Exploring the Cutting Edge of Pharmacokinetics: Current Trends and Future Directions in Drug Behaviour and Therapy

Dear Colleagues,

In the last few years, we have seen that, after the COVID-19 pandemic, research has been advanced and focused mainly towards statistical, mathematical, machine learning, Artificial Intelligence and Deep learning. These methods were proved to be helpful in drug discovery and solving other biological problems. Among the utility of these methods, one field of focus is pharmacokinetic research, which is also called in silico pharmacokinetic (PK) research, which involves the use of computer models and simulations to study the behaviour of drugs in the body. This research aims to predict a drug’s pharmacokinetics, including its absorption, distribution, metabolism, and elimination (ADME), to improve drug development and design.

One of the main advantages of in silico PK research is that it allows for the efficient and cost-effective screening of large numbers of compounds, reducing the time and resources required for traditional in vivo and in vitro studies. This can lead to a faster and more accurate identification of the best drug candidates and a better understanding of the PK properties of new drugs. PK allows for the prediction of drug interactions, toxicity, and side effects, optimizing dosing regimens and reducing the risks associated with clinical trials. In addition, in silico PK models can also be used to predict PK behaviour in specific populations, such as children, the elderly, and patients with specific diseases, allowing for personalized medicine.

However, in silico PK research also has some limitations, including the need for accurate and reliable data, to build and validate the models, as well as the limited ability to fully capture the complexity of drug behaviour in the body of individuals due to differences in genetics, age, sex, weight, liver and kidney function, and disease state. The pharmacokinetics of a drug can be greatly impacted by interactions with other drugs, including alterations in absorption, distribution, metabolism, and elimination. This can lead to unpredictable drug responses and increased toxicity. Overall, the field of pharmacokinetics is constantly evolving, with new advances and technologies leading to new areas of research. These research efforts are aimed at improving our understanding of drug behaviour in the body and optimizing drug development and therapy.

In this Issue, we will cover the most recent advances in all aspects of PK, and we invite original research articles and review papers, which present a better understanding of pharmacokinetics.

Dr. Yogesh Kumar
Guest Editor

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• pharmacokinetics
• artificial intelligence
• machine learning
• deep learning
• personalized medicine
• in silico pharmacokinetics
• toxicity