Customize SciSure to work your way

Most of the universities I work with may or may not be using chemical inventory software. They might have a facilities system, a training platform, a chemical inventory spreadsheet that one person really understands, and maybe a homegrown database someone built a decade ago. What they're short on is information they can trust.

When a university starts looking at academic lab safety software, the conversation usually opens with features. Can it do inspections? Does it track chemicals? Can it produce a Tier II report? Those questions matter. But after more than ten years of helping research institutions with lab safety and chemical inventory, and now leading solutions consulting at SciSure, I've found that the decision comes down to something simpler: will the people in your labs even use it?

Here's what I'd encourage any university to think through before signing a contract.

1. Put ease of use for the end user first

One of the biggest things universities should prioritize is ease of use for the end user. You can have a system with great functionality, but if researchers, lab staff, or PIs find it difficult to use, you're going to struggle to get the participation and information you need.

In fact, when I attended CSHEMA (the Campus Safety, Health and Environmental Management Association conference) this summer, a senior EHS leader described adoption as his single biggest buying criterion. Ahead of module coverage, and ahead of price.

Think about who the end user really is on a university campus. It's the second-year graduate student logging a new bottle of acetonitrile at 6pm on a Friday. It's the postdoc fitting biosafety refresher training between experiments. It's the PI approving a protocol amendment in the same week as a grant deadline and a full teaching load. For every one of them, safety software is a small part of the day. Every extra click is a reason to put it off.

G2 users have also given SciSure Health & Safety Leader badges for Best Usability and Highest User Adoption, which honestly means more to me than any single feature.
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"As an EHS professional, I'm able to get all necessary information, i.e., inspections, training, personnel, chemical inventory, etc., all at my fingertips."

‍- Tom K, Laboratory Safety Program Manager, Enterprise (>1000 employees)

2. Plan for turnover

Every fall, a new cohort of students arrives, and every spring experienced lab members leave. A system that only makes sense after an afternoon of training will always be playing catch-up. So, test your lab safety software of choice with the people who'll actually use it.

For example, put the tool in front of a graduate student, a lab manager, and a PI, and watch them work without a guided demo. Or time a few everyday tasks: adding a chemical container, finding an SDS, checking whether someone's training is current. Make sure to ask how it works at the bench, with barcode scanning or a phone, and not only at a desk.

At SciSure, we measure adoption across our customers' labs instead of assuming it. Averaged across those labs, here's what changed when 30+ labs and organizations implemented SciSure Health & Safety.

Those numbers matter to me because they show people opening the system instead of working around it. It's the same reason we treat the scientist experience as a design requirement.

3. Choose software that works the way a university works

You want a system that understands the relationships between people, lab groups, spaces and hazards, so information lands in the right place without anyone typing it in twice.

Jennifer Ramil, Director of EHS at San Diego State University (SDSU), described exactly this after her team moved to SciSure:
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"If a person is in multiple labs, their training applies to all labs... Other systems (besides SciSure) were unable to make these kinds of relationships."

When those links exist, PIs can see what's happening in their own labs, and they start to take part. At SDSU, Jennifer found that this visibility led to "the PIs taking an active role in managing their labs." That's the shift every EHS team hopes for, and it's very hard to get from a system PIs never open.

4. Look for depth where your risk actually is: Inside the lab

A research university holds a lot of risk in a small amount of space. One building might contain thousands of chemical containers, biological agents covered by an Institutional Biosafety Committee (IBC) protocol, radioactive materials and lasers, all looked after by people whose main job is research.

Ask each vendor to walk through these lab-level workflows in detail:

• Chemical inventory
  Can you track chemicals at the container level with SDSs attached automatically and locations you can trust?

• Training
  Can training be assigned by role and hazard, with automatic reminders, to support requirements like the OSHA Laboratory Standard?

• Biosafety and radiation
  Does it support protocol workflows, risk classification and radioisotope inventory?

• Inspections
  Can you run lab inspections and self-inspections, track corrective actions, and see coverage across every lab space?

• Regulatory reporting
  Can it produce Tier II, Right-to-Know and fire code reports from the inventory you already keep?

SciSure Health & Safety was built around research lab workflows like these. ChemTracker handles container-level chemical inventory with SDS matching, barcode and RFID (radio-frequency identification) scanning, and push-button reports where configured, including Tier II and fire code maximum allowable quantity (MAQ) reports. Those reports support your review with the local fire authority; they don't replace it.

Alongside ChemTracker sit modules for biosafety, radioisotopes, inspections, training, incidents, hazardous waste and medical surveillance, so a university can switch on what it needs.

Pamela Fatland, Director of Occupational and Environmental Health and Safety at Tulane University, summed up what that looks like day to day:  
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"ChemTracker created a much safer place; people can look up chemicals quickly and discover PPE needs from SDSs."

If you'd like to go further, 5 lab problems ChemTracker solves out of the box and the 5 best EHS software platforms for labs cover each area in more detail.

5. Ask what "low-cost" really costs

In my experience, lower-cost or free solutions can work to a point, but they're often fairly basic and may not be designed around the holistic, end-user experience. If the tool creates friction for the people you rely on to enter or maintain information, it becomes much harder for EHS to standardize, get accurate, complete data and ultimately run a successful program.

The license fee is the easy number. The harder numbers are the hours your team spends reconciling inventories, chasing training records, and building reports by hand. Those costs never appear on a purchase order, but you feel them in every audit and every inspection cycle. When you build your business case, count the license and implementation costs, plus the staff time spent today on data entry, reconciliation and reporting.

Two of our university customers show how big that hidden cost can be:

• At Boston College, lab group reports that used to take all day now take five minutes.

• At SDSU, department-level training compliance reports went from two weeks to 10 minutes, and looking up one person's training went from several hours to about a minute.

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6. Treat implementation and training as part of the purchase

Even a great system can stall with a rushed rollout. Most of the common reasons EHS software implementations fail have little to do with the software: unclear ownership, messy data carried over from spreadsheets, and training that doesn't match how people actually work.

That's why you should ask every vendor:

• Who configures the system, and what does a typical university rollout look like?

• How will our existing spreadsheets, old databases and paper records be cleaned up and moved over?

• How are researchers and PIs trained, and what support is there after go-live?

From SDSU, Jennifer described their SciSure rollout as "very easy, organized and informed by best practices," and the results followed. The number of training courses on offer doubled from 8 to 16; annual training records grew from about 500 to more than 4,600, and training compliance rose from 56% to over 80%. That's what happens when people find the training easy to complete.

We've found that lab software ROI starts with implementation, so give this part of your evaluation as much attention as the demo.

7. Check security, hosting, and accessibility early

• Security
  Which certifications does the vendor hold, such as ISO/IEC 27001? Where is your data stored, and who can access it?

• Hosting
  Can you choose between cloud and on-premises hosting if your research IT team needs it?

• Accessibility
  How does the software support accessibility requirements such as the Americans with Disabilities Act (ADA) and Section 508?

SciSure offers cloud, private cloud, and on-premises hosting and publishes its security and compliance details in its Trust Center. For SciSure Health & Safety, you'll need private cloud hosting.

Start with the people who'll use it

If you take one thing into your next evaluation meeting, let it be this: judge every system by how it will feel to the graduate student, the lab manager, and the PI who have to use it every week. Features matter, and depth in research lab workflows matters a lot. Participation is what turns all of it into a working safety program.

If you're in the middle of an evaluation, building a business case for your leadership, or trying to work out why your current system isn't getting used, I'd be glad to talk it through with you.

FAQs

What should universities look for in lab safety software?

Start with how easy it is for researchers, lab staff, and PIs to use. Then check that it links people, lab groups, spaces and hazards, goes deep on chemical inventory, SDS access, biosafety and training, produces the regulatory reports you need, and comes with solid implementation support.

Who should be involved in choosing academic lab safety software?

Involve the people who will run it and the people who will use it. That usually means EHS, research IT, research compliance, or the office of the VP for research, procurement, and at least one PI, lab manager, and graduate student to test everyday tasks.

How can lab software support OSHA Laboratory Standard compliance?

The OSHA Laboratory Standard requires hazard information and training for lab workers, and a written Chemical Hygiene Plan. Software can assign training by role and hazard, track completion, and give people quick access to SDSs. The university still owns its plan, procedures, and oversight.

What results have universities seen with SciSure Health & Safety?

At San Diego State University, training compliance rose from 56% to over 80%, and department-level reports went from two weeks to 10 minutes. At Boston College, training compliance reached up to 97%, and lab group reports went from all day to five minutes.

How can SciSure Health & Safety be hosted?

SciSure Health & Safety (EHS) currently requires Private Cloud hosting. Get in touch with our team to discuss your university’s hosting and data requirements.

[Boston, MA, USA, October 13, 2026]--SciSure, the Scientific Management Platform (SMP) for safer, more efficient research environments, today announced the availability of BioSkepsis in the SciSure Marketplace. Developed by EFEVRE TECH LTD, BioSkepsis is an AI-powered research assistant for the life sciences that brings literature review and evidence synthesis directly into researchers’ existing workflows.

For scientists, deciding what to test next often means searching across papers, comparing conflicting findings, and determining how published evidence relates to their own results. BioSkepsis brings that process closer to the experiment itself, allowing researchers to investigate scientific questions and evaluate their results against published literature from within SciSure.

“Researchers shouldn’t have to separate the work of running an experiment from the evidence that informs it. Partnering with BioSkepsis allows scientists in Scisure a way to explore the literature, evaluate their findings, and make more informed decisions within the same environment where their research is documented. It’s a strong example of how we want to expand SciSure through tools that fit naturally into the way scientists work."
- Andrew Martin, Director of Marketplace Development

From research question to evidence-backed next step

Researchers can ask BioSkepsis a scientific question or describe an experiment directly within SciSure. The AI research assistant searches the relevant literature, evaluates findings, and produces a cited research brief showing where evidence aligns, conflicts, or remains limited.

Researchers can also use BioSkepsis to benchmark their own experimental findings against published research and identify potential mechanisms and follow-up experiments.

Each research brief includes verified citations and a Trust Index designed to make the strength and limitations of the underlying evidence easier to assess. The Trust Index evaluates evidence across six factors, helping researchers identify areas where findings may be well-supported, conflicting, or require closer review.

The need for greater confidence in published research is significant. A widely cited 2015 analysis estimated that more than half of preclinical research may be irreproducible, representing approximately $28 billion in annual research spending in the United States alone.*

Keeping research decisions connected to a changing evidence base

BioSkepsis also helps researchers continue following the evidence after an initial review.

With Evidence Watch, researchers can monitor the claims behind a research brief as new literature becomes available, including retractions, corrections, and newer evidence that may change the scientific picture.

The Research Feed helps researchers follow new publications around topics relevant to their work, while the Literature Landscape provides a visual view of a research field through citation networks, clusters, and timelines. Researchers can also organize relevant papers and briefs into Collections for future reference.

“Every research decision is only as strong as the evidence behind it. We built BioSkepsis AI to give life-science researchers a rigorous and transparent way to analyze the literature: it searches more than 40 million biomedical papers in full text, grounds every finding in a verifiable citation, and makes it clear where the evidence converges, conflicts or falls short. Joining the SciSure Marketplace brings that capability directly into the environment where experiments are planned and documented, so researchers can benchmark their results against the published record and choose their next step with greater confidence.”
- Dimitris Kyriakou, Co-founder and CEO, EFEVRE TECH LTD

Bringing AI into the research workflow

Through its integration with SciSure, BioSkepsis brings evidence-based research support into the environment where scientists plan and document their experiments. Files and experimental results remain within the SciSure workspace when the add-on is used through the integration.  

BioSkepsis is also available through the Claude connector directory, giving researchers another way to access its research capabilities.

Availability

BioSkepsis is available now through the SciSure Marketplace. A free plan is available with no credit card required, with additional plans available for researchers, teams, and organizations.

To learn more about BioSkepsis and its integration with SciSure, visit our Marketplace.

About EFEVRE TECH LTD

EFEVRE TECH LTD is a biotechnology company based in Larnaca, Cyprus, developing hardware and software for the working laboratory. Its products include AMGEL, VITALE, and BioSkepsis, an AI research assistant purpose-built for the life sciences.

Learn more at bioskepsis.ai.

About SciSure

SciSure is a Scientific Management Platform for safer, more efficient research environments. Supporting scientists, LabOps, and EHS teams, SciSure helps organizations improve reproducibility, strengthen safety and compliance, and gain greater visibility across laboratory operations.

Learn more at scisure.com.

Media contacts

SciSure: Olivia Hulst, o.hulst@scisure.com  

EFEVRE TECH LTD / Skepsis AI: Dimitris Kyriakou, dkyriakou@efevretech.com  

* Freedman LP, Cockburn IM, Simcoe TS. “The Economics of Reproducibility in Preclinical Research.” PLOS Biology. 2015;13(6).

A LIMS can look effortless in a vendor demo - and then a scientist sits down to actually follow a real sample from experiment to storage to analysis, and the cracks appear: three logins, two manual copy-and-paste steps, a barcode label that requires a separate application, and no obvious way to retrieve the full history.

Nearly every LIMS vendor claims their product is intuitive, but buyers need something more testable than a claim. This post gives you a practical definition of usability grounded in recognized frameworks, a set of 10 measurable criteria, and a workflow scenario you can run in every vendor demo.

What is a user-friendly LIMS?

A user-friendly LIMS is one that enables scientists, LabOps managers, and administrators to complete the tasks their roles require, accurately, in reasonable time, and with enough confidence to keep records current and complete. Usability is a property of the whole system in context, not just a feature list.

The NIST summary of ISO 9241-11 defines usability across four dimensions: effectiveness, efficiency, satisfaction, and context of use. These are not abstract categories. Each one translates directly into R&D LIMS evaluation criteria.

A LIMS that removes important controls to look clean has made a different tradeoff, not a better one. The goal is progressive simplicity: users see what is relevant to their role and task, and the system guides them toward complete, accurate records without unnecessary friction.

Why connectivity is part of usability in R&D

In R&D, disconnected software creates a usability tax. Every extra login, manual transfer, missing relationship, and out-of-system spreadsheet becomes part of the user experience, even if each individual application has a polished interface.

Consider a realistic end-to-end scenario: a scientist registers a biological sample from an experiment, splits it into three child aliquots, labels each with a barcode, places them in storage, records reagent use, updates two records at once, attaches an instrument result, shares findings with a collaborator, and retrieves the complete sample history for a reviewer.

In a disconnected environment, that workflow spans multiple applications. The experiment lives in one system. The sample is registered in another. The barcode label requires a third tool. The instrument results sit in a folder somewhere. The reviewer reconstructs the history by searching across all of them, if they can at all.

But in a connected environment, each step flows from the last. The experiment links to the sample. The sample links to storage and reagent consumption. The instrument result attaches to the same record. The history is complete and retrievable in one place.

This is the specific problem SciSure's ELN and LIMS were built to remove. A sample section in a SciSure experiment links to the actual registered sample record rather than a hand-typed sample name, which is the step where transcription errors usually enter.

The honest version of this argument is broader than one vendor: a well-integrated specialist stack can also be usable, provided the connections between systems are reliable, governed, and feel natural to the scientist using them. The question to ask is not "Is this one system?" but "Does the connection between systems preserve scientific context and audit history without forcing manual work?"

For more practical ways to measure if your lab is succeeding, check out our guide on 12 practical lab KPIs.

Looks user-friendly vs. works user-friendly

Do flexibility and compliance controls make a LIMS harder to use?

They can, when designed poorly. But the tradeoff between ease and control is not inevitable.

Required fields, controlled vocabularies, role-based permissions, electronic signatures, and audit history can actually guide users toward complete, accurate records. A required field prevents a scientist from saving an incomplete entry. A controlled vocabulary ensures that "cell line" is always recorded in the same way. An audit trail tells a reviewer exactly what changed, and when, without anyone needing to reconstruct it manually.

The friction comes when controls are applied too broadly. Irrelevant required fields slow down every entry. Blanket approval workflows interrupt tasks that do not carry meaningful risk. Fields inherited from a QA/QC template that do not map to R&D practice frustrate scientists without improving data quality.

This is why configurable sample types matter more than they sound like they should. With SciSure, different scientific groups can model the materials and metadata their own work requires while still operating inside a shared organizational structure, so a chemistry group is not filling in fields designed for a cell line.

R&D teams need a balance: common structure for shared data, room for methods to evolve, and controls that protect the records that actually matter for reproducibility and compliance.

Compliance also depends on more than software. Configuration, validation procedures, training, governance, and change control all play a role. A LIMS that supports GLP or 21 CFR Part 11 workflows provides the controls; the organization still owns the implementation.

When you evaluate a LIMS, keep in mind: a system that feels smooth for scientists but impossible to audit is not a usability success.

What should R&D teams ask LIMS vendors?

These twelve questions cut through demo-mode polish and surface the information you need to evaluate usability in your actual environment.

1. Can you show us a usability test conducted with real users, not demo specialists?

2. How does the system link an experiment in the ELN to the samples created during that experiment?

3. How does advanced search work? Can we filter by custom fields, parent-sample relationships, and date ranges simultaneously?

4. What batch and barcode actions are available without additional add-ons or custom code?

5. Who in our lab can configure a new sample type or add a custom field? Does it require a support ticket?

6. What changes require custom code or professional services to implement?

7. How does the system handle error correction while preserving audit history?

8. What does onboarding typically look like, and how long before a scientist reaches independent use?

9. When two systems are integrated, does the scientific context (experiment origin, parent-sample relationship) carry across? What happens to the audit trail?

10. Do you have adoption data from similar R&D labs we can review?

11. What are the most common complaints from scientist users in your G2 or peer reviews?

12. Can we run an unscripted trial with our own data before committing?

What reviewers actually say

On G2, SciSure holds 4.2 out of 5 across 206 reviews, with an Ease-of-Use score of 7.9 drawn from 190 ratings.

• Ease of Use is likewise our single most frequently tagged strength in those reviews (43 mentions).
• Quality of Support scores 8.9 across 146 ratings.
• Sample Management for SciSure comes in at 8.9
• Inventory Management for SciSure comes in at 8.8.

Where SciSure fits for R&D laboratories

SciSure Research combines ELN and LIMS capabilities in one structured environment, designed for research and R&D labs where flexibility, evolving sample types, and fast iteration matter alongside traceability and governance.

Within SciSure Research, your team can:

• Register samples with configurable sample types and custom fields

• Track lineage, parent-child relationships, and lifecycle history

• Manage storage locations, compartments, and physical positions

• Use advanced search to filter by sample type, location, metadata, experiment link, or date

• Generate barcode labels and run batch updates across multiple records

• Link samples directly to experiments in the SciSure ELN

• Assign roles and permissions at group and organization level

• Capture audit logs, electronic signatures, and workflow automation where configured

• Extend functionality through APIs, an SDK, and Marketplace add-ons

• Access onboarding support and training through SciSure Customer Success

What customers have reported

The Diel Lab at Cornell University needed a system that scientists and PhD students could incorporate into daily work. The lab implemented SciSure's inventory, sample, and specimen tracking alongside the electronic lab notebook, replacing paper records and the time spent manually searching for samples and experimental information.

After onboarding and migration, the team reported more accurate inventory and stronger traceability across samples, reagents, experiments, SOPs, and research data. Search and retrieval let users pinpoint sample locations within seconds and made experimental details easier to share with internal and external collaborators.

Terminus Bio likewise needed to manage cell lines and trace their lineage without forcing specialized client workflows into an overly broad or rigid system. Before SciSure, the team relied on spreadsheets and manual markers, with individual sample entries taking around two minutes.

Using SciSure's cloning capabilities, customizable QR codes, and the Barcode Automation add-on, Terminus Bio brought data entry for subcultured cell lines down to around ten seconds while maintaining traceability across the cell-line lifecycle. The company also reported cutting data-management time by more than 90% through API access and custom reporting scripts.

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Other systems are either too broad in scope or too rigid in their setup. SciSure offers a healthy balance of flexible functionality and the ability to customise certain aspects of our workflow without getting overly bogged down in features.

Since we have a unique workflow, the ability to customise certain aspects of our data tracking methods was key to our ability to successfully incorporate a LIMS.

Joshua Paster, Founder, Terminus Bio

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The easiest way to evaluate a user-friendly LIMS is to test one

Every LIMS vendor can describe their product as intuitive. What you need to know is whether your scientists can register a sample, trace its history, and share a complete record with a reviewer, without extra logins, manual transfers, or lost context.

Bring us the workflow that gives your team the most trouble and we'll run it, not a demo dataset.

Frequently asked questions about LIMS usability

What makes a LIMS user-friendly?

A user-friendly LIMS allows scientists, LabOps managers, and administrators to complete their actual daily tasks accurately, efficiently, and with confidence. Based on the NIST summary of ISO 9241-11, usability covers effectiveness (can users complete tasks correctly?), efficiency (how long does it take?), satisfaction (do users feel confident?), and context of use (does the system fit real R&D workflows?). A clean interface is necessary but not sufficient on its own.

Is SciSure easy to use?  

On G2, SciSure holds a 7.9 Ease of Use score on G2 from 190 ratings, and Ease of Use is the most frequently cited strength across its 206 reviews. Reviewers point to sample logging, real-time team visibility, and locating documents as the areas that work well, and some ask for interface improvements. Customers including the Diel Lab at Cornell and Terminus Bio have reported faster sample retrieval and substantially reduced data entry time. The most reliable test is still your own: run your workflow, with your data, before committing.

How can you test whether a LIMS is easy to use?  

Run a standardized workflow scenario with a representative user during the vendor demo. The scenario should cover sample registration, aliquot creation, barcode labeling, storage assignment, reagent recording, batch updates, result attachment, and history retrieval. Capture task completion, time, re-entry points, application switches, errors, and user confidence. Score each vendor against the same criteria.

Can a LIMS be flexible and still support compliance?  

Yes. Required fields, controlled vocabularies, permissions, electronic signatures, and audit trails can guide users toward complete, accurate records while still allowing methods and sample structures to evolve. The tradeoff becomes real when controls are applied too broadly, such as mandatory fields that are irrelevant to the current workflow, or approval steps that create friction without meaningful governance value. The goal is controls that match the actual risk level of each workflow.

Why should an R&D LIMS connect with an ELN?  

In R&D, samples and experiments are inseparable. A sample is created during an experiment, used in subsequent experiments, and its history only makes sense alongside the experimental context. When the ELN and LIMS are disconnected, scientists must manually track which experiment produced which sample, creating re-entry burden, context loss, and audit gaps. An ELN-LIMS connection, whether within one platform or through a governed integration, preserves that context automatically.

How much LIMS training should users need?  

There is no universal answer, but less is generally better, provided it does not come at the cost of record completeness or compliance. A well-designed LIMS should allow a scientist to complete core workflows within their first few sessions with structured onboarding. Complex administrative tasks and configuration may require more preparation. If common daily workflows require repeated support requests, that is a usability signal worth investigating.