UK

London-Based Big Picture Bio Secures €2.55 Mn for AI-Driven Cancer Drug Development

Sep 19, 2026 | By Oliver Bennett

London-Based Big Picture Bio Secures €2.55 Mn for AI-Driven Cancer Drug Development

London-based BioTech startup Big Picture Bio has come out of stealth mode with a total funding of €2.55 million (£2.2 million). The company is developing AI-designed combination treatments for cancer and other complex diseases.

SUMMARY

  • Big Picture Bio has emerged from stealth with €2.55 million (£2.2 million) in total funding.
  • The London-based BioTech startup is developing AI-designed combination therapies for cancer and complex diseases.
  • Big Picture Bio combines AI modelling and laboratory testing to identify promising drug combinations.

The funding includes a €1.75 million (£1.5 million) pre-Seed round, co-led by Kadmos Capital and Exceptional Ventures. Gloucester Ventures and angel investor John White also participated in the round.

Big Picture Bio also received €815,000 (£700,000) in non-dilutive funding through Innovate UK’s Investor Partnerships Programme. The company will use the funding to support the development of its AI-based approach to combination therapies.

Dr Kerstin Papenfuss, CEO and co-founder, Big Picture Bio, said: “Cancer is not one disease driven by one target, but we still develop drugs as if it were. Combinations are how we beat it – and with more than 900 billion of them possible, no lab on earth can test its way to the right ones. That is
the problem we built Big Picture Bio to solve: model the disease as the dynamic system it actually is,then design against it – combinations chosen because they are most likely to work in patients, not because they were the ones we could get to. This funding takes our first designed combinations out of the model and into the lab.”

Dom Falcao, Founder of Deep Science Ventures, added: "For a decade, Mark and Kerstin have steered DSV through the creation of a slew of extremely exciting companies solving precisely these kinds of complex diseases, including Neobe, Cureage and Kindling, and almost every company they have built is on track to make it into the clinic. Instilling that experience and expertise into a model that moves beyond the bleeding edge in AI to solve complex diseases at scale is a natural evolution of the methodology for building advanced therapeutics companies at DSV. It's been the greatest privilege of my career to build DSV alongside Mark and Kerstin, and I am so glad DSV can be a part of the next phase of their journey."

Remy Kesrouani, Managing Partner, Kadmos Capital, said: “I had the privilege of working closely with Kerstin and Mark at the very beginning of Deep Science Ventures, and saw first-hand the determination, conviction and sheer resolve they bring to building ambitious, scalable businesses. Big Picture Bio is the culmination of that journey, applying a genuinely differentiated approach to AI to one of drug development’s hardest problems: predicting how complex clinical trials will actually behave.”

Paolo Pio, Co-Founder and General Partner, Exceptional Ventures, commented: "Big Picture Bio is going after a problem at the heart of modern oncology - how to identify the right combination therapies faster and with greater confidence. We believe the team has the scientific depth, technical ambition, and commercial focus to build something genuinely important - a platform that can deliver value to partners today while laying the foundation for the next generation of cancer therapies. We are proud to co-lead the round along with Kadmos and support the company's next stage of growth."

Big Picture Bio is developing AI-designed combination treatments for cancer and other complex diseases. Its AI technology is built to understand how tumours, immune cells, and nearby tissues interact. This helps the company find and improve promising drug combinations before they are tested in patients.

The company combines AI-based modelling with laboratory testing to identify effective treatment options. Big Picture Bio aims to reduce the traditional trial-and-error approach to combination therapies and eventually use AI to help design new treatments from the beginning.

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