In Silico Pharmacokinetic and Pharmacodynamic (PK-PD) Modeling

Dear Colleagues,

Pharmacokinetic and pharmacodynamic (PK-PD) modeling is an essential tool in modern drug development and therapeutic optimization. Leveraging recent advancements in computational methods, including physiologically based pharmacokinetic (PBPK) modeling and machine learning, researchers can simulate complex biological systems, predict therapeutic outcomes, and refine dosing strategies with unprecedented precision.

This Special Issue aims to focus on the transformative integration of in silico approaches into PK-PD modeling, showcasing advancements in methodology, computational tools, and their translational applications. By addressing key challenges in precision medicine, regulatory science, and clinical decision-making, we aim to foster interdisciplinary innovation and broaden the impact of in silico modeling on healthcare outcomes.

Key Topics of Interest:

• Physiologically Based Pharmacokinetic (PBPK) and Toxicokinetic (PBTK) Modeling: Predicting ADME processes across populations and physiological conditions; regulatory applications.
• Population Pharmacokinetics (PopPKs): Mixed-effects modeling of inter-individual variability in drug exposure and response.
• Quantitative Systems Pharmacology (QSP): Integrating systems biology with PK-PD to evaluate drug interactions within complex networks.
• Bayesian Pharmacometric Modeling: Utilizing Bayesian methods to incorporate prior knowledge for personalized therapy optimization.
• Artificial Intelligence and Machine Learning in PK-PD: Applications in drug interaction prediction, dose optimization, and precision medicine.
• In Silico Bioequivalence: Reducing clinical trial reliance through computational approaches.
• Multi-Objective Optimization: Balancing efficacy and toxicity in therapeutic regimens using advanced algorithms.
• Regulatory Science and Quality Assessment: Computational tools in regulatory decision-making and pharmaceutical product evaluation.
• Translational and Predictive Modeling: Real-world case studies demonstrating successful clinical implementation of in silico predictions.

Benefits of Publishing in This Special Issue:

• Enhanced visibility and citation potential through focused dissemination.
• Opportunities for interdisciplinary collaboration across computational biology, clinical pharmacology, and pharmaceutical sciences.
• Contribution to the advancement of cutting-edge in silico modeling techniques and applications.

Submit your manuscript today and contribute to the future of precision pharmacology and computational innovation!

Prof. Dr. Neal M. Davies
Prof. Dr. Raimar Löbenberg
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 250 words) can be sent to the Editorial Office for assessment.

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.