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An overview of pharmacodynamic modelling, ligand-binding approach and its application in clinical practice

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journal contribution
posted on 2023-05-19, 17:20 authored by Mohammed SalahudeenMohammed Salahudeen, Nishtala, PS
The study of the magnitude and variation of drug response is defined as pharmacodynamics (PDs). PD models examine plasma concentration and effect relationship. It can predict the archetypal effect (E) of a drug as a function of the drug concentration (C) and estimate an unknown PD parameter (θpd). The PD models have been described as fixed, linear, log-linear, Emax, sigmoid Emax, and indirect PD response. Ligand binding model is an example of a PD model that works on the underpinning PD principle of a drug, eliciting its pharmacological effect at the receptor site. The pharmacological effect is produced by the drug binding to the receptor to either activate or antagonise the receptor. Ligand binding models describe a system of interacting components, i.e. the interaction of one or more ligands with one or more binding sites. The Emax model is the central method that provides an empirical justification for the concentration/dose-effect relationship. However, for ligand binding models justification is provided by theory of receptor occupancy. In essence, for ligand binding models, the term fractional occupancy is best used to describe the fraction of receptors occupied at a particular ligand concentration. It is stated that the fractional occupancy = occupied binding sites/total binding sites, which means the effect of a drug should depend on the fraction of receptors that are occupied. In the future, network-based systems pharmacology models using ligand binding principles could be an effective way of understanding drug-related adverse effects. This will facilitate and strengthen the development of rational drug therapy in clinical practice.


Publication title

Saudi pharmaceutical journal








School of Pharmacy and Pharmacology


Saudi Pharmaceutical Society

Place of publication

Saudi Arabia

Rights statement

Copyright 2016 The Authors. Licensed under Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)

Repository Status

  • Open

Socio-economic Objectives

Evaluation of health outcomes

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