Models & Molecules

In this special in-person episode, recorded in San Diego, we sit down with Melody Shahsavarian, Senior Director of Data Strategy and Digital Transformation at Eli Lilly. Before Lilly, she led NGS and AI for biologics discovery at Sanofi, where she moved from antibody discovery researchinto the data and digital side of biologics R&D.

Melody discusses the role of agentic AI in pharma R&D: why scientists have adopted it so readily, where deterministic automation ends and agents begin, and what validation and governance should look like. She makes the case for specialized agents with deep domain context, and closes with her contrarian take: not every problem needs an agent.

In this episode, we sit down with Iddo Weiner, co-founder and CSO of Converge Bio, to discuss the evolving biotech and AI landscape: where models, data, and scale actually create advantage, why delivering AI services calls for a customer-centric approach, and how openness pays off for scientists and businesses alike.

When an AI model generates an image, you can tell at a glance whether it's any good. In life sciences, that feedback loop is fragmented across data, modelling, experiments, and the clinic, and signal gets lost at every handoff. In this episode, we sit down with Talip Uçar, founding member of Boltz, to discuss why data is the real competitive advantage, why pharma needs a tech-first mindset to make AI work, and why a unified data fabric remains the field's missing layer.

Watch the full conversation and read the transcript → https://enpicom.com/models-molecules/talip-ucar-inside-boltzs-open-source-bet-on-the-future-of-ai-driven-drug-discovery/

Generative models can now propose novel antibody sequences from antigen structure alone, but how far does that actually get you? In this episode, we sit down with Principal Scientist Steve Comeau to discuss what current models can realistically deliver, where the data falls short, and why the harder problems are still ahead of us.

Read the full conversation: ⁠⁠https://enpicom.com/models-molecules/steve-comeau-from-novel-binder-design-to-the-realities-of-ai-in-complex-therapeutics/

Jiwon Kim, Product Lead at AWS AI Life Sciences, joins Models & Molecules to break down pharma’s digital shift: where cloud and software are becoming core infrastructure for modern drug discovery.

We touch upon the potential of agentic AI, why zero-shot models are the future, why lab in the loop is the essential bridge for getting there.

Read the full conversation: ⁠https://enpicom.com/models-molecules/jiwon-kim-from-lab-in-the-loop-to-zero-shot-the-role-of-cloud-and-ai-agents/

In this episode of Models & Molecules, Do Soon Kim, Head of Product at Xaira Therapeutics, discusses his journey in the biotech and AI sectors, emphasizing the importance of effective communication in fostering collaboration between different scientific disciplines. The conversation explores the potential of machine learning to reshape our understanding of intelligence and moving beyond the limits of human intuition to decode complex biology.

Read the full interview: https://enpicom.com/models-molecules/do-soon-kim-navigating-the-convergence-of-tech-and-pharma/

In this episode of Models & Molecules, Jaap Goudsmit, MD, PhD, immunologist, epidemiologist, and one of the scientific forces behind Crucell, the Dutch biotech acquired by Johnson & Johnson, explores the critical evolution of antibody research. Jaap reflects on the journey from traditional discovery to the complexities of modern drug development, highlighting the transformative role of AI and why high-quality training data is essential for the next generation of therapeutics.

Read the full conversation: https://enpicom.com/models-molecules/jaap-goudsmit-from-rabies-to-covid-antibody-discovery-in-the-age-of-ai/

In this episode of Models & Molecules, René Hoet reflects on game-changing technologies like phenotypic screening, the unique innovation dynamics of small biotechs versus large pharma, and the real-world impact of AI in antibody discovery. We touch upon bridging academia and industry and discuss why taking calculated risks is essential for the next breakthroughs in drug discovery.

Read the full conversation here.