Related Experiment Video

Updated: Mar 26, 2026

A Robust Pneumonia Model in Immunocompetent Rodents to Evaluate Antibacterial Efficacy against S. pneumoniae, H. influenzae, K. pneumoniae, P. aeruginosa or A. baumannii
09:17

A Robust Pneumonia Model in Immunocompetent Rodents to Evaluate Antibacterial Efficacy against S. pneumoniae, H. influenzae, K. pneumoniae, P. aeruginosa or A. baumannii

Published on: January 2, 2017

15.4K

Simulation-Based Evaluation of PK/PD Indices for Meropenem Across Patient Groups and Experimental Designs

Anders N Kristoffersson1, Pascale David-Pierson2, Neil J Parrott2

  • 1Department of Pharmaceutical Biosciences, Uppsala Universitet, Box 591, Uppsala, SE-751 24, Sweden. anders.kristoffersson@farmbio.uu.se.

Pharmaceutical Research
|January 21, 2016
PubMed
Abstract

Insights

Antibiotic dose predictions using PK/PD indices are sensitive to drug susceptibility and pharmacokinetics. Simulations suggest an integrated PK-PKPD model is preferable to fixed targets for meropenem dosing against Pseudomonas aeruginosa.

Area of Science:

  • Pharmacology
  • Microbiology
  • Computational Biology

Background:

  • Pharmacokinetic/pharmacodynamic (PK/PD) indices are crucial for predicting antibiotic efficacy.
  • Current models often assume PK/PD index insensitivity to factors like bacterial susceptibility and pharmacokinetics (PK).
  • Meropenem and Pseudomonas aeruginosa serve as a model system to challenge these assumptions.

Purpose of the Study:

  • To evaluate the sensitivity of PK/PD indices to experimental design, bacterial susceptibility, and PK variability.
  • To challenge the assumption that PK/PD index type and magnitude are independent of these factors.
  • To compare the predictive performance of different PK/PD indices for meropenem.

Main Methods:

  • In silico replication of a published murine dose fractionation study.
  • Evaluation of PK/PD index sensitivity to variations in MIC, PK profiles, and experimental design.
  • Utilizing a longitudinal PK/PD model based on in vitro data.

Main Results:

  • The time above the minimum inhibitory concentration (fT>MIC) best predicted outcomes in the murine model.
  • Predictive capacity shifted to the area under the concentration-time curve divided by MIC (AUC/MIC) with increased dosing frequency.
  • Both indices' magnitudes were sensitive to bacterial susceptibility, and human PK data showed similar predictive capacities for fT>MIC and AUC/MIC.

Conclusions:

  • A PK/PD model successfully predicted in vivo meropenem study outcomes.
  • PK/PD index type and magnitude are sensitive to experimental design, MIC, and PK.
  • Integrated PK-PKPD modeling is recommended over fixed PK/PD targets for optimizing antibiotic dosing.
Keywords:
antibioticdose selectionmeropenempharmacometricpseudomonas aeruginosa

More Related Videos

Antimicrobial Synergy Testing by the Inkjet Printer-assisted Automated Checkerboard Array and the Manual Time-kill Method12:03

Antimicrobial Synergy Testing by the Inkjet Printer-assisted Automated Checkerboard Array and the Manual Time-kill Method

Published on: April 18, 2019

28.0K
Development of a Polymicrobial Colony Biofilm Model to Test Antimicrobials in Cystic Fibrosis07:16

Development of a Polymicrobial Colony Biofilm Model to Test Antimicrobials in Cystic Fibrosis

Published on: September 20, 2024

2.0K

Related Concept Videos

Pharmacodynamic Models: Overview01:27

Pharmacodynamic Models: Overview

Pharmacodynamic (PD) responses describe the interaction between a drug and its biological target, culminating in a physiological effect. These responses can be classified into different types: continuous variables, such as blood glucose levels; categorical outcomes, like survival rates; and time-to-event metrics, such as disease progression. Understanding and modeling PD responses are critical for optimizing drug efficacy and safety.PD models describe the relationship between drug concentration...
78
Analysis of Population Pharmacokinetic Data01:12

Analysis of Population Pharmacokinetic Data

Analysis of population pharmacokinetic data involves studying the behavior of drugs within diverse populations to understand their pharmacokinetic parameters. Traditional pharmacokinetic methods typically involve collecting samples from a few individuals and estimating these parameters. While these methods are commonly used, they have limitations in capturing the variability in drug response among individuals or heterogeneous populations. Population pharmacokinetics is employed to address these...
906
Impact of Pharmacokinetic–Pharmacodynamic Models: Regulatory Decisions01:15

Impact of Pharmacokinetic–Pharmacodynamic Models: Regulatory Decisions

PK–PD modeling has significantly influenced FDA regulatory decisions, particularly drug approval, dosage optimization, and labeling. These models integrate pharmacokinetics (PK) and pharmacodynamics (PD) to predict drug behavior and effects, aiding in optimizing dosing regimens and enhancing the probability of clinical trial success.One notable example is Nesiritide (Natrecor®), a recombinant human brain natriuretic peptide for treating acute decompensated congestive heart failure...
71
Dosage Regimens: Partial Pharmacokinetic Parameters01:01

Dosage Regimens: Partial Pharmacokinetic Parameters

It is not uncommon for complete drug pharmacokinetic profiles to remain elusive in pharmacokinetics. This necessitates certain educated assumptions by pharmacokineticists to determine appropriate dosage regimens without comprehensive pharmacokinetic data from animal or human studies. One prevalent assumption is setting the bioavailability factor, denoted as F, to 1 or 100%. This assumption caters to the scenario where a drug doesn't achieve full systemic absorption, resulting in the patient...
254
Pharmacokinetic–Pharmacodynamic Relationship: Problems01:24

Pharmacokinetic–Pharmacodynamic Relationship: Problems

The empirical approach to drug therapy optimization relies on correlating pharmacological response with administered dosage. Such an approach can be costly, time-consuming, and often yields poor correlation due to variables like formulation factors and drug elimination characteristics. A more precise approach correlates response with plasma drug concentration or the amount of drug in the body, rather than dosage. This is achieved through pharmacokinetic-pharmacodynamic (PK/PD) modeling, which...
76
Bioequivalence Experimental Study Designs: Repeated Measures, Cross-Over, Carry-Over, and Latin Square Designs01:15

Bioequivalence Experimental Study Designs: Repeated Measures, Cross-Over, Carry-Over, and Latin Square Designs

Bioequivalence experimental study designs play a pivotal role in testing the effectiveness of various treatments. Key among these are the repeated measures, cross-over, carry-over, and Latin square designs. In the repeated measures design, each subject receives all treatments, allowing for temporal comparisons. This type of design is useful in reducing variability but requires careful planning to avoid bias.The cross-over design, an economical method, involves sequential administration of...
384