Oxford Drug Design, a biotechnology company with a proprietary computational and machine learning platform, has raised £2.2 million in funding.

A spinout of Oxford University, ODD has been at the forefront of computer-aided drug design with its dual-track AI proprietary platform for drug discovery. 

The company has recently entered an oncology expansion phase, capturing molecular and biological features which enable machine learning models with increased predictive power and accuracy of molecule selection. 

The company is currently focused on unmet therapeutic needs in oncology, initially against lung and colorectal cancers.

The funding comes from existing investors ACF Investors, o2h Ventures, Meltwind Advisory, a number of returning angels and new investors and the US-based R42 Group. It takes the firm’s total amount of grant and equity funding to over £10m.

This growth capital will enable ODD to further its drug research and discovery starting with a proof-of-concept study to validate its pioneering, innovative approach against cancer. It will also establish a new commercial offering of its proprietary AI platform to pharmaceutical and biotechnology companies. 

OOD’s validated platform is in increasing demand from third parties in the pharmaceutical space and is already generating revenue separately from the company’s direct work in oncology drug discovery. The investment will also go towards operational purposes and further expansion ahead of a Series A investment round this year. 

My wife’s cancer showed need to give patients control

Alan D. Roth, CEO of Oxford Drug Design, said: “We are excited to be playing a pivotal role in the innovation of oncological treatments leading to better outcomes for cancer patients worldwide. 

“Our groundbreaking new approach stands to be initially validated by the proof-of-concept studies. We are achieving rapid progress not only with our industry-leading drug discovery programme, but also our proprietary AI platform. 

“This has led to increasing interest from third parties in our machine learning capabilities, so we are keen to capitalise on this demand and establish a commercial effort in this area.”