Pharma R&D Today
Ideas and Insight supporting all stages of Drug Discovery & Development
Introducing e-Therapeutics: An In Silico Drug Discovery Lab
Posted on May 1st, 2017 by Thibault Geoui in Chemistry
When laypeople think of drug development, they almost certainly imagine clinical labs filled with chemistry and biology labware or trials with control and test groups receiving different doses of the proposed new treatments. They might also imagine researchers in libraries or online, reading up on what is known about the diseases and existing drugs.
It’s unlikely that a layperson would imagine a drug development workspace that entirely consists of computers, where all the research focuses on creating and manipulating models of disease. Even in the pharmaceutical researcher community, the potential of in silico approaches has not always been broadly recognized: a computer-only drug discovery lab would not have been considered viable even a few years ago.
However, such labs exist and are doing promising work. In silico pharmaceutical research has grown in popularity and application as the possibilities for working with drug and disease data and modeling software have evolved. This has changed the paradigm of early drug discovery.
Standing at the forefront of this paradigm shift in the methodologies used to identify and optimize new drugs is Oxford-based drug development group e-Therapeutics. Their research subjects are models of biological networks, which they manipulate to see what roles each protein plays. Then, using compound chemistry and bioactivity data, they can predict what compounds might affect a given protein and with what potency.
e-Therapeutics has empirically proven that their network-based approach to drug discovery works: 10–20% of the candidates that they send to phenotypic testing demonstrate the desired activity profile.
In a recent interview with Elsevier, the company’s Head of Discovery Informatics Dr. Jonny Wray explains in more detail how normalized chemistry and bioactivity data can be applied to network models of disease to accurately predict compound activity profiles.
Read the full interview here.
All opinions shared in this post are the author’s own.
R&D Solutions for Pharma & Life SciencesWe're happy to discuss your needs and show you how Elsevier's Solution can help.
- Quantitative Proteomics: A Major Piece in the Precision Medicine Puzzle
- Compound Discovery May Spur Therapies for Autoimmune Conditions
- Chemists Concerned About How Their Field is Viewed
- As The Hive Evolves, More Companies Prepare to Join the Program
- Pills Have Gone Digital