Application of PKPD Modeling in Drug Discovery and Development

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About this Research Topic

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Background

Applying PKPD modeling in drug discovery and development has emerged as a powerful and indispensable approach to understanding the intricate relationship between drug kinetics and pharmacological effects. The integration of PKPD modeling allows researchers to quantitatively explore drug behavior, optimize dosing regimens, predict efficacy and safety, and identify potential drug-drug interactions.

In recent years, advances in computational methods, data availability, and technology have bolstered the application of PKPD modeling across various drug development stages. This interdisciplinary field has provided crucial insights into dose selection, personalized medicine, and translating preclinical findings to human responses. Moreover, PKPD modeling has accelerated drug development, minimized trial costs, and facilitated regulatory approvals.

This Research Topic seeks to present innovative studies, methodological advancements, and comprehensive reviews that highlight the ever-evolving significance of PKPD modeling in advancing drug discovery and development, ultimately promoting safer and more effective medications for patients worldwide.

Dose Selection and Optimization: PKPD modeling helps in determining the most appropriate dose and dosing regimen for a drug candidate. It allows researchers to understand the relationship between drug exposure (pharmacokinetics) and pharmacological effects (pharmacodynamics), guiding the selection of doses that achieve the desired therapeutic outcomes with minimal side effects.

Predicting Efficacy and Safety: By modeling the concentration-effect relationship, PKPD modeling can predict drug efficacy and safety in different patient populations. It aids in identifying potential responders and non-responders, as well as individuals at higher risk of adverse events, enabling personalized treatment approaches.

Drug-Drug Interactions: PKPD modeling allows the assessment of drug-drug interactions by analyzing how co-administered medications may affect a drug's pharmacokinetics and pharmacodynamics. This helps in predicting potential interactions and adjusting dosing regimens accordingly.

Translation to Humans: PKPD modeling facilitates the translation of preclinical data from animal studies to predict drug behavior in humans. This supports early decision-making in the drug development process and reduces the risk of costly and time-consuming clinical trials for ineffective candidates.

Therapeutic Window: PKPD modeling helps define the therapeutic window, which is the range of drug exposures associated with optimal efficacy and acceptable safety. This information guides the establishment of safe and effective dosing regimens.

We welcome contributions that cover a wide range of themes, including but not limited to predicting drug behavior, optimizing dose selection, assessing drug-drug interactions, individualizing treatment strategies, and translating preclinical data to human efficacy and safety predictions.

We encourage original research articles, reviews, methodological papers, and perspective articles that present novel insights, cutting-edge methodologies, and case studies demonstrating the utility of PKPD modeling in various stages of drug development. Manuscripts should showcase the significance of PKPD modeling in accelerating drug discovery, enhancing therapeutic outcomes, and ultimately advancing personalized medicine. This Research Topic will be an informative platform for researchers, pharmacologists, and clinicians to exchange knowledge and foster innovations in the field of PKPD modeling in drug discovery and development.

Keywords: PKPD;drug efficacy;drug development

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