AI Strategies - L&L with Remco Jan Geukes Foppen

The traditional model of drug discovery and development has reached a point of diminishing returns, characterized by stubbornly low success rates, exorbitant costs, and protracted timelines. For decades, the industry has operated within a linear, resource-intensive framework, resulting in a systemic stagnation of productivity. However, a profound paradigm shift is underway, driven by the transformative power of Artificial Intelligence (AI). This report argues that AI is moving beyond a theoretical tool to become a practical, proven engine for accelerating the delivery of life-saving therapies.

The core value proposition of AI is not merely in its ability to reduce costs or expedite processes, but in its capacity to fundamentally increase the Probability of Success (PoS) for drug candidates. By leveraging advanced modalities such as Multimodal AI, which integrates diverse data sources—from genomic and clinical to chemical and imaging data—AI systems can identify hidden patterns and generate more robust and reliable drug candidates. This integrated, holistic approach is already yielding demonstrable results, with AI-driven programs achieving record-breaking discovery timelines and a significant increase in early-stage clinical PoS.

However, this revolution is not without its challenges. The inherent risks of AI, particularly the "insidious" problem of hallucinations, necessitate a strategic and transparent approach. The report highlights the critical role of Explainable AI (xAI) as a foundational tool for building trust among stakeholders and navigating the complex regulatory landscape. Ultimately, the successful future of AI in the pharmaceutical sector depends on a nuanced understanding of its capabilities and limitations, a commitment to collaboration, and a strategic investment in platforms that can generate de-risked portfolios. The path forward is one of augmented intelligence, where human expertise is amplified by AI to fulfill the ultimate mission of delivering more effective treatments to patients with unprecedented speed and confidence.

Making sense of AI: bias, trust and transparency in pharma R&D. Marcella Zucca, Vincenzo Gioia, Alessio Zoccoli, Remco Jan Geukes Foppen (2025). A Featured Article in Drug Target Review.

https://www.drugtargetreview.com/article/183358/making-sense-of-ai-bias-trust-and-transparency-in-pharma-rd/

Methodology for Safe and Secure AI in Diabetes Management in Journal of Diabetes Science and Technology, 19, 620–627. (2025). Geukes Foppen, Remco Jan; Gioia, Vincenzo; Gupta, Shreya; Johnson, Curtis; Giantsidis, John; Papademetris, Maria

https://pmc.ncbi.nlm.nih.gov/articles/PMC11672366/