Turn On, Tune In, Turnover! Target Biology Impacts In Vivo Potency, Efficacy, and Clearance

Johan Gabrielsson1, Stephan Hjorth2

  • 1MedDoor AB, Gothenburg, Sweden (J.G.) and Pharmacilitator AB, Vallda, Sweden (S.H.) Professor.Gabrielsson@gmail.com.

Pharmacological Reviews
|January 10, 2023
PubMed

Insights

Introducing target turnover into pharmacokinetic models enhances understanding of drug potency and clearance. New open models reveal how fractional turnover rates, not absolute concentrations, determine drug exposure and efficacy across diverse physiological conditions.

Area of Science:

  • Pharmacology and Drug Development
  • Biochemical Kinetics
  • Translational Medicine

Background:

  • Significant knowledge gaps persist in defining determinants of in vivo drug potency and clearance.
  • Existing models often lack the integration of crucial biological system dynamics.
  • Optimizing translational dose-concentration-response predictions requires a deeper understanding of these determinants.

Purpose of the Study:

  • To develop novel open model expressions for in vivo potency and efficacy parameters that incorporate target turnover.
  • To analyze the commonalities and differences between potency and efficacy parameters within these new models.
  • To comprehensively review literature on factors influencing target turnover rates in biological systems.

Main Methods:

  • Derivation of new open model expressions integrating system and drug properties, including target turnover, binding, and complex kinetics.
  • Examination of these open models to elucidate the relationships between potency, efficacy, and drug exposure.
  • Conducting a comprehensive literature review on the variability of target turnover rates across different biological contexts.

Main Results:

  • Fractional turnover rates, rather than absolute target or ligand-target complex concentrations, dictate necessary drug exposure for in vivo potency.
  • Absolute ligand-target concentrations, along with transduction and in vivo efficacy parameters, determine the drug's requirement.
  • Free enzyme concentration influences clearance and metabolic rate, while fractional turnover rate governs equilibrium kinetics.

Conclusions:

  • The novel open model provides a more accurate framework for predicting drug behavior by integrating target turnover.
  • Understanding target turnover variability is crucial for optimizing drug discovery, development, and clinical dosing strategies.
  • This approach may explain inter-individual differences in drug response and requirements.

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