Life Sciences & Pharma Governance
21 CFR Part 11 Compliant AI Validation Consulting
What FDA's new AI credibility framework means for 21 CFR Part 11 validation work, and how the two standards fit together.
21 CFR Part 11 governs electronic records and signatures for FDA-regulated drug and biologics work, requiring validated systems, secure audit trails, and record integrity. FDA's 2025 draft guidance adds a risk-based credibility assessment framework specifically for AI models used in regulatory submissions. Kriv AI helps sponsors validate AI systems against both standards, starting at $200 per hour.
context
What 21 CFR Part 11 Actually Requires
21 CFR Part 11 sets the FDA's rules for treating electronic records and electronic signatures as trustworthy and legally equivalent to paper, and it predates AI by three decades.
Scope: electronic records and signatures
Part 11 applies to records in electronic form that are created, modified, maintained, archived, retrieved, or transmitted under FDA recordkeeping requirements, and to electronic records submitted to the agency under the Federal Food, Drug, and Cosmetic Act and the Public Health Service Act. In practice, that covers electronic data capture systems, laboratory information management systems, electronic trial master files, and any system generating data that supports a regulatory submission.
Validation is the load-bearing requirement
The regulation requires that systems be validated to ensure accuracy, reliability, and consistent intended performance, along with secure, computer-generated, time-stamped audit trails and the ability to generate accurate copies of records for inspection. A system that cannot produce a defensible audit trail on demand fails Part 11, regardless of how good its output looks.
ai gap
Where AI Systems Complicate Part 11 Compliance
Part 11's validation model assumes a deterministic system: the same input produces the same output, so validation means proving the system does that reliably. Most AI and machine learning models, including the large language models now used to draft study reports, triage adverse event narratives, or support regulatory submissions, do not behave that way. The same prompt can produce different phrasing on different runs, which is exactly the property traditional computer-system validation was not built to evaluate.
That gap does not exempt AI systems from Part 11. If an AI tool touches a GxP record, whatever it outputs still has to be traceable, auditable, and reproducible enough to defend in an inspection. What changes is the validation method, not the requirement.
fda framework
FDA's Risk-Based AI Credibility Framework
On January 6, 2025, FDA published draft guidance, Considerations for the Use of Artificial Intelligence to Support Regulatory Decision-Making for Drug and Biological Products, proposing a risk-based credibility assessment framework for AI models used to generate information supporting drug and biologic submissions. The framework is built around a model's context of use, the specific role the AI plays and the decision it informs, and calibrates how much validation evidence that context demands.
The guidance is informed by more than 800 public comments on FDA's 2023 discussion papers and the agency's own experience reviewing over 300 drug and biologic submissions that already included AI or machine learning components. It does not cover AI used in drug discovery or internal operational efficiency, since those uses do not directly affect participant safety or submission integrity; it is scoped to AI that supports establishing safety, effectiveness, or quality.
engagement
What an AI Validation Engagement Includes
The work starts with an inventory: every AI or ML system touching GxP data or a regulatory submission, mapped to its context of use and assigned a risk tier under FDA's framework. A model summarizing internal meeting notes sits in a different tier than one drafting language for a submission dossier.
Validation then follows a risk-based structure adapted for AI, in the spirit of the GAMP 5 computerized-system validation methodology already familiar to GxP quality teams: instead of a single deterministic test script, it uses structured output sampling against a scoring rubric, documented review of a statistically meaningful sample of outputs, and drift monitoring over time, all captured in an audit trail that satisfies Part 11's record-integrity requirement.
The deliverable is a validation package a sponsor can hand to an FDA inspector or a quality auditor: the risk assessment, the credibility evidence gathered, the validation protocol, and the ongoing monitoring plan, not a one-time slide deck.
tiers
What You Get at Each Tier
1. Enterprise / regulated (life sciences, pharma, medical device)
A full AI validation program: system inventory, context-of-use risk tiering under FDA's framework, a validation protocol adapted for non-deterministic AI output, and an audit-trail package ready for inspection.
2. Fractional AI governance lead
Ongoing oversight of the validation program as new AI use cases enter the pipeline, plus regular reporting to quality and regulatory affairs leadership.
3. Specialized advisory
Targeted review of a single AI system's validation package, or a second opinion ahead of an FDA inspection or submission.
rate card
Kriv AI's Rates for This Work
These are Kriv AI's own published rate floors, not an industry average.
| Track | Kriv hourly rate | Typical engagement model | Minimum engagement |
|---|---|---|---|
| Enterprise / regulated (life sciences, pharma, medical device) | From $200/hr | Fixed-scope project or retainer | $8,000 |
| Fractional CTO / AI governance lead | $300 to $400/hr | Part-time, ongoing (monthly) | $8,000 |
| Specialized advisory (model risk, expert consults) | $400 to $700/hr | Hourly, per-session | Varies by engagement |
| Small business | $150/hr | Referred to Kriv AI's partner network | n/a |
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How to Get a Real Quote
The rates above are floors, not a quote. Actual price depends on how many AI systems touch GxP data, how many submissions they support, and whether the work is a one-time validation package or ongoing oversight as new AI use cases appear. Book a discovery call and we will scope it honestly.
Sources
Cited sources
- FDA Draft Guidance, Considerations for the Use of Artificial Intelligence to Support Regulatory Decision-Making for Drug and Biological Products (January 2025)
- Federal Register, Considerations for the Use of Artificial Intelligence To Support Regulatory Decision-Making for Drug and Biological Products (January 7, 2025)
- eCFR, 21 CFR Part 11, Electronic Records; Electronic Signatures
- NIST AI Risk Management Framework
Straight answers
Frequently asked questions about 21 CFR Part 11 Compliant AI Validation Consulting
What is 21 CFR Part 11?
21 CFR Part 11 is the FDA regulation setting the criteria under which electronic records and electronic signatures are considered trustworthy and equivalent to paper records and handwritten signatures, for records created or submitted under FDA requirements.
Does 21 CFR Part 11 apply to AI models used in drug development?
Yes, if the AI system touches a record that supports a regulatory submission or GxP process. Part 11's validation, audit trail, and record-integrity requirements apply regardless of whether the system is deterministic software or an AI model.
What is FDA's risk-based AI credibility assessment framework?
Draft guidance FDA published in January 2025 proposing that the validation evidence required for an AI model scale to its context of use, the specific role it plays in a drug or biologic submission, rather than applying one validation standard to every AI system.
How is an AI model validated if its output changes between runs?
Through structured output sampling against a scoring rubric, documented review of a representative sample of outputs, and ongoing drift monitoring, rather than the single deterministic test script used for traditional software validation.
What does 21 CFR Part 11 AI validation consulting cost?
Kriv AI's rates start at a $200/hr floor for enterprise and regulated life sciences work, with an $8,000 minimum engagement. Specialized model-validation advisory runs $400 to $700/hr.
Does Kriv AI work with small biotech or medical device startups?
Small-business work is referred to Kriv AI's partner network at a $150/hr rate. Kriv AI's own consulting practice focuses on enterprise and regulated life sciences organizations.
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