Want to avoid late-stage failure of your drug candidates? Understanding the metabolism of your compounds is crucial.
In silico modelling provides an early opportunity to spot problems, such as potential highly reactive sites of metabolism, or possible toxic metabolites which could be formed, and resolve them by guiding the design of improved compounds. Traditionally, predictive modelling has targeted human Cytochrome P450s, a key enzyme family involved in drug metabolism. However, P450s aren’t the only enzymes to consider; there is a whole range which should be evaluated to reduce risks of unexpected drug metabolism, including additional phase I enzymes, such as AO and FMO, and phase II enzymes including UGT and SULT.
On 24 May, join Optibrium CEO Matt Segall and Principal Scientist Mario Öeren to explore groundbreaking new quantum mechanics and machine learning models which go beyond P450s and provide insights on a broad range of enzymes involved in drug metabolism.
Listen as they discuss:
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The processes and key enzymes involved in phase I and II drug metabolism
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State-of-the-art methods to predict metabolism for a broad range of enzymes
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The science behind our combined quantum mechanics and machine learning models
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StarDrop’s capabilities to predict metabolism, including a sneak peek at new upcoming releases
Following the presentation there will be an interactive Q&A session, so please come prepared with any questions specific to your area of interest!
