Exogene, a startup based in Oxford, UK, is developing an AI-based platform to identify target-specific TCRs and enable the development of TCR-based cell therapies. Exogene sequences millions of TCRs from patient and donor-derived T cells and uses its technology to comprehensively screen these natural TCR repertoires and identify rare, potent TCRs against targets of interest.
To identify TCRs, Exogene has developed AI that uses the protein sequences of millions of receptors and potential targets to predict interacting TCR–target pairs. The AI solves the scalability problem that is at the heart of ‘why finding TCRs is hard’ using current wet-lab technology.
“With AI, you can screen billions of TCRs in a matter of seconds. That means you have much higher chances of finding a potent cancer-targeting TCR because you cast a much wider net, and you can do it much faster and at a much lower cost than with any other platform,” said Federico Paoletti, CEO and co-founder of Exogene.
Exogene’s deployment of AI differentiates it from conventional TCR biotech companies, which mostly rely on wet-lab technologies that lack the speed and scalability of the computing-enabled approach. Other companies have also identified AI as the way to perform comprehensive, scalable screening of TCRs but they often lack Exogene’s in-house, high-throughput data generation capabilities.
Using novel high-throughput display technologies coupled with deep sequencing, Exogene tests TCRs identified by its AI in the laboratory. Exogene can generate functional data for up to 100 million TCR-target pairs during each lab testing step. The display libraries are deep sequenced and the results are then fed back into the AI, creating a virtuous cycle that continually improves the output of the AI (Fig. 2). Laboratory testing also enables Exogene to determine which TCRs to advance for use in T cell therapies.