial training sessions, detailed user manuals, and a helpdesk for troubleshooting. Ensuring that all team members are comfortable with the tools will maximize their effectiveness and improve overall productivity.

4. Think scalability

Choose tools that can easily scale with your lab's growth. As your team expands or your projects become more complex, the tools should be able to handle increased demands without compromising performance. Look for solutions that offer scalable pricing models and additional features to accommodate future needs.

5. Foster a climate of collaboration

Focus on tools that enhance collaboration among team members. This includes features like real-time editing for shared documents, video conferencing for virtual meetings and instant messaging for quick communication. By fostering an environment of seamless collaboration, you can improve teamwork and drive project success.

By following these top tips, it's possible to build an efficient and modern digital lab that maximises productivity, centralises data management and promotes collaboration.

Time to get connected 

Enhancing lab communication and collaboration is crucial for the success and efficiency of any research environment. Effective communication ensures that all team members are well-informed and aligned with the lab's goals, minimizing misunderstandings and errors. By fostering a culture of collaboration, labs can leverage diverse perspectives and expertise to drive innovation and solve complex problems.

Digital tools such as ELNs and LIMS play a significant role in this process, offering centralized platforms for data sharing, project management, and secure communication. By integrating these advanced solutions, laboratories can optimize their operations, enhance research quality, and contribute to scientific advancements. Embracing these strategies and technologies will pave the way for more streamlined, productive, and innovative lab environments.

When evaluating the right digital platform for your lab, make sure to put communication and collaboration at the forefront of your priorities. Look for features that promote real-time communication, data sharing and project management to ensure your team can work efficiently and effectively towards common goals.

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In April of 2024 the Environmental Protection Agency (EPA) finalized a rule banning most uses of methylene chloride (CAS RN: 75-09-2).

Read on to learn: Why they are banning this chemical? Why now? And how this will this impact laboratories, where methylene chloride is still critical to chemical research.

What is so bad about methylene chloride?

If you know anything about methylene chloride (common synonyms: dichloromethane, DCM, MC), you probably know that it is nasty stuff. Short-term exposures can affect the central nervous system, and chronic exposures can lead to liver toxicity, and cancer of the liver and lungs. If you have personally handled this chemical, then you may also know that it is highly volatile and quickly penetrates standard thickness disposable nitrile gloves, presenting challenges for protecting against exposure by both inhalation and dermal absorption routes. Like many highly potent chemicals, the properties that make it so hazardous are also what make it useful for commercial, industrial, and research purposes! It is a low boiling point, polar aprotic solvent, ideal for degreasing, paint stripping, aerosols, and a variety of other applications including synthesis, extraction, and purification in the laboratory.

The Occupational Safety and Health Administration (OSHA) has regulated methylene chloride to protect workers in General Industry since 1997 (29 CFR 1910.1052). In that standard, OSHA set a permissible exposure limit (PEL) for an 8-hour time-weighted average (TWA) exposure, a short-term exposure limit (STEL) for a 15-minute period, as well as an “action level,” which triggers the need for exposure monitoring and medical surveillance to ensure that exposures remain below those thresholds. This OSHA standard also includes requirements for establishing designated areas for methylene chloride use, hazard communication and training requirements for employees, and recommendations for safety controls to maintain methylene chloride concentrations below the permissible limits.

Why is the EPA banning methylene chloride now?

If this infamously hazardous material has already been regulated for decades, why is the EPA only now imposing this ban? The answer is, in short, because now they can!

In 2016, congress passed legislation to revise the EPA’s Toxic Substances Control Act (TSCA), granting the agency new powers and responsibilities for ensuring that “no chemical in U.S. commerce poses an unreasonable risk to human health or the environment.” Of 90 high-risk substances identified to be evaluated by the EPA, methylene chloride is among the first 10 for which they are conducting a mandatory risk review. In 2019, the EPA banned the use of methylene chloride and another chemical, N-methylpyrrolidone (NMP) (CAS RN: 872-50-4), for consumer and most types of commercial paint and coating removal. The agency focused on the paint and coating removal process first because of the high potential for exposure in this frequent, routine, and high-concentration usage. For evidence of that danger, just look at the worker fatality statistics, which show that between 1980 and 2018, of the 85 reported worker deaths related to methylene chloride exposure, 60 of them involved paint strippers.

The EPA’s revised methylene chloride risk evaluation in November of 2022, which evaluated an expanded set of conditions of use – unsurprisingly – determined that the chemical, “as a whole chemical substance, presents an unreasonable risk of injury to health under the conditions of use [evaluated].” In May of 2023, the EPA proposed their methylene chlorine regulation to ensure that this chemical would no longer present unreasonable risk to human health or the environment. After a period of public comment, the EPA finalized the rule in April of 2024, but as of the publication of this article in May of 2024, it has not yet been entered into the Federal Register.

Does this ban apply to laboratory use?

Although the rule does not impose a complete ban on the use of methylene chloride, it does prohibit it in most industrial, commercial, and consumer uses. The EPA, however, is allowing for “limited and controlled continued use in tandem with additional work protections for several purposes [. . .].” Among the list of 13 permitted uses is “industrial and commercial use as a laboratory chemical.”

The pre-publication of the rule explains that “laboratory settings are expected to be more conducive to the implementation of engineering controls such as fume hoods to ventilate vapors and adequately reduce overall exposure to methylene chloride consistent with the hierarchy of controls.” Of course, the use of methylene chloride in a laboratory setting will also be necessary for the analysis of the air samples that this rule requires!

How does the EPA rule compare with the OSHA standard for methylene chloride?

The EPA sought to keep their methylene chloride rule consistent with existing health and safety regulations for this chemical; however, it differs from the 1997 OSHA standard in some key ways. OSHA standards cover worker protection, but the EPA methylene chloride rule under TSCA applies to all “potentially exposed persons,” which is inclusive of not just workers, but also university students, volunteers, self-employed persons, and state and local government workers not covered by a state occupational health and safety plan.

The exposure thresholds in the EPA rule are also lower than OSHAs by an order of magnitude. EPA’s Existing Chemical Exposure Limit (ECEL) is 2 ppm as an 8-hour TWA, and 15-minute STEL is 16 ppm, whereas OSHA’s are 25 ppm and 125 ppm, respectively. Both agency’s use 1/2 the respective 8-hour TWA as an action level to trigger monitoring and medical surveillance.

Comparison of OSHA and EPA Exposure Thresholds

OSHA (1997)  

EPA (2024)  

8-hour TWA  

PEL 25 ppm  

ECEL 2 ppm  

15-min STEL

125 ppm

16 ppm

Action Level

12.5 ppm

1 ppm

What will the requirements be for laboratories that continue to use methylene chloride?

Workplace Chemical Protection Program (WCPP)

While laboratories are still permitted to use methylene chloride, if they do so, they will be required to have a Workplace Chemical Protection Program (WCPP) in place. The WCPP requires monitoring to verify that the exposure thresholds are not exceeded, as well as record keeping requirements, and other measures such as dermal protection.

The requirement for the WCPP will take effect 180 days after publication of the final rule. This is when any affected organizations will be required to do their initial monitoring to establish a baseline of exposure for potentially exposed persons. Within 1 year of publication of the final rule, any necessary controls to reduce exposure are required to be in place. Because of the new, lower exposure thresholds set by the EPA, even organizations that are currently in compliance with the OSHA methylene chloride standard will need to perform these baseline monitoring activities. That is, unless they can provide EPA with data from within the past 5 years proving that methylene chloride levels cannot exceed the new ECEL action level or STEL.

These air samples are to be taken in the ambient air, so they will not take into account any respiratory protection devices that may already be in use.

The rule includes details for how to select appropriate representatives of individuals for conducting personal-breathing-zone air sample monitoring, and this guidance aligns with the existing approach in the OSHA standard for methylene chloride. Unlike the OSHA standard, however, EPA is requiring “initial” exposure monitoring to be repeated every 5 years for as long as the chemical remains in use at the facility.

If any of the results from the initial monitoring exceed the action level, STEL, or ECEL, then additional periodic monitoring will be required on frequencies of 3 months or 6 months depending on the results. Each potentially exposed person must also be informed of these results, and an exposure control plan (ECP) must document the actions taken to reduce exposures.

Exposure Control Plan

The EPA’s requirements for exposure control are meant to be flexible and will not prescribe specific methods or devices for reducing exposure. Rather, the EPA encourages the use of the recognized “Hierarchy of Controls” which emphasizes elimination and substitution of the hazard to be considered before engineering controls, administrative controls, and personal protective equipment are put in place. One of the requirements of the ECP is that it must document the process that was used to decide which controls are selected and justification for any less preferred approaches, such as requiring respiratory protection instead of using engineering controls to reduce the ambient concentration.

Although most of the requirements in the EPA rule pertain to respiratory exposures, it does also state that “gloves that are chemically resistant to methylene chloride” and “activity-specific training” must be included in the ECP for any task where dermal contact with methylene chloride is possible, assuming that the exposure cannot otherwise be avoided through substitution, elimination, and engineering controls.

Timeline for compliance for (Non-Government) laboratories

Required Action

Amount of time after date of publication of the final rule in the Federal Register

Establish initial exposure monitoring

360 days (and every 5 years, thereafter)

Ensure ECEL and STEL are not exceeded

450 days

If needed, sufficient respiratory protection provided to reduce exposures below thresholds

9 months (or 3 months after receipt of monitoring results)

Implement and document exposure control plan

540 days

What should laboratories do to prepare for the new requirements?

A suggested “Checklist to Prepare Laboratories for the Methylene Chloride” is included at the end of this article.

How do we know if we have any methylene chloride?

The first step should be to identify if your labs are storing and/or using methylene chloride. Utilize tools like SciSure's (formerly SciShield's) SDS QR Code to quickly access and manage Safety Data Sheets, ensuring up-to-date information and compliance with safety regulations. And if so, where, and how? If you have a trusted chemical inventory system, that could be as easy as searching the records for methylene chloride by name, CAS RN (75-09-2), and by any of the common synonyms (dichloromethane, DCM, MC).

If you are not confident in the completeness of the inventory, you can use messaging tools to target groups and individuals who may be storing or using the chemical. Instructing the lab inspection team to ask about this and to check chemical cabinets while in the lab space is another method for finding undocumented stocks of methylene chloride. Keep in mind that this chemical is often stored with other solvents, but it is not flammable and, thus, is not necessarily stored in the flammable liquids storage cabinets.

Although methylene chloride has been banned from paint strippers and other coating-removal products since 2019, now would also be a good opportunity to check products in maintenance and facilities shops or studios and replace any items that contain methylene chloride or N-methylpyrrolidone (NMP) (CAS RN: 872-50-4).

Can we just eliminate methylene chloride from the labs?

Although substitutions can be made for some methylene chloride uses, there may very well be lab operations where it will still be essential. In in Green Chem., 2008,10, 31-36 (DOI: 10.1039/BE) the Environmental, Health and Safety (EHS) group at Pfizer Global Research and Development recommend replacing methylene chloride with Ethyl Acetate/Hexane for chromatography and with Ethyl Acetate, MTBE, Toluene, or 2-MeTHF for extractions.

In Teledyne ISCO’s January 2023 “Dichloromethane (DCM) Substitutes and Selectivity” post, they suggest a 3:1 ratio of ethyl acetate to ethanol as a starting point for creating new methods without DCM for chromatography purification.

Chromatography and extraction are good targets for substitution, because they are two of the most common and high-volume laboratory tasks where methylene chloride is used.

How will we convince the lab personnel to make these changes?

You may encounter resistance as you try to remove this common solvent from the laboratory, as swapping for alternatives will require additional experimentation before appropriate substitutions can be validated. Discussing with laboratory leadership what will be realistic and beneficial before announcing any policies or mandates is critical to successful change management. It is important that your laboratory personnel are well aware of the hazards and the new requirements as soon as possible to get their buy-in and to enable a smooth transition.

One strategy for encouraging the use of alternative solvents is to enforce limits on the total permitted amount and/or the largest permitted container size of methylene chloride. By not instituting a complete ban, you enable critical processes to continue, while still promoting the use of substitutions by making it less convenient and more expensive to use the more hazardous chemical. Additionally, by limiting the largest container size (for example, to 500 mL), the chances of a large-volume spill or large-volume chemical transfers will be reduced.

Instituting a permit-for-use system, such is sometimes done with pyrophoric or other high-hazard materials, can also help with the ongoing monitoring of where and how the chemical is used while also checking that the proper training and safety controls are in place where needed.

Will we need to perform air monitoring everywhere methylene chloride is in use?

The EPA rule contains guidance on how to select representative “potentially exposed persons” for initial and periodic air monitoring, but figuring out which activities have the highest potential for exposure is the first step.

This may require first carefully observing operations where methylene chloride is used and talking to health-and-safety minded laboratory personnel about real practices. Keep in mind that the tasks with the highest short-term exposure may include set-up, start-up, or shut-down activities such as transfers from larger containers for filling reservoirs or creating stock solutions, combining purification fractions, emptying rotary evaporator traps, or pouring into waste containers.

When thinking about potentially exposed persons, remember to include any personnel who may be involved with waste consolidation operations, emergency response, and routine laboratory tasks. You may need to update emergency response plans to include new monitoring requirements and the use of supplied-air respirators for entry into methylene chloride spill areas.

What is next?

Now that the EPA has made available the pre-publication version of their proposed Methylene Chloride Regulation, chemical hygiene professionals can start communicating with lab personnel and their own health and safety teams to prepare for what is to come.

Although responsible lab safety programs will already have training and controls in place for management of this famously toxic chemical, this will be a time for revisiting past assessments, approvals, and results to consider whether ongoing use of methylene chloride is still warranted in light of the more stringent regulations.

The reality is, for many laboratory facilities, especially where basic chemical research, synthesis, and a wide range of analytical methods are everyday occurrences, it is unlikely that this chemical can be eliminated entirely. However, if health and safety teams lead with a collaborative mindset and a focus on risk assessment and mitigation, they will benefit from the creativity and problem-solving skills that laboratory workers and management can bring to the conversation.

After all, this will lay the groundwork for the chemical safety community to tackle compliance with many similar regulations in the coming years. At the time of writing this article, the EPA is currently evaluating 33 existing chemicals under the revised Toxic Substances Control Act to determine which others present unreasonable risk of injury to health or the environment; methylene chloride is simply the first to have a final published rule. The strategies and relationships developed now will set the precedent for successful responses to these future EPA chemical bans and restrictions.

Checklist to prepare laboratories for the methylene chloride regulation

Communicate and Plan Ahead

• Communicate with laboratories about methylene chloride hazards and new regulations
• Identify where methylene chloride is stored or in use
• Review any previous methylene chloride monitoring results to gauge which activities have already been assessed and whether those measurements indicate that the new, lower, thresholds are likely to be exceeded

Check Equipment

• Confirm that any equipment to be used for routine or emergency air-monitoring is calibrated and appropriate for measuring concentrations of methylene chloride to the level of detection necessary for the new exposure threshold values
• Confirm that local exhaust ventilation controls such as fume hoods and extractors are in service, inspected, and certified

Eliminate and Substitute Where Possible

• Work in close partnership with lab personnel to eliminate and substitute methylene chloride wherever possible— Consider instituting limits on total volumes or largest-container size to encourage the use of alternatives
• Identify where and how methylene chloride must still be permitted— Consider requiring a written approval (e.g., a permit) for any project or team where methylene chloride use will be allowed

Plan for Initial and Ongoing Compliance

• Work with a Certified Industrial Hygienist to create a monitoring plan for initial monitoring
• Document a Workplace Chemical Protection Program (WCPP)
• Update the Chemical Hygiene Plan and write a separate methylene chloride exposure control plan if needed
• Update initial and refresher training for chemical handling to highlight the health hazards of methylene chloride and any new approvals or other requirements that will be put in place

Our Developer Hub is the newest addition to our Digital Lab Platform (DLP). It's the 1st ever democratic end-to-end developer experience that allows you to build new or extend existing functionalities to automate, integrate, and optimize your lab operations in a sustainable, secure, and compliant digital ecosystem. 

With the launch of our Developer portal, we are democratizing access to your favorite digital molecular biology, chemistry, and AI tools, elevating your lab's day-to-day operations, and revolutionizing how your researchers do research!

The core feature of the Developer Hub is that it enables companies and third-party vendors using the eLabNext Biotech software-as-a-service (SaaS) to develop their add-ons on top of our core platform. This capability has several high-value benefits for both developers (via eLabNext Developer) and eLabNext customers (via Marketplace), as discussed below.

Opportunity to Reach a New Audience

A developer portal can be a stage where developers can showcase their add-ons to users of the underlying platform. By listing their add-ons in our Marketplace, third-party vendors gain exposure to our highly targeted audience of potential customers already using SciSure (formerly eLabNext). These users will likely be interested in complementary solutions that enhance their software's functionality, making it an ideal place for vendors to showcase their offerings. This eliminates the need for vendors to invest time and resources into marketing independently, allowing them to focus exclusively on developing high-quality add-ons instead.

While an add-on may be offered for free through a platform, exposure to this new audience can indirectly lead to monetization, either through additional purchases or subscriptions from the add-on company outside of SciSure.

Community Engagement

Community engagement provides add-on developers with a valuable feedback loop for their products. Exposure to a new audience can provide add-on developers with a new way of interacting with users and tracking usage statistics. Vendors can gather insights into how their services are being used within the SciSure, what features are most valued, and where there may be room for improvement. 

This feedback helps vendors refine their existing offerings and validates the market demand for their solutions. Additionally, engaging with the existing SciSure community allows vendors to build relationships with potential customers, establish credibility, and gain valuable product endorsements by associating with an established and trusted brand.

Flexible Functionalities

Allowing companies to develop their add-ons enables them to complement the software better to suit their specific needs. This can increase efficiency and productivity, as SciSure customers can tailor the software to fit their workflows.

Tailored Solutions to Unique Needs

The flexibility offered by the Developer portal allows customers to tailor the platform to their specific requirements. Customers in the biotech industry often have unique workflows, data management needs, and compliance requirements. With access to a wide range of add-ons developed by third-party vendors, customers can choose and integrate solutions that best fit their needs, ensuring that the platform aligns closely with their business processes and objectives.

Adaptability to Changing Requirements

Biotech research and development is a dynamic field characterized by rapid advancements and evolving regulatory landscapes. Customers need software solutions that can adapt to these changes quickly and seamlessly. The flexibility of the Developer Hubprovides enables developers to create add-ons to address this new requirement and allows customers to quickly and easily adapt to these changing requirements in the Marketplace. For instance, the NIH recently required all grant applications to submit a data management and sharing plan (DMP). DMPTool, a recent addition to the Marketplace, enables SciSure users to pull DMPs from DMPTool and present plan summaries within eLabNext, along with a link to download the complete plan.

Flexible User Experience

Every organization within the biotech industry may have different preferences and priorities regarding user experience. The flexibility offered by our Marketplace allows customers to customize the user interface, data visualization tools, reporting capabilities, and other aspects of the platform to match their preferences and workflows. This level of customization enhances user satisfaction, productivity, and overall usability, as customers can tailor the platform to meet their teams' unique needs and preferences.

Scalability

The Developer portal allows add-on creators to create a vibrant ecosystem around the core eLabNext platform. As more developers contribute add-ons, the software's overall functionality and usefulness have grown rapidly and will continue to grow. This scalability ensures that the software remains relevant and competitive in the long term.

Laboratories in the biotech industry often experience workload and resource fluctuations due to project timelines, research initiatives, and regulatory demands. A scalable Biotech SaaS platform like SciSure allows customers to scale up their software usage as their needs grow. This means handling larger datasets, accommodating more users, and supporting increased computational demands without compromising performance or stability.

Biotech labs may also need to expand their operations or collaborate with external partners, such as academic institutions, research organizations, or contract research organizations (CROs). SciSure enables customers to seamlessly onboard new users, integrate additional data sources, and extend access to collaborators without significant infrastructure investments or disruptions to ongoing activities. This flexibility fosters collaboration, accelerates research efforts, and facilitates knowledge sharing across interdisciplinary teams.

Scalability also allows customers to embrace future innovations more rapidly without constraints. By investing in SciSure, customers future-proof their operations, enabling them to stay ahead of the curve, capitalize on new opportunities, and drive continuous advancements in biotechnology.

Reduced Development Costs 

Leveraging the creativity and expertise of third-party developers can reduce the development costs associated with expanding the functionality. Instead of building every feature in-house, customers can rely on the Developer community to contribute ideas and solutions, saving time and resources.

Instead of investing time and resources in developing software solutions from scratch, customers can select off-the-shelf functionalities that meet their requirements. This saves on development costs and accelerates the implementation timeline, allowing customers to integrate new features into their workflows quickly.

Shared Development Costs Across the Community

It also saves add-on developers money. SciSure Developer fosters a collaborative ecosystem where multiple developers can contribute to creating add-ons. As a result, development costs are shared across the community, reducing the financial burden on individual customers. By pooling resources and expertise, customers can access a wide range of functionalities at a fraction of the cost of developing them independently.

Cost-Effective Functional Expansion Over Time

While customization is essential to meet specific business needs, developing custom solutions can be expensive for SciSure customers. With the eLab Marketplace portal, customers can customize the platform using existing add-ons, significantly reducing the cost of expanding functions.

In-house development requires ongoing maintenance and support to keep the software up-to-date and address any issues. By relying on our Marketplace portal, customers benefit from continuous updates made by developers in the Developer Hub and support provided by third-party vendors. This ensures that the software remains current and functional without additional investment in maintenance and support services.

Faster Innovation

Access to Marketplace provides SciSure customers with an agile way to find cutting-edge features and capabilities without waiting for lengthy development cycles. As a result, customers can stay ahead of the curve and leverage the latest advancements in biotechnology to drive innovation in their research and development activities.

The biotech industry is characterized by rapid technological advancements, evolving regulatory requirements, and shifting market dynamics. The interplay between the Developer Hub and our Marketplace enables customers to respond quickly to these changes by adopting new functionalities and tools as they become available. By staying agile and adaptable, customers can capitalize on emerging trends, seize opportunities, and maintain a competitive edge in the market.

Just look at the emergence of voice assistants like Google Assistant and Alexa. This technology has recently been applied in laboratories and incorporated into the our Marketplace with the addition of the ASCENSCIA add-on. It provides an easy way for SciSure users to access information and record data while working in the lab, freeing up their hands and allowing them to focus on their experiments.

Streamlined Workflows & Automation

With access to our Marketplace, customers can create custom automated workflows tailored to their specific needs. They can develop scripts, plugins, or integrations that automate repetitive tasks, such as data processing, analysis, or report generation. 

End-to-End Automation

Customers can automate entire end-to-end processes by orchestrating multiple tasks and integrations within the system. They can automate data collection, analysis, and visualization workflows, leading to faster insights and decision-making. SciSure's integration with Elemental Machines, a temperature detection system, is a great example of how add-ons can facilitate automation in a life sciences laboratory.

Robotics Control and Integration

Robots in biotech labs often perform repetitive tasks such as pipetting, sample handling, or plate manipulation. By integrating robots with the system's developer platform, customers can automate these tasks, reducing the need for manual intervention and improving throughput and efficiency.

Workflow Orchestration

Automation allows customers to orchestrate complex workflows involving multiple instruments and robotic systems. They can develop scripts or plugins that control the sequence of operations, coordinate interactions between robots and instruments, and optimize resource allocation to maximize productivity.

Integration with External Systems

Automation facilitates integration with external systems, databases, or software platforms, enabling customers to exchange data seamlessly between different tools and environments. For example, add-on developers can develop software that interfaces with SciSure or other data analysis software to streamline data exchange and collaboration.

Quality Control and Assurance

Real-Time Monitoring and Feedback

Automated systems can monitor instrument performance and data quality in real-time, detecting anomalies or deviations from expected norms. Add-ons available in our Marketplace can help customers trigger alerts or notifications when issues arise, enabling immediate corrective actions to ensure data integrity and experimental reproducibility.

Standardization and Compliance 

Automation enforces standardized procedures and quality control measures, ensuring compliance with regulatory requirements, industry standards, and best practices. Customers can develop automated workflows using SciSure that enforce validation checks, calibration routines, and data integrity controls, minimizing the risk of errors and ensuring regulatory compliance.

Audit Trails and Documentation

Automated systems maintain detailed audit trails and documentation of instrument usage, experimental protocols, and data processing steps. Customers can use SciSure to generate automated reports, logs, and documentation that comprehensively record experimental activities, facilitating traceability, reproducibility, and regulatory audits.

Conclusion

In the rapidly evolving biotechnology landscape, the convergence of automation, robotics, and data integration is paving the way for rapid advancements. With the Developer Hub enabling add-on developers to integrate with SciSure and our Marketplace, enabling SciSure customers to seamlessly expand and tailor functionality, biotech labs can harness the power of automation to streamline workflows, enhance precision, and drive innovation. 

By controlling robots and receiving real-time data from instruments, researchers can accelerate experimentation, scale effectively, optimize resource utilization, and ensure data integrity. This transformative approach increases efficiency and productivity and opens new frontiers in research and development. As biotech continues to push the boundaries of what's possible, the future undoubtedly lies in the seamless integration of automation technologies, positioning it at the forefront of scientific discovery and breakthrough innovation.

To see SciSure's Developer Hub or Marketplace portals and hear about how these tools have improved digitalization in the life sciences, send us a request and schedule your demonstration today.

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In the rapidly evolving landscape of modern laboratories, the integration of a Laboratory Information Management System (LIMS) has become vital. Not only does this digital lab solution facilitate improved data management and accuracy, but it also streamlines lab operations, paving the way for improved efficiency and productivity.

Choosing the right LIMS is a pivotal decision for any laboratory looking to optimize its operations. The right LIMS streamlines workflows enhance data accuracy and provides comprehensive sample tracking and reporting capabilities. With the myriad of options available, selecting the ideal LIMS tailored to your lab's specific needs can be daunting. In this blog, we'll guide you through everything you need to make this crucial decision.

In this blog, we'll cover:

• What is a LIMS?
• Benefits of implementing a LIMS
• Differentiating between LIMS and ELN
• Key factors to consider when choosing a LIMS
• Practical tips for selecting the best LIMS for your lab
• Weighing up your options

What is a laboratory information management system?

A LIMS is a software-based digital lab solution designed to support laboratory operations by managing data, automating workflows, and ensuring compliance with regulatory standards. By integrating various laboratory functions, a LIMS enables seamless data entry, storage, and retrieval, which significantly reduces the risk of errors and enhances data integrity. 

LIMS play a central role in modern labs by handling complex data management tasks and providing a structured and efficient approach to laboratory processes. They also facilitate better resource management, such as inventory tracking and equipment maintenance, and can generate insightful reports to aid in decision-making and regulatory submissions. Overall, a LIMS is an indispensable tool for laboratories aiming to improve productivity, accuracy, and compliance in today's fast-paced scientific environment.

Benefits of implementing a LIMS

The benefits of implementing a LIMS are vast and varied, offering significant enhancements across various facets of lab operations:

• Improved data management: A LIMS ensures the integrity and accessibility of data, which is crucial for reducing errors and improving the accuracy of decision-making processes. Centralizing data storage facilitates easier retrieval and analysis, thereby supporting more informed scientific conclusions and business strategies.
• Streamlined workflows: By automating routine and repetitive tasks, LIMS frees up valuable time for research and development activities. This automation can include sample handling, data entry, and report generation, leading to increased efficiency and productivity within the laboratory.
• Enhanced sample tracking: A LIMS provides precise tracking of samples within the lab, from collection to final analysis. This improved traceability ensures accountability and reduces the risk of sample loss or contamination, which is vital for maintaining the quality and reliability of lab results.
• Inventory management: By keeping track of lab inventory in real-time, LIMS aids in resource planning and budgeting. This feature helps labs manage their supplies more effectively, avoiding shortages and minimizing waste, which can result in cost savings and more efficient operations.

LIMS can be beneficial for a wide range of laboratories, including those involved in research and development, quality control, and biobanks. In research and development labs, it supports innovation by streamlining data management and sample tracking, allowing scientists to focus on their core scientific activities. Quality control labs benefit from enhanced data integrity and regulatory compliance, while biobanks can manage large volumes of biological samples with greater accuracy and reliability. 

Overall, the implementation of a LIMS can lead to significant improvements in lab efficiency, accuracy, and productivity.

Differentiating between LIMS and ELN

In addition to LIMS, another popular digital lab solution is electronic lab notebooks (ELNs). These solutions serve distinct purposes – understanding the difference between the two is crucial when deciding on a digital platform for your lab:

LIMS (Laboratory Information Management System)

• Primary focus: Managing samples, associated data, and laboratory workflows. It tracks the lifecycle of samples from receipt to disposal and supports various laboratory processes.
• Key Features: Sample tracking, inventory management, quality control, reporting and analytics, workflow automation.
• Use Cases: Managing high-throughput laboratories, clinical diagnostics, environmental testing, and any lab requiring rigorous sample tracking and process automation. Common in clinical labs, environmental labs, and industrial testing facilities.
• User Interaction: Used by lab managers, technicians, and analysts to track and manage samples, workflows, and lab resources.
• Rigidity: LIMS are designed to enforce strict protocols and standard operating procedures (SOPs) to ensure consistency, accuracy, and compliance with regulatory standards.

ELN (Electronic Lab Notebook)

• Primary Focus: Documenting experiments, research notes, observations, and procedures. It serves as a digital replacement for traditional paper lab notebooks.
• Key Features: Templates for experimental protocols, electronic documentation and signatures, search functionality, and version control.
• Use Cases: Documenting detailed experimental procedures, capturing research data in real-time, and supporting collaborative research projects. Common in academic research, pharmaceutical R&D, and biotech labs.
• User Interaction: Scientists and researchers use ELN interactively to document their daily work and experimental details.
• Flexibility: ELNs are designed to be more flexible and user-friendly. They allow scientists and researchers to document their experiments, observations, and notes in a manner that suits their individual needs and preferences. 

The best of both worlds

SciSure's (formerly eLabNext's) ELN capabilities are a comprehensive platform that bridges the functionalities of both LIMS and ELN and is tailored to the R&D Sector. This unified system seamlessly combines sample management, workflow automation, and experiment documentation, providing an all-in-one solution for modern laboratories. Some of the top features include:

• Adaptability: Adapts to the specific needs of various laboratory environments, ensuring it can be tailored to fit unique workflows and requirements. This adaptability makes it a versatile choice for a wide range of scientific research settings.
• User-friendly interface: Boasts an intuitive design, making it easy for lab staff to adopt and integrate into their daily routines. This ease of use helps to minimize the learning curve and ensures that teams can quickly start benefiting from the system.
• Data integrity: Ensures that all data is securely stored and easily accessible. This guarantees that essential information is always protected and readily available when needed, enhancing the overall efficiency of laboratory operations.
• Collaboration and data sharing: Enhances collaboration among team members with its collaborative tools. These features facilitate better communication and coordination, allowing for more effective teamwork and streamlined research processes.

Our Digital Lab Platform offers LIMS and ELN capabilities, which are comprehensive solutions for automating and optimizing lab processes.

Key factors to consider when choosing a laboratory information management system

When selecting a LIMS for your lab, several key factors must be carefully considered to ensure the system supports your unique workflows and research demands. Here are some critical aspects to evaluate:

Flexibility

The ability to adapt the LIMS to your lab's unique processes is crucial for operational success. SciSure offers unparalleled flexibility, allowing labs to tailor the system to their specific workflow requirements. Whether you need to customize data fields, create specific workflows, or integrate unique lab protocols, SciSure can be configured to meet your lab's precise needs, ensuring that it grows and evolves alongside your research demands.

API and integration capabilities

A robust Application Programming Interface (API) facilitates seamless integration with other systems and instruments, enhancing data flow and operational efficiency across the lab. SciSure's API and Software Development Kit (SDK) capabilities allow for extensive customization and integration, catering to the unique needs of your lab.

User-friendliness

An intuitive interface is key to ensuring all team members, regardless of their technical expertise, can effectively interact with and utilize the LIMS. SciSure boasts an easy-to-use interface designed specifically for life science R&D, ensuring a smooth user experience. The user-friendly design minimizes the learning curve, allowing researchers to focus more on their scientific work rather than navigating complex software, thereby increasing overall productivity and user satisfaction.

Automation capabilities

Automation within a LIMS significantly reduces manual data entry, minimizes errors, and boosts productivity. SciSure offers powerful automation features, streamlining various laboratory processes such as sample tracking, data entry, and report generation. By automating repetitive tasks, labs can reduce the risk of human error, ensure data accuracy, and free up valuable time for scientists to focus on critical research activities.

Implementation timeline

A swift and smooth implementation process is essential to minimize disruption to lab operations and ensure quick adoption of the new system. SciSure provides a streamlined implementation process, ensuring your lab can quickly benefit from its features. The dedicated implementation team works closely with your lab to provide training, support, and customization, ensuring that the transition is seamless and that your team is well-equipped to utilize the system effectively from day one.

Practical tips for selecting the best LIMS for your lab

Selecting the right LIMS for your lab can be a daunting task, but these practical tips will guide you through the process. From assessing your lab's specific needs to planning for future growth, we've got you covered:

1. Assess your lab's specific needs

Understanding your lab's specific requirements is the first step in selecting the right LIMS. Consider both current needs, such as sample tracking and data management, and future growth to ensure the selected LIMS can scale with your lab. Additionally, evaluate any specialized requirements your lab might have, such as integration with existing equipment or specific compliance standards.

2. Evaluate multiple vendors

Take the time to explore and compare what different vendors offer. Request demos and trials to get a hands-on understanding of how each LIMS works. Consider feedback from existing users and look for reviews or case studies that reflect the experiences of labs similar to yours. This can provide invaluable insights into the reliability, user-friendliness, and overall performance of the LIMS from each vendor.

3. Consider the total cost of ownership

Look beyond initial costs and assess the long-term value of the LIMS. Consider aspects such as ongoing maintenance, customer support, training, and software upgrades, all of which can significantly impact the total cost of ownership. Make sure to ask vendors about any hidden costs or fees that might arise over the product's lifespan.

4. Plan for the future

Ensure the LIMS you choose is capable of scaling with your lab. Look for solutions like SciSure for Research, which offers flexibility and ongoing support to help you adapt to your evolving needs. Make sure the system can handle increased data loads, support additional users, and integrate with new technologies as they become available. Planning for future expansion will help ensure your lab remains efficient and effective as it grows.

By carefully following these steps, you can ensure that you choose a LIMS that will serve your lab effectively now and in the future.

Weighing up your options

Choosing the right LIMS is a critical decision that can significantly impact the efficiency and effectiveness of your laboratory operations. By considering the specific needs of your lab, evaluating the options available, and focusing on long-term value, you can choose a LIMS that will support your lab's success well into the future. 

SciSure offers a comprehensive, customizable solution that combines the best of LIMS and ELN functionalities, making it an ideal choice for labs of all sizes and specialties. Discover the benefits of investing in the right LIMS for long-term success and take the first step towards optimizing your lab operations with SciSure.

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This article was originally published by eLabNext prior to its integration into SciSure. SciSure was formed in 2025 through the merger of eLabNext and SciShield.

We live in an incredible time where labs have access to great tools, from automation to AI. But in a world where technological advancements rapidly evolve and shape our world, scientific laboratories are often playing catch-up. The reluctance to fully accept digitization has profoundly impacted our scientific research efficiency and quality. Paper-based and manual documentation processes are one of the core methods that are outdated and hinder progress, leaving labs scrambling to catch up with the rapid pace of innovation.

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In the following blog, we discuss how electronic lab notebooks (ELNs) and other digital platforms enable labs to digitize their operations more quickly and how integration with voice assistants drives the next leap in lab efficiency.

The Era of Lab Digitization

The laboratory digitization movement has already started and is accelerating. Labs worldwide have recognized the need to modernize their operations and change how they manage their data. ELNs are emerging as vital tools for enhancing lab operations through better data management. Such tools offer scientific lab features such as structuring and tracking data, flexible collaboration between scientists, time-saving add-ons, and inventory management platforms. Labs that have embraced and continue to embrace digitization are more flexible, organized, and collaborative, putting them at the forefront of groundbreaking discoveries and allowing them to respond rapidly to biomedical emergencies like COVID-19 by developing novel vaccines and managing in-house viral testing facilities.

However, using such tools can come with a price. Adopting ELNs and a new way of doing lab work can be very challenging. Given the diversity and complexity of scientific labs, scientists may need help accessing ELNs from the lab or documenting their data instantly, creating additional burdens. For instance, scientists may need to dedicate a whole day of their week to updating their ELNs through a manual process of collecting old, scribbled notes. Such inefficiencies can impact the adoption of ELN solutions in the lab, slow the lab’s digitization process, and impede the overall research operations.

Integrating Voice Assistants with ELNs – A Game-Changer

Now, imagine taking this digitization journey a step further by incorporating a voice assistant into a lab’s ELN. This solution is now accessible through a partnership between ASCENSCIA, the creator of a voice assistant mobile app, and eLabNext, the developer behind an all-in-one digital lab platform. Through this software collaboration, scientists get access to this intermediary tool, making documenting data effortless. By offering a seamless user experience, labs can eliminate adoption barriers and revolutionize how scientists interact with eLabNext, producing higher-quality experiments. 

Here’s how:

1. More accessible data: Labs can sync the ASCENSCIA voice assistant with their eLabNext account with one click. This connection creates a two-way seamless data flow between the lab scientists and the eLabNext solution. Whether connected to the ELN or LIMS capabilities in eLabNext, scientists can access their experiments and protocols or locate their samples through simple, hands-free voice commands. Every detail of a researcher’s experiment is just one voice command away, without printed protocols or double-checking a paper lab notebook.
2. No experimental detail left behind: There are moments during experiments when things can get out of control, and a protocol needs to be paused to take notes, compromising the quality of experiments for the quality of data. With the integration of the ASCENSCIA voice assistant with eLabNext, scientists can focus solely on their experimental workflows while ASCENSCIA captures every detail in real-time. Every detail is captured in a structured format with a time stamp directly in eLabNext, leaving no work to be done later and saving your scientific team the unnecessary days of manually updating their system. Furthermore, ASCENSCIA’s voice assistant has 97% accuracy for scientific terminology, so there’s no need to correct entries manually. 
3. Fewer errors, accelerated R&D: Human errors can be costly in scientific research, leading to unnecessary repeated experiments and prolonged timelines. By leveraging ASCENSCIA voice assistant with your eLabNext solution, labs can minimize errors, streamline R&D operations, and reduce costs. 

Futurising Laboratory Operations and Empowering Scientists

In conclusion, the journey of lab digitization is not without its challenges, but the rewards are undeniable. By embracing voice technology, labs can revolutionize their workflows, making scientific research more accessible, efficient, and impactful. The rise of voice-activated labs heralds a new era of innovation, where scientists have unprecedented access to information and resources, reshaping the landscape of scientific discovery. ASCENSCIA and eLabNext invite you to be part of the future of scientific research to empower scientists to create a healthier world — one voice command at a time.

Whether you are starting your lab digitization journey or want to take it a step further, ASCENSCIA and eLabNext teams are here to guide you into the future of laboratory research.

Reach out to us at elabnext.com or book a demo at ascenscia.ai

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In today's rapidly evolving research landscape, effective sample management is fundamental to the success of laboratory operations. Laboratories, ranging from biobanks and diagnostic centers to pathology departments, must navigate the complex challenge of managing vast volumes of samples. Precision and efficiency are paramount as these facilities strive to uphold the integrity of their work and accelerate scientific progress.

The ability to meticulously track, securely store, and swiftly retrieve lab samples is not merely a logistical requirement; it directly influences the productivity, cost-effectiveness, and accuracy of research outcomes.

In this blog, we will cover: 

1. Types of lab sample
2. Common pitfalls in lab sample management
3. Digital lab sample management solutions
4. 5 top tips to improve your lab's sample management processes

Modern labs are under increasing pressure to enhance throughput and accuracy while reducing costs and minimizing errors. Traditional methods of sample management, often manual and error-prone, are proving inadequate in the face of these demands. Combatting the challenges of sample management, innovative technologies such as Electronic Lab Notebooks (ELNs) and digital lab inventories are redefining the landscape of lab sample management.

This guide delves into the challenges posed by sample management and outlines our top tips and best practices to elevate your lab's sample management regime.

Types of lab sample

Laboratories across various fields handle diverse types of samples, each presenting unique challenges in terms of storage, preservation, and management. Understanding these sample types and their specific requirements is crucial for implementing effective sample management systems.

Biological samples

(Blood, tissues, cells, DNA)

• Storage: Biological samples often require precise temperature conditions, such as refrigeration or cryogenic storage, to prevent degradation. The risk of cross-contamination is also a concern, necessitating strict protocols.
• Management: Tracking the lineage and treatment of samples (e.g., aliquoted, stained) is vital, especially in biobanking, where samples may be stored for long periods and used in multiple studies.

Environmental samples

(Soil, water, air filters, plant material)

• Storage: These samples may change over time if not stored properly, with factors like temperature, humidity, and light affecting their integrity.
• Management: Traceability and the ability to link samples back to their collection point are essential.

Clinical samples

(Patient tissues, swabs, biopsy specimens)

• Storage: Many clinical samples are sensitive to environmental conditions and must be processed or preserved quickly to retain their diagnostic value.
• Management: Clinical samples require stringent labeling to protect patient confidentiality and ensure traceability. Compliance with health regulations and standards (e.g., HIPAA, GDPR) is also mandatory.

Microbiological Samples

(Bacteria, viruses, fungi)

• Storage: These require specific growth mediums or inhibitors to maintain viability or dormancy. Controlling contamination is particularly challenging given the infectious nature of many such samples.
• Management: Ensuring that microbial strains are not mixed or contaminated during handling requires meticulous sample tracking and personnel training.

Material Samples

(Metals, polymers, semiconductors)

• Storage: Some materials may be sensitive to atmospheric conditions, such as humidity or temperature, which can alter their properties.
• Management: Tracking the batch and source of material samples is crucial, especially when these materials are used in high-stakes applications like aerospace or medical devices.

Each type of lab sample demands a tailored sample management strategy. This underscores the need for robust inventory and sample tracking systems that can accommodate the volume of samples, their tracking and labeling needs, and storage requirements. 

Common pitfalls in lab sample management

Managing laboratory samples is a multifaceted task that brings a variety of challenges. When relying on traditional sample management systems, like error-prone manual labeling, these challenges become even more pronounced. Here are some common mistakes commonly made in lab sample management:

Mislabelling

Manual labeling, predominant in traditional sample management systems, is highly susceptible to human error. Incorrect, incomplete, or illegible labeling can lead to confusion in sample identification. Such errors compromise the integrity of data, undermining the reproducibility and reliability of research findings. Mislabelling can disrupt entire research projects or lead to incorrect patient diagnoses in clinical settings.

Lost or perished samples

Logbook-based sample management systems often lack robust tracking and monitoring mechanisms, making it easy for samples to be misplaced or improperly stored. Without precise, real-time tracking, samples can easily be left in non-optimal conditions, leading to degradation or spoilage. The loss or deterioration of samples can waste valuable resources, delay research progress, and result in irrevocable data loss in cases of irreplaceable samples (such as those from unique clinical trials).

Sample tracking mismanagement

As labs grow and sample volumes increase, manual tracking methods such as logbooks or spreadsheets become overwhelmed. These methods are time-consuming, prone to oversight, and often cannot be updated in real-time, creating bottlenecks in sample management. Inefficient sample tracking leads to delays in sample retrieval and can cause bottlenecks in data analysis, reducing the overall efficiency and responsiveness of research activities.

Errors in sample management can have far-reaching consequences, from compromised patient diagnoses to invalidated research findings. To minimize the incidence of these errors, many labs are turning to digital lab solutions. 

Digital lab sample management solutions

Adopting digital lab solutions is a highly effective strategy for enhancing and streamlining lab sample management processes. A number of technologies are available to support these improvements. For example, a platform that combines a Laboratory Information Management System (LIMS) with an Electronic Lab Notebooks (ELNs) centralizes sample management, storage data, study data and protocols on a real-time updated and accessible platform. Meanwhile, specialized inventory management systems automate numerous aspects of sample management and tracking, significantly boosting efficiency.

These tools not only simplify daily operations but also ensure that data is consistently accurate and easily retrievable. Digital solutions offer a range of features to streamline and strengthen lab sample management:

• Automation: Digital lab solutions such as SciSure, as a standalone LIMS or complete Digital Lab Platform, automate sample tracking, data entry, and storage management. Automating these critical processes minimizes human error while enhancing operational efficiency. ensures that every sample action is accurately logged and standardized, leading to fewer errors and consistent handling procedures.
• Barcode labeling and tracking: By incorporating barcode systems, labs can ensure precise tracking of each sample from collection to disposal. Barcode tracking simplifies the retrieval and auditing of samples, allowing for a seamless flow of information throughout the sample's lifecycle. The use of barcode ID virtually eliminates the risks associated with manual sample labeling, drastically reducing errors in sample handling and processing.
• Enhanced documentation and reproducibility: Digital lab solutions play a crucial role in enhancing the documentation and reproducibility of experiments. By integrating an ELN, researchers can maintain detailed, time-stamped records of samples during storage and research.
• Centralized sample data: Digital platforms such as LIMS and ELNs serve as a centralized repository for all sample information, facilitating easy access and data sharing across the lab. SciSure offers real-time sample tracking data among lab members, accessible from anywhere. Centralized systems also enhance data security and facilitate compliance with regulatory standards.
• Customizable Workflows: ELNs, LIMS, and inventory management solutions such as SciSure can be customized to fit the specific needs of individual labs, optimizing sample management processes.

The adoption of digital tools in laboratory environments is not merely a trend but a pivotal shift towards more sophisticated, efficient, and error-resistant sample management. As labs continue to modernize, the integration of technologies such as ELNs and digital inventories will become increasingly essential.

5 top tips to improve your lab's sample management processes 

Implementing digital solutions is just one aspect of effective sample management. There are a number of best practices that you can adopt to optimize your processes and minimize errors. Here are our top five tips to improve your sample management system:

1. Standardize protocols and procedures

Develop and enforce standardized protocols for all sample-related activities, from collection to storage to disposal. Clear, consistent guidelines and SOPs help reduce errors and improve efficiency, ensuring that all team members follow the same procedures.

2. Implement robust training programs

Regularly train all personnel on the latest sample management practices and technologies. Comprehensive training ensures that staff are proficient in both manual and automated systems, which is crucial for maintaining the integrity and accuracy of samples.

3. Regularly audit and update your systems

Conduct periodic audits of your sample management system to identify areas for improvement. Regularly updating your processes and systems in response to new technologies, changes in compliance regulations, or internal reviews can help you stay ahead of potential issues.

4. Maintain a contingency plan

Prepare for unexpected events, such as power outages, equipment failures, or natural disasters, by having a robust contingency plan in place. This should include backup storage solutions and detailed plans for protecting and recovering samples to prevent loss and ensure continuity of operations.

5. Ensure robust labeling and tracking

Consistent, accurate sample labeling and tracking are crucial for maintaining the integrity of samples and ensuring their traceability. Digital lab solutions are the easiest way to achieve this, bringing invaluable automated labeling and tracking capabilities to eliminate human error, streamline processes, and ensure accurate data management.

These tips are applicable to labs of all disciplines and sizes. By embracing these best practices, you can be sure to improve operational efficiency and research outcomes.

A smarter way to manage lab samples

Effective sample management is a critical component of modern laboratory operations, directly impacting research outcomes, productivity, and cost efficiency. By embracing digital solutions like our Digital Lab Platform, labs can overcome the challenges of traditional sample management practices and unlock new levels of efficiency.

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2024 is already shaping up to be a “highly digital” year: AI and digitalization are increasing exponentially, bringing new applications and breakthroughs. In the life sciences, including academia and biotech, labs with 30 years of legacy samples and data are experiencing pressure to digitize and organize. 

Every day, we hear stories from very reputable and historical academic, healthcare, and industry institutions asking us how they should digitize their samples because they have no idea where to start. Just yesterday, I visited a biotech lab with 14 freezers completely full. There was an average of 80,000 samples in each freezer, amounting to approximately 1.1M samples in total. The samples' owners and authors are no longer with the company, so the lab manager had to reach out to alumni to understand what is in those samples and whether they have any value. 

Imagine a world where you don’t have to do that because everything is already digitized! This process alone allowed the organization above to discard 1/3rd of these samples – 373,000 samples gone and 4.6 freezers liberated! Imagine the amount of money saved because of this. 

You didn’t need new freezers; you just needed better sample management!

The Path to Lab Digitalization

Embarking on the journey to digitize a laboratory, especially with extensive sample storage, can be overwhelming. However, breaking down the process into manageable steps and utilizing tools like SciSure (formerly eLabNext) can streamline the transition. 

This 9-step actionable guide provides detailed strategies to digitize your lab effectively, one sample at a time, ensuring a smooth and systematic approach.

1. Conduct a Comprehensive Inventory Assessment

Begin by thoroughly assessing your lab's sample inventory. Document the types of samples, storage conditions, and the quantity of samples stored. Reach out to all PIs, request clarification on sample metadata, and make a master Excel file of your legacy samples. If you currently use outdated software, export everything into CSV or Excel and organize it. This is an excellent opportunity for spring cleaning: Anything that is not claimed within a month of starting this process should be discarded to save space!

2. Develop a Prioritization Framework

Establish a prioritization framework to determine which samples to digitize first. I call those samples “high-profile samples.” Consider factors such as sample relevance to ongoing research projects, frequency of use, regulatory requirements, or even the cost associated with those samples. Engage with researchers and stakeholders to gather input and consensus on prioritization criteria. Don’t be afraid to be very direct and progress-oriented in your discussions!

3. Formulate a Digitization Task Force

Create a dedicated task force responsible for overseeing the digitization process. This team should comprise members from various departments, including researchers, lab managers, IT specialists, and data analysts. Assign clear roles and responsibilities to each team member to ensure accountability. You, as the lead, will use SMART/RACI or AGILE project management methodologies to complete this, with timelines and deadlines!

4. Standardize Data Entry Processes

Develop standardized data entry processes and protocols to maintain consistency and accuracy across digitized samples. Define data fields, naming conventions, and metadata requirements in collaboration with stakeholders. Provide comprehensive training to team members on these protocols. Platforms like SciSure have large-scale import features and a Customer Success team readily available to help you import thousands of samples at a time! This feature also allows you to convert existing data into compatible formats, such as Excel sheets, and utilize SciSure to upload information efficiently. Conduct thorough data validation checks before importing to ensure data integrity.

5. Adopt an Incremental Approach

Adopt an incremental approach to digitisation by starting with a small subset of samples before scaling up. Begin with a single freezer, rack, or shelf, and gradually expand to larger batches. This approach minimizes disruptions to ongoing research activities and allows for iterative improvements.

6. Implement Rigorous Quality Control Measures

Implement robust quality control measures to ensure the accuracy and reliability of digitized data. Establish data validation, cross-checking, and auditing protocols to identify and rectify errors promptly. Monitor data entry processes regularly and provide ongoing training to mitigate quality issues.

7. Document Standard Operating Procedures (SOPs)

Document standardized operating procedures (SOPs) for digitization processes and best practices. Create detailed guides covering data entry protocols, troubleshooting steps, and system usage instructions. Maintain an accessible repository of SOPs for reference and training purposes.

8. Foster Continuous Feedback and Adaptation

Encourage open communication and feedback loops throughout digitization. Regularly solicit input from stakeholders, including researchers and lab personnel, to identify challenges and areas for improvement. Adapt digitization strategies based on feedback to optimize efficiency and user satisfaction.

9. Celebrate Achievements and Sustain Motivation

This is one of the most overlooked attributes of this process! Scientists are so focused on day-to-day tasks that we forget to stop and smell the roses and celebrate people who accomplish things! Celebrate milestones and achievements reached during the digitisation journey to sustain motivation and morale. Recognize the efforts of the digitization task force and acknowledge progress towards the ultimate goal of a fully digitized lab. Set new goals and benchmarks to maintain momentum and drive continuous improvement.

Summary

Digitizing a lab, one sample at a time, demands a systematic and collaborative approach. By conducting a comprehensive inventory assessment, prioritizing samples, and leveraging tools like SciSure, the digitization process can be effectively managed. Establishing standardized processes, implementing rigorous quality control measures, and fostering continuous feedback is essential for ensuring data integrity and user satisfaction. With each step taken towards digitization, celebrate achievements and sustain motivation towards the overarching goal of an entirely digitized laboratory. Remember, it's a journey that starts with one sample, one box, one rack, and one shelf until the entire lab is seamlessly digitized.

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This article was originally published by eLabNext prior to its integration into SciSure. SciSure was formed in 2025 through the merger of eLabNext and SciShield.

eLabNext, an Eppendorf Group Company and leading provider of Digital Lab Platforms that include lab information management systems (LIMS), electronic lab notebooks (ELN), and artificial intelligence (AI)/machine learning (ML) solutions for life science laboratories, has joined forces with Zifo, a distinguished scientific informatics services company specializing in data and informatics consulting and software validation. This strategic partnership aims to deliver cutting-edge digitization tools to life sciences laboratories worldwide.

As part of this partnership, Zifo will offer product selection, configuration, integration, rollout, validation, and managed services support to eLabNext and its clients across the entire ELN lifecycle. Through this alliance, customers will benefit from streamlined processes and enhanced collaboration capabilities, ensuring optimal performance of their laboratory operations.

"We're excited about this partnership as it merges Zifo's bilingual expertise in science and technology with eLabNext's innovative product," explains Kannan Jagamoorthy, General Manager, Americas at Zifo. "This collaboration will usher in a new era of digital solutions in the laboratory space."

Further, eLabNext will deploy Zifo's GxP validation package for internal and external customer use, enabling a further commitment to achieving the highest quality assurance standards. As part of this arrangement, eLabNext will manage the procurement process for clients seeking GxP compliance services from Zifo, thus ensuring seamless delivery of validation reports.

"As a company, we make decisions based on value-driven impact for our current and future customers," says Zareh Zurabyan, Head of eLabNext, Americas. This aligns with Zifo's mission and vision, and the decision to partner with Zifo was a no-brainer, given our multiple customers in common. We are especially excited to collaborate with Zifo on enacting meaningful, positive change in the digital transformation of the pharmaceutical industry and the GMP space."

This strategic partnership heralds a new era in laboratory digitization, combining the expertise of two industry leaders to deliver unparalleled solutions and services to the life sciences community. With a shared commitment to innovation and excellence, eLabNext and Zifo are poised to redefine laboratory informatics and drive transformative outcomes for their customers.

About Zifo

Zifo is a global specialist in scientific and process informatics services, operating across research, development, manufacturing, and clinical domains. With expertise in over 90 partner technologies and platforms, Zifo serves customers in pharmaceuticals, biotechnology, contract research, industrial chemicals, food & beverage, consumer goods, and oil and gas industries. Zifo's "Glocal" approach leverages remote delivery to ensure cost-effective solutions and dedicated local support, providing engagement, success, and quality.

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Everyone who has worked in a lab has encountered a lab protocol or SOP at some point, but why are these documents important? Adherence to protocol ensures efficiency, Standardisation, and safety in daily lab processes. 

In this blog, we will highlight: 

1. Key differences between lab protocols and SOPs 
2. The importance of standardization in lab procedures 
3. How to write an effective lab procedure
4. Streamlining lab protocol creation and sharing with digital lab solutions

Laboratory protocols and Standard Operating Procedures (SOPs) are fundamental frameworks that ensure the consistency, safety, and accuracy of scientific experiments.

Lab protocols are detailed step-by-step instructions designed to carry out a specific experimental task or lab process. On the other hand, SOPs provide a comprehensive set of guidelines for almost any lab procedure, from ensuring lab cleanliness to proper equipment use, safe handling of hazardous substances, and lab maintenance procedures.

Together, lab protocols and SOPs form the backbone of daily laboratory operations, enabling scientists to conduct their work efficiently, securely and in compliance with regulatory standards. They serve as a blueprint for conducting research in a consistent and optimal manner.

Read on for our quick guide to lab procedures and protocols. We'll examine different procedure types, highlight the importance of standardization, and give our top tips on how to write effective SOPs for your lab—including how to streamline protocol writing with advanced digital lab solutions.

What are the main differences between Lab Protocols and SOPs?

The terms "lab protocol" and "SOP" are sometimes used interchangeably in the context of laboratory environments, although they often have distinct meanings depending on the context and specific use:

Lab Protocols:

• Purpose: A lab protocol typically refers to a set of instructions designed to carry out a specific experiment or a testing procedure. It details the steps necessary to perform a scientific experiment, a clinical test, or any sequence of actions in a lab setting.
• Specificity: Protocols are usually very specific and can be more detailed about experimental conditions, such as concentrations, temperatures, and equipment settings.
• Flexibility: While they should be followed as written to ensure consistency and reproducibility of results, protocols might be slightly adjusted or optimized according to specific research needs or objectives.

Standard Operating Procedures (SOPs):

• Purpose: An SOP is a broader document that provides step-by-step instructions to perform any task within a lab (or other environments) consistently and correctly. SOPs are used not only for experiments but for any procedure that should follow a specific standard to ensure lab safety and compliance.
• Scope: They cover a wider range of activities beyond scientific experiments, including general lab maintenance, daily procedures, data documentation, and other operational processes.
• Regulatory Compliance: SOPs are often required to comply with industry standards and regulatory guidelines. They are designed to ensure that different individuals can perform the same task in the same manner over time, enhancing efficiency and quality control.

While there may be some overlap between lab protocols and SOPs, both are crucial for maintaining high standards of practice, though their applications and the rigidity with which they must be followed can differ.

Importance of standardization in lab procedures

Lab protocols and procedures are central to establishing standardization within daily lab operations, ensuring that every process is performed consistently and effectively. 

Standardization in lab procedures is crucial for several reasons, particularly in scientific research, diagnostic testing, and any setting where precise and reproducible results are necessary. Here are some key aspects of why standardization is so important:

Consistency and Reproducibility

Standardization ensures that experiments or tests conducted in a laboratory yield the same results, irrespective of who performs them or when they are performed. This consistency is crucial for validating experiments and confirming results across different studies or even different laboratories.

Quality Control

Standard procedures help maintain high quality and reliability in experimental results. By following a standardized protocol, labs can minimize variability that might arise from different methodologies or operator errors, ensuring the data's accuracy and reliability.

Lab Safety

SOPs include detailed safety guidelines that are crucial for handling hazardous materials, operating complex machinery and ensuring general laboratory safety. Standardisation in these procedures helps prevent accidents and ensures the safety of lab personnel.

Efficiency and Time Management

Having a set of well-defined, standardized procedures reduces the time needed for training and briefing. New personnel can quickly learn and adapt to established methods, which increases the overall efficiency of the laboratory. It also helps to manage resources better by eliminating unnecessary variations in the use of materials and equipment.

Regulatory Compliance

Many laboratories operate under strict regulatory conditions imposed by governmental and international bodies, especially in the pharmaceutical, medical, and food industries. Standardized procedures ensure that labs comply with these regulations, helping to maintain certifications and avoid legal or ethical violations.

Cost Efficiency

By reducing errors and reiterations of experiments, standardised procedures can lead to significant cost savings. Consistent protocols minimise the waste of expensive reagents and samples, which can have a substantial impact on lab budgets.

In summary, the standardization of lab procedures is integral to the scientific process, ensuring that results are accurate, reliable, and verifiable. This not only boosts the credibility of the scientific findings but also enhances operational efficiency within laboratories.

How to write an effective lab procedure

When writing a lab protocol or SOP, it can be useful to follow a stepwise process. Follow this guide to start writing effective lab protocols or SOPs for your lab:

1. Define the Purpose

Start by clearly stating the purpose of the protocol or SOP. Specify what the procedure will accomplish and why it is important. This sets the context and ensures all users understand the intent behind the procedure.

2. Scope and Application

Outline the scope of the protocol or SOP. Explain when and where it should be used and by whom. This section should also list any prerequisites, such as necessary qualifications, training, or conditions required before performing the task.

3. List of Materials and Equipment

Provide a detailed list of all materials, equipment and software needed to complete the procedure. Include specific models, settings and any safety gear required.

4. Detailed Steps

Break down the procedure into clear, numbered steps. Each step should be concise and describe precisely what needs to be done. Use bullet points for clarity and ensure that the steps are in the correct order.

5. Safety and Compliance Notes

Include any safety instructions related to the procedure. Highlight critical steps, potential hazards, and emergency response actions. Ensure all compliance guidelines are met and documented within the SOP.

6. Quality Control Checks

Integrate checkpoints or quality control measures to ensure the procedure's output meets the required standards. Specify how results should be evaluated and recorded.

7. Documentation and Reporting

Detail how the results should be documented, who should receive the reports, and the format for these reports. Ensure the process aligns with data integrity and record-keeping requirements.

8. Review and Approval

Before finalizing, the protocol or SOP should be reviewed by senior staff or peers. This review ensures accuracy and practicality. Once reviewed, it should be approved by the required authority.

9. Revision History

Keep a revision log at the end of the document to track changes. Include dates, the nature of revisions, and who approved the changes.

Adopting a structured approach such as this helps create comprehensive and reliable lab protocols and SOPs, enhancing the efficacy of daily laboratory operations.

Streamlining lab protocol creation and sharing with digital lab solutions

Whether your lab relies on paper-based lab protocols or stores key protocol documents in an online file-sharing system, your lab could benefit from a comprehensive digital lab solution tailored to creating, sharing, and accessing key lab protocols and SOPs.

SciSure (formerly eLabNext) for Protocol and SOP Management is an advanced digital system for creating and sharing dynamic and interactive protocols and SOPs. The platform allows lab personnel to easily access necessary protocols anywhere, anytime, reinforcing compliance and facilitating seamless collaboration through a shared protocol library and integrated communication tools.

This powerful digital lab solution offers a user-friendly interface, making it easy for labs to generate step-by-step interactive protocols that guide laboratory processes. Every change made to a protocol is tracked, ensuring transparency and accuracy throughout your work processes. In addition, our platform comes equipped with a wide range of templates for common lab protocols, saving you time when creating protocols. 

SciSure can enhance adherence, lab safety, and collaboration within your team via a shared library for protocols and SOPs.

AI protocol generation and beyond

In addition to the robust protocol creation and sharing that can be achieved with our platform, SciSure has recently developed an AI-powered Protocol Generation Add-On – an innovative tool designed to transform and streamline your lab's protocol and SOP creation experience.

Powered by advanced generative AI software, the add-on overcomes the tedious task of manually creating protocols, automating the generation of comprehensive protocols from a brief description of your experiment, significantly cutting down your time and effort.

Available as an add-on, the generative AI tool eases the burden of documentation. Beyond protocols and SOPs, the tool can also assist in swiftly producing detailed lab reports and experiment summaries, allowing you to dedicate more time to research and less to paperwork.

A better way to manage lab procedures?

Understanding and utilizing lab protocols and SOPs is not just about maintaining standards; it's about enhancing the efficiency, safety, and efficacy of scientific research.

Adopting digital tools can greatly enhance the creation, management and adherence to these crucial documents. Whether you're drafting your first SOP or looking to refine existing procedures, adopting digital solutions from SciSure can not only streamline the protocol creation process, but also ensures that all procedures are up-to-date, consistent and accessible, reducing human error and increasing productivity.

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Biomedical research is critical in advancing healthcare and understanding biological processes. This work often involves handling potentially hazardous biological agents, making biosafety a critical aspect of laboratory operations. As research continues to innovate and explore new frontiers, the need for robust biosafety programs remains a priority.

Understanding Biosafety Levels (BSLs)

The Centers for Disease Control and Prevention (CDC) define biosafety levels through the Biosafety in Microbiological and Biomedical Laboratories (BMBL) guidelines. The BSL framework is intended to categorize laboratories based on the risk posed by the biological agents they handle. This framework outlines four biosafety levels (BSL-1 to BSL-4) with increasing stringency in safety practices and containment measures.

• BSL-1: This is the basic level for handling minimal risk agents, suitable for work involving well-characterized agents not known to cause disease consistently in immunocompetent adult humans. Basic practices such as hand washing, the use of personal protective equipment like lab coats and gloves, and good laboratory hygiene are typically sufficient.
• BSL-2: This level applies to laboratories working with moderate-risk agents that can cause human disease but are typically spread through direct contact. Additional precautions beyond BSL-1 include controlled access to the laboratory, specific training for personnel, and the use of appropriate personal protective equipment.
• BSL-3: This level is for handling high-risk agents that can cause serious or fatal diseases via inhalation or exposure to bodily fluids. In addition to BSL-2 controls, BSL-3 facilities have additional engineering controls such as specialized ventilation systems to prevent the release of infectious aerosols.
• BSL-4: This is the highest biosafety level for laboratories working with dangerous and exotic agents that pose a high individual risk of aerosol-transmitted infections and life-threatening disease that are frequently fatal and for which there are no vaccines or treatments. This level is required for related agents with unknown risk or route of transmission. Most stringent safety and containment measures including complete isolation from the outside environment through multiple airlocks and highly specialized ventilation systems.

Key Components of Biosafety

Effective biosafety controls include several key components:

• Facility Design: The laboratory design itself plays a critical role in biosafety. Well-designed facilities incorporate physical barriers like self-closing doors, airlocks, sealed walls, and HEPA-filtered ventilation systems to control airflow and prevent the escape of pathogens. The layout of the lab should also minimize the risk of contamination by separating areas with different biosafety levels.
• Engineered Equipment: Safety equipment plays a critical role in biosafety. Primary barriers in biosafety are physical containment measures (e.g., biological safety cabinets (BSCs), centrifuge safety cups) that protect laboratory personnel and the environment from exposure to infectious agents. They are the first line of defense against splashes, spills, and aerosols that can contain harmful biological agents.
• Safe Work Practices, Training, and Procedures: Safe lab practices minimize the risk of exposure to infectious agents by ensuring aseptic techniques, having established protocols for handling biological materials, and ensuring proper disposal of biohazardous waste.
• Risk Assessment: A biosafety risk assessment is a systematic process that identifies, evaluates, and mitigates risks associated with the use of biological agents. It aims to:
  • Identify procedural hazards and hazardous characteristics of biological agents that are handled.
  • Classifies biological agents into risk groups according to their degree of risk of infectivity, virulence, pathogenicity, availability of preventive measures and effective treatments, and potential damage to the environment.
  • Determine the appropriate biosafety level for controls and restriction understanding.
  • Consider biosecurity which focuses on the prevention of theft, loss, and misuse of hazardous biological agents and toxins, equipment, and/or valuable information.
  • Identify and implement controls to minimize the risk of exposure to biological agents for workers, the environment, and the community.
  • Ensure regulatory compliance with local and national biosafety regulations.

Learn how to create your own biosafety risk assessments in our guide.

• Personal Protective Equipment: Personal protective equipment (PPE) like gloves, gowns, and respirators are the last line of defense and provide additional protection. This combination minimizes the risk of exposure to infectious agents during laboratory procedures.

Maintaining Biosafety in the Workplace

Improving biosafety hazard identification, evaluation and control can be attained by doing the following:

• Form a Biosafety Committee: A dedicated committee with expertise in biosafety and laboratory operations should oversee the implementation and monitoring of biosafety research and operations. This committee, composed of laboratory personnel, EHS professionals, and operational stakeholders should oversee all aspects of biosafety within the facility.  Their responsibilities include reviewing proposed research activities for EHS concerns, approving the use of biological agents, and ensuring compliance with biosafety requirements.
• Conduct Regular Risk Assessments: Employers must conduct biosafety risk assessments to determine which employees have exposures from work activities or conditions that are reasonably anticipated to elevate risk of contracting a disease caused by an infectious agent. Laboratories that perform procedures with biohazardous materials that contain transmissible pathogens are likely to have occupational exposure to these agents. A biosafety risk assessment evaluates risks, so the appropriate control measures are implemented to prevent illness. Regularly assess the risks associated with the biological agents being handled and adjust protocols as needed.
• Develop Emergency Preparedness and Response Plans: Emergency preparedness and response plans must cover procedures to handle spills and exposures, an exposure control plan, accessing emergency contact information, and how to report an incident involving biohazards. Facilities where human blood or other potentially infectious materials (OPIM) exist as an occupational hazard should have a specific exposure control plan. The purpose of the exposure control plan is to describe practices to prevent or minimize exposure to human blood, bloodborne pathogens (BBP), or other potentially infectious materials (OPIM).
• Training and Competency: The priority of biosafety training is to reduce the risks of biological agents through awareness and work practices. Do the following in biosafety training:
  • Communicate containment measures associated with biological risk groups and biosafety levels.
  • Educate laboratory personnel on safe practices for handling biological materials and the prevention of laboratory acquired infections.
  • Ensure compliance with regulations.

Challenges and Solutions in Biosafety Management

Challenges to managing effective biosafety programs include:

• Keeping Up with Emerging Threats: New and emerging infectious diseases can pose unforeseen risks.
  • Regular biosafety program reviews and updates are critical to address evolving threats. Design biosafety programs with the ability to adapt to new threats.  
  • Encourage collaboration and information sharing between researchers, institutions, and public health agencies to stay informed about emerging pathogens.
  • Regularly review risk assessments to categorize biological agents and adjust biosafety levels as needed.

• Resource Limitations: Implementing and maintaining stringent biosafety measures can be resource-intensive, especially for smaller labs. Biosafety programs require investment in proper facilities, equipment, training, and qualified personnel.
  • Explore grant opportunities and public-private partnerships to secure funding for biosafety infrastructure and training.
  • Focus resources on areas with the highest risk profiles.
  • Technology like hazardous substance inventory software can help address some of these challenges by streamlining processes, improving data management, and facilitating regulatory compliance.
• Training Needs: Ensuring continuous training for all laboratory personnel requires ongoing commitment and resources.
  • Implement training programs to keep staff up-to-date on the latest biosafety protocols and techniques.
  • Conduct regular assessments to evaluate staff proficiency in biosafety procedures.
  • Best practices like sharing resources and collaborating with institutions or industry groups can optimize training programs and cost-effectiveness.

Biosafety Regulatory Bodies and International Standards

Organizations like the CDC, NIH, and WHO play a crucial role in establishing and promoting global biosafety standards. Their guidelines offer a framework for national regulations and promote international collaboration in research.

• Centers for Disease Control and Prevention (CDC) - In collaboration with the National Institutes of Health (NIH), the CDC publishes the Biosafety in Microbiological and Biomedical Laboratories (BMBL) guidelines.  This document serves as the primary reference for safe laboratory practices in the US, outlining recommendations for containment measures, biosafety levels, and safe work practices for various biological agents.

• National Institutes of Health (NIH) – In addition to the BMBL guidelines mentioned above, the NIH sets biosafety requirements for institutions that receive NIH funding for research involving biological agents.

• World Health Organization (WHO) - The WHO issues biosafety guidelines that provide recommendations for laboratory practices in resource-limited settings and other international contexts.

Conclusion

In conclusion, biosafety controls are crucial during the design of laboratories and operational stages. Engineering controls, safe work practices, risk assessments, biosafety stakeholder engagement, and PPE will assist in mitigating risks to as low as reasonably achievable. By proactively identifying potential and emerging hazards associated with biological agents – including storage, use, and modification – and including the appropriate cross-functional interested parties in management of biosafety, organizations can establish a strong foundation for continual improvement of biosafety programs.

Materials that are hazardous due to their biological or infectious properties are called biohazardous materials or simply biohazards. Research laboratories work with a variety of biological agents including recombinant or synthetically derived nucleic acid, blood, tissues, body fluids, cell lines, bacteria, viruses, viral vectors, plasmids, fungi, prions, or parasites that cause disease in humans, animals, or plants. Recognizing these hazards and their associated risks is essential for implementing effective health & safety controls.

Understanding Biological Hazards

To ensure the safety of people, the environment, and the public, it’s crucial to have proper biosafety measures in place. Certain workplace safety laws require employers that are exposed to transmissible infectious pathogens to have effective written safety plans and controls in place. Laboratories that perform procedures with biohazardous materials that contain transmissible pathogens are likely to have occupational exposure to these agents.

Here are some common biohazard examples found in laboratories:

• Blood and Other Potentially Infectious Materials (OPIM): Human and animal blood, along with other bodily fluids, can transmit various pathogens.
• Laboratory Cultures and Samples:Working with cultured microorganisms and biological research materials carries the risk of exposure to infectious agents.
• Contaminated Sharps: Used syringes, needles, and other sharp instruments contaminated with biohazardous materials pose a significant risk of puncture wounds and potential infection.
• Fungal Growth: Mold and yeast can thrive in laboratory environments, causing respiratory problems and allergic reactions.
• Waste from Animals: Animal waste or contaminated bedding can harbor harmful pathogens.

Risk Groups and Biohazard Safety Levels

Biological agents are classified according to their risk level when considering infectivity, pathogenicity and availability of preventive measures and treatments for the corresponding disease. The National Institute of Health has established classification of biological agents into four risk groups (1-4).

The Centers for Disease Control and Prevention (CDC) define biosafety levels through the Biosafety in Microbiological and Biomedical Laboratories (BMBL) guidelines. The BSL framework is intended to categorize laboratories based on the risk posed by the biological agents they handle. This framework outlines four biosafety levels (BSL-1 to BSL-4) with increasing stringency in safety practices and containment measures. See our Biosafety Guidelines guide for more information on these risk groups and BSLs.

5 Opportunities to Prevent Biohazards Through Effective Biosafety and Biosecurity Governance

1. A single, centralized system for biological registration approvals

There's a growing demand for stricter regulations regarding oversight. Organizations in the US receiving federal funding have to comply with NIH Guidelines, and the White House OSTP recently introduced a comprehensive Policy for Oversight of Dual Use Research of Concern and Pathogens with Enhanced Pandemic Potential (DURC), effective from May 6, 2025. Similarly, the EU has its own directives concerning exposure to biological agents.

The emphasis is shifting from considering robust registration and approval systems for work involving biological agents as optional to regarding them as essential. Having a single, centralized system for biological registration approval ensures an organization adheres to high standards for biosafety, regulatory compliance, and internal processes with efficient oversight of projects, biological materials, and potential exposures.

2. Biosecurity - Who is working on what? Where?

Understanding who is working on what and where within a biomedical lab presents a pivotal opportunity for enhancing overall biohazard prevention strategies. By implementing comprehensive biological registration and authorization systems, organizations can gain real-time visibility into project activities, including tracking material, personnel, and space exposure levels.

Streamlining registration management processes reduces approval times and facilitates efficient communication, ensuring robust oversight and risk management throughout the project lifecycle.

Furthermore, driving consistency in materials management through standardized biomaterials libraries enables organizations to establish controls over materials usage, personnel, and locations, thereby enhancing biosecurity and internal compliance processes. This holistic approach to understanding lab activities fosters a culture of accountability and transparency, ultimately mitigating risks associated with biohazard incidents and safeguarding the well-being of personnel and the broader community.

3. Institutional Biosafety Committee Oversight for Biologicals Projects

Expanding the requirement for institutional biosafety committees to encompass all institutions engaged in high-containment laboratory activities presents a significant opportunity to enhance effective biosafety and biosecurity governance. Currently, only federally funded institutions conducting recombinant or synthetic nucleic acid research are mandated to have such committees, leaving privately funded institutions exempt from compliance. This discrepancy in regulatory oversight underscores the need for a level playing field, ensuring that all institutions conducting similar high-risk activities adhere to standardized review processes and oversight mechanisms.

By mandating a universal requirement for local oversight bodies, potential risks associated with laboratory-acquired infections and biological incidents can be mitigated. This approach not only ensures a consistent level of review and approval across all institutions but also addresses public concerns regarding the oversight and input of risky research conducted within communities. While there are challenges such as additional bureaucracy for non-compliant organizations and the need to establish and operate biosafety committees, the benefits of standardized oversight outweigh the disadvantages, promoting transparency, safety, and community trust in biosafety practices.

4. De-risking the Organization and Personnel with Training and Assessment of Biohazards

In high-containment laboratories like BSL-3 and BSL-4 facilities, personnel handle indigenous or exotic agents capable of causing severe or fatal diseases. Training in the safe handling of such pathogens is crucial for personnel, who must be supervised by knowledgeable scientists. However, the consistency and rigor of this training vary across institutions, highlighting the need for standardized assessment and guidance to ensure personnel proficiency and risk awareness.

Establishing minimum education and training requirements for personnel in high-containment laboratories offers several benefits for effective biosafety governance. It fosters confidence in the competence of individuals working with hazardous pathogens, promoting trust within the community. Moreover, by ensuring that personnel understand and can manage risks effectively, such standards enhance overall laboratory safety. However, implementing new requirements may pose challenges, particularly in adapting regulations across diverse research operations and ensuring compliance among existing workforce members. Despite these obstacles, standardized training protocols are essential for safeguarding personnel, institutions, and the wider community from biohazard risks.

5. Inspections and Medical Surveillance

By implementing robust biosafety management protocols with software such as SciSure for Health & Safety (formerly SciShield), organizations can identify personnel handling biological agents and mitigate exposure risks effectively. Leveraging Learning Management Systems (LMS) presents an opportunity to automate training assignments tailored to individual staff members' risk exposures, ensuring they receive necessary medical clearances, vaccinations, and skill enhancements. Simultaneously, optimizing equipment management processes ensures the availability and functionality of safety gear, bolstering biosecurity measures.

Strategic biosafety inspections of laboratory spaces provide organizations with a chance to ensure compliance with safety protocols, promptly addressing vulnerabilities. Embracing medical surveillance systems enables proactive tracking and management of personnel health, facilitating timely interventions such as medical clearances and vaccinations. By capitalizing on these opportunities, organizations can fortify their biosafety and biosecurity frameworks, creating safer environments for personnel and the wider community.

Managing Biological Hazards with Software

Implementing a robust biosafety program is essential to protect yourself, your colleagues, and the environment from biohazards. Investing in biological software solutions can significantly enhance your biohazard management practices, promoting safety, regulatory compliance, and overall lab hazard awareness.

Biotech R&D has birthed some of the most impressive innovations, from recombinant DNA to genome editing. While the road to commercialization has always been challenging, many fundamental barriers to innovation have grown bigger. Currently, there’s an overload of unstructured data and ideas. Translating these into world-changing ideas presents a huge organizational and logistical challenge.

With the rise of generative AI in the past year, a solution to some of these issues is on the horizon. Generative AI can promote divergent thinking, challenge the bias of experts, evaluate and refine ideas, and facilitate collaboration across niche research areas. It’s also streamlining the data lifecycle and changing the creative aspects of biotech lab operations, such as automating and improving the quality of content, from lab notebooks to published scientific literature. 

In the following blog, we look at what generative AI is, how it works, and its applications in biotech and the broader life sciences.

What is Generative AI? 

Generative AI, or Gen AI, is a class of artificial intelligence techniques and algorithms that generate new data samples or content, including audio, code, images, text, simulations, and videos. 

Unlike discriminative models that focus on classification or prediction tasks based on existing data, generative models learn the underlying patterns and structures of the data to generate new instances that are statistically similar to the training data.

Gen AI Encompasses a Wide Range of Algorithms and Approaches

Gen AI has applications across various domains, including image generation, text synthesis, music composition, drug discovery, and content creation. It enables the generation of realistic and diverse data samples, facilitates data augmentation for training machine learning models, and fosters creativity and innovation in AI-driven applications.

There are several algorithms and approaches, including:

• Generative Adversarial Networks (GANs): GANs consist of two neural networks, a generator and a discriminator, which are trained simultaneously in a competitive manner. The generator learns to generate realistic data samples, such as images, text, or audio, while the discriminator learns to distinguish between real and generated samples. Through adversarial training, GANs produce high-quality synthetic data that closely resembles the distribution of real data.
• Variational Autoencoders (VAEs): VAEs are probabilistic generative models that learn to encode and decode data samples into a lower-dimensional latent space. By sampling from the latent space and decoding the samples back into the original data space, VAEs can generate new data samples that capture the variability and structure of the training data. VAEs are commonly used for generating images, text, and other complex data types.
• Autoregressive Models: AutoRegressive models, such as autoregressive neural networks (ARNs) and autoregressive moving average (ARMA) models, generate data sequences by modeling the conditional probability distribution of each data point given the previous observations. By iterative sampling from the conditional distribution, autoregressive models generate sequences of data samples, such as time series data, speech, or text.
• Transformers: Transformers are a class of deep learning architectures that have achieved state-of-the-art performance in natural language processing (NLP) tasks. Transformers, particularly variants like GPT (Generative Pre-trained Transformer) and BERT (Bidirectional Encoder Representations from Transformers), can generate coherent and contextually relevant text by modeling the relationships between words or tokens in a sequence.

How Does Gen AI Work?

Gen AI uses various techniques – including neural networks and deep learning algorithms – to identify patterns and generate new outcomes based on them. The training process for a generative model involves feeding it a large dataset of examples, such as images, text, audio, and videos. While traditional AI aims to perform specific tasks based on predefined rules and patterns, gen AI goes beyond this limitation and strives to create entirely new data that resembles human-created content. A language model is an example of gen AI, using a probabilistic model of a natural language that can generate probabilities of a series of words based on text corpora in one or multiple languages it was trained on. Large language models, in their most advanced form, are a combination of feedforward neural networks and transformers.

In the area of natural language processing, there is also a neural network, a method in artificial intelligence that teaches computers to process data in a way inspired by the human brain. Deep learning is a type of machine learning process that uses interconnected nodes or neurons in a layered structure that resembles the human brain. These algorithms can take different data inputs and be used for speech and voice recognition.

How is Gen AI Currently Used in Biotech?

Gen AI is increasingly utilized in biotech and life sciences across several applications, leveraging its ability to generate realistic and diverse data samples. Some key areas where Gen AI is currently being used in biotech and life sciences include:

• Drug Discovery and Development: Gen AI generates novel molecular structures with desired properties for drug candidates. Generative models like GANs and VAEs can generate new chemical compounds with specific pharmacological properties, helping identify potential drug candidates and accelerating the drug discovery process.
• Protein Design and Engineering: Gen AI techniques are employed to design and engineer proteins with enhanced functionalities or specific biological activities. Researchers can design novel enzymes, antibodies, or therapeutics for various applications, including enzyme engineering, drug delivery, and immunotherapy, by generating protein sequences or structures with desired properties.
• Biological Image Synthesis: Generative models synthesize realistic biological images, such as microscopy images of cells, tissues, or organisms. These synthesized images can be used to augment training datasets for image analysis algorithms, improve the generalization of machine learning models, and generate data for virtual screening and testing of algorithms in silico.
• Omics Data Generation: Gen AI techniques are applied to generate synthetic omics data, including genomics, transcriptomics, proteomics, and metabolomics data. Synthetic omics data can be used to supplement real experimental data, simulate biological processes, and validate computational models, enabling researchers to explore complex biological systems and discover biomarkers or therapeutic targets.
• Text and Literature Generation: Generative models generate text-based content, such as scientific articles, literature reviews, or drug interaction reports. These generated texts can assist researchers in literature mining, knowledge discovery, and data summarisation, facilitating literature-based research and biotech and life sciences decision-making.
• Biomolecule Design and Synthesis: Gen AI techniques are used to design and synthesize novel biomolecules, such as peptides, aptamers, or nucleic acids, with specific functions or properties. By generating sequences or structures with desired characteristics, researchers can develop biomolecules for diagnostics, therapeutics, and biosensing applications.

Overall, Gen AI is revolutionizing biotech and life sciences by enabling the generation of novel data samples, molecules, and biological entities, fostering innovation, and accelerating research and development efforts in various domains. As the field continues to advance, Gen AI is expected to play an increasingly pivotal role in shaping the future of biotechnology and life sciences, including clinical research. Gen AI can help identify which patient cohorts will respond best to specific drugs, developing more personalized medicine. On the operational and marketing sides, generative AI can optimize the supply chain, manufacturing processes, and marketing and advertising strategy. 

What Are the Concerns About Using Generative AI in Biotech?

• Data Quality and Bias: Gen AI models rely heavily on the quality and representativeness of training data. In biotech and life sciences, datasets may suffer from biases, inaccuracies, or limited diversity, impacting performance and generalization ability. Biases in training data can lead to the generation of biased or unrealistic samples, hindering the reliability and validity of generated results.
• Interpretability and Trustworthiness: Many Gen AI techniques, such as deep neural networks, are complex and opaque, making it challenging to interpret and trust the generated outputs. In critical applications like drug discovery and biomolecule design, it is crucial to understand how and why generative models generate specific outputs. Lack of interpretability can impede the adoption of Gen AI in decision-making processes and regulatory approval, limiting its utility in real-world applications.
• Mapping Data: Mapping data in biotech and life sciences presents challenges due to the complexity and heterogeneity of biological systems and the diversity of data types and sources. Integrating and mapping heterogeneous data types requires harmonizing data structures, ontologies, and metadata to ensure data consistency across datasets. Challenges in mapping data can affect the accuracy and reliability of Gen AI models trained on such data, impacting their performance and applicability in real-world scenarios. Addressing issues related to mapping data is essential to ensure the quality and reliability of data inputs for Gen AI models in biotech and life sciences. 

Day-to-Day Usage of AI for Lab Operations

Above, we’ve listed the broader research applications in which Gen AI can be used. However, in day-to-day lab operations, the average life sciences and biotech scientist can utilize Gen AI in several ways. Gen AI can replace manual and repetitive tasks, freeing up resources for more complex and creative tasks. 

• Data Analysis and Interpretation: Gen AI can assist scientists in analyzing and interpreting experimental data more efficiently. By employing machine learning algorithms, scientists can train models to recognize patterns, identify correlations, and extract meaningful insights from complex datasets, such as omics data, biological images, or high-throughput screening results. Gen AI can automate data analysis tasks, streamline data interpretation processes, and provide actionable insights to guide experimental design and decision-making in the lab.
• Experimental Design and Planning: Gen AI can aid scientists in designing and planning experiments by generating hypotheses, optimizing experimental conditions, and predicting outcomes. By leveraging predictive modeling techniques, scientists can simulate experimental scenarios, predict experimental outcomes, and identify optimal experimental parameters to achieve desired objectives. Gen AI can assist in experimental design optimization, resource allocation, and risk assessment, helping scientists make informed decisions and maximize experimental efficiency in the lab.
• Literature Mining and Knowledge Discovery: Gen AI can assist scientists in literature mining and knowledge discovery by analyzing scientific literature, extracting relevant information, and synthesizing knowledge from diverse sources. Natural language processing (NLP) techniques can extract key concepts, identify relationships between scientific entities, and summarise findings from research articles, patents, and databases. Gen AI can automate literature review processes, facilitate literature-based research, and accelerate knowledge discovery in specific research areas, enabling scientists to stay up-to-date with the latest advancements and make informed decisions in the lab.

Summary

Integrating generative AI into the biotech industry brings significant benefits and notable concerns. By leveraging generative AI, researchers can tackle the challenge of navigating through vast amounts of unstructured data and ideas, fostering divergent thinking, and facilitating collaboration across niche research areas. Moreover, generative AI streamlines various aspects of biotech lab operations, from automating content generation to improving the quality of scientific literature. However, concerns regarding data quality and bias, interpretability, trustworthiness, and data mapping remain pertinent. Despite these challenges, the day-to-day usage of generative AI in lab operations holds promise, enabling scientists to enhance data analysis and interpretation, optimize experimental design and planning, and accelerate literature mining and knowledge discovery. As generative AI continues to evolve, its role in revolutionizing biotech research and development is poised to expand, shaping the future of precision medicine, drug discovery, and other critical areas within the life sciences.

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A Digital Lab Platform (DLP) helps streamline complex and time-consuming tasks by automating, integrating, or optimizing lab operations and workflows. This allows scientists to focus on research rather than administrative tasks, resulting in more efficient use of resources and fewer manual errors. Through an open ecosystem design that seamlessly integrates with existing tools and services, the Developer Hub extends the digital lab platform capabilities to provide a scalable and future-proof solution for life science research and development laboratories. 

In contrast to the one-dimensional nature of traditional ELNs (Electronic Laboratory Notebooks) and LIMS (Laboratory Information Management Systems) systems, the foundation of eLabNext serves as a unifying force, connecting various laboratory operations and making the platform multi-dimensional. This truly transformative platform is designed to improve efficiency, speed of innovation, and seamless integration of digital tools within the laboratory in the world of life science research and development. As a result, the Developer Hub is changing the way scientists and developers work together to improve the way laboratories operate and is leading the way in a new era of digitization for scientists around the world. 

Innovative Digital Features to Accelerate Lab Operations

An open ecosystem is a powerful tool for facilitating sharing and collaboration within and across organizations. By enabling easy integration with a wide range of tools and services, a digital lab platform contributes to a more connected and collaborative research environment. eLabNext Developer is built to provide a broad range of tools to users to customize features for a digital laboratory environment. The laboratory information management platform is designed as an open ecosystem that seamlessly integrates with various tools and services, which increases the system’s flexibility and capabilities. This includes a powerful Software Development Kit (SDK) and an Application Programming Interface (API), which allow developers to innovate, automate, and improve their workflows and system operation. Together, these features empower developers with everything they need to access their next-generation all-in-one Digital Lab Platform capabilities. 

Key SciSure Developer Features for Lab Digitalization

• The first-to-market developer hub for the life science R&D lab platform with a comprehensive, all-in-one platform for access to developer tools for building, deploying, testing, and releasing add-ons to the Marketplace. 
• SciSure extension or customization of workflows and functionality in eLabNext, or extend and integrate existing IT and information systems using our Software Development Kit (SDK) and API. Further increase efficiency, data consistency, and process automation in the lab. 
• Device, product and service providers can use SciSure to connect their products and services to a digital lab used by over 60,000 scientists worldwide to enable the complete digitisation of the laboratory. 
• As a truly scalable digital lab platform, the Developer Hubwill empower R&D laboratories and organizations to adapt to changing market needs and new products by easily integrating software tools, products, and services as they become available. 

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