Computationally designed novel therapeutic proteins
Novel protein therapeutics have the potential to be very valuable. but there are literally no established computational tools to explore or design them (whereas small molecules do). However, by going beyond typical proteomic space (e.g. whats in nature) we can create therapeutics that are more stable, specific and potent. Allowing us to functionally interact with diseases that are traditionally undruggable such as those driven by intracellular protein-protein interactions.
In working with 3 of the top 25 pharma companies we have helped them find drug like candidates for diseases which they had previously found to be intractable. We work on drug candidates that no other computational company would help design. Despite the fact that non-canonical amino acids and chemical modifications (as well as radioligands and peptide-drug-conjugates) are proving their potential to address huge unmet needs (e.g. Trulicity or Semiglutide). We need computational tools to built to help explore that chemical space.
Yes we have 5 collaborations including 3 with top 25 pharma companies. AstraZeneca and Daiichi Sankyo are two disclosed partners. We are inventing new technologies. The partnerships provide valuable validation that the technology works and that are scientific hypothesis was even possible. Including direct competition with other startups and internal teams showing our superiority.