Life Sciences
AI that accelerates discovery and survives FDA scrutiny
You get AI agents for clinical trial operations, research intelligence, and regulatory documentation — built to meet the FDA's 2025 AI guidance framework, running on your cloud with full audit trails.
21 CFR Part 11 compliant. Built on your AWS, Azure or GCP tenant. IRB and FDA-ready.
Proof of concept
To measurable ROI
AWS, Azure or GCP
The FDA issued its first AI guidance in January 2025. Most organisations are not ready.
AI that influences GxP decisions — manufacturing, labelling, safety, QC, batch release, or clinical data interpretation — is now subject to device-level controls. The FDA has already issued warning letters for misclassified AI products.
We build AI that meets the credibility assessment framework the FDA requires: defined context of use, risk-assessed models, verified and validated outputs, and documented results — before we write a line of production code.
first AI guidance for drug and biological products issued
validation standard for AI in GMP manufacturing
new EU GMP annex bridging AI and pharma standards
governance frameworks your review boards can sign off
From research data to regulatory-ready output — in one workflow
We connect your EDC, LIMS, EHR, and study management systems to AI agents that accelerate trial operations, flag protocol deviations, and generate documentation that meets FDA and EMA submission standards — all on your cloud tenant
EDC, LIMS, EHR and study systems
- Approval gates
- Human-in-loop
- Audit logging
AWS, Azure or GCP
- FDA submissions
- Audit trails
- 21 CFR Part 11
What we deliver for life sciences organisations
FDA-ready agents built for regulated research environments
Clinical trial recruitment
Screen patient data and accelerate trial enrolment.
ROI
Process
Screen patient data
EHR records and patient registries queried against inclusion/exclusion criteria automatically
Match and rank
AI scores patient eligibility and ranks candidates by protocol fit and site proximity
Accelerate enrolment
Pre-screened candidate lists delivered to sites with documentation for IRB review
Sources
Originally published: AWS Case Study — Roche; Azure Case Study — Pfizer — reproduced for illustrative purposes
Protocol deviation detection
Flag protocol deviations in real time with full audit trails.
ROI
Process
Monitor trial data
EDC entries, lab results, and visit schedules streamed and compared against protocol requirements
Flag deviations
AI detects protocol deviations in real time — missed visits, dosing errors, and eligibility violations
Document for review
Deviation records with full decision trails generated for IRB and CRO review
Sources
Originally published: GCP Case Study — Medidata/Dassault; Azure Case Study — Parexel — reproduced for illustrative purposes
Regulatory submission support
Structure and quality-check eCTD submissions automatically.
ROI
Process
Structure submission content
Study data, CMC sections, and clinical narratives organised into eCTD format
Quality-check documents
AI cross-references data tables, narratives, and regulatory requirements for consistency
Prepare for filing
Flagged issues resolved, eCTD package assembled for regulatory affairs final review
Sources
Originally published: AWS Case Study — Veeva; Azure Case Study — IQVIA — reproduced for illustrative purposes
Research intelligence
Search and synthesise your internal research corpus securely.
ROI
Process
Index research corpus
Internal publications, study reports, and experimental data indexed with access controls preserved
Search and synthesise
Natural language queries return relevant findings with cross-study synthesis and citation trails
Deliver insights
Summarised research intelligence with source links and data classification labels
Sources
Originally published: GCP Case Study — Elsevier; AWS Case Study — Benchling — reproduced for illustrative purposes
Pharmacovigilance automation
Classify adverse events and draft ICSRs automatically.
ROI
Process
Ingest AE reports
Adverse event data from trials, spontaneous reports, and literature ingested automatically
Classify and prioritise
AI scores signal severity, assesses causality, and ranks cases for medical review
Draft ICSRs
Individual case safety reports drafted with human-in-the-loop review before submission
Sources
Originally published: Azure Case Study — IQVIA; AWS Case Study — Oracle Argus — reproduced for illustrative purposes
Lab data analysis
Flag lab anomalies and escalate results for scientific review.
ROI
Process
Process LIMS outputs
Analytical results from instruments ingested via LIMS with full chain-of-custody preserved
Detect anomalies
AI flags out-of-range results, trend deviations, and instrument drift requiring investigation
Escalate with context
Anomalous results delivered to scientists with historical context and recommended actions
Sources
Originally published: GCP Case Study — Thermo Fisher; Azure Case Study — Waters — reproduced for illustrative purposes
Study reporting and narratives
Generate study reports and patient narratives from trial data.
ROI
Process
Extract trial data
Efficacy, safety, and demographic data extracted from EDC and statistical analysis outputs
Generate draft reports
AI produces CSR sections, study summaries, and patient narratives from structured data
Review and finalise
Medical writers review AI-generated drafts, refine language, and approve for submission
Sources
Originally published: AWS Case Study — Certara; GCP Case Study — Medidata — reproduced for illustrative purposes
Outcomes and biomarker analysis
Identify biomarker patterns and patient subgroups in trial data.
ROI
Process
Integrate multi-omic data
Genomic, proteomic, and clinical data unified for biomarker discovery and subgroup analysis
Identify patterns
ML models detect biomarker signatures, patient subgroups, and outcome predictors
Deliver explainable outputs
Results presented with feature importance, confidence intervals, and clinician-readable explanations
Sources
Originally published: GCP Case Study — Tempus; AWS Case Study — Foundation Medicine — reproduced for illustrative purposes
21 CFR Part 11 compliance
21 CFR Part 11 compliance built in from day one.
ROI
Process
Build compliant architecture
Electronic records, signatures, and audit trails designed into every AI workflow from day one
Validate and document
IQ/OQ/PQ executed with evidence packages structured for FDA inspection readiness
Maintain and revalidate
Change control and periodic review protocols established for ongoing Part 11 compliance
Sources
Originally published: AWS Case Study — Veeva Vault; GCP Case Study — Benchling — reproduced for illustrative purposes
EVP & Chief Digital Officer, Sanofi
Emmanuel Frenehard
"AWS is helping us accelerate our AI-powered drug discovery and clinical development programmes. By deploying large-scale machine learning on AWS, Sanofi is transforming how we identify, design, and test new therapies — compressing timelines that once took years into months"
Originally published: AWS Customer Stories — Sanofi — reproduced for illustrative purposes
How we work in regulated life sciences environments
We map each AI use case to your regulatory obligations before we write code. We assess model risk using the FDA's credibility assessment framework. We build 21 CFR Part 11-compliant audit trails into every workflow. And we run everything on your cloud tenant — your data never leaves your environment.
Every agent we deploy can be explained to your IRB, your legal team, your data privacy officers, and your regulators — because we document governance as we build, not after the fact.
01
Regulatory mapping
We identify your use case's regulatory classification and map it to FDA, EMA, or ICH obligations before any build begins.
02
30-day proof of concept
A production-ready AI agent on your cloud tenant, integrated with your existing data systems and compliant from day one.
03
Governance by design
Audit trails, explainable outputs, and human-in-the-loop controls built to meet FDA credibility assessment requirements.
04
Scale in 12–18 weeks
From one validated workflow to measurable operational ROI — with documentation your regulatory affairs team can submit.
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