Pharmacoinformatics: New developments and challenges in drug design

Pharmacoinformatics combines bio- and chemoinformatics approaches as well as artificial intelligence to support drug design and development at various stages, starting from preclinical research support to clinical trial design and execution support (stages I, II and III), as well as pharmacovigilance, pharmacoeconomics and personalized medicine. The rational use of these methods, combined with the relevant experimental approaches, is crucial to face the new challenges in drug design and development.

In recent years, a growing number of pharmacoinformatics approaches have been developed and implemented to enhance the design and development of therapeutic alternatives for multiple pathologies. In fact, the training of professionals working in this field is getting increasingly complemented by this type of approaches.

As such, we consider it crucial to show the most relevant advances in the design, development, improvement, and implementation of approaches that face the main challenges when designing new drugs. They aim at improving pharmacokinetic and toxicological profiles, increasing selectivity and bioavailability, finding novel chemical groups with activity against key targets in complex pathologies, finding molecular descriptions of mechanisms of action, pharmaceutical monitoring and surveillance, clinical trials, personalized medicine, etc.

The scope of this research topic involves subtopics where pharmacoinformatics tools are used to enhance drug design processes such as:

- Accelerate drug discovery and development.
- Identify novel molecular targets.
- Increase the efficacy of clinical trials.
- Computer-driven polypharmacology.
- Personalize and create targeted drugs.
- Reduce cost and increase drug adherence.
- Gain improved insight into marketing and sales performance.
- Improve safety and risk management.

Research articles, review articles as well as short communications are welcome.

Keywords: Bioinformatics, Chemoinformatics, Drug design, Multitarget drug design, System Pharmacology Network Pharmacology, Machine Learning, Artificial Intelligence, QSAR/QSRP modeling Ligand-based drug design, Structure-based drug design, Molecular docking, Molecular Dynamics Simulations, Virtual screening, ADME/Tox prediction

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.