Generative AI

In the future of AI-driven biopharma, reusable data is the most undervalued asset.

In this episode of Denatured, you’ll hear from Jason Jones, head of global business development at Cellular Origins and Alexander Seyf, founder & CEO of Autolomous. They discuss how the push to scale cell and gene therapy manufacturing is accelerating interest in automation, digitization, robotics and deeper collaboration across the ecosystem.

As cell and gene therapy developers face rising pressure to produce therapies faster and at lower cost, the industry is leaning on robotics, digital systems and partnerships to bridge the gap between innovation and delivery.

Anthropic in October last year iterated its Claude AI model to better cater to biopharma purposes. Sanofi, Novo Nordisk, AbbVie and others already use Claude in their operations.

The recent uptick in IPOs is an encouraging signal after a drought for much of 2025. Experts point to AI as a driving force behind this resurgence.

The Insilico Medicine agreement plays into Eli Lilly’s recent AI push, anchored by a partnership last year with NVIDIA to build a supercomputer to optimize drug discovery and shorten the development timeline.

Earendil Labs’ AI-centered platform has produced more than 40 programs, including anti-inflammatory assets that have attracted a pair of partnership agreements with Sanofi.

In this episode of Denatured, you’ll listen to Viswa Colluru, CEO and founder of Enveda and Akshay Rai, principal, Healthcare & Biotech Investments at Premji Invest. We speak about how AI platforms must now prove themselves through proprietary data, focused pipelines and clinical readouts in competitive diseases to garner investor interest.

In a highly competitive space, AI platforms must now prove themselves through proprietary data, focused pipelines and clinical readouts in competitive diseases. Promises of faster, cheaper drug discovery are not enough to entice strong investor engagement.

Single-trial approvals are raising the bar on trial design and execution. The new paradigm is pushing sponsors to plan earlier, step up their data and risk‑based quality management and use modeling and AI to generate one compelling, regulator‑ready evidence package.