Etcembly, a revolutionary biotech company that uses machine learning to identify and predict the effectiveness of future immune therapies, has agreed a partnership with leading Norwegian firm Zelluna to engineer T-cell receptors (TCRs) from Zelluna’s pipeline against an undisclosed cancer target.
Etcembly notes the commercial agreement will involve Etcembly engineering Zelluna’s TCR candidates and Zelluna developing these further through comprehensive preclinical assessments and beyond into development.
The Oxford-based business will incorporate “hundreds of millions of data points” to rigorously test molecular adaptations within a quarter of the time it typically takes using traditional methods.
It is hoped the deal will help in the development of future treatments for a variety of cancers.
Etcembly CEO Dr Michelle Teng said the agreement could be a major turning point for discovering new immunotherapies for the disease.
“This partnership agreement with Zelluna represents a huge step forward for the research and development of new cancer treatments,” she said.
“We aim to drastically compress preclinical timelines and provide solid validation for clinical candidates by delivering evidence for TCR efficacy and safety.
“We very much look forward to working with Zelluna to help speed up pre-clinical research in the race to find new cancer treatments.”
The deal will involve Etcembly testing and optimising Zelluna TCR candidates over the next 12 months.
The Norwegian business hopes the move will help to develop optimised TCR-guided natural killer cell therapies for multiple solid cancers.
As one of the only companies in the world to incorporate machine learning into its molecular testing, Dr Teng added that Etcembly’s approach to combining machine learning with gene therapy could save the pharma industry “years of testing and millions of pounds”.
Dr Teng also believes the deal with Zelluna could help to accelerate the wider adoption of machine learning technologies across the sector.
“The benefits are too great to ignore,” she said. “The latest technologies, combined with the data points we now have available, makes it an invaluable tool to rapidly increase turnaround in the development of new therapies.
“As machine learning gathers momentum, it will no doubt become a staple for pharmaceutical companies in the future.
“Already, we are pushing the frontiers to explore the intersection between immunology and machine learning, which has the potential to transform the sector in the coming years.”