Use AI in CMC, QA & Regulatory Work — Without Risking Your Credibility.
A live, half-day workshop where you'll build a complete AI Use Policy for your practice or organization. Walk out with a finished document.
Less than half a day of your professional time to protect every deliverable after that.
Registration is now closed
AI is already part of your work. But do you have a system for it?
Every week, life science professionals are using AI to draft SOPs, summarize literature, scaffold regulatory responses, and speed up CMC documentation. The tools are good — and they're getting better fast.
Most people don't have a documented policy for how they use them.
There are no guidelines for what's AI-appropriate vs. off-limits, no verification protocol, no model selection criteria, and no answer ready for when a client, auditor, or leadership team asks, "What's your AI policy?"
That question is coming. For many of you, it's already here.
What happens when AI literacy doesn't keep up with AI adoption
Deloitte Australia, 2024
A Big Four firm delivered a 237-page government report to the Australian Senate containing fabricated court quotes, 12+ citations to academic papers that don't exist, and made-up book titles attributed to real professors. They reportedly used GPT-4o — even though they had access to better models with lower hallucination rates.
The cost: a $290K partial refund, a public correction, and a senator calling it "the kind of thing a first-year university student would be in deep trouble for."
The AI worked exactly as designed. The people using it chose the wrong model, ran no verification, and worked without a policy governing what's appropriate. If it can happen to a Big Four firm with unlimited resources, it can happen to any practice or organization. The difference is whether you have a framework to prevent it.
You already know how to do most of this.
If you work in life sciences, you've spent years building and maintaining Data Integrity programs — ALCOA+ principles, audit trails, validated systems, data lifecycle mapping, and traceability from source to output.
Your DI foundation is your AI readiness foundation.
The same principles that govern how you handle data in a GxP environment are exactly what responsible AI use demands. You're extending a framework you already understand.
If you understand ALCOA+, you're already closer to responsible AI than you think — you just need the bridge to connect the two.
In 3 hours, you'll build a complete AI Use Policy — customized to your work.
You'll build the actual document during the workshop, tailored to your practice or your team.
1. Scope & Applicability
Define which tasks are AI-appropriate, which are off-limits, and which require human-in-the-loop verification. Your policy will reflect your specific work and risk profile.
2. Model Selection Guidelines
Document which AI tools you'll use for which task types, and why. Learn which models are appropriate for citation-heavy work vs. first-draft scaffolding vs. data summarization.
3. Verification & QA Protocol
Establish the specific checks required before any AI-assisted deliverable goes out the door, mapped to the ALCOA+ principles your organization already follows.
4. Disclosure & Traceability
Get ready-to-use language for communicating your AI practices, and document the data lineage from AI input to final output so every deliverable is traceable and defensible.
5. Incident Response
Document what happens when something slips through. Having a plan for mistakes is just as important as preventing them — and your existing CAPA framework gives you a head start.
You'll fill in every one of these sections during the workshop, customized to your practice, your organization, and the type of work you do.
What the 3 hours look like
Hour 1
The Credibility Problem
Dissect real case studies and examine why "having AI tools" without AI literacy is a growing liability in regulated industries. Understand why your DI programs are the strongest foundation for AI governance.
Hour 2
The Policy Build
The hands-on core. Build your AI Use Policy live — which tasks are appropriate, what verification looks like, how to choose the right model, how to write disclosure language.
Hour 3
Pressure Test & Implementation
Stress-test your policy against real scenarios from CMC, QA, and Regulatory work. Walk away knowing how to use it day-to-day and present it as a trust signal.
This workshop is for you if…
- You work in life sciences (CMC, QA, Regulatory, or a related function) and you're using AI or about to start
- You're an independent consultant who needs a professional AI framework for your practice
- You're a team lead who's been asked to "figure out our AI approach"
- You already run a Data Integrity program and want to extend those principles to AI governance
- You want to use AI confidently without worrying that a hallucinated citation will damage your reputation
- You're tired of "winging it" and want a documented, defensible approach
This is NOT a coding workshop, a prompt engineering class, or a deep dive into transformer architectures.
If you can use ChatGPT or Claude, you have all the technical background you need. This is about building a responsible framework for AI use in regulated work.
Meet your instructor
Alexa Kopf is the founder of LabScale AI, where she provides AI literacy coaching and education for life science professionals. She works with independent consultants and in-house teams across CMC, QA, and Regulatory.
She's developed proprietary frameworks including the ALIGN loop and the 3x3 Test for evaluating AI use cases. She writes the weekly LabScale AI newsletter and speaks regularly at industry events.
Speaking at trusted industry events
Investment
AI-Proof Your Practice Workshop
$497
Registration is now closed
- Live 3-hour workshop via Zoom
- Hands-on policy-building with expert guidance
- Completed, customized AI Use Policy document
- Model selection guide for life science deliverables
- Full workshop recording for future reference
- Access to the policy template framework
Limited to 25 seats so everyone gets personal attention.
For an independent consultant billing $200/hr, this pays for itself the first time a client asks about your AI practices and you have a confident answer.
Bringing a colleague? If you're a team lead who wants to attend with a peer, reply to your confirmation email and I'll set up a two-seat bundle.
Questions you might have
Stop winging it and start documenting it.
The next time someone asks about your AI practices, have a confident, professional answer.
Live via Zoom · 25 seats · 48-hr full refund