Advancing Precision Medicine: A Review of Innovative In Silico Approaches for Drug Development, Clinical Pharmacology and Personalized Healthcare

Abstract

The landscape of medical treatments is undergoing a transformative shift. Precision medicine has ushered in a revolutionary era in healthcare by individualizing diagnostics and treatments according to each patient’s uniquely evolving health status. This groundbreaking method of tailoring disease prevention and treatment considers individual variations in genes, environments, and lifestyles. The goal of precision medicine is to target the “five rights”: the right patient, the right drug, the right time, the right dose, and the right route. In this pursuit, in silico techniques have emerged as an anchor, driving precision medicine forward and making this a realistic and promising avenue for personalized therapies. With the advancements in high-throughput DNA sequencing technologies, genomic data, including genetic variants and their interactions with each other and the environment, can be incorporated into clinical decision-making. Pharmacometrics, gathering pharmacokinetic (PK) and pharmacodynamic (PD) data, and mathematical models further contribute to drug optimization, drug behavior prediction, and drug–drug interaction identification. Digital health, wearables, and computational tools offer continuous monitoring and real-time data collection, enabling treatment adjustments. Furthermore, the incorporation of extensive datasets in computational tools, such as electronic health records (EHRs) and omics data, is also another pathway to acquire meaningful information in this field. Although they are fairly new, machine learning (ML) algorithms and artificial intelligence (AI) techniques are also resources researchers use to analyze big data and develop predictive models. This review explores the interplay of these multiple in silico approaches in advancing precision medicine and fostering individual healthcare. Despite intrinsic challenges, such as ethical considerations, data protection, and the need for more comprehensive research, this marks a new era of patient-centered healthcare. Innovative in silico techniques hold the potential to reshape the future of medicine for generations to come.

A Physiologically Based Pharmacokinetic (PBPK) Study to Assess the Adjuvanticity of Three Peptides in an Oral Vaccine

“…Additionally, it is possible to include physiological characteristics in the model, allowing the prediction of pharmacokinetics (PK) and dose under specific disease states or in special populations such as the elderly, children, and pregnant women. These studies also provide capabilities to explore Drug–Drug Interactions (DDIs) and different formulations, allowing predictions of drug behavior if administered through different routes [ 17 , 18 ].…”

“…The aim of this model was to predict the biodistribution of α-tocopherol in a healthy male human after a single dose of squalene-containing adjuvant through the IM route [ 20 ]. For vaccines, in addition to PBPK studies, there are other in silico studies that may help testing immunologic properties and correlates of protection [ 17 ]. For instance, a Population Pharmacokinetics (PopPK) model was built in 2021 for an HIV vaccine.…”

Editorial: Precision medicine: recent advances, current challenges and future perspectives

“…Unlike most medical treatments obtained from large-scale studies and designed as “one-size-fits-all” approach, precision medicine is a modern concept of personalized treatment that aims to provide patients with tailored medical interventions to each individual characteristics ( Beckmann and Lew, 2016 ; Akhoon, 2021 ; Marques et al, 2024 ). Precision medicine is advantageous in being dynamic, evolving, and wholesome as it accounts for patients’ medical history, molecular profiles, lifestyle, and external factors within their environment ( Faulkner et al, 2020 ; Denny and Collins, 2021 ).…”

“…This patient-centered clinical approach needs to identify specific disease subtypes and to classify patients into various subpopulations that differ in their response and susceptibility to traditional treatments ( Wang and Wang, 2023 ; Marques et al, 2024 ). The diversity of pharmacological mechanisms and targets can permit therapies to efficiently treat particular clinical patients.…”

“…These studies highlight the importance of collective knowledge of the diverse pharmacological strategies, mechanisms, and targets as well as the in-and-out details of patients for the success of treatments. Such integration may also ultimately lead to changes in the regulatory, ethical, and policy domains of drug therapy ( Faulkner et al, 2020 ; Marques et al, 2024 ).…”