Recent Advances in Population Pharmacokinetics and Pharmacodynamics

A special issue of Pharmaceutics (ISSN 1999-4923). This special issue belongs to the section "Pharmacokinetics and Pharmacodynamics".

Deadline for manuscript submissions: closed (31 January 2023) | Viewed by 5596

Special Issue Editors


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Department of Pharmacokinetics and Clinical Pharmacy, Faculty of Pharmacy, University of Belgrade, 11221 Belgrade, Serbia
Interests: clinical pharmacokinetics; population PKPD models; pharmacometrics; TDM; model-informed dosing optimization; NONMEM
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Guest Editor
Department of Pharmaceutics and Food Technology, School of Pharmacy, Complutense University of Madrid, CP 28040 Madrid, Spain
Interests: model-based drug development; pharmacokinetics; pharmacodynamics; disease modeling; HIV-TB therapy optimization
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Special Issue Information

Dear Colleagues,

Population pharmacokinetic/pharmacodynamic (PopPKPD) modeling represents the youngest and most powerful of all of the methodological approaches used for drug data analysis; therefore, it still evolves, advances, and expands its application. Nevertheless, its contribution to decision making throughout all drug development phases and clinical therapy decisions is greatly supported by the EU and US regulatory bodies while being acknowledged by the pharmaceutical industry and academia. PopPKPD analysis can be utilized to identify covariates that significantly impact variability in drug exposure and response, inform dosing regimens for evaluation in clinical trials, support dose recommendations in special populations, or optimize dosages according to patients’ characteristics in clinical settings.

The goal of this Special Issue is to provide some insight into a few of the recent advances seen in the PopPKPD field. Therefore, we invite you to contribute with your competencies via review and original scientific manuscripts as well as shape the upcoming Special Issue of Pharmaceutics.

Prof. Dr. Katarina Vučićević
Dr. Maria Garcia-Cremades Mira
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. Pharmaceutics 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

  • population PK/PD models
  • nonlinear mixed-effects modeling
  • variability in drug response
  • disease models
  • model-informed drug dosing optimization
  • time-to-event models
  • simulation analysis

Published Papers (3 papers)

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19 pages, 3317 KiB  
Article
Comparison of Seven Non-Linear Mixed Effect Model-Based Approaches to Test for Treatment Effect
by Estelle Chasseloup and Mats O. Karlsson
Pharmaceutics 2023, 15(2), 460; https://doi.org/10.3390/pharmaceutics15020460 - 30 Jan 2023
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Abstract
Analyses of longitudinal data with non-linear mixed-effects models (NLMEM) are typically associated with high power, but sometimes at the cost of inflated type I error. Approaches to overcome this problem were published recently, such as model-averaging across drug models (MAD), individual model-averaging (IMA), [...] Read more.
Analyses of longitudinal data with non-linear mixed-effects models (NLMEM) are typically associated with high power, but sometimes at the cost of inflated type I error. Approaches to overcome this problem were published recently, such as model-averaging across drug models (MAD), individual model-averaging (IMA), and combined Likelihood Ratio Test (cLRT). This work aimed to assess seven NLMEM approaches in the same framework: treatment effect assessment in balanced two-armed designs using real natural history data with or without the addition of simulated treatment effect. The approaches are MAD, IMA, cLRT, standard model selection (STDs), structural similarity selection (SSs), randomized cLRT (rcLRT), and model-averaging across placebo and drug models (MAPD). The assessment included type I error, using Alzheimer’s Disease Assessment Scale-cognitive (ADAS-cog) scores from 817 untreated patients and power and accuracy in the treatment effect estimates after the addition of simulated treatment effects. The model selection and averaging among a set of pre-selected candidate models were driven by the Akaike information criteria (AIC). The type I error rate was controlled only for IMA and rcLRT; the inflation observed otherwise was explained by the placebo model misspecification and selection bias. Both IMA and rcLRT had reasonable power and accuracy except under a low typical treatment effect. Full article
(This article belongs to the Special Issue Recent Advances in Population Pharmacokinetics and Pharmacodynamics)
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13 pages, 2076 KiB  
Article
Alternative Pharmacokinetic Metrics in Single-Dose Studies to Ensure Bioequivalence of Prolonged-Release Products at Steady State—A Case Study
by Víctor Mangas-Sanjuán, Marta Simón, Esperanza González-Rojano, Dolores Ochoa, Francisco Abad-Santos, Manuel Román, Mercedes Ramos, Carlos Govantes and Alfredo García-Arieta
Pharmaceutics 2023, 15(2), 409; https://doi.org/10.3390/pharmaceutics15020409 - 26 Jan 2023
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Abstract
(1) Background: this article investigates which PK metrics in a single-dose study (concentration at the end of posology interval, Cτ, partial areas under the curve, pAUCs, or half-value duration, HVD) are more sensitive and less variable for predicting the failure of [...] Read more.
(1) Background: this article investigates which PK metrics in a single-dose study (concentration at the end of posology interval, Cτ, partial areas under the curve, pAUCs, or half-value duration, HVD) are more sensitive and less variable for predicting the failure of a prolonged-release product at steady-state that was the bioequivalent for Cmax, AUC0-t and AUC0-inf, in the single-dose study; (2) Methods: a cross-over study was performed in 36 subjects receiving desvenlafaxine 100 mg prolonged-release tablets. Conventional (Cmax, AUC0-t and AUC0-inf) and additional (Cτ, pAUCs and HVD) PK metrics were considered after single-dose conditions. Predicted PK metrics at steady state (AUC0-τ, Cmax,ss, and Cτ,ss) were derived using a population PK model approach; (3) Results: the existing differences in the shape of the concentration–time curves precluded to show equivalence for Cτ,ss in the simulated study at steady state. This failure to show equivalence at steady state was predicted by Cτ, pAUCs and HVD in the single-dose study. Cτ was the most sensitive metric for detecting the different shape, with a lower intra-subject variability than HVD; (4) Conclusions: conventional PK metrics for single-dose studies (Cmax, AUC0-t and AUC0-inf) are not enough to guarantee bioequivalence at steady state for prolonged-release products. Full article
(This article belongs to the Special Issue Recent Advances in Population Pharmacokinetics and Pharmacodynamics)
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6 pages, 603 KiB  
Brief Report
Shedding a Light on Acyclovir Pharmacodynamics: A Retrospective Analysis on Pharmacokinetic/Pharmacodynamic Modelling of Acyclovir for the Treatment of Varicella Zoster Virus Infection in Immunocompromised Patients: A Pilot Study
by Geeske F. Grit, Anne-Grete Märtson, Marjolein Knoester, Marlous L. Toren-Wielema and Daan J. Touw
Pharmaceutics 2022, 14(11), 2311; https://doi.org/10.3390/pharmaceutics14112311 - 27 Oct 2022
Cited by 1 | Viewed by 1673
Abstract
Background: Acyclovir and valacyclovir are used for the treatment and prophylaxis of infections with herpes simplex virus (HSV) and varicella zoster virus (VZV). The aim of this study is to provide insight into the pharmacodynamics (PD) of (val)acyclovir. Methods: Patients were retrospectively selected, [...] Read more.
Background: Acyclovir and valacyclovir are used for the treatment and prophylaxis of infections with herpes simplex virus (HSV) and varicella zoster virus (VZV). The aim of this study is to provide insight into the pharmacodynamics (PD) of (val)acyclovir. Methods: Patients were retrospectively selected, based on therapeutic drug monitoring for acyclovir, to create a population pharmacokinetic (PK) model in Pmetrics. This PK model was used to develop a PK/PD model to study the effect of acyclovir levels on VZV viral load in plasma in immunocompromised patients. Results: Immunocompromised patients with known VZV viral loads in plasma were included for PK/PD modelling (N = 4, with 23 measure points); they were part of the population of 43 patients used for PK model building. The PK/PD model described the data well (r2 = 0.83). This is a hopeful first step in clarifying the pharmacodynamics of acyclovir; however, the data in this study are limited. Conclusions: Our preliminary PK/PD model can be used in further research to determine the effect of acyclovir levels on VZV viral load. Full article
(This article belongs to the Special Issue Recent Advances in Population Pharmacokinetics and Pharmacodynamics)
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