Integration of pharmacokinetic and pharmacodynamic data to understand how a drug is likely to be distributed through the body over time and the access it will have to its molecular target. This understanding provides the basis for dosing strategies (see Dose finding and Dose fractionation study).
Typically, PK/PD modelling is used to simulate how a drug is distributed across different tissues (or ‘compartments’) over time. These models can be used to estimate drug concentrations at different body sites for different dosing regimens and drug effect.
The role of infection models and PK/PD modelling for optimising care of critically ill patients with severe infections (Intensive Care Medicine, 2017)
Pharmacokinetic and Pharmacodynamic Principles of Anti-Infective Dosing (Clinical Therapeutics, 2016)
PK/PD models in antibacterial development (Current Opinion in Microbiology, 2014)
Considerations for Dose Selection and Clinical Pharmacokinetics/Pharmacodynamics for the Development of Antibacterial Agents (Antimicrobial Agents and Chemotherapy, 2019)
Guideline on the use of pharmacokinetics and pharmacodynamics in the development of antimicrobial medicinal products
Generating Robust and Informative Nonclinical In Vitro and In Vivo Bacterial Infection Model Efficacy Data To Support Translation to Humans (Antimicrobial Agents and Chemotherapy, 2019)
REVIVE webinar: ‘PK-PD in support of accelerated programmes for antimicrobial development: how much is enough?’ by William Hope (GARDP, 2018)
REVIVE webinar: ‘Models for antimicrobial R&D: Computational modelling for population PK and PKPD’ by Lena Friberg & Elisabet Nielsen (GARDP, 2019)
REVIVE webinar: ‘PK/PD murine infection models: Focus on study elements, variability, and interpretation of results’ by Alexander J. Lepak (GARDP, 2020)
REVIVE webinar: ‘Probability of target attainment analyses for dose selection in antimicrobial drug development’ by Shampa Das (GARDP, 2020)
REVIVE webinar: ‘Test tube to patient: PK/PD of fixed dose beta-lactam/beta-lactamase inhibitor combinations’ by Vincent Tam (GARDP, 2020)