Find it, trust it, reuse it: how to specify a LIMS for R&D
A strong R&D LIMS RFP or URS asks whether scientists can trace a result back to its data, compare it with prior work, and reuse it safely. Tracking samples, storing files, and digitizing spreadsheets are only the starting point. Find it, trust it, reuse it is a handbook for the teams who write the RFP or URS and choose the LIMS their scientists will rely on.
Research works differently from quality control. A LIMS for quality is built around repeatable, controlled work, and its unit of work is the sample and its tests. In a LIMS for R&D the unit of work is the experiment, study, formulation, project, or campaign. Methods evolve, scientists explore ranges, and a result can be useful without a pass/fail specification.
So the most important selection question is whether the system can model the relationships that make research data reusable: materials and lots, sample lineage, versioned protocols, experiments, instrument runs, datasets, and projects.
What should an R&D LIMS RFP or URS include?
An R&D LIMS RFP or URS should include requirements for sample and experiment data management, search and institutional knowledge, DOE and predictive tooling, visualization and reporting, and instrument integration. It should also cover non-functional requirements such as hosting, security, audit trails and validation support, commercial terms, data ownership, migration, and governance.
Write each requirement as a testable “The system shall…” statement and ask suppliers to demonstrate one connected workflow with your own data, not a sequence of unrelated screens. A connected LIMS lets a scientist trace an unexpected result back to the material lot and forward to every related test and conclusion.
Who this handbook is for
R&D leaders, laboratory managers, informatics and IT teams, and project sponsors who write the RFP or URS and choose the LIMS for a research and discovery laboratory.
For a one-page overview of how Uncountable approaches this, read the solution brief LIMS built on the whole recipe.
What's inside
Inside this handbook:
- How R&D and QC laboratories differ, and what that means for your requirements
- A connected research data model for materials, lots, samples, formulations, protocols, experiments, instruments, and datasets
- Requirements tagged Core or Differentiating for sample and experiment data, search, DOE and predictive tooling, reporting, and instrument integration
- A scripted supplier demonstration scenario and common mistakes for each chapter
- How to structure the RFP document, with non-functional and commercial requirements to include
- A scoring method to compare supplier responses consistently
- Implementation and governance requirements: data ownership, migration, security and IP, validation, and success measures
- A final evaluation checklist to use before you issue the RFP or URS
Download the handbook to specify a LIMS that makes experimental work discoverable, comparable, reproducible, and reusable.
FAQs
Find it, trust it, reuse it is a handbook on how to specify a LIMS for R&D. It explains what makes R&D informatics different from quality control, which requirements to include for samples and experiments, search, DOE and predictive tooling, reporting, and instrument integration, what suppliers should demonstrate, how to structure and score the RFP, and where implementations commonly fail.
The handbook is for R&D leaders, laboratory managers, informatics and IT teams, and project sponsors who write the RFP or URS and choose the LIMS their scientists will rely on in a research and discovery laboratory.
A LIMS for quality control is built around repeatable, controlled work, with the sample and its tests as the unit of work and success measured in throughput, compliance, and release readiness. A LIMS for R&D works with experiments, studies, formulations, and projects, supports iterative and exploratory workflows, and is measured on faster learning, reproducibility, and knowledge reuse. It still needs governance, access control, version history, and traceability.
An R&D LIMS RFP or URS should include requirements for materials and lots, sample identity and lineage, experiments and versioned protocols, structured parameters and units, search and provenance, DOE and model governance, dashboards and reporting, and instrument integration with matching and error handling. It should also cover hosting, security, audit trails, validation support, commercial terms, data ownership and export, migration, and governance.
Agree the weight of each area before suppliers respond. Score each requirement on the evidence given, for example 3 for native, 2 for configurable or partner-delivered, 1 for custom development or roadmap, and 0 for unavailable. Mark only true needs as mandatory, score demonstrations against your own scripted scenarios, have each evaluator score alone first, and check references from organizations with similar research domains and data volumes.
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