Life Sciences & Biotech - Overview
$5.6B invested. 530+ companies in the pipeline. Phase I success rates are being transformed by AI. But GxP, FDA 21 CFR Part 11, and EMA guidelines demand full traceability. Governance is 35% -- the framework exists. Ontic extends it to generative AI outputs.
$5.6 billion invested. 530+ companies in the AI drug discovery pipeline. Phase I success rates are being transformed by AI-driven target identification and molecular optimization. But GxP requirements -- FDA 21 CFR Part 11, ICH E6(R2) Good Clinical Practice, EMA guidelines -- demand full traceability for every decision that influences a regulatory submission. Governance is 35%, built on decades of regulatory infrastructure. The challenge is extending GxP discipline to generative AI outputs that contribute to IND applications, clinical study reports, and label claims. When an FDA reviewer examines a submission and asks whether AI contributed to the efficacy analysis, the response must include model version, training data provenance, and validation evidence. The GxP framework exists. The AI-specific implementation does not.
This industry includes 2 segments in the Ontic governance matrix, spanning risk categories from Category 1 — Assistive through Category 2 — Regulated Decision-Making. AI adoption index: 5/5.
Life Sciences & Biotech - Regulatory Landscape
The life sciences & biotech sector is subject to 10 regulatory frameworks and standards across its segments:
- EU Clinical Trials Regulation
- FDA 21 CFR Parts 11 and 58 (GLP)
- GAMP 5 (computerized systems)
- ICH E6(R2) GCP
- Institutional biosafety committee (IBC) requirements
- NIH guidelines
- OHRP (if human subjects)
- OHRP regulations (45 CFR 46)
- Patent/IP governance
- State biotech regulations
The specific frameworks that apply depend on the segment and scale of deployment. Cross-industry frameworks (GDPR, ISO 27001, EU AI Act) may apply in addition to sector-specific regulation.
Life Sciences & Biotech - Life Sciences -- Biotech / Research Startup
Risk Category: Category 1 — Assistive Scale: SMB Applicable Frameworks: NIH guidelines, Institutional biosafety committee (IBC) requirements, OHRP (if human subjects), State biotech regulations, Patent/IP governance
NIH expects research integrity from AI-assisted grant applications the same way it expects it from humans.
The Governance Challenge
Biotech startups use AI for grant application drafting, literature review summarization, and lab notebook documentation. NIH guidelines, institutional biosafety committee requirements, and OHRP human subjects regulations apply to AI-assisted research outputs. Patent and IP governance applies to AI-generated research documentation. When an AI-assisted grant application contains a hallucinated citation or an inaccurate claim, the PI carries the research integrity liability.
Regulatory Application
NIH guidelines apply to AI-assisted research outputs. Institutional biosafety committee requirements govern AI-assisted experimental design documentation. OHRP regulations (45 CFR 46) apply to AI-generated human subjects research materials. Patent and IP governance applies to AI-generated research documentation. Research integrity standards do not exempt AI-assisted work.
AI Deployment Environments
- Studio: Grant application drafting | Literature review summarization | Lab notebook assist
- Refinery: Research protocol documentation | IRB submission drafting | Data management plan governance
Typical deployment path: Studio → Studio → Refinery
Evidence
- $5.6B invested in AI drug discovery pipeline
- NIH research integrity requirements apply to AI-assisted outputs
- Patent challenges based on AI-generated prior art are emerging
Life Sciences & Biotech - Life Sciences -- CRO / CDMO
Risk Category: Category 2 — Regulated Decision-Making Scale: Mid-Market Applicable Frameworks: FDA 21 CFR Parts 11 and 58 (GLP), ICH E6(R2) GCP, OHRP regulations (45 CFR 46), EU Clinical Trials Regulation, GAMP 5 (computerized systems)
Sponsor audit findings for AI documentation gaps become the CRO's problem before they become the FDA's.
The Governance Challenge
CROs and CDMOs deploy AI for protocol summary drafting, site monitoring report assistance, regulatory submission preparation, study report narrative governance, and adverse event documentation. FDA 21 CFR Parts 11 and 58 (GLP), ICH E6(R2) GCP, and GAMP 5 computerized systems validation requirements apply to every AI-generated document that flows into a regulatory submission or sponsor deliverable. Sponsor audits are the first line of examination — and sponsors are increasingly asking CROs to demonstrate AI governance as part of qualification. When a sponsor audit identifies an AI documentation gap, the CRO loses the contract before the FDA ever sees the issue.
Regulatory Application
FDA 21 CFR Parts 11 and 58 (GLP) govern AI-generated electronic records and laboratory documentation. ICH E6(R2) GCP requires full documentation of clinical trial processes. OHRP regulations (45 CFR 46) apply to AI-assisted human subjects research documentation. EU Clinical Trials Regulation adds cross-border requirements. GAMP 5 computerized systems validation framework applies to AI tools used in GxP processes.
AI Deployment Environments
- Studio: Protocol summary drafting | Site monitoring report assist | Regulatory submission prep
- Refinery: Study report narrative governance | Adverse event documentation | Data integrity compliance
- Clean Room: FDA inspection readiness packages | Sponsor audit evidence bundles
Typical deployment path: Refinery → Refinery → Clean Room
Evidence
- Sponsor audits increasingly include AI governance qualification criteria
- FDA Part 11 warning letters for electronic records traceability are the most common category
- CRO market consolidation is driving AI adoption for competitive differentiation
- ICH E6(R2) requirements are absolute for AI-assisted trial documentation