White Papers & Case Studies

Accelerating SUD Therapy Discovery with AI/ML Driven BBB Permeability Predictions

Accelerating SUD Therapy Discovery with AI/ML Driven BBB Permeability Predictions

4/3/2023

VeriSIM Life partnered with our client to translate drug candidates targeting SUD patient therapies more rapidly and accurately than traditional methods that depend on the experimental uncertainty of modeling for data.

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Pathways for Successful AI Adoption in Drug Development

Pathways for Successful AI Adoption in Drug Development

Artificial intelligence in drug development has transformative potential when it comes to pharma research and development (R&D). Download the white paper to advance the adoption of AI within your organization.

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Frost & Sullivan Report: AI-enabled Preclinical Development, VeriSIM Life

Frost & Sullivan Report: AI-enabled Preclinical Development, VeriSIM Life

12/13/2022

Frost & Sullivan 2022 Competitive Strategy Leader Award North American Artificial Intelligence Enabled Preclinical Development Industry

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Predicting Patient-Specific Drug Bioavailability with AI

Predicting Patient-Specific Drug Bioavailability with AI

09.28.2020

This study covers one of the many applications of BIOiSIM. Our aim was to establish what the pharmacokinetic (PK) profile would look like in the different subjects studied.

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BIOiSIM™ Drug Decision Engine: Breakthrough Intelligence to De-risk R&D Translation, Without Disruption

BIOiSIM™ Drug Decision Engine: Breakthrough Intelligence to De-risk R&D Translation, Without Disruption

09.30.2022

This white paper showcases how fusing artificial intelligence and mechanistic modeling can be used to accurately predict the disposition of small molecules across different subjects for translation to clinical success.

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Optimizing Dosing with AI/ML Driven Transdermal Drug Permeation Simulation

Optimizing Dosing with AI/ML Driven Transdermal Drug Permeation Simulation

07.22.2020

This study covers the development and validation of a transdermal model using the BIOiSIM framework, which was further used to describe the relationship between compound exposure and therapeutic effect.

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