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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.
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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.
Molecular Modeling: A Detailed Guide
With the growth of computational capabilities over the last decade, molecular modeling has been called a game changer in drug discovery research and the biopharma industry.
Molecular Modeling: A Detailed Guide
With the growth of computational capabilities over the last decade, molecular modeling has been called a game changer in drug discovery research and the biopharma industry.
Chemical Absorption Explained in Simple Terms
In pharmacology, absorption is studied as part of drug development and during clinical trials. In this context, absorption is the process by which a drug moves from the delivery site into the bloodstream.
Chemical Absorption Explained in Simple Terms
In pharmacology, absorption is studied as part of drug development and during clinical trials. In this context, absorption is the process by which a drug moves from the delivery site into the bloodstream.
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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.
