Bringing together industry practitioners, quality leaders, regulators, and technology experts, the Summit focuses on moving beyond hype to practical, compliant, and sustainable AI implementation across GxP environments.
Two featured voices—Frank Henrichmann, International Program Committee Member, and Nikolai Makaranka, CEO of Daikon AI and planned Summit speaker—offer a compelling preview of what attendees can expect: real-world experience, objective measurement, and actionable guidance for deploying AI responsibly in regulated life sciences.
AI as a Defining Industry Shift—With Compliance at the Core
Frank Henrichmann, International Program Committee Member, frames AI not as a passing trend, but as a once-in-a-generation transformation—on par with the introduction of computers or the smartphone. In his view, the life sciences industry is standing at a clear inflection point: there is a before AI and an after AI.
What makes this Summit distinct is its focus on how AI can be implemented in a compliant way, ensuring patient safety while enabling the industry to become more effective and efficient. Rather than theoretical discussions, the event emphasizes practical learning grounded in experience.
A key strength of the Summit is its diversity of perspectives. Alongside experts from within the ISPE community, participants will hear from other industries that have adopted AI more rapidly. These sectors have already navigated their “trial-and-error” phases, providing valuable lessons that life sciences organizations can leverage—without repeating the same mistakes.
Importantly, the agenda reflects the realities of regulated operations. Approximately 80% of the content is focused on GxP topics, but the scope goes well beyond GMP alone. Sessions will span:
- Clinical operations
- Drug safety and pharmacovigilance
- Laboratory environments
- Validation approaches across GxP systems
Henrichmann also highlights a critical theme: using AI to validate AI—exploring how advanced tools can support more effective, risk-based system validation across regulated domains. The ultimate goal is clear: enable innovation in a way that stands up to regulatory scrutiny and builds confidence with inspectors and quality teams alike.
Reducing AI Failure Rates Through Objective Measurement
While AI offers enormous potential, Nikolai Makaranka, CEO of Daikon AI, brings a sobering data point into focus ahead of his presentation, “2026 ISPE AI in Life Sciences Summit: Practical Guide to Measuring Large Language Models (LLMs)”: more than 90% of AI projects fail, a statistic that is particularly concerning for the pharmaceutical industry. The root causes, he argues, are familiar—overpromising and a lack of rigor in testing, evaluation, and ongoing monitoring.
His session tackles one of the most pressing questions facing regulated organizations today: How do you come something as powerful—and as unpredictable—as AI be effectively brought into a GxP environment?
Rather than relying on intuition or “gut feel,” Makaranka’s presentation dives into practical, objective methods for measuring the performance of large language models (LLMs) and AI agents. Attendees will learn how to:
- Define meaningful performance metrics for models and agents
- Test AI systems against realistic, production-like data
- Monitor model behavior over time to detect drift and degradation
- Generate evidence of control that satisfies regulators and quality organizations
Crucially, this session is not about selling AI’s transformative potential. It assumes the audience already believes in the technology. Instead, it focuses on execution—how to bring AI into production, keep it working reliably with real-world data, and demonstrate ongoing compliance.
For professionals responsible for validation, quality, IT, and regulatory readiness, this session provides a concrete framework for reducing risk while unlocking AI’s benefits.
Why These Sessions—and This Summit—Matter Together
The perspectives of Henrichmann and Makaranka converge around a shared message:
- AI adoption in life sciences is inevitable—but how it is implemented determines success or failure
- Compliance, validation, and measurement are not barriers to innovation; they are enablers of scale and trust
- Objective evidence, not enthusiasm, is what regulators and quality teams ultimately require
Together, these insights exemplify the broader value of the 2026 ISPE AI in Life Sciences Summit — Powered by GAMP: delivering practical, experience-driven guidance for organizations looking to operationalize AI responsibly in regulated environments.
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