The funds will support expanding Valence's artificial intelligence (AI)-based generative chemistry engine, scaling its partnerships with discovery organizations, and advancing internal drug discovery efforts, the company said.

The company has developed proprietary AI technologies for low/no data drug design, including techniques for few-shot learning, graph-based molecular representation learning, structure and ligand-based de novo design, and chemical reaction prediction. These technologies have been featured in journals and conferences such as Neural Information Processing Systems, the International Conference on Machine Learning, and the International Conference on Learning Representations.

Valence has integrated its techniques into a chemistry engine that is capable of rapid end-to-end design of novel chemical matter optimized for complex property profiles against challenging disease targets, according to the company. It is deploying its engine across multiple target classes and indications through drug design collaborations with biotech and pharmaceutical companies, contract research organizations, and academic centers, including Charles River Laboratories, Repare Therapeutics, and Servier.

The firm will expand its team across multiple functions, including medicinal and computational chemistry, biology, machine learning, and software engineering to support further development of its generative chemistry engine to better accommodate emerging modalities such as degraders, molecular glues, and protein-protein interactions, it said.