When using traditional approaches, such as pharmacokinetics and pharmacodynamics, the entire cellular or molecular response to drugs in the body cannot be fully ascertained or established. The oral medication process involves pharmacokinetics, followed by oral microbiomics and then gut microbiomics and pharmacodynamics. Recently, there has been increasing interest in the role of genetics (pharmacogenetics and pharmacogenomics) in both humans and microbiomes, as well as omics alterations (e.g., epigenetic, transcriptomic, proteomic, and metabolomic alterations as a consequence of drug exposure), which can help to ascertain the cellular responses to medications. Both the efficacy and toxicity of a drug are influenced by these factors. To assess these at an individual level, an integrative Personalized Medicine Model may be needed to help with medication management. Two example application cases for SSRIs and statins demonstrate the clinical usefulness of such a model, which can guide clinicians during drug selection and dosing to reduce reliance on trial-and-error, thus potentially improving patient outcomes and safety. Integrating this framework into practical clinical workflows requires the capture, analysis, and translation of multi-omics data in order to realize decision support protocols and actionable drug recommendations. This review also discusses IT requirements and different stakeholder roles. Although the proposed model can guide the treatment of diseases at the individual patient level, further research is still needed before it can be implemented as part of drug development research, clinical care, and healthcare delivery systems.
Alagiakrishnan et al. (Fri,) studied this question.