VeriSIM Life November Newsletter
VeriSIM Life
Introducing BIOiSIM, an AI-driven drug development engine designed to de-risk and inform R&D decision-making.
News and Views from the team at VeriSIM Life
This month was full of exciting developments, including winning Gold in the Stevie Awards for Women in Business in the category of Most Innovative Company! Read on to hear the latest news, and be sure to reach out to a member of our team to learn more about how BIOiSIM could help your organization achieve your drug development goals.
VeriSIM Life Wins Most Innovative Company of the Year in Stevie Awards
The Stevie Awards for Women in Business celebrate and recognize the achievements of women executives, entrepreneurs, employees, and the companies they lead across the globe. VeriSIM Life was proud to earn the recognition of winning Gold for Most Innovative Company of the Year for its accomplishments addressing “the translational gap” in drug development, and for the BIOiSIM platform’s capability to direct drug developers on where to focus their experimentation and investment. “It’s an immense honor to have our team recognized for leading innovation in life sciences, and we celebrate alongside the other winners,” says Dr. Varshney. “This Gold Stevie Award affirms our dedication to revolutionizing drug development and our mission to deliver critical therapies to patients faster than ever.”
Case Study: Complex Organ Toxicity - Hybrid AI Provides Superior Prediction Accuracy with Very Limited Data
Drug-induced liver injury (DILI) is a major concern in the pharmaceutical industry, accounting for a significant number of drug failures and withdrawals. Traditional ways to predict DILI rely a lot on animal studies and in vitro tests. These can take a long time, cost a lot, and often don't accurately predict human DILI. As a result, there is a growing interest in using computational approaches to predict DILI. However, these methods fail to adequately consider detailed aspects of interspecies differences in drug pharmacological behavior, gene dysregulation due to the drugs, accurate drug chemistry, and integration of specific liver toxicity pathways. In this case study, VeriSIM Life performed research aimed to solve these problems by leveraging knowledge-AI hybrid technology (hybrid AI) to provide robust solutions even in severely data-limited scenarios.
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Dr. Jo Varshney in “AI Saving Lives” Panel at UBS Tech Conference
Attending the UBS Global Technology Conference in December? Dr. Jo Varshney will be speaking on the panel “AI Saving Lives” alongside other industry leaders from Synchron, Illumina, and Quest Diagnostics.
Topics to be discussed include how AI can improve healthcare delivery/patient outcomes, ethical considerations around the use of AI for handling patient data, strategies to maintain a competitive edge in the rapidly evolving AI landscape and more.
Blog Post: Solving First in Human Dosing Challenges with AI
One major difficulty in FIH dosing is considering variability in human response. The complexity of possible individual responses is challenging to account for using traditional FIH dosing methods, and failure to properly consider these possible variations can result in heightened risk of adverse effects in clinical trial participants. It can also increase the already high cost/time investment of clinical trials. This underscores the need for more sophisticated approaches in FIH dosing that can account for the myriad factors that influence individual human response. Read our latest blog to learn more about how hybrid AI can provide the solution.
"De-Risking Drug Translation with Jo Varshney from VeriSIM Life": Podcast with Pixel Scientia Labs
Last week, Dr. Jo Varshney was featured in the Impact AI podcast by Pixel Scientia Labs, "De-Risking Drug Translation with Jo Varshney from VeriSIM Life." The podcast explored Jo's background, VeriSIM Life's mission of bridging the translational gap, and more. “[Hybrid AI] helps us not only unravel newer methods and mechanisms of actions or novel targets but also helps us identify better drug candidates that could eventually be safer and more effective in human patients," Dr. Varshney explained during the podcast.