Special Issue "Innovative Tools for Therapeutic Drug Monitoring, 2nd Edition"

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

Deadline for manuscript submissions: 30 November 2023 | Viewed by 538

Special Issue Editor

Department of Pharmacology and Toxicology, Université de Reims Champagne-Ardenne, HERVI, CHU Reims, 51100 Reims, France
Interests: pharmacology and pharmacokinetic-pharmacodynamic modelling; therapeutic drug monitoring; clinical research methodology
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Special Issue Information

Dear Colleagues,

The variability of drug response complicates the prediction of the risk–benefit balance, limiting the real benefit of a treatment. The pharmacometrics approach provides an attractive solution to characterize the variability of response to drugs and identify the clinical and biological parameters for therapeutic drug monitoring.

If this variability is considered, a priori adaptation can be proposed. A more precise a posteriori optimization can also be made when integrating drug concentrations and metabolites in biological matrices, combined, if necessary, with pharmacogenetic data. The integration of clinical data (patient characteristics, clinical response, undesirable effects, toxic effects) finally makes it possible to propose a more rational individualization.

Pharmacological therapeutic monitoring aims to satisfy this need to adapt treatments to each clinical situation.

This Special Issue provides a panorama of state-of-the-art therapeutic drug monitoring and its tools. Examples of modern approaches to adapting dosages for different pharmacological classes in different medical specialties and situations such as anesthesia, infection, psychiatry, neurology, cardiology, oncology, intensive care medicine, nephrology, chronic inflammatory diseases, etc., are also welcome.

Prof. Dr. Zoubir Djerada
Guest Editor

Manuscript Submission Information

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  • therapeutic drug
  • monitoring pharmacokinetic/pharmacodynamic modeling
  • bayesian therapeutic drug monitoring
  • biomarkers
  • bioanalysis

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Published Papers (1 paper)

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LC-MS/MS Method for the Quantification of PARP Inhibitors Olaparib, Rucaparib and Niraparib in Human Plasma and Dried Blood Spot: Development, Validation and Clinical Validation for Therapeutic Drug Monitoring
Pharmaceutics 2023, 15(5), 1524; https://doi.org/10.3390/pharmaceutics15051524 - 18 May 2023
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Poly (ADP-ribose) polymerase inhibitors (PARPis) are becoming increasingly meaningful in oncology, and their therapeutic drug monitoring (TDM) might be beneficial for patients. Several bioanalytical methods have been reported for PARPis quantification in human plasma, but advantages might be obtained using dried blood spot [...] Read more.
Poly (ADP-ribose) polymerase inhibitors (PARPis) are becoming increasingly meaningful in oncology, and their therapeutic drug monitoring (TDM) might be beneficial for patients. Several bioanalytical methods have been reported for PARPis quantification in human plasma, but advantages might be obtained using dried blood spot (DBS) as a sampling technique. Our aim was to develop and validate a liquid chromatography-tandem mass spectrometric (LC-MS/MS) method for olaparib, rucaparib, and niraparib quantification in both human plasma and DBS matrices. Additionally, we aimed to assess the correlation between the drug concentrations measured in these two matrices. DBS from patients was obtained using Hemaxis DB10 for volumetric sampling. Analytes were separated on a Cortecs-T3 column and detected with electrospray ionization (ESI)-MS in positive ionization mode. Validation was performed according to the latest regulatory guidelines, in the range (ng/mL) 140–7000 for olaparib, 100–5000 for rucaparib, and 60–3000 for niraparib, within the hematocrit (Hct) range 29–45%. The Passing–Bablok and Bland–Altman statistical analyses revealed a strong correlation between plasma and DBS for olaparib and niraparib. However, due to the limited amount of data, it was challenging to establish a robust regression analysis for rucaparib. To ensure a more reliable assessment, additional samples are required. The DBS-to-plasma ratio was used as a conversion factor (CF) without considering any patient-related hematological parameters. These results provide a solid basis for the feasibility of PARPis TDM using both plasma and DBS matrices. Full article
(This article belongs to the Special Issue Innovative Tools for Therapeutic Drug Monitoring, 2nd Edition)
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