Industry Specialization

ISO 42001 Consulting for
Pharmaceutical & Life Sciences Companies

Build the AI governance system your regulators expect. Gap assessments, AIMS implementation, and certification prep from a consultant who speaks both AI governance and GxP.

200+

Certification Projects

CPGP

GMP Certified

RAC

Regulatory Affairs

Pharmaceutical companies are adopting AI faster than their governance systems can keep up. Drug discovery teams use machine learning models to predict molecular behavior. Manufacturing operations deploy AI for process optimization, predictive maintenance, and real-time quality monitoring. Quality systems use AI-enabled tools for deviation detection, CAPA trending, and complaint analysis. Regulatory affairs teams explore AI for document preparation and submission review.

Each of these applications carries risk — to patient safety, to product quality, to data integrity, and to regulatory standing. Without a structured governance framework, companies manage these risks inconsistently: individual teams make ad hoc decisions about AI validation, documentation, and oversight that may or may not satisfy regulatory expectations.

ISO/IEC 42001:2023 is the first international standard for Artificial Intelligence Management Systems (AIMS). It gives pharmaceutical companies a recognized, auditable framework to manage AI responsibly — and to demonstrate that management to regulators, partners, and auditors. If you already operate within an ISO-certified quality management system, ISO 42001 is designed to layer on top of it — not replace it.

The Regulatory Landscape

Why Pharma & Life Sciences Companies Need ISO 42001 Now

The regulatory expectation for AI governance is forming now. Companies that wait for final enforcement actions to build governance will find themselves scrambling to build systems under pressure that should have been built deliberately.

FDA AI Credibility Framework

FDA's January 2025 draft guidance establishes a risk-based approach to AI credibility assessment. Sponsors must define the regulatory question the AI model addresses, assess model risk, develop a credibility assessment plan, and document outcomes. ISO 42001's risk management framework provides the systematic approach FDA expects.

EU AI Act (Aug 2026 Deadline)

The EU AI Act classifies many pharmaceutical AI applications as high-risk — particularly AI used in medical devices, diagnostics, and clinical decision-support. By August 2026, high-risk systems require conformity assessments, technical documentation, and post-market monitoring. Penalties reach 35 million euros or 7% of global turnover.

ISPE GAMP AI Guide (July 2025)

The pharma industry's own practical framework for AI in GxP environments. It builds explicitly on ISO 42001 principles and addresses AI system lifecycle management, quality risk management, supplier qualification, and data integrity. ISO 42001 is the management system that operationalizes GAMP AI.

21 CFR Part 11 & Annex 11

Your existing electronic records requirements don't disappear when AI enters the picture — they intensify. AI systems that generate, process, or store GxP-relevant data must maintain data integrity, audit trails, and validated states. ISO 42001's data governance controls complement your Part 11/Annex 11 compliance program.

The bottom line: No single regulation tells pharmaceutical companies exactly how to govern AI. But every relevant regulation points toward the same fundamentals — risk-based management, documented lifecycle controls, data governance, and human oversight. ISO 42001 organizes all of those fundamentals into a single, auditable system.

Familiar Framework

How ISO 42001 Maps to GxP Requirements

If you've spent years building quality management systems for pharmaceutical manufacturing, the structure of ISO 42001 will feel familiar. The concepts translate directly — the vocabulary just changes.

GxP Concept ISO 42001 Equivalent
Quality Policy (ISO 9001 / 21 CFR 211)AI Policy (Clause 5.2)
Quality Risk Management (ICH Q9)AI Risk Assessment (Clause 6.1, Annex B)
Computer System Validation (GAMP 5)AI System Lifecycle Management (Annex A, A.6)
Change ControlAI System Change Management (Annex A, A.7)
Data Integrity (21 CFR Part 11 / Annex 11)Data Governance for AI (Annex A, A.10)
Supplier QualificationThird-Party AI Component Assessment (Annex A, A.9)
CAPA SystemContinual Improvement (Clause 10)
Management ReviewAI Management System Review (Clause 9.3)
Training and CompetencyAI Competency Requirements (Clause 7.2)
Document ControlAI Documentation and Records (Annex A, A.5)

ISO 42001 follows the same Annex SL high-level structure that ISO 9001 and ISO 13485 use. For pharmaceutical companies already operating within ISO-certified management systems, ISO 42001 integration is a natural extension — not a ground-up rebuild. The challenge is knowing which AI-specific controls matter most in a GxP context, which existing QMS processes can be extended rather than duplicated, and where the gaps actually are.

Consulting Services

How I Help Pharmaceutical & Life Sciences Companies

Every engagement is built on regulated-industry compliance experience — not generic AI consulting frameworks.

AIMS Gap Assessment

1–3 weeks • Foundation engagement

Understand where your organization stands before building anything. The gap assessment inventories your current AI applications across R&D, manufacturing, quality, and regulatory affairs — then assesses each against ISO 42001 control objectives.

  • Inventory of current AI applications across your organization
  • Assessment of each application against ISO 42001 control objectives
  • Review of existing QMS documentation for AI-relevant coverage
  • Evaluation of AI risk management practices against Annex B requirements
  • Assessment of data governance practices for AI training data, model inputs, and outputs
  • Written gap report with risk-rated findings and prioritized corrective action plan

ISO 42001 Implementation

3–6 months • Full system build

Build a formal AI management system with your team — one that accounts for your existing QMS maturity, your regulatory context, and your actual AI applications.

  • AI policy development aligned with organizational strategy
  • AI risk assessment framework design (building on existing QRM practices)
  • AI system lifecycle procedures — development, testing, validation, deployment, monitoring, retirement
  • Data governance procedures for AI systems (training data quality, bias assessment, privacy)
  • Third-party AI component assessment and supplier qualification procedures
  • Integration mapping with existing QMS (ISO 9001, ISO 13485, or cGMP systems)
  • Training program for AI governance roles

Pre-Certification Audit Preparation

4–8 weeks • Certification readiness

Prepare for both the certification auditor and the regulator — because in pharma, passing the audit is necessary but not sufficient.

  • Pre-assessment review of all AIMS documentation against ISO 42001 requirements
  • Internal audit of the AI management system using certification body criteria
  • Mock certification audit with written findings
  • Corrective action support for any non-conformances identified
  • Readiness check before Stage 1 and Stage 2 audits

AI Governance QMS Integration

2–4 months • Extend your existing QMS

For companies that already operate mature quality management systems and want to extend them to cover AI governance — without building a separate parallel system.

  • Mapping ISO 42001 requirements against your current QMS structure
  • Identifying which existing procedures can be extended vs. which require new documents
  • AI-specific procedures that integrate with existing document control, change control, CAPA, and management review
  • AI risk assessment procedures building on your ICH Q9 or ISO 14971 framework
  • AI supplier qualification criteria for your existing vendor management program

Target Audiences

Who This Is For

Pharmaceutical Manufacturers

Deploying AI in manufacturing execution, process analytics, predictive maintenance, or quality control — and recognizing that these systems need formal governance beyond what your current computer system validation program covers.

Biotech & Life Sciences Companies

Using machine learning in drug discovery, clinical trial design, or regulatory submissions — particularly those preparing for FDA engagement where AI credibility assessment will be expected.

Medical Device Companies

Developing AI-enabled devices or Software as a Medical Device (SaMD) — where EU AI Act high-risk classification creates immediate compliance obligations by August 2026.

Contract Manufacturing Organizations (CMOs)

Whose pharmaceutical clients are beginning to ask about AI governance as a supplier qualification requirement — similar to how retail buyers began requiring NSF 455-2 certification from supplement manufacturers.

Quality & Regulatory Affairs Leaders

Who have been tasked with "figuring out AI governance" and need a structured starting point that connects to the regulatory frameworks they already know.

Why Regulated-Industry Experience Matters

My Background

I'm Jared Clark. My career has been spent inside regulated industries — building, assessing, and remediating the quality management systems that keep companies in compliance and products safe.

My ISO 42001 practice builds on the same foundation that has made me effective in GMP consulting: the ability to translate regulatory requirements into practical, documented quality systems that organizations can actually operate. The frameworks are different. The discipline is the same.

I bring regulated-industry compliance experience to a space that is currently dominated by IT security consultants and management system generalists. If your organization needs AI governance that speaks the language of GxP, validation, and regulatory affairs — not just information security — that's the gap I fill.

CPGP

Certified GMP Professional

CMQ/OE

Manager of Quality

PMP

Project Management

RAC

Regulatory Affairs

CFSQA

Food Safety Auditor

CSA

Computer Software Assurance

PVM

Pharma Validation Mgmt

JD

Juris Doctor

Common Questions

Frequently Asked Questions

Answers to the questions pharmaceutical and life sciences companies ask most about ISO 42001.

Not yet — no regulator currently mandates ISO 42001 certification specifically. However, the regulatory direction is clear. FDA's AI credibility framework, the EU AI Act's high-risk requirements, and ISPE's GAMP AI Guide all point toward the same governance fundamentals that ISO 42001 organizes. Companies that implement ISO 42001 now will be positioned to meet whatever specific requirements emerge — rather than scrambling to build governance systems retroactively.
ISO 42001 provides the management system framework for governing AI across your organization. GAMP 5 (Second Edition) and the GAMP AI Guide provide the practical validation approach for individual computerized systems, including AI-enabled ones. They are complementary: ISO 42001 tells you how to manage your AI governance program; GAMP tells you how to validate individual AI systems within that program. If you already have a CSV/CSA program, ISO 42001 extends its scope to cover AI-specific risks that traditional validation approaches don't fully address.
No. ISO 42001 is designed to integrate with existing management systems — ISO 9001, ISO 13485, 21 CFR Part 211, or whatever framework you currently operate under. It uses the same Annex SL high-level structure that ISO 9001 and ISO 13485 use, which means your existing management review, internal audit, document control, and CAPA processes can be extended rather than duplicated.
For a pharmaceutical company with a mature QMS already in place, a focused implementation typically takes 3-6 months. The timeline depends on the number of AI applications in scope, the maturity of existing governance practices, and the organization's decision-making velocity. Companies starting from scratch with both AI governance and general quality management infrastructure will need longer.
Certification costs have two components: the consulting engagement to build and implement the AIMS (which varies by scope and complexity), and the certification body's audit fees. Certification body fees vary by organization size and scope — contact registrars like BSI, DNV, or Bureau Veritas for current pricing. The consulting investment depends on your starting point; a gap assessment gives you the clearest picture of what's actually required.
Yes — and this is one of the most common misconceptions. ISO 42001 applies to organizations that use AI-based products and services, not only those that develop them. If your lab is using AI-powered analytical software, your manufacturing team is using AI-enabled process optimization tools, or your regulatory team is using AI for document review, you have AI governance obligations. The standard includes specific controls for third-party AI components (Annex A, A.9) and requires you to assess and manage the risks of AI systems regardless of who built them.
If your products reach EU markets, the EU AI Act applies to you — similar to how GDPR applies to any company processing EU residents' data. High-risk AI systems (including many pharmaceutical and medical device applications) must comply with conformity assessment, technical documentation, and post-market monitoring requirements by August 2, 2026. Penalties reach up to 35 million euros or 7% of global annual turnover. ISO 42001 provides the management system infrastructure to demonstrate systematic compliance.
Yes — and this is actually the ideal time to build your governance framework. Establishing AI policies, risk assessment procedures, and lifecycle management processes before AI deployment means you govern from the start rather than retrofitting governance onto systems that are already in production. The gap between "we should use AI" and "we are using AI" closes faster than most organizations expect.

Start With a Conversation

If you're evaluating AI governance options for your pharmaceutical or life sciences company — whether you're responding to a regulatory inquiry, preparing for EU AI Act compliance, or building governance proactively — the starting point is understanding exactly where you stand.

Free 30-minute consultation. No pitch. No commitment. Just an honest assessment of your AI governance situation and the most practical path forward.

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Jared Clark, CPGP, CMQ/OE, PMP, RAC • Certify Consulting Group