A Quantitative Clinical Pharmacology-Based Framework For Model-Informed Vaccine Development.
| Autor: | Desikan R; Clinical Pharmacology Modelling & Simulation, GSK, United Kingdom. Electronic address: rajat.x.desikan@gsk.com., Germani M; Clinical Pharmacology Modelling & Simulation, GSK, Belgium., van der Graaf PH; Certara QSP, Canterbury Innovation Centre, University Road, Canterbury CT2 7FG, United Kingdom; Leiden Academic Centre for Drug Research, Einsteinweg 55, 2333 CC Leiden, Netherlands., Magee M; Clinical Pharmacology Modelling & Simulation, GSK, United States. |
|---|---|
| Jazyk: | angličtina |
| Zdroj: | Journal of pharmaceutical sciences [J Pharm Sci] 2024 Jan; Vol. 113 (1), pp. 22-32. Date of Electronic Publication: 2023 Nov 02. |
| DOI: | 10.1016/j.xphs.2023.10.043 |
| Abstrakt: | Historically, vaccine development and dose optimization have followed mostly empirical approaches without clinical pharmacology and model-informed approaches playing a major role, in contrast to conventional drug development. This is attributed to the complex cascade of immunobiological mechanisms associated with vaccines and a lack of quantitative frameworks for extracting dose-exposure-efficacy-toxicity relationships. However, the Covid-19 pandemic highlighted the lack of sufficient immunogenicity due to suboptimal vaccine dosing regimens and the need for well-designed, model-informed clinical trials which enhance the probability of selection of optimal vaccine dosing regimens. In this perspective, we attempt to develop a quantitative clinical pharmacology-based approach that integrates vaccine dose-efficacy-toxicity across various stages of vaccine development into a unified framework that we term as model-informed vaccine dose-optimization and development (MIVD). We highlight scenarios where the adoption of MIVD approaches may have a strategic advantage compared to conventional practices for vaccines. Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.) |
| Databáze: | MEDLINE |
| Externí odkaz: |
|