Evaluating AI Vendors for Life Sciences Compliance: A GxP Framework

Executive Summary

Enterprise AI providers serving regulated life sciences fall into five identifiable categories: compliance-first AI infrastructure, life-science-native AI platforms, governance and framework consultancies, regulatory-product lines built inside larger platforms, and general-purpose AI vendors that have added healthcare-specific compliance terms. Evaluating any vendor in any of these categories comes down to the same underlying checklist: does its system support 21 CFR Part 11, does it anticipate EU Annex 11, is its validation approach consistent with GAMP 5, does its risk documentation reflect real ICH Q9 methodology, does ISO 13485 apply to its workflow, how does it handle data residency and training-data exclusion, what does its BAA actually cover, and can it produce audit-trail documentation ready for IQ/OQ/PQ review. This guide lays out that checklist pillar by pillar, with the concrete question to ask and what a strong versus a weak vendor answer looks like, reviewed against a real computer system validation (CSV) practice's own hands-on experience validating regulated systems for life sciences clients.

What Enterprise AI Providers Actually Focus on Compliance

The market answering "which enterprise AI providers focus on regulatory-compliant life science solutions" is not a single winner. It is a fragmented field of five distinct approaches, each solving a different piece of the compliance problem. Understanding which category a vendor sits in is the first step in evaluating it, since the compliance claims that matter, and the questions worth asking, differ by category.

Compliance-first AI infrastructure

The clearest example of this category is Accenture's investment in Iridius, described as a "compliance-by-design AI platform" built specifically for regulated pharma workflows.[1] Iridius is built around the idea that compliance controls are native to the platform rather than layered on afterward, which is a meaningfully different starting point than a general-purpose AI vendor adding compliance features later. For a life sciences buyer, this category is worth a close look first, because compliance-by-design is the strongest structural claim a vendor can make, provided the vendor can actually document what "by design" means in practice: which controls are architecturally enforced versus which are configurable options a client has to turn on themselves. Ask a vendor in this category to name the specific control, not just the phrase. If the answer is a slide with the words "compliance-by-design" and nothing underneath it, that is a weak answer regardless of how large the vendor is.

Life-science-native AI platforms

Certara's AI platform is built specifically for life sciences workflows and describes itself as "secure, scalable, and specialized."[2] Certara states HIPAA and GxP alignment along with SOC 2 Type II certification, and describes full AI-output traceability, meaning individual outputs can be traced back to their source data points and the specific model version that produced them. That combination, a named certification plus concrete traceability mechanics, is a stronger and more checkable claim than a vendor simply asserting it is "compliant." When evaluating a life-science-native platform, ask specifically whether it can name its certifications and describe its traceability mechanism, not just whether it uses the word "compliant" in its marketing. A strong answer names the certification body, the certification date or renewal cycle, and points to an actual audit trail feature a reviewer can inspect. A weak answer restates the marketing copy back to you.

Governance and framework consultancies

USDM Life Sciences publishes a framework document, "AI Governance for Life Sciences: The Enterprise Framework for Compliant, Scalable AI," structured in three parts: the current state of AI adoption in life sciences, a six-stage AI System Lifecycle governance framework, and four strategic pillars anchoring AI initiatives to revenue, efficiency, innovation, and risk.[3] This is a framework document, not a vendor pitch, and that distinction matters. Framework and checklist-style content tends to stay useful and referenceable well after a narrative "everything you need to know" piece has gone stale, because a framework describes a repeatable evaluation process rather than a point-in-time feature list. USDM's own structure is worth noting as a model for how a life sciences organization should think about AI governance internally, independent of any specific vendor relationship. When a consultancy in this category pitches a framework, ask whether the framework was built to be applied against any vendor, or whether it quietly only produces one recommended answer.

Regulatory-product lines inside larger platforms

IQVIA's SmartSolve RIM is a purpose-built regulatory information management product, not a generic enterprise AI offering.[4] It centralizes submissions, product registrations, and health-authority interactions, and is explicitly framed around 21 CFR Part 11 and CTD/eCTD compliance requirements. This category is useful to know about because it shows that some of the biggest life sciences technology vendors have chosen to build narrow, regulation-specific products rather than positioning a single broad AI platform as "compliant" across every use case. A narrower, named-regulation product is often easier to evaluate honestly than a broad platform claiming blanket compliance, because the vendor has already scoped its own claim for you. The evaluation question shifts from "is this vendor compliant" to "is this specific product's compliance scope the one my use case actually needs."

General-purpose AI vendors with healthcare-specific compliance terms

Anthropic launched Claude for Healthcare at JPM26, offering HIPAA-ready infrastructure for enterprise customers along with models tuned for healthcare and life sciences tasks and native integrations to resources like the CMS Coverage Database, ICD-10, and PubMed.[5][6] Beyond the announcement itself, Bristol Myers Squibb's rollout of Claude to 30,000 staff, covered by the Wall Street Journal, is a real-world proof point of enterprise-scale deployment in a regulated pharmaceutical environment.[7] This category matters directly to IntuitionLabs' own work: IntuitionLabs is a member of the Claude Partner Network, and understanding how Anthropic itself frames HIPAA readiness (see the BAA pillar below) is directly relevant to any client evaluating Claude-based deployments in a regulated setting. The evaluation trap in this category is treating "the vendor has a HIPAA-ready product" as equivalent to "every product this vendor sells is HIPAA-ready." Those are not the same claim, and the BAA pillar below walks through exactly why that distinction matters using Anthropic's own documentation as the concrete case.

A Framework for Evaluating AI Vendor Compliance

The five categories above describe who is building compliance-oriented AI. The eight pillars below describe what to actually check, regardless of which category a vendor falls into. Each pillar is phrased as a question a buyer should be able to get a straight answer to, not a feature a vendor's marketing page claims to have.

21 CFR Part 11: electronic records and signatures

The question to ask: does the vendor's system support validated audit trails, properly bound electronic signatures, and record retention consistent with the FDA's scope-and-application guidance for Part 11?[8] A vendor that can answer this with specifics, which records are covered, how signatures are bound to specific records and users, how retention periods are configured, is in a different position than one that answers with "yes, we're Part 11 compliant" and stops there.

A useful follow-up question is whether the vendor can walk through a single record's lifecycle: creation, the point at which a signature is applied, what happens if that record is later amended, and how long it is retained before archival or deletion. A vendor that can answer that sequence concretely has almost certainly been through a real Part 11 validation exercise before. A vendor that cannot has probably only ever been asked about Part 11 in a sales conversation, not a validation one.

For a deeper walkthrough of what Part 11 actually requires, see IntuitionLabs' own breakdown of electronic records and signatures requirements in AI and GxP contexts.[il-1]

EU Annex 11 and the incoming Annex 22 (AI-specific)

The question to ask: for organizations operating in the EU, does the vendor's documentation anticipate the pending Annex 22, which will address AI-based systems specifically?

This is worth stating precisely, because the timeline matters: as of late July 2026, the EU's Annex 11 revision and the new Annex 22 are still in draft form, not final. The European Commission released drafts on 7 July 2025, the public consultation closed 7 October 2025 with roughly 1,300 comments received, and the European Medicines Agency held a stakeholder workshop on 30 June and 1 July 2026. Final publication is expected in mid-to-late 2026 but has not yet been issued.[9]

A vendor claiming to already be "Annex 22 compliant" should be evaluated with that draft status in mind; there is no final standard yet to be fully compliant against. What is worth checking instead is whether a vendor is tracking the draft closely enough to describe, in its own words, what the current draft actually proposes, and whether it has a stated plan for aligning once the final version publishes. That is a meaningfully more honest answer than a premature compliance claim. This is also the pillar most likely to go stale fastest in this guide itself, worth re-checking directly against the EU's own published timeline before treating any vendor's Annex 22 position, or this guide's own summary of it, as current.

GAMP 5 (Second Edition): risk-based validation approach

The question to ask: does the vendor support GAMP 5's risk-based categorization and supplier-involvement model, meaning a client can rely on vendor-supplied documentation plus targeted internal testing rather than re-validating an entire system from scratch?

The GAMP 5 Second Edition Guide is published by ISPE, the International Society for Pharmaceutical Engineering, which is the authoritative source on the framework itself.[10] ISPE has also published AI-specific coverage of how this framework is evolving, including "How AI Will Transform Computerized System Validation"[11] and "Transforming Pharmaceutical Quality with GAMP AI Guardrails."[12]

A concrete way to test this pillar: ask the vendor which GAMP 5 software category its system falls into, and what supplier-side documentation it provides to support a client's own risk assessment. A vendor that has genuinely thought through where it sits in GAMP 5's categorization will answer this without hesitation. A vendor that has not will usually redirect to a general statement about being "GAMP 5 aligned," which is not the same as being able to name a category.

For a full walkthrough of GAMP 5 in a pharmaceutical validation context, including how it connects to FDA Computer Software Assurance and both Part 11 and EU Annex 11, see IntuitionLabs' guide to GAMP 5 and computerized system validation.[il-2]

ICH Q9: quality risk management

The question to ask: does the vendor's own risk-assessment documentation demonstrate a real ICH Q9-aligned methodology, with an actual artifact you can review, rather than just an assertion of being "risk-based"?

This pillar is intentionally short, because the evaluation question is simple: ask for the artifact, not the adjective. A vendor that produces an actual risk-assessment document, showing hazard identification, risk evaluation, and risk control steps, has done the work. A vendor that only offers the phrase "risk-based approach" in a sales deck has not, regardless of how confidently the phrase is delivered.

ISO 13485 (where relevant)

The question to ask: for AI systems that touch medical-device-adjacent workflows specifically, does the vendor's quality management approach align with ISO 13485?

This pillar has the narrowest applicability of the eight and matters mainly when a system's outputs feed into medical device design, manufacturing, or post-market surveillance processes. For a buyer whose use case sits entirely outside medical devices, this pillar can reasonably be marked not applicable rather than forced into the evaluation. For a buyer whose use case does touch device-adjacent workflows, the same standard applies as the other pillars: ask for a clear scoped answer, not a blanket claim that stretches ISO 13485 alignment across the vendor's entire product line.

Data residency and training-data exclusion

The question to ask: does the vendor contractually exclude client data from model training, and where specifically is inference and data processing performed?

It is also worth noting, evenhandedly, that AI-specific validation itself is still an emerging sub-discipline rather than a single settled standard. ISPE's own coverage describes AI-specific validation tests, checking for no train/test data leakage, evaluating bias across subgroups, and locking training datasets, as evolving practice, not yet a fixed industry standard. A vendor further along in defining and documenting these tests is worth more credit than one that has not yet addressed the question, and a vendor that claims a fully settled, industry-standard AI validation process should be asked which standard specifically, since no single one yet exists across the industry.

Practically, this pillar comes down to two separate questions that are easy to conflate: where is data processed geographically (residency), and is that data used to improve the vendor's models going forward (training exclusion). A vendor can answer one well and dodge the other. Both need a direct, contractual answer, not a general privacy-policy reference.

BAA / HIPAA terms

The question to ask: what does a vendor's Business Associate Agreement actually cover, versus what its marketing language implies about "HIPAA compliance" more broadly?

This is the pillar where reading the fine print matters most, and there is a concrete, checkable example worth knowing. Anthropic's own support documentation states that Claude Cowork is not an eligible BAA service in any configuration, while Claude Enterprise and the first-party API are BAA-eligible once a primary account owner signs the BAA and activates HIPAA compliance settings.[13][14]

That is exactly the kind of product-by-product distinction a buyer needs to check for any AI vendor: the brand name being "HIPAA-ready" does not mean every product under that brand is covered by the same BAA terms. Two products from the same company, under the same overall brand promise, can sit on opposite sides of a compliance line. The only reliable way to know which side a specific use case falls on is to ask which named product and tier is actually covered by a signed BAA, not whether the vendor as a whole "does HIPAA."

Audit trail and IQ/OQ/PQ readiness

The question to ask: can the vendor produce a documentation package ready for Installation Qualification, Operational Qualification, and Performance Qualification (IQ/OQ/PQ) review, not just a marketing bullet point that says "audit logging"?

A useful way to see what this looks like in practice is to review a validated vendor relationship that already exists: IntuitionLabs' own Egnyte GxP validation work is a worked example of validating a third-party platform for regulated use, describing Egnyte's own certifications as the vendor being validated, not IntuitionLabs' own infrastructure.[il-3] For the broader CSV service this work sits within, see IntuitionLabs' computer system validation service page.[il-4]

A strong vendor answer here typically includes a sample or redacted example of an actual IQ/OQ/PQ package, or at minimum names a prior client engagement where one was delivered. A weak answer treats "audit logging" as a complete substitute for a structured validation package, when in practice audit logs are one input into that package, not the package itself.

Where IntuitionLabs Fits: A CSV Practitioner's View

What our CSV practice actually validates

IntuitionLabs runs a computer system validation practice that works against 21 CFR Part 11, EU Annex 11, GAMP 5, ICH Q9, and ISO 13485. The practice validates client systems including Egnyte, Veeva Vault, LIMS and ELN systems, MES systems, and custom AI and machine learning systems used in regulated environments. This is a consulting practice, meaning IntuitionLabs helps clients validate their own systems against these frameworks; it is worth being direct about that distinction, and the next section addresses it further.

Named in-house expertise, not a formal byline

The framework above reflects the real-world validation experience of IntuitionLabs' own team. Pesh Joshi, IntuitionLabs' Veeva Practice Lead, spent 13 years at Veeva Systems, including time as Practice Director for Global Program Management and Vault Quality. Amie Harpe, who leads Quality Systems and Digital Transformation work at IntuitionLabs, spent 23 years in Pfizer's Quality Operations organization and holds PMP, SAFe, and Lean Six Sigma Green Belt credentials. Their combined background, on both the vendor side (Veeva) and the pharmaceutical operator side (Pfizer), is the practical experience this framework draws on. Full bios are available on IntuitionLabs' leadership page.[il-5]

What This Framework Doesn't Claim

It is worth being precise about what IntuitionLabs does not claim, rather than leaving it implicit. IntuitionLabs does not hold its own SOC 2, ISO 27001, or HIPAA BAA-issuing certification. IntuitionLabs does not have a dedicated security or trust page; the site publishes only standard privacy and terms pages. Where certifications appear anywhere on IntuitionLabs' site, such as on the Egnyte validation page referenced above, they describe Egnyte's certifications as a third-party vendor being validated, not IntuitionLabs' own infrastructure or product.

This is a genuine and useful distinction to draw against a vendor like Certara, discussed earlier, which does state its own SOC 2 Type II certification as a platform provider. IntuitionLabs' CSV practice operates as a consulting service that helps validate other systems, not as a certified platform itself, and those are two different models worth evaluating differently. Naming that difference plainly is more useful to a buyer than staying silent on it. The same discipline this framework asks of every vendor in Section 2 applies here too: state the actual scope of the claim, not a broader version of it.