Simulations Plus, Inc. , a leading provider of modeling and simulation solutions for the pharmaceutical and biotechnology industries, announced the release of ADMET Predictor® 11, its flagship machine learning modeling platform.
The latest version of ADMET Predictor includes:
- New industry partner data that more than doubles the number of ionization constants (pKa), leading to enhanced predictive accuracy and wider applicability of our S+pKa model
- New functionality to perform 3D virtual screening based on shape and pharmacophore-feature similarity
- New CYP inhibition (Ki) models to allow for rapid drug-drug interaction (DDI) risk assessment
- Significant enhancements to the AI-driven drug design (AIDD) module
“The advancements the team incorporated into ADMET Predictor 11 enable us to seamlessly connect research endeavors across biology, chemistry, and early drug development phases,” stated Dr. David Miller , Vice President of ADMET Cheminformatics. “With the enriched and expanded property prediction models, combined with the newly introduced 3D virtual screening functionality, the AIDD module becomes an even more valuable tool, opening doors for accelerated hit-to-lead and lead optimization stages.”
“Amidst the growing adoption of machine learning in the pharmaceutical industry, there has been an influx of software platforms boasting machine learning capabilities,” commented Dr. Robert Fraczkiewicz , Research Fellow at Simulations Plus and project leader for the pKa collaborations. “However, it is important to recognize that rapid and reliable predictions cannot be achieved through machine learning alone. It necessitates training on premium, extensively curated datasets and the implementation of refined, time-tested algorithms. ADMET Predictor 11 stands out as the sole platform in the market that fulfills all these key criteria, setting a new benchmark for excellence in the field.”
“We continue to support our clients through the integration of machine learning with mechanistic modeling,” added Dr. Eric Jamois , Senior Director of Key Accounts and Strategic Alliances. “The latest advancements enable our users to complement high-throughput pharmacokinetic (HTPK) simulations with rapid assessment of drug-drug interaction (DDI) liabilities, powering the novel selection of clinical candidates. We are proud to deliver this cutting-edge version to our expanding user community and help propel drug discovery research to unprecedented heights.”
