Biotech R&D

Spend less time assembling data for R&D program decisions.

Scispot’s R&D Digital Brain automates assay data handling and analysis. Our scientists and engineers connect experiments, partner results and review workflows.
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Explore LabOS

Trusted by 200+ life science labs

Supporting 250+ instrument types, more than 1,000 experiments each month, and millions of samples across diagnostics, genomics, biotech, and regulated testing.

Your best fit

Built for translational and clinical-stage biotech teams.

When evidence spans instruments, CROs and internal teams, review preparation grows. Start with one costly assay or partner handoff. Keep the research and analysis tools that work.

Map your research workflow
Features

Published Customer Outcomes

From assay data to usable evidence.

Up to 50%

Less manual reporting and admin

Across a Biotech's connected assay-data workflows.

15% → 5%

Lower data-entry error rate

In one workflow connecting scientific data and reporting.

10h → <1h

Shorter data processing time

In one scientific data workflow at a Biotech Lab.

40%

Less time creating cross-team requests

Connected wet and dry lab workflows for a synthetic protein and peptide team.

One system, three layers

One Digital Brain moves experimental work into program decisions.

Program Plans & Experimental Work

Link program questions, candidates, materials, assay plans and protocols. Use Labsheets for sample and result records; Labspaces for plans and methods. Assign work with selected versions and required readouts.

Check identifiers and plan details before intake or execution. Keep method versions linked to their experiments so earlier evidence stays traceable.

Assay Capture & Partner Intake

GLUE maps supported instrument and partner outputs to experiment and candidate records with identifiers, units and metadata. Retain source versions; route incomplete deliveries for clarification.

Smart Actions can run agreed calculations. Scientists review outputs with source, material and method context, spending less time preparing files.

Evidence Review & Program Decisions

Review assay results, controls, analysis versions and figures. Summarize selected records; flag missing evidence before program discussions. Keep endpoints and experimental conditions distinct.

Record interpretations and next experiments beside reviewed evidence. For regulated development, use agreed review gates; scientific and Quality owners retain decisions and approvals.

One connected operating layer

Start every program review with evidence ready.

Scispot helps capture, check and analyze incoming data, reducing repeated cleanup so scientists can focus on what results mean for the program.

Ask what the program learned.
Draft the next evidence summary.

Bring experiments, partner results and recorded decisions into view.

Meet Scibot
Scibot, the Scispot AI coworker
Which assays support this candidate decision?
Draft a summary for this program review
Show partner deliveries missing sample metadata
What changed between these method versions?
Find candidates awaiting reviewed assay data
Compare results under these recorded conditions
Which assays support this candidate decision?
Draft a summary for this program review
Show partner deliveries missing sample metadata
What changed between these method versions?
Find candidates awaiting reviewed assay data
Compare results under these recorded conditions
AI-native lab transformation

Research workflows that adapt as your program advances.

Evidence Across Programs & Partners

Connect candidate, sample and experiment records across teams and partners. Keep reviewed results traceable to their data and methods as programs advance.

Assay Data Without Repeated Copying

GLUE maps supported instrument and partner outputs to records. Smart Actions can return agreed calculations with source files and analysis versions for scientific review.

Personalized Research & Review Apps

Jazz provides focused screens for experiment requests, partner intake and evidence review. Apps use shared Scispot data to preserve one research record.

Experts From Mapping to Adoption

Scispot scientists and engineers map and configure workflows, connect tools, test representative data and train users. Measure preparation time and adoption before expanding.

Cut manual preparation from research handoffs.

01

Assay Results to Candidate Review

Bring candidate evidence into program discussions.

Link biochemical, cellular and other assay outputs to candidates. Run agreed calculations; retain controls, method versions and units. Jazz can bring selected evidence and missing inputs into review.

Scientists review each endpoint in its experimental context before choosing next steps. Keep assays distinct; unlike measurements are not interchangeable scores.

Explore candidate evidence workflows

02

Partner Delivery to Program Evidence

Make partner deliveries usable with less manual preparation.

Match files to requested assays and samples. Map partner IDs, check required metadata and route discrepancies for clarification. Link original files and revisions to analysis.

Our scientists and engineers define intake with research and partner owners. Test recurring deliveries for missing units and sample mismatches; measure preparation before review.

Explore partner data intake

03

SPR Data to Shared Evidence

Prepare assay outputs for scientific review and downstream use.

Ingest supported surface plasmon resonance exports and images. Retain target and compound context, source links, QC comments and reviewed values in the assay record.

Arrakis Therapeutics’ published SPR case reports data processing cut from hours to minutes, with connected team review and downstream database delivery.

Explore assay data automation

Show us the data work delaying program review.

Bring one assay workflow or partner delivery. Our scientists and engineers map manual steps and review needs, define a first automation and measure preparation time.
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FAIR data • pipelines • automation

Instruments • ELN/LIMS/SDMS • 200+ connectors

FAIR data • pipelines • automation

Instruments • ELN/LIMS/SDMS • 200+ connectors

Frequently asked questions

Which biotech R&D teams are the strongest fit?

Translational and clinical-stage biotechs preparing program evidence across instruments, teams and CRO/CDMO partners are a strong fit. Discovery teams can use the same foundation. Start where manual preparation, missing sample history or repeated coordination has measurable cost.

Can we keep our ELN, LIMS and specialist analysis tools?

Yes. Scispot can work alongside supported systems or add native apps. Keep specialist analysis tools and link their inputs, versions and outputs to experiments. We scope file/API connections, access and return paths. You retain access to your Scispot data and exports.

How do we start as research needs change?

Our scientists and engineers start with one assay or partner handoff, linking programs, candidates and samples. Configure protocol versions, screens and review steps; test revisions with representative records, train users and track adoption. Subscriptions include software, integrations, expert delivery and unlimited users within agreed workflow and validation scope.

What research analysis can Scispot automate?

Smart Actions can run agreed calculations, with user preview and approval before saving. Scibot searches permitted evidence, compares recorded fields and drafts summaries. External analysis tools can stay connected. Define inputs, methods and review gates. Scientists assess biological meaning and approve decisions.

How do controls change for regulated development?

Match controls to intended use, from source history and versioned methods to formal procedures, electronic approvals and validation where required. Scispot provides configurable permissions, audit trails and review gates. Trust Vault organizes evidence; scientific and Quality owners define requirements, approve validation and retain regulated sign-off.

Preserve research evidence as your program advances.

Keep source files, method versions, calculations and review decisions in controlled records. Scientific and Quality teams define intended use, validation and final approval.