Blog
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VeriSIM Life Partners on Digital Endpoints Adoption in Clinical Trials
DATAcc’s’s latest initiative, "Building the Business Case for Digital Endpoints," aims to catalyze investment in digital measurement development and deployment within clinical trials. Through the development of a comprehensive value framework, benchmarking tools, ROI forecasting models, and a modular business case template, both of our organizations strive to empower innovators across the industry to embrace digital endpoints and drive their universal adoption and scalability in clinical research. VeriSIM Life has joined this groundbreaking project as a partner to boost investment and utilization of digital endpoints by equipping decision-makers with tangible data to articulate the value of integrating these strategies into their business operations.
VeriSIM Life Partners on Digital Endpoints Adoption in Clinical Trials
DATAcc’s’s latest initiative, "Building the Business Case for Digital Endpoints," aims to catalyze investment in digital measurement development and deployment within clinical trials. Through the development of a comprehensive value framework, benchmarking tools, ROI forecasting models, and a modular business case template, both of our organizations strive to empower innovators across the industry to embrace digital endpoints and drive their universal adoption and scalability in clinical research. VeriSIM Life has joined this groundbreaking project as a partner to boost investment and utilization of digital endpoints by equipping decision-makers with tangible data to articulate the value of integrating these strategies into their business operations.
Webinar Transcript: Accelerating Clinical Translation of Antibody-Drug Conjugates with Hybrid AI
The following transcript was taken from a recorded conversation between Dr. Jo Varshney, CEO of VeriSIM Life, and Dr. Annick Menetrey, Clinical Pharmacology Lead at Debiopharm. Read on to understand how VeriSIM Life and Debiopharm partnered to scalably investigate first-in-human (FIH) dosing strategies for antibody-drug conjugates to reduce tumor burden safely and effectively. (Edited for clarity and length.)
Webinar Transcript: Accelerating Clinical Translation of Antibody-Drug Conjugates with Hybrid AI
The following transcript was taken from a recorded conversation between Dr. Jo Varshney, CEO of VeriSIM Life, and Dr. Annick Menetrey, Clinical Pharmacology Lead at Debiopharm. Read on to understand how VeriSIM Life and Debiopharm partnered to scalably investigate first-in-human (FIH) dosing strategies for antibody-drug conjugates to reduce tumor burden safely and effectively. (Edited for clarity and length.)
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The Top 5 Challenges in Drug Bioavailability That Can Be Solved by AI
There are several critical challenges that can affect bioavailability, including solubility, permeability, drug-drug interactions, and metabolic profile. Traditional methods for addressing these challenges are often time-consuming and expensive, but luckily, Artificial intelligence (AI) can act as a powerful tool to overcome these challenges and improve drug bioavailability.
The Top 5 Challenges in Drug Bioavailability That Can Be Solved by AI
There are several critical challenges that can affect bioavailability, including solubility, permeability, drug-drug interactions, and metabolic profile. Traditional methods for addressing these challenges are often time-consuming and expensive, but luckily, Artificial intelligence (AI) can act as a powerful tool to overcome these challenges and improve drug bioavailability.
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VeriSIM Life’s AtlasGEN Novel Drug Designer Bridges the Translational Gap, Bringing Life-Saving Treatments to Patients Faster
VeriSIM Life recently announced the availability of AtlasGEN™ Novel Drug Designer, which is the first and only platform that combines generative chemical discovery with biological validation to compress drug candidate selection and reduce costly experimental research dramatically. AtlasGEN is different because it constrains the generative AI with biological data, ensuring relevant and accurate results. Instead of returning 1000 potential molecular hits, most of which are not good, AtlasGEN reduces wasted time, energy and money by returning only the results that are viable.
VeriSIM Life’s AtlasGEN Novel Drug Designer Bridges the Translational Gap, Bringing Life-Saving Treatments to Patients Faster
VeriSIM Life recently announced the availability of AtlasGEN™ Novel Drug Designer, which is the first and only platform that combines generative chemical discovery with biological validation to compress drug candidate selection and reduce costly experimental research dramatically. AtlasGEN is different because it constrains the generative AI with biological data, ensuring relevant and accurate results. Instead of returning 1000 potential molecular hits, most of which are not good, AtlasGEN reduces wasted time, energy and money by returning only the results that are viable.
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Introducing AtlasGEN™ Novel Drug Designer
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.
