Big Picture Bio emerges from stealth with €2.55M Pre-Seed to find cancer drug combinations by simulation

Big Picture Bio (London) has emerged from stealth with a €2.55 million Pre-Seed round co-led by Kadmos Capital and Exceptional Ventures, with additional participation from Gloucester Ventures and angel investor John White. The company also received a £700,000 (approximately €815,000) non-dilutive grant from Innovate UK's Investor Partnerships Programme alongside the equity raise, bringing total funding to approximately €2.55 million (£2.2 million equivalent). Founded by Dr. Kerstin Papenfuss (CEO) and Dr. Mark Hammond (CTO), both former members of Deep Science Ventures, the company is building a generative AI system designed to identify optimal cancer drug combinations.

The core technology is described as a generative "world model" — a simulation that models the interactions between tumour cells, immune cells, and the surrounding tissue environment, and searches computationally for drug-dose combinations that are most likely to produce a therapeutic response. The company claims that a full pairwise screen of 100 drugs at 100 doses would require approximately 50 million laboratory experiments; its model can search the same space in seconds. Big Picture Bio further claims to have correctly forecast the failure of Regeneron's fianlimab trial and posted 12 correct predictions out of 14 at ASCO 2026.

The arithmetic of combination therapy

Cancer combination therapy has been one of oncology's most productive strategies — many of the most effective current treatments, from HIV-era drug cocktails to modern immune checkpoint inhibitor combinations, work because multiple mechanisms inhibit the disease simultaneously. The problem is that the combinatorial space grows faster than any laboratory programme can explore. Two drugs at 10 dose levels each produce 100 combinations; ten drugs at 10 dose levels each produce 10 billion.

Most clinical-stage combination research uses a narrow prior — two drugs with overlapping but non-identical mechanisms, at doses established by single-agent trials — because the space is too large to screen systematically. The result is that a large fraction of potentially effective combinations is never tested. An accurate computational model that can predict which combinations are most likely to work, and which are likely to be toxic, would change the economics of that search.

Papenfuss: "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."

Deep Science Ventures provenance

Deep Science Ventures is a London-based company builder that creates companies from scientific first principles — backing founders who start from a scientific hypothesis rather than a market gap. Dr. Hammond co-founded DSV and grew it from approximately €174,000 to a portfolio valued at over €1.16 billion; Dr. Papenfuss led its therapeutics team. The spinout carries the methodological discipline of a programme that has built several credible biotechs from scratch, which is a different risk profile from a software company with a biology team.

The Innovate UK grant — through the Investor Partnerships Programme, which co-invests non-dilutive funding alongside qualifying private investors — adds institutional credibility and extends the company's runway without additional equity dilution. Kadmos Capital is a London-based deep-tech fund; Exceptional Ventures focuses on pre-seed and seed-stage technology in the UK.

The €1.75 million equity component (£1.5 million) plus non-dilutive grant positions Big Picture Bio to move its top predictions from model into wet-lab validation over the next 12-18 months. The predictions track record is the company's most concrete asset at this stage; wet-lab confirmation at a meaningful hit rate is what converts that track record into a Series A thesis.