The rate of drug development, especially novel therapeutics, for the diseases of the nervous system is constrained by the lack of fast target discovery and validation. Development of efficacious treatments for brain diseases have thus been slow, despite constant advances in gene discovery. Hence there is large unmet need of powerful techniques for identifying drug targets and expand our understanding of the molecular processes underlying the diseases.
Treatments for epilepsy, a devastating brain disease, are beset by conventional drug discovery methods. Researchers from Imperial College London, U.K.; UCB, a multinational biopharmaceutical company, Belgium; and Duke-NUS Medical School, Singapore collaborated to develop a completely new approach to anti-epileptic drug target based on advanced computational framework. The framework called Causal Reasoning Analytical Framework for Target discovery (CRAFT) combines systems genetics approaches with ‘casual reasoning’ and genomic ‘big data’. The researchers in proof-of-concept experiments identified a potential therapeutic target and showed that these targets are helpful in reducing the effect of epilepsy seizures in three pre-clinical models of epilepsy.
The findings are published on September 3, 2018 in a peer-reviewed open access journal Nature Communications.
CRAFT based on Systems Genetics Approaches to prove Equally Promising for Several Similar Diseases
The researchers identified tyrosine kinase receptor Csf1R as the potential drug target for epilepsy. They found CRAFT’s predictive framework to be especially effective in validation of antiepileptic drug candidates in preclinical studies. This could be attributed to its ease of development and validation. The researchers used CRAFT to identify cell membrane receptors that is a key determinant of gene networks and expression driving the disease. These receptors are effective drug targets for the disease, which can be validated in an early stage in drug discovery process.
The study approach is ground-breaking as the CRAFT is promising for computationally predicting novel drug targets in any disease in which researchers can identify the underlying disease expression.
The researchers opine that computational identification of key disease drivers is a novel way to screen drugs and will accelerate the drug development process of epilepsy and various other similar diseases.