Publications & Blog
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.
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.
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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.
