How 'in silico' testing is accelerating drug R&D

Raconteur, the business report from The Times of London, published "How 'in silico' testing is accelerating drug R&D: AI is helping pharmaceutical firms to drastically reduce the time and cost they incur in the lab on evaluating the medicinal potential of hundreds and thousands of chemicals." The article features CBO Jane Rhodes talking about how our AI-powered CONVERGE™ technology sped the discovery of VRG50635, a potential treatment for ALS. While a subscription is required to access the article here https://www.raconteur.net/report/future-data-ai-2023/, below are highlights:

In another recent first, a new AI-aided drug designed to treat amyotrophic lateral sclerosis (ALS), a motor neurone disease for which there is no known cure, has entered clinical trials. The therapy – going under the name VRG50635 at this stage – was discovered by Verge Genomics using Converge, an AI platform it has developed.

“We used Converge to build an ALS ‘disease signature’ based on more than 11 million data points, sourced from almost 1,000 human tissue samples,” explains the firm’s chief business officer, Dr Jane Rhodes. “Our signature comprises more than 200 genes that are dysregulated compared with neurons from healthy brains and spinal cords. This gave us insights into the complexity of the disease and enabled us to discover novel molecular mechanisms that we believe can cause ALS. We achieved all this in half of the industry’s standard time.”

"The next challenge we face is to scale up this approach,” Rhodes says. “We need to systematically apply the use of AI across the entire drug discovery pipeline and embed it effectively into business processes. By using large quantities of high-quality human data, we can reduce the need for animal experimentation and move towards a system of predictive modelling that can save both time and cost while increasing the probability of technical success.”