Publications & Blog
Pathways for Successful AI Adoption in Drug Development
Specific benchmarking practices, the use of Explainable AI and a well-developed technology roadmap are critical success factors to effectively onboard AI/ML for drug development.
Pathways for Successful AI Adoption in Drug Development
Specific benchmarking practices, the use of Explainable AI and a well-developed technology roadmap are critical success factors to effectively onboard AI/ML for drug development.
How Taking Smart Risks Makes Drug Development Less Speculative
Originally published by Forbes Technology Council. It’s impossible to totally eliminate risk in drug discovery. However, AI-driven approaches and other breakthrough technologies are continually proving their worth, helping create tangible efficiencies and better outcomes for drugmakers.
How Taking Smart Risks Makes Drug Development Less Speculative
Originally published by Forbes Technology Council. It’s impossible to totally eliminate risk in drug discovery. However, AI-driven approaches and other breakthrough technologies are continually proving their worth, helping create tangible efficiencies and better outcomes for drugmakers.
.png)
An In-Depth Guide to Pharmacokinetic Modeling
Quantifying how a drug moves into, through, and out of the body is at the heart of pharmacokinetic modeling (PK), helping inform many aspects of the drug development process.
An In-Depth Guide to Pharmacokinetic Modeling
Quantifying how a drug moves into, through, and out of the body is at the heart of pharmacokinetic modeling (PK), helping inform many aspects of the drug development process.
.jpeg)
Protein Characterization & Identification: What To Know
There are a range of different protein characterization techniques that can be used to detect, isolate and map the unique amino acids that make up a protein chain.
Protein Characterization & Identification: What To Know
There are a range of different protein characterization techniques that can be used to detect, isolate and map the unique amino acids that make up a protein chain.
.png)
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.
