Publications & Blog
When It Comes to AI in Drug Development, Should We Believe the Hype?
AI technologies like deep learning, machine learning and natural language processing have the potential to address many of the challenges that traditionally plague drug R&D – accelerating molecule design and testing, streamlining essential processes, improving chances of clinical success, and reducing costs throughout the development pipeline.
When It Comes to AI in Drug Development, Should We Believe the Hype?
AI technologies like deep learning, machine learning and natural language processing have the potential to address many of the challenges that traditionally plague drug R&D – accelerating molecule design and testing, streamlining essential processes, improving chances of clinical success, and reducing costs throughout the development pipeline.
Accelerating novel drugs to patients together–how combining discovery and development technologies will transform drug decision making
BIOiSIM is a first-in-class decision-making engine that can take your toughest questions and generate answers to guide your next steps at any stage of drug development. With the acquisition of Molomics, it will be powered by one of the largest and fastest growing inferential search spaces in existence, encompassing over 1 trillion compounds.
Accelerating novel drugs to patients together–how combining discovery and development technologies will transform drug decision making
BIOiSIM is a first-in-class decision-making engine that can take your toughest questions and generate answers to guide your next steps at any stage of drug development. With the acquisition of Molomics, it will be powered by one of the largest and fastest growing inferential search spaces in existence, encompassing over 1 trillion compounds.
Patient Stratification: What You Need to Know to Do it Right
In today’s complex world, we truly only understand a tiny fraction of biology. When performing clinical trials, scientists/researchers must figure out ways to develop methods to effectively represent a whole with a subset or sampling due to costs and time. These methodologies, when done correctly, are all based on statistical methods. This is true for population genetics and patient stratification for clinical trials and studies.
Patient Stratification: What You Need to Know to Do it Right
In today’s complex world, we truly only understand a tiny fraction of biology. When performing clinical trials, scientists/researchers must figure out ways to develop methods to effectively represent a whole with a subset or sampling due to costs and time. These methodologies, when done correctly, are all based on statistical methods. This is true for population genetics and patient stratification for clinical trials and studies.
Biomarker Discovery: Function and Advancement
Biomarker Discovery & Validation Biomarker discovery is defined as the process in which biological markers, or “biomarkers” for short, are evaluated and measured. This process begins with defining a biological process and analyzing for different types of biomarkers. These can be prognostic, diagnostic, or predictive to determine treatment efficacy or monitor patient safety. Expanding upon this definition, the World Health Organization defines this term as "almost any measurement reflecting an interaction between a biological system and a potential hazard, which may be chemical, physical, or biological.” Biomarkers are also an integral part of drug development as they help accurately determine drug safety and efficacy. In contemporary medicine, many clinical decisions are based upon laboratory test results. According to the Centers for Disease Control, these tests account for 70% of clinical decisions.
Biomarker Discovery: Function and Advancement
Biomarker Discovery & Validation Biomarker discovery is defined as the process in which biological markers, or “biomarkers” for short, are evaluated and measured. This process begins with defining a biological process and analyzing for different types of biomarkers. These can be prognostic, diagnostic, or predictive to determine treatment efficacy or monitor patient safety. Expanding upon this definition, the World Health Organization defines this term as "almost any measurement reflecting an interaction between a biological system and a potential hazard, which may be chemical, physical, or biological.” Biomarkers are also an integral part of drug development as they help accurately determine drug safety and efficacy. In contemporary medicine, many clinical decisions are based upon laboratory test results. According to the Centers for Disease Control, these tests account for 70% of clinical decisions.
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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.
