SAN FRANCISCO, Nov. 9, 2023 /PRNewswire-PRWeb/ -- VeriSIM Life— the leading artificial intelligence (AI)-enabled, unique R&D decisions de-risker for breakthrough drug development— today announced that it has once again been named "Predictive Analytics Solution of the Year" at the 2023 BioTech Breakthrough Awards. The company was first recognized in the same category in 2022. The awards program, now in its third year, is conducted by BioTech Breakthrough, a leading independent marketing intelligence organization that evaluates and recognizes standout life sciences and biotechnology companies, products, and services around the globe.
VeriSIM was recognized for continued advances with the company's virtual drug development engine, BIOiSIM, a platform that combines artificial intelligence and machine learning with biosimulation to make early and accurate predictions about the safety and efficacy of compounds used in drug development. The use of BIOiSIM is proven to decrease the risk of errors and failures in the drug development process and de-risk clinical trials and early patient applications by predicting outcomes before treatments are given. Ultimately, BIOiSIM helps to accelerate pathways to market for novel therapeutics, positively impacting the lives of patients for whom these treatments may otherwise never have been available.
This award highlights the ongoing positive changes that VeriSIM and BIOiSIM are making in the life sciences industry and drug development pipeline that will make a positive difference for doctors and their patients.
"It is an honor to be recognized for our innovations in predictive analytics for drug development for a second consecutive year," said Dr. Jo Varhsney, Founder and CEO of VeriSIM Life. "This award highlights the ongoing positive changes that VeriSIM and BIOiSIM are making in the life sciences industry and drug development pipeline that will make a positive difference for doctors and their patients."
Earlier this year, VeriSIM announced a new partnership with Clarivate— a leading global information services provider, to further expand the company's capabilities in accelerating and de-risking drug development. Working together, VeriSIM and Clarivate have now released a new Translational Index Dashboard product for customers to accelerate early scientific investigation powered by Clarivate data and VeriSIM Life's AI platform.
Recently, the company also conducted a client collaboration focused on optimizing treatments for substance use disorders by improving the accuracy of predictions for drug partitioning into brain tissue crossing the blood brain barrier. Using BIOiSIM, the team demonstrated prediction accuracy exceeding the industry standard threshold for reliability and identified ~20,000 molecules capable of blood brain barrier permeability and disposition into the brain.
"Our ever-growing number of client collaborations and partnerships is indicative of an industry-wide desire for positive changes and acceleration in the drug development pipeline," said Varshney. "We're proud to be a part of a community that is willing to work together to improve what we're all doing in order to achieve better patient outcomes."
VeriSIM's work is being honored alongside other major breakthroughs in life sciences and biotechnology from ThermoFisher, Acumen Pharmaceuticals, Colossal Biosciences, Guardant Health, Mission Bio, Travere Therapeutics, Vaxess Technologies, Waters, and more.
The mission of the annual BioTech Breakthrough Awards program is to conduct the industry's most comprehensive analysis and evaluation of the top technology companies, solutions, and products in the life sciences and biotechnology industry today. This year's program attracted thousands of nominations coming in from all over the world.
About VeriSIM Life
VeriSIM Life has developed a sophisticated computational platform that leverages advanced AI and ML techniques to improve drug discovery and development by significantly reducing the time and money it takes to bring a drug to market. BIOiSIM® is a first-in-class 'virtual drug development engine' that offers unprecedented value for the drug development industry by narrowing down the number of drug compounds that offer anticipated value for the treatment or cure of specific illnesses or diseases. The platform predicts the likelihood of a candidate's success in clinical trials early in the preclinical stage, while reducing unnecessary experimentation and better informing key program decisions. For more information, visit www.verisimlife.com.
About BioTech Breakthrough
Part of Tech Breakthrough, a leading market intelligence and recognition platform for global technology innovation and leadership, the BioTech Breakthrough Awards program is devoted to honoring excellence in life science and biotechnology solutions, services and companies. The BioTech Breakthrough Awards provide public recognition for the achievements of biotechnology companies and products in categories including BioPharma, Genomics, Therapeutics, Food Science and BioAgriculture, and more. For more information visit BioTechBreakthroughawards.com
AtlasGEN Novel Drug Designer efficiently identifies new molecules based on favorable chemical properties and simultaneously evaluates them for clinical safety and effectiveness based on biology using VeriSIM Life’s groundbreaking Translational Index™ technology.
Iterative ranking of target engaging hits by their Translational Index values reduces the time and cost associated with other computational hit discovery approaches, while compressing the hit-to-lead refinement and optimization process by pre-validating hits for translatability. This unique integration dramatically reduces the number of compounds to evaluate in subsequent experimental research.
The ability to generate target engaging compound hits depends largely on the size of the molecular search library. The AtlasGEN search space is supported by more than 1 trillion compounds. Generative AI and deep learning techniques deliver unprecedented discovery capability.
AtlasGEN accurately predicts protein-lygand binding affinity by combining geometric conformer analysis with machine learning based on experimental data 72% more efficiently than molecular docking-based approaches.
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