VeriSIM Life March '24 Newsletter

News and Views from the team at VeriSIM Life

At VeriSIM Life, our experts work to solve hard problems in translational science, and to share their knowledge with the pharma community. This week we sponsored the 3Rs Collaborative AI Initiative workshop at the Society of Toxicology Annual Meeting. Our team will also attend the American Association of Cancer Research (AACR) Annual Meeting in April. And we’ve published another innovative client success showcase. Plug into our AI expertise by following Dr. Jo Varshney and Dr. Szczepan Baran for their industry perspective and educational insights.

Meet with the VeriSIM Life Executive Team at AACR

VeriSIM Life will be attending the AACR Annual Meeting in San Diego, and our team would love the chance to meet with you to share how our AI and machine learning-powered computational platform, BIOiSIM? has helped clients in the realm of preclinical oncology drug research. Don’t be shy— schedule a meeting with Dr. Jo Varshney and other VeriSIM Life executives to learn what we have accomplished for clients striving to get life-saving cancer drugs to patients faster.?

Book a Meeting

New Client Case Study: Using AI/ML to Discover and Analyze Metabolites for Efficacy, Toxicity and Bioavailability

This case study documents how VeriSIM Life supported our client’s investigation of novel small molecule drug candidates targeting metastatic melanoma. VeriSIM Life’s analysis found key translational efficacy deficiencies in the client’s lead compound, while also identifying superior metabolite-related alternatives. Armed with these insights, the client was able to avoid investing in a compound destined not to be efficacious in the clinic, while redirecting development into a more promising compound. Read more to learn how we saved the client expense, time to market and helped de-risk the program from a business sense.

Download the Case Study

VeriSIM Life in Pharma’s Almanac: Q&A with Dr. Jo Varshney

“The technology was the foundation for everything else. Initially, I was not interested in starting a company; things just moved in that direction serendipitously. With our early technology, we participated in a hackathon exploring data about a cancer patient. We won that hackathon, but more importantly, the three days we spent working on solutions for that patient motivated me to create a scalable platform,” Dr. Varshney explains in this Pharma’s Almanac Q&A, “The Translational Index Score: Improving the Entire Drug Development Cycle.” Read the whole piece to learn the full background of BIOiSIM’s inception, purpose and mission, then check out this blog post to learn more about the “translational gap” and how the smartest companies are using AI to bridge it.

Read the Q&A

“BIOiSIM assigns ‘credit scores’ to drug candidates”: VeriSIM Life in Drug Discovery & Development?

?“It’s like a FICO score for drug development,” founder and CEO Dr. Jo Varshney says of BIOiSIM in this featured article published in Drug Discovery & Development. “BIOiSIM’s scoring system draws from an inferential search space of more than 1 billion drug-like compounds and capacity to model 800 billion total simulation scenarios powered by 10 billion deep learning neural network effects. The vast search space of drug-like compounds and data processing capabilities enable it to evaluate numerous factors such as its potency, selectivity, and safety profile to determine a drug’s overall likelihood of success.” Read more to learn how BIOiSIM helps clients de-risk their drug development programs.?

Read the Article

What We're Reading: How the New MRSA Antibiotic Cracked AI's 'Black Box'

The article discusses how a new antibiotic targeting MRSA was discovered through the use of artificial intelligence (AI), specifically by cracking open the "black box" of AI analysis to make the process more explainable. The drug discovery process typically involves complex AI algorithms that analyze vast amounts of data, making it difficult for scientists to understand how the AI arrives at its conclusions. However, by incorporating techniques to make AI analysis more explainable, researchers were able to gain insights into the molecular mechanisms underlying antibiotic activity against MRSA.

As the article notes, AI explainability is increasingly of interest to regulators. Read VeriSIM Life's perspective on this, and how we've engineered explainability into BIOiSIM.

Read the Article