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Ground-breaking approach accelerates drug discovery process
International study develops innovative method to discover new anti-epileptic drug in record time, with potential to do the same for other diseases

An international collaboration between Imperial College London, Singapore’s Duke-NUS Medical School and Belgium-based pharmaceutical company UCB has led to the discovery of a new anti-epileptic drug target and a whole new approach that promises to speed up the discovery of future drugs to treat debilitating diseases, such as epilepsy.

Led by Prof. Michael Johnson, Division of Brain Sciences, Imperial College London, UK; A/Prof. Enrico Petretto, Centre for Computational Biology, Duke-NUS Medical School; and Dr. Rafal Kaminski, UCB, Belgium, this collaboration developed an advanced computational approach to predict new drug targets.

CRAFT (Causal Reasoning Analytical Framework for Target discovery) draws on genomic ‘big data’ and applies a systems-level computational framework to drug target discovery that combines gene regulatory information with causal reasoning.

Starting from gene expression data from the target tissue, CRAFT’s predictive framework identifies cell membrane receptors that play a regulatory role in disease-related gene expression. This enables researchers to understand the mechanism of action of a disease, and computationally predict the effectiveness of a potential drug target.

Epilepsy is a debilitating brain disease where approximately one in three epilepsy patients are resistant to all currently available anti-epileptic drugs. Conventional drug development methods, particularly for diseases of the central nervous system, suffers from a high rate of attrition due to inadequate drug target validation in the early stages of discovery.

By moving away from traditional drug screening approaches, the team discovered and validated a potential new anti-epileptic drug in less than two years. This will greatly accelerate the drug development process and bring new treatments to patients much faster.

The study was published on 3 September 2018 in Nature Communications.

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