Join fellow Pistoia Alliance members for an engaging discussion of Pharma and Profits: Balancing Innovation, Medicine, and Drug Prices by Dr. John LaMattina, former President of Pfizer Global Research and Development. The book explores one of the pharmaceutical industry’s most debated topics: how to balance innovation, patient access, and the economics of drug development. […]
Initiatives at Pistoia Alliance to improve pharmacovigilance Pharmacovigilance teams across the industry face the same problems: fragmented systems, duplicated effort, and no shared playbook for adopting AI safely and compliantly. The Pistoia Alliance has two complementary, pre-competitive initiatives to tackle these challenges together: Pharmacovigilance Systems & Processes Standards (PS²): building common business-process, system and interoperability […]
Your people are already using AI. They’re writing code with it, analyzing data with it, drafting regulatory documents with it – with or without your governance frameworks, your ontology standards, or your validation processes. The question isn’t whether to enable this; it’s whether you’re going to lead it or clean up after it. The Pistoia […]
For decades, the standard response to a research bottleneck has been simple: “We need more data.” But in today’s landscape, the limiting factor is rarely a lack of information—it is the fragmentation of the data we already own. Join info pro Mary Ellen Bates and Mark Hahnel (Digital Science) for a discussion on “The […]
This end-of-summer seminar takes a longitudinal view of AI across the full drug development pipeline — from the earliest stages of target identification and validation through to clinical trial design and execution. Through in-depth case studies and expert presentations, participants will examine where AI is delivering genuine, measurable value and where significant challenges remain. […]
In an industry where failure is rarely discussed openly, this round table offers something genuinely valuable: a safe, pre-competitive space to share what has gone wrong with AI projects — and what was learned as a result. From misaligned expectations and poor data quality to underestimated complexity and organisational resistance, AI initiatives fail for […]
Building on the AI-Ready Data Workshop held at the Boston Conference, this follow-up session reports back on the discussions, consensus, and open questions that emerged including how FAIR data principles map to AI readiness, and what additional dimensions of data quality the community identified as critical. As with all LSAIE round tables, numbers are […]
A year-end look back at how the field of AI in life sciences has evolved over 2026, featuring reflections from returning LSAIE contributors alongside forward-looking perspectives on priorities for 2027. This session also closes the loop on the AI-Ready Data initiative for members of the wider community. Register
