All Insights Report Axtria Ignite 2025 Fireside Chat: Charting the Future of Commercialization in an Agentic Era
Axtria Ignite 2025 Fireside Chat: Charting the Future of Commercialization in an Agentic Era
Axtria Ignite 2025 Fireside Chat: Charting the Future of Commercialization in an Agentic Era
Discover how Agentic AI in pharma will once again redefine commercialization strategy.

In a captivating fireside chat at Axtria Ignite 2025, Jassi Chadha, co-founder and CEO of Axtria, and Greg Meyers, EVP and Chief Digital & Technology Officer at Bristol Myers Squibb, discussed the next transformation in life sciences and pharma analytics: the power of agentic AI. The two leaders explored how generative AI, and now AI agents, have profound impacts on research, clinical trials, and pharma commercial strategy. They also addressed critical challenges like regulatory hurdles and workforce adaptation.
Drawing from their diverse backgrounds in technology and cross-industry leadership, they painted a forward-looking vision of AI-powered analytics that accelerates innovation, enhances precision in patient care, and demands flexibility to combat complacency and gain a true competitive edge.
The Future of AI-Powered Analytics - What You’ll Learn Inside:
- Agentic AI's potential to evolve pharma processes, from drug discovery to market engagement, through autonomous operation.
- The urgent need to harness real-world evidence and integrate diverse data sets to stay ahead of payers and physicians in understanding drug performance.
- Overcoming regulatory and cultural barriers requires shifting to agile methodologies and fostering trust in AI to unleash workforce productivity and drive meaningful change.
Actionable Insights - Why You Need to Read This Report:
- Uncover hidden differences between pharma analytics and other industries that could be holding back your AI adoption—and how to break free from them.
- Explore a game-changing shift in clinical trials and drug discovery that might slash validation times dramatically, but only if you navigate the pitfalls first.
- Dive into the exploding role of real-world data that's flipping traditional models upside down, potentially leaving unprepared companies in the dust.
- Learn why personalized medicine's deepest mysteries could soon be solved, transforming how you look at patient populations and design product pipelines.
- Discover the secrets to building trustworthy AI agents in healthcare, including real-world examples that could redefine evidence generation and physician trust.
FAQs
Pharma's heavy regulatory environment, including quality standards such as “Good Manufacturing Practice,” “Good Clinical Practice,” and “Good Laboratory Practice,” all create extensive documentation burdens and slows innovation, unlike less constrained sectors. This leads to a culture where long delays are normalized. AI and agentic AI can redefine those norms without sacrificing compliance.
AI agents could automate communications between life sciences companies and regulators, moving away from legacy tools like Word documents to streamline submissions, reduce documentation reviews, and overhaul approvals for faster outcomes.
RWE is exploding with real-time data on millions of patients, potentially giving payers and physicians more insights into drug performance than pharma companies themselves. This will require firms to be proactive with integrating RWE, rather than reactive, to avoid disruptions in traditional models.
AI can analyze vast datasets to uncover why drugs work differently in patients by considering complex biological interactions. This could inform better pipeline development, clinical designs, and targeted market positioning.
Abandon rigid project management for agile methodologies, address the 20% trapped productivity from underused tools, and link AI initiatives to personal pain points to overcome adaptation hurdles and foster continuous experimentation.

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