Blog
Biomarker Discovery and Validation Explained
Biomarkers play a crucial role in drug development, helping measure the effects of investigational treatments in humans during clinical trials. Recently, advancements in biomarker discovery and validation methods, spurred on by innovations in instrumentation and in silico predictive tools , are improving diagnosis, prognosis and disease monitoring. Let’s take a closer look at biomarker discovery and validation.
Biomarker Discovery and Validation Explained
Biomarkers play a crucial role in drug development, helping measure the effects of investigational treatments in humans during clinical trials. Recently, advancements in biomarker discovery and validation methods, spurred on by innovations in instrumentation and in silico predictive tools , are improving diagnosis, prognosis and disease monitoring. Let’s take a closer look at biomarker discovery and validation.
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University of Toronto Study Confirms What VeriSIM Life Already Knows About the Potential of AI in Drug Development
This discussion around budding research into the benefits of AI and machine learning in drug discovery matters not only because it demonstrates that these topics aren’t going away anytime soon, but that it further validates the ability of AI to predict drug behavior accurately and reduce the time and cost of developing a new drug candidate.
University of Toronto Study Confirms What VeriSIM Life Already Knows About the Potential of AI in Drug Development
This discussion around budding research into the benefits of AI and machine learning in drug discovery matters not only because it demonstrates that these topics aren’t going away anytime soon, but that it further validates the ability of AI to predict drug behavior accurately and reduce the time and cost of developing a new drug candidate.
Parting Thoughts from Fierce@JPM Week LIVE 2023
The 2023 edition of the annual JP Morgan Healthcare conference was eagerly expected after 2 years of “virtual” meetings, and for those fortunate enough to attend, the gathering did not disappoint. While the main event featured headlines from the major pharma companies, we’re happy to report firsthand that events around the edges fostered innovative collaborations and partnerships. Fierce’s JPM Week day at the San Francisco Fairmont was one such venue. Here’s a few hot takes from the day’s presenters and networking chatter.
Parting Thoughts from Fierce@JPM Week LIVE 2023
The 2023 edition of the annual JP Morgan Healthcare conference was eagerly expected after 2 years of “virtual” meetings, and for those fortunate enough to attend, the gathering did not disappoint. While the main event featured headlines from the major pharma companies, we’re happy to report firsthand that events around the edges fostered innovative collaborations and partnerships. Fierce’s JPM Week day at the San Francisco Fairmont was one such venue. Here’s a few hot takes from the day’s presenters and networking chatter.
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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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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.
