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Improving the Prediction of In vivo Drug Activity

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  • UserPeter Tonge, Institute for Chemical Biology & Drug Discovery, Stony Brook University USA
  • ClockTuesday 16 January 2018, 16:00-17:00
  • HouseWolfson Lecture Theatre.

If you have a question about this talk, please contact Alice Wood.

Time-dependent enzyme inhibitors are of particular interest in drug discovery programs since the rate of complex dissociation (koff) can be slower than the time scale of in vivo drug metabolism and elimination, leading to sustained target occupancy, and thus enabling dosing frequency and exposure to be reduced. We have developed a mechanistic PK/PD model that enables the kinetic parameters for time-dependent target engagement to be used to predict in vivo drug efficacy. To inform and interrogate the PK/PD model, we are developing compounds with altered residence times on their targets and quantifying the molecular factors that modulate the coupling of time- dependent enzyme inhibition to prolonged drug activity following compound washout. This analysis provides direct insight into target vulnerability. Data on three systems will be discussed including reversible inhibitors of two antibacterial targets, and a covalent inhibitor of Bruton’s tyrosine kinase (Btk), a target for treating diseases stemming from B cell dysregulation. The ability to accurately quantify target engagement as a function of time and drug concentration is expected to dramatically improve the prediction of in vivo drug activity across all therapeutic areas. http://pubs.acs.org/doi/pdf/10.1021/acschemneuro.7b00185

This talk is part of the Biological Chemistry Research Interest Group series.

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