Out now in Drug Target Review, Optibrium’s Director of Computational Chemistry, Dr Peter Hunt discusses why early in silico metabolism prediction is crucial to mitigate the problem of clinical-stage drug failures. He shares insights on in silico modelling methods and how you can ensure a smooth transition from preclinical to clinical analysis. The article also talks through a real-world example where early stage modelling could have saved huge expense and effort.
Introduction
Approximately 40% of drug failures at the clinical stage are due to ADMET issues1. These failures are often due to problems around drug metabolism, including poor metabolic stability resulting in low bioavailability of the active compound, unforeseen drug-drug interactions or the formation of reactive or toxic metabolites causing adverse side effects. To overcome these issues and avoid wasting time and money in fruitless experimental trials, early in silico metabolism prediction is crucial.
About the author
Peter Hunt, PhD
Director Computational Chemistry, Optibrium
Want more information?
You can hear more from us in our webinars.
Integrated prediction of Phase I and II metabolism
Watch Optibrium CEO Matt Segall and Principal Scientist Mario Öeren as they explore groundbreaking new quantum mechanics and machine learning models which go beyond P450s and provide insights on a broad range of enzymes involved in drug metabolism.
Overcoming challenges in drug metabolism: in silico approaches
Interpreting metabolite-ID experiments; determining the right species for animal studies; providing optimisation suggestions for your medicinal chemistry colleagues to overcome…
3D ligand-based drug design: webinar
In this webinar, we demonstrate intuitive workflows for 3D ligand-based drug design
Related content from across the site
Optibrium demonstrates superior molecular docking method for small molecules and macrocycles
CAMBRIDGE, UK, 22 October 2024 – Optibrium, a leading developer of software and AI solutions for molecular design today announced…
7th RSC-BMCS AI in chemistry conference
The Chemical Information & Computer Applications Group (CICAG) and Biological & Medicinal Chemistry Sector (BMCS) of the Royal Society of Chemistry are once again organising a conference to present the current advances in AI and machine learning in Chemistry.
26th North American ISSX and JSSX Meeting
The joint ISSX/JSSX meeting is for researchers looking to gain a deeper understanding of drug metabolism and pharmacokinetics.