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Introducing the Models & Molecules podcast

Drug discovery is entering a period of profound transformation, driven by an explosion in data generation, advanced automation, and the game-changing power of artificial intelligence. To explore this new frontier, we’re launching Models & Molecules, a new interview series about the innovation at the intersection of biology and computational science.

Join host Nicola Bonzanni, ENPICOM’s founder and CEO, in conversations with leading scientific and industry experts about learning points and innovations shaping the future of drug discovery.

Candid conversations on AI, biology, and beyond

We’ve always believed that computational biology, and more broadly software, will define the next era of drug discovery. From our vantage point, we now see that transformation underway: across the industry, from small biotechs to global pharmaceutical organizations, teams are learning to think natively in a world where computation and biology are inseparable.

What can you expect from the series? Open, candid conversations where Nicola sits down with R&D leaders and scientists who are driving this change. Tune in for:

  • Honest takes on what’s worked in drug discovery R&D, what hasn’t, and why
  • “Off-script” reflections on emerging trends, career turns, and lessons learned
  • Perspectives on the breakthroughs and technologies shaping the future of the field

Whether you’re leading a global R&D organization, managing a research team, or working at the bench, join us as we reflect, draw inspiration, and explore the future of drug discovery.

Episode 1: A conversation with René Hoet

We couldn’t be more excited about our first guest, René Hoet, a distinguished biologics R&D leader with over 35 years of extensive experience at companies like Bayer and FairJourney Biologics.

In this premiere episode, we discuss:

  • How Big Pharma and small biotechs approach innovation differently
  • How combining phenotypic and targeted approaches can enhance drug discovery
  • The role of AI in drug discovery and why the industry needs a cultural shift for AI to truly transform science
  • The challenges and rewards of making the leap from academia to industry

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