A London-headquartered artificial-intelligence company developing medicines has raised $140m in a Series C financing round, in a significant investment for the capital’s life-sciences and AI sector.
Basecamp Research said the oversubscribed round will fund the next generation of its EDEN biological foundation models and support a pipeline of AI-designed treatments as it moves towards clinical development. The company is headquartered in London and has offices and laboratories in Cambridge, Massachusetts.
Funding for biological AI
The financing was led by S32. Basecamp Research said the investor group also included NVIDIA, Menlo Ventures’ Anthology Fund, Catalio Capital Management, the NATO Innovation Fund, Redalpine, The Rockefeller Foundation and other backers. Andy Conrad, a general partner at S32 and a former chief executive of Verily, is joining the company’s board.
For London, the deal is a sizeable example of investment flowing into businesses that combine machine learning with experimental biology. Such companies aim to use computing to shorten stages of scientific discovery, although a financing round is not proof that a prospective medicine will work in people or secure regulatory approval.
Basecamp Research was founded in 2019. Its approach centres on a proprietary genomic dataset, the Trillion Gene Atlas, which it says has been assembled through access and benefit-sharing partnerships in more than 30 countries. The company uses that data to train EDEN, a family of models intended to identify patterns in biology and generate possible therapeutic candidates from information about disease.
From models to potential treatments
The company’s initial therapeutic focus is in vivo cell therapy: altering or reprogramming cells inside a patient’s body rather than removing cells for modification and reinfusion. It says that pairing its models with large serine recombinases could allow long and complex DNA sequences to be integrated precisely into the genome.
That is an ambitious scientific proposition rather than a clinical result. Basecamp Research says it has produced preclinical findings across several therapeutic modalities and disease areas, but it has not set out a timetable for clinical trials. Preclinical evidence, usually generated in laboratory or animal studies, does not establish safety or effectiveness in patients.
The company says its platform could have applications in cancer and autoimmune disease, where existing cell therapies can involve complex manufacturing and high costs. Its stated aim is to make treatments more sophisticated, more customisable and simpler to administer. Whether those objectives can be realised will depend on further research, clinical testing and assessment by regulators.
A London role in a competitive field
AI has become an increasingly prominent tool in drug discovery, helping researchers examine biological data and prioritise molecules for laboratory work. The harder task is translating promising computational designs into treatments that can be manufactured reliably and shown to be safe and effective. Basecamp Research is seeking to operate across both stages, using its models while also advancing its own therapeutic programmes.
The new capital is also intended to expand pharmaceutical partnerships. To support that effort, the business has appointed Richard Pearce, formerly of Biogen, as chief business officer. The appointment signals that the company is pursuing collaborations alongside development of its internal pipeline.
The funding gives a London-based business greater resources to train computational models and undertake the costly work needed to take candidates towards human studies. It also underlines why investors are watching the intersection of AI, genomics and cell therapy closely: the opportunity is substantial, but the technical, clinical and regulatory hurdles remain high.
For the capital’s technology ecosystem, the round is a reminder that AI investment is not confined to general-purpose software. London’s research, finance and life-sciences networks are increasingly being drawn together by companies trying to apply advanced computing to fundamental scientific problems. The ultimate value of this investment, however, will be determined not by the size of the round alone, but by the quality of the evidence generated as the programmes progress.
