We have grown and advanced a rich portfolio of programs through both internal and partnered programs in which Cyclica owns all or a portion of the underlying IP. Our current focus spans both low and high data protein targets (including mutant targets) with a focus on oncology and CNS diseases.
OUR APPROACH
We’ve built the only platform that is powered by a single model for the entire proteome. This opens a large and unconstrained protein universe of exciting and unexplored opportunities. Unlike industry standard, we are not confined solely to high data protein targets.
Positioned to scale, our process allows Cyclica’s drug discovery team to move at pace and volume.
Two ever evolving machine-learning engines underly our platform: MatchMaker™ and POEM™.
MatchMaker™, Cyclica’s core differentiator, is an AI-enabled deep learning engine that predicts the polypharmacology of small molecules as the foundation for small molecule drug discovery. It is able to generalize across the proteome and uses both AlphaFold2 structures and homology models.
POEM™ (Pareto Optimal Embedding Model) is a unique similarity-based property prediction model. In contrast to other AI prediction models, POEM uses multiple types of molecular fingerprints to describe molecules, providing a much richer measure of similarity that leads to greater accuracy.
By exploring the unexplored and drugging the undrugged, we’re on a mission to positively impact patient health. Work with us on discovering the medicines of tomorrow.
