Big Picture Bio Ltd., has been founded to identify, design and optimise promising cancer combination therapies, using a generative world model to understand how tumours, immune cells and surrounding tissue interact across disease sites and patient subgroups.
By combining AI-driven modelling with targeted wet lab validation, the company aims to address one of oncology’s most challenging drug discovery problems – identifying combinations with a greater likelihood of working in patients.
The company has closed a £1.5m pre-seed funding round, co-led by Kadmos Capital and Exceptional Ventures with participation from Gloucester Ventures and angel investor John White. The pre-seed funding is in addition to £700,000 in non-dilutive funding received from Innovate UK through its Investor Partnerships Programme. Together, the funding provides £2.2m to support Big Picture Bio as it takes its first designed drug combinations from in silico design into wet lab validation.
A key test of Big Picture Bio’s combination-design approach is whether it can predict how treatments will perform in patients. The company’s platform has been validated against real-world clinical outcomes presented at ASCO, as well as correctly predicting the failure of Regeneron’s recent fianlimab trial. Rather than positioning clinical prediction as the end product, Big Picture Bio uses the validation to test whether its models are identifying combinations with potential for clinical impact. The model reasons from the ground up, so its predictions are explainable and can be traced back to the underlying biology.
Big Picture Bio was founded by Kerstin Papenfuss, CEO and co-founder, and Mark Hammond, CTO and co-founder, bringing extensive experience across drug discovery, venture creation and AI-enabled scientific discovery. Kerstin previously served as Director of Pharma at Deep Science Ventures (DSV), where she founded 12 therapeutics and enabling-technology companies, while Mark co-founded DSV and led its engineering work in agentic scientific discovery.
Papenfuss 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 900bn 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.”