GxP AI - How Quality Systems Can Responsibly Control AI to Enhance Productivity and Streamline Operations
As AI capabilities push into GxP regulated business functions, how can Quality and IT teams partner to ensure they are properly controlled? Join us as a panel of experts walks you through emerging practices for how Life Sciences companies can integrate AI-based solutions into GxP functions responsibly.
See below for speaker info and a list of additional resources about AI.
SwareLinkedIn Profile
Global Exponential Technologies
(GxT)LinkedIn Profile
Tulip Interfaces, Inc.LinkedIn Profile
KPMGLinkedIn Profile
Speaker Resources
See below for a curated list of resource from the speakers panel the audience may find useful.
From the FDA
- Artificial Intelligence / Machine Learning in Drug Development Notification
- Using Artificial Intelligence & Machine Learning in the Development of Drug and Biological Products (Discussion Paper & Request for Feedback, published 11May2023)
- Artificial Intelligence in Drug Manufacturing (Discussion Paper)
- FDA Releases Two Discussion Papers to Spur Conversation about Artificial Intelligence and Machine Learning in Drug Development and Manufacturing (Discussion Papers)
- Good Machine Learning Practice for Medical Device Development: Guiding Principles (SAMD)
- Joint US FDA/Health Canada/UK MHRA Good Machine Learning Practice for Medical Device Development
From the ISPE
- The Road to Explainable AI in GXP – Regulated areas (Jan/Feb 2023)
- Machine Learning Risk and Control Framework (Jan/Feb 2024)
- AI Maturity Model for GxP Application: A Foundation for AI Validation (April 2022)
- ISPE GAMP® 5 Guide: A Risk-Based Approach to Compliant GxP Computerized Systems (2022)
- Figure 11.3 Typical Use of Risk-Based Decision Making p. 112
- Figure 31.1 GAMP 5 Life Cycle with ML Sub-System, Appendix D11, p. 271
- Application of principles included in Risk Analysis and Mitigation Matrix (RAMM) – A Risk Tool for Quality Management (2012) (Page 26)
- ChatGPT, BARD and other Large Language Models Meet Regulated Pharma (July/Aug 2023)
- AI Governance and QA Framework: AI Governance Process Design (July/Aug 2022)
- Note: ISPE has created an AI Community of Practice
EMA
- Software and AI as a Medical Device Change Programmme-Roadmap (Guidance, June 2023)
- The use of Artificial Intelligence (AI) in the medicinal product lifecycle (Reflection paper, Nov 2023)
- Proposal for Laying down the rules for regulation in AI
Additional Resources
- Regulators Face Novel Challenges as Artificial Intelligence Tools Enter Medical Practice
- Preparing a Framework for AI / ML Validation: A 3 Step Process
- A succinct article that outlines 3 main points aligned with the Validation 4.0 approach but with a focus on AI/ML specific concepts.
- AI Integration in Drug Manufacturing - GMP Insights for Operational Excellence
- Hugging Face – Learn
- Intro to AI Ethics
- Natural Language Processing (for those who want to learn how GenAI for text works)
Featured Resources
The future of life sciences validation and compliance is not so far away. Already, we are seeing life sciences companies rush to integrate AI where possible, while at the same time striving to manage risk with fewer human and material resources available.
Read the WhitepaperLearn how Nuvolo is leveraging a combination of Sware's Res_Q Platform and expert resources to deliver a fully GxP compliant offering to the life sciences industry, enabling Nuvolo and their customers to meet business goals.
Read the case studyManual computer software validation processes cost life sciences organizations up to 30% in additional project budget. As companies struggle to keep up with a surge of app and software integrations, they incur validation debt: the mounting cost of stretched resources, blanket testing, and missed GxP requirements.
Download the EbookValidation Debt Stops Here
If your organization is ready to embrace the future of life sciences validation, we’re ready to help.