Charles River and Related Sciences partner for AI drug platform
15 Sep 2023
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Source: Pharmaceutical Technology
The new medicines will be used to meet unmet requirements across a range of disease areas. Credit: Steve Buissinne from Pixabay.
Charles River Laboratories International has signed a multi-programme collaboration agreement with Related Sciences (RS) for the artificial intelligence (AI)-powered drug platform, Logica.
Last year, Charles River and Valo Health unveiled Logica, a solution that leverages the AI-powered Valo Opal Computational Platform, along with Charles River’s preclinical expertise.
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Logica will be used on multiple previously undrugged targets within the RS portfolio.
RS will collaborate with the teams from both Charles River and Valo Health to deploy Logica to discover significant new medicines.
These medicines will be used to meet unmet requirements across disease areas including autoimmunity, cancer immunotherapy and inflammatory diseases.
Charles River senior vice-president and chief scientific officer Julie Frearson stated: “Logica’s unique platform, which combines AI/machine learning (ML)-enabled in silico discovery, high-powered DNA-encoded libraries and traditional screening techniques, has the capability to accelerate the drug discovery and development pipeline, transforming a target to a candidate in just over two years.”
Logica uses predictive models, synthesis capabilities, chemical design, DNA-encoded libraries and in silico high throughput screening from Valo’s Opal Computational Platform, along with Charles River’s capabilities in all discovery optimisation aspects.
These aspects include medicinal chemistry, absorption, distribution, metabolism and excretion, biology, pharmacology and high throughput screening. These elements combine to create a computation-powered, unified target-to-candidate offering.
Related Sciences founder and CEO Adam Kolom 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.”
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