Charles River, Related Sciences team up for AI-driven drug discovery
Charles River Laboratories International, Inc. (NYSE: CRL) and Related Sciences have announced a multi-program collaboration valued at an undisclosed amount to deploy Logica, an AI-powered drug solution, across several previously undrugged targets. This initiative aims to discover new medicines that address key unmet needs in a variety of disease areas, including cancer immunotherapy, autoimmunity, and inflammatory diseases.
Leaders Comment on the Potentials of the Collaboration
“Partnering with the team at Related Sciences, we are excited to deploy Logica in the hunt for first-in-class therapeutics,” said Julie Frearson, PhD, Senior Vice President and Chief Scientific Officer at Charles River.
Adam Kolom, Founder and CEO of Related Sciences, also stated, “Logica’s combination of advanced AI/ML and state-of-the-art hit finding approaches, within a unique risk-sharing business model, pairs beautifully with Related Sciences’ data science-driven, multi-technology approach to drug discovery.”
Logica: Revolutionizing the Drug Discovery Process
Logica is an advanced AI-driven solution that leverages predictive models, chemical design, DNA-encoded libraries, and in silico high throughput screening. The platform combines Charles River’s preclinical expertise and Valo Health’s AI technology, aiming to transform the traditional drug discovery process. According to Charles River, Logica has the ability to accelerate the drug development timeline from target identification to candidate selection in just over two years.
Previous Collaborations and Future Goals
In 2022, Charles River and Valo Health initially launched Logica, offering a fully managed, risk-sharing model to clients. Last year, Charles River also announced a collaboration with Flagship’s Pioneering Medicines to apply Logica in the discovery of optimized small molecules for novel therapies in unmet medical needs. This new multi-program collaboration with Related Sciences marks another significant step in the use of AI-driven technologies for drug discovery and development.