In-silico Pharmacology for Evidence-Based and Precision Medicine

Precision medicine, driven by genetic and physical characteristics, has emerged as a transformative approach in healthcare, aiming to provide personalised treatments with optimised efficacy and minimised side effects. This approach contrasts evidence-based medicine, which emphasises population-level data and trends. Technological advancements in pharmacometrics and quantitative systems pharmacology have revolutionised pharmaceutical research, enabling the identification of new drug targets and the development of innovative drug delivery systems. Computational methods, such as quantitative structure-activity relationship (QSAR) analysis and in silico pharmacology tools, have played a pivotal role in identifying potential drugs and repurposing existing ones. These computational approaches leverage diverse data sets and predictive models, leading to significant advancements in optimising drug safety and effectiveness. This transformative era, driven by precision medicine and computational pharmacology, holds immense potential for improving patient outcomes and advancing the field of medicine towards personalised and targeted therapeutic interventions.