Your industry runs on validation, documentation, and regulatory defensibility. Your AI strategy should too. I help pharmaceutical, biotech, and medical device companies build AI programs that satisfy FDA expectations and actually deliver business value.
Most AI consultants treat pharma like any other industry. They recommend the same tools, the same "start with a pilot" playbook, and the same governance frameworks they'd give a retail company. That approach fails in regulated environments because it ignores the constraints that actually matter.
In pharma and life sciences, AI doesn't operate in a vacuum. It operates inside a regulatory architecture built on 21 CFR Part 11 electronic records requirements, GxP data integrity principles, FDA machine learning validation expectations, and quality system mandates that have legal consequences when violated. An AI strategy that doesn't account for these realities isn't a strategy -- it's a liability.
I work with pharma companies that want to adopt AI without creating regulatory exposure. That means building strategies where every AI use case has a clear validation path, every model decision has an audit trail, and every deployment satisfies the expectations of the quality organization and the regulators who audit it.
Four service areas designed for the unique requirements of pharmaceutical, biotech, and medical device companies adopting AI.
Evaluate your organization's preparedness for AI in regulated workflows. I assess your data infrastructure, quality system integration points, regulatory documentation readiness, and team capabilities -- all through the lens of what FDA expects.
Build the AI risk assessment framework your regulators expect. I design risk classification systems, validation protocols, and governance structures tailored to pharmaceutical AI use cases -- from drug discovery through manufacturing and post-market surveillance.
A phased implementation plan that prioritizes AI use cases surviving FDA scrutiny. I map opportunities across drug development, manufacturing, quality, and commercial operations -- then sequence them by regulatory feasibility, business impact, and resource requirements.
Connect your AI governance to the management system framework regulators already recognize. I help pharma companies implement ISO 42001 AI Management Systems that integrate with existing quality systems (ISO 13485, GMP) and satisfy EU AI Act requirements.
AI opportunities exist across the pharmaceutical value chain. The strategic question isn't whether to adopt AI -- it's which use cases to prioritize given your regulatory obligations and organizational readiness.
Most AI consultants understand technology. Most pharma consultants understand regulation. I operate at the intersection.
JD, RAC, CPGP, CFSQA, PMP -- I bring regulatory affairs certification, pharmaceutical GMP expertise, and legal training to AI strategy work. When I design a governance framework, it's built to survive an FDA inspection, not just a board presentation.
I've audited pharmaceutical manufacturers, dietary supplement companies, cosmetics operations, and food producers. I know what FDA inspectors look for, what triggers 483 observations, and how to build systems that hold up under scrutiny.
I don't just advise on AI strategy -- I build and deploy AI systems. That hands-on experience means my recommendations are grounded in what actually works in production, not theoretical frameworks from a whiteboard session.
Common questions from pharmaceutical and life sciences companies evaluating AI strategy consulting.
Deep dives into FDA AI requirements, pharma risk frameworks, and AI strategy for regulated industries.
Risk frameworks as essential to AI strategy in regulated environments.
FDA MLFDA ML guidance driving demand across healthcare, pharma, and med-tech.
FDA AIAligning your AI strategy with FDA's evolving regulatory framework.
Your pharma company needs AI. Your regulators need governance. I help you build both -- so you get the competitive advantages of AI without the regulatory exposure.