This Research Topic aims to delve into the intersection of pharmacokinetics (PK), pharmacodynamics (PD), and cutting-edge computational technologies like artificial intelligence (AI) and machine learning (ML), offering a comprehensive view of how these areas are revolutionizing drug development.

Over the past decade, advancements in PK/PD modeling and simulation have transformed the way we understand drug behavior, leading to more precise dose predictions, improved safety profiles, and tailored therapeutic strategies. The integration of AI and ML has further accelerated these innovations, enabling the discovery of new drug candidates, optimizing treatment protocols, and personalizing healthcare in ways previously unimaginable. By combining traditional pharmacological insights with advanced computational tools, the field is moving toward a future where drug development is faster, more efficient, and increasingly predictive.

We invite original research, review articles, and case studies that address innovations, challenges, and the application of cutting-edge technologies in these areas. Key topics of interest include:

Pharmacokinetics and Pharmacodynamics:

-Recent advances in PK/PD modeling techniques.

-Applications of PK/PD in understanding drug efficacy, safety, and dose optimization.

-Population-based approaches and special populations (e.g., pediatrics, geriatrics).

-Integration of PBPK (Physiologically Based Pharmacokinetic) and PBBM (Physiologically Based Biopharmaceutics) models.

AI and Machine Learning in Drug Development:

-The role of AI and ML in accelerating drug discovery and development.

-Machine learning applications in predicting drug absorption, distribution, metabolism, and excretion (ADME).

-AI-based predictive models for drug efficacy and safety.

-Case studies on AI-driven drug repositioning and optimization.

-Ethical considerations and regulatory perspectives on the use of AI/ML in drug development.

Interdisciplinary Approaches and Future Perspectives:

-How AI/ML can enhance PK/PD modeling and simulations.

-Novel algorithms and computational tools for improving drug design and personalized medicine.

-Collaborative efforts between computational scientists, biopharmaceutics experts, and clinicians to foster innovation.

Are you interested in contributing a manuscript to this Research Topic?

Innovative Horizons in Pharmaceutical Modeling: Cutting-Edge Research and Applications.