Population Pharmacokinetic and Pharmacodynamics

A special issue of Pharmaceuticals (ISSN 1424-8247). This special issue belongs to the section "Pharmacology".

Deadline for manuscript submissions: 30 June 2024 | Viewed by 2405

Special Issue Editors

Institute of Technological and Research, Tiradentes University, Aracaju, Brazil
Interests: nanoparticle; dermal absorption; PK/PD
1. Faculty of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, Ribeirão Preto, São Paulo 14040-900, Brazil
2. Simulations Plus, Lancaster, CA, USA
Interests: pharmacokinetics; pharmacodynamics

Special Issue Information

Dear Colleagues,

Submitting a manuscript to the Special Issue “Population Pharmacokinetics and Pharmacodynamics” offers an excellent opportunity for researchers and scholars in pharmacometrics and related disciplines to contribute to a diverse and extensive collection of research. The Issue covers a broad range of areas, including population pharmacokinetics-pharmacodynamics, physiological-based pharmacokinetics (PBPK), systems pharmacology (QSP), virtual bioequivalence (vBE), precision medicine, and mathematical pharmacology. Additionally, the Issue features computational biology, bioengineering, biophysics, and the use of machine learning in pharmacokinetics-pharmacodynamics. With such a diverse range of topics covered, this Special Issue offers a unique opportunity for researchers to showcase their expertise in the field and contribute to the advancement of pharmacometrics and related disciplines. Moreover, publishing in this Special Issue will provide visibility to authors’ work within the scientific community and help them to establish their credibility as experts in their field.

Prof. Dr. Patricia Severino
Prof. Dr. Frederico Severino Martins
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Pharmaceuticals is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2900 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • PK/PD
  • PBPK/PD
  • popPK

Published Papers (2 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Research

16 pages, 6394 KiB  
Article
A Physiologically Based Pharmacokinetic Model to Predict Systemic Ondansetron Concentration in Liver Cirrhosis Patients
by Faleh Alqahtani, Abdullah H. Alruwaili, Mohammed S. Alasmari, Sultan A. Almazroa, Khaled S. Alsuhaibani, Muhammad F. Rasool, Abdulkarim F. Alruwaili and Sary Alsanea
Pharmaceuticals 2023, 16(12), 1693; https://doi.org/10.3390/ph16121693 - 06 Dec 2023
Cited by 1 | Viewed by 992
Abstract
Introduction: Ondansetron is a drug that is routinely prescribed for the management of nausea and vomiting associated with cancer, radiation therapy, and surgical operations. It is mainly metabolized in the liver, and it might accumulate in patients with hepatic impairment and lead to [...] Read more.
Introduction: Ondansetron is a drug that is routinely prescribed for the management of nausea and vomiting associated with cancer, radiation therapy, and surgical operations. It is mainly metabolized in the liver, and it might accumulate in patients with hepatic impairment and lead to unwanted adverse events. Methods: A physiologically based pharmacokinetic (PBPK) model was developed to predict the exposure of ondansetron in healthy and liver cirrhosis populations. The population-based PBPK simulator PK-Sim was utilized for simulating ondansetron exposure in healthy and liver cirrhosis populations. Results: The developed model successfully described the pharmacokinetics of ondansetron in healthy and liver cirrhosis populations. The predicted area under the curve, maximum systemic concentration, and clearance were within the allowed twofold range. The exposure of ondansetron in the population of Child–Pugh class C has doubled in comparison to Child–Pugh class A. The dose has to be adjusted for liver cirrhosis patients to ensure comparable exposure to a healthy population. Conclusion: In this study, the developed PBPK model has described the pharmacokinetics of ondansetron successfully. The PBPK model has been successfully evaluated to be used as a tool for dose adjustments in liver cirrhosis patients. Full article
(This article belongs to the Special Issue Population Pharmacokinetic and Pharmacodynamics)
Show Figures

Figure 1

0 pages, 2653 KiB  
Article
External Evaluation of Population Pharmacokinetics Models of Lithium in the Bipolar Population
by Aurélie Lereclus, Andréa Boniffay, Gauvind Kallée, Olivier Blin, Raoul Belzeaux, Dayan Frédéric, Sylvain Benito and Romain Guilhaumou
Pharmaceuticals 2023, 16(11), 1627; https://doi.org/10.3390/ph16111627 - 18 Nov 2023
Viewed by 907
Abstract
Lithium has been used in the treatment of bipolar disorder for several decades. Treatment optimization is recommended for this drug, due to its narrow therapeutic range and a large pharmacokinetics (PK) variability. In addition to therapeutic drug monitoring, attempts have been made to [...] Read more.
Lithium has been used in the treatment of bipolar disorder for several decades. Treatment optimization is recommended for this drug, due to its narrow therapeutic range and a large pharmacokinetics (PK) variability. In addition to therapeutic drug monitoring, attempts have been made to predict individual lithium doses using population pharmacokinetics (popPK) models. This study aims to assess the clinical applicability of published lithium popPK models by testing their predictive performance on two different external datasets. Available PopPK models were identified and their predictive performance was determined using a clinical dataset (46 patients/samples) and the literature dataset (89 patients/samples). The median prediction error (PE) and median absolute PE were used to assess bias and inaccuracy. The potential factors influencing model predictability were also investigated, and the results of both external evaluations compared. Only one model met the acceptability criteria for both datasets. Overall, there was a lack of predictability of models; median PE and median absolute PE, respectively, ranged from −6.6% to 111.2% and from 24.4% to 111.2% for the literature dataset, and from −4.5% to 137.6% and from 24.9% to 137.6% for the clinical dataset. Most models underpredicted the observed concentrations (7 out of 10 models presented a negative bias). Renal status was included as a covariate of lithium’s clearance in only two models. To conclude, most of lithium’s PopPK models had limited predictive performances related to the absence of covariates of interest included, such as renal status. A solution to this problem could be to improve the models with methodologies such as metamodeling. This could be useful in the perspective of model-informed precision dosing. Full article
(This article belongs to the Special Issue Population Pharmacokinetic and Pharmacodynamics)
Show Figures

Figure 1

Back to TopTop