Inductive Bio secured first place in the OpenADMET-ExpansionRx blind challenge by developing Beacon models that excelled in predicting ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) properties. The competition attracted over 370 submissions from participants representing pharmaceutical companies, biotechnology firms, academic institutions, and artificial intelligence organizations. The challenge utilized real-world datasets to evaluate the accuracy and robustness of predictive models.
The OpenADMET-ExpansionRx challenge was conducted in collaboration with Expansion Therapeutics and aimed to advance computational methods for drug property prediction. Inductive Bio’s achievement highlights the growing role of machine learning in improving the drug discovery process by providing reliable predictions of key pharmacokinetic and toxicity parameters.
**Why this matters**
Accurate ADMET predictions are critical for identifying potential drug candidates with favorable safety and efficacy profiles early in development. Success in large-scale challenges like OpenADMET demonstrates the potential of AI-driven models to streamline drug discovery, reduce costs, and minimize late-stage failures in pharmaceutical research.
Source: NewsData