Economic Outcomes Following Combinatorial Pharmacogenomic Testing for Elderly Psychiatric Patients

Scoping review of enablers and challenges of implementing pharmacogenomics testing in the primary care settings

INTRODUCTION

Pharmacogenomic testing (PGx) plays a crucial role in improving patient medication safety, yet ethical concerns and limitations impede its clinical implementation in the primary care settings.

AIMS

To systematically review the current state of PGx in the primary care settings and determine the enablers and challenges of its implementation.

DESIGN

A scoping review was carried out by adhering to Arksey and O'Malley's 6-stage methodological framework and the 2020 Joanna Briggs Institute and Levac et al. DATA SOURCES: Cochrane Library, EMBASE, Global Health, MEDLINE and PubMed were searched up to 17 July 2023.

ELIGIBILITY CRITERIA

All peer-reviewed studies in English, reporting the enablers and the challenges of implementing PGx in the primary care settings were included.

DATE EXTRACTION AND SYNTHESIS

Two independent reviewers extracted the data. Information was synthesised based on the reported enablers and the challenges of implementing PGx testing in the primary care settings. Information was then presented to stakeholders for their inputs.

RESULTS

78 studies discussing the implementation of PGx testing are included, of which 57% were published between 2019 and 2023. 68% of the studies discussed PGx testing in the primary care setting as a disease-specific themes. Healthcare professionals were the major stakeholders, with primary care physicians (55%) being the most represented. Enablers encompassed various advantages such as diagnostic and therapeutic benefits, cost reduction and the empowerment of healthcare professionals. Challenges included the absence of sufficient scientific evidence, insufficient training for healthcare professionals, ethical and legal aspects of PGx data, low patient awareness and acceptance and the high costs linked to PGx testing.

CONCLUSION

PGx testing integration in primary care requires increased consumer awareness, comprehensive healthcare provider training on legal and ethical aspects and global feasibility studies to better understand its implementation challenges. Managing high costs entails streamlining processes, advocating for reimbursement policies and investing in research on innovation and affordability research to improve life expectancy.

Optimising Seniors' Metabolism of Medications and Avoiding Adverse Drug Events Using Data on How Metabolism by Their P450 Enzymes Varies with Ancestry and Drug-Drug and Drug-Drug-Gene Interactions

Many individuals ≥65 have multiple illnesses and polypharmacy. Primary care physicians prescribe >70% of their medications and renew specialists’ prescriptions. Seventy-five percent of all medications are metabolised by P450 cytochrome enzymes. This article provides unique detailed tables how to avoid adverse drug events and optimise prescribing based on two key databases. DrugBank is a detailed database of 13,000 medications and both the P450 and other complex pathways that metabolise them. The Flockhart Tables are detailed lists of the P450 enzymes and also include all the medications which inhibit or induce metabolism by P450 cytochrome enzymes, which can result in undertreatment, overtreatment, or potentially toxic levels. Humans have used medications for a few decades and these enzymes have not been subject to evolutionary pressure. Thus, there is enormous variation in enzymatic functioning and by ancestry. Differences for ancestry groups in genetic metabolism based on a worldwide meta-analysis are discussed and this article provides advice how to prescribe for individuals of different ancestry. Prescribing advice from two key organisations, the Dutch Pharmacogenetics Working Group and the Clinical Pharmacogenetics Implementation Consortium is summarised. Currently, detailed pharmacogenomic advice is only available in some specialist clinics in major hospitals. However, this article provides detailed pharmacogenomic advice for primary care and other physicians and also physicians working in rural and remote areas worldwide. Physicians could quickly search the tables for the medications they intend to prescribe.

Challenges and Future Prospects of Precision Medicine in Psychiatry

Precision medicine is increasingly recognized as a promising approach to improve disease treatment, taking into consideration the individual clinical and biological characteristics shared by specific subgroups of patients. In specific fields such as oncology and hematology, precision medicine has already started to be implemented in the clinical setting and molecular testing is routinely used to select treatments with higher efficacy and reduced adverse effects. The application of precision medicine in psychiatry is still in its early phases. However, there are already examples of predictive models based on clinical data or combinations of clinical, neuroimaging and biological data. While the power of single clinical predictors would remain inadequate if analyzed only with traditional statistical approaches, these predictors are now increasingly used to impute machine learning models that can have adequate accuracy even in the presence of relatively small sample size. These models have started to be applied to disentangle relevant clinical questions that could lead to a more effective management of psychiatric disorders, such as prediction of response to the mood stabilizer lithium, resistance to antidepressants in major depressive disorder or stratification of the risk and outcome prediction in schizophrenia. In this narrative review, we summarized the most important findings in precision medicine in psychiatry based on studies that constructed machine learning models using clinical, neuroimaging and/or biological data. Limitations and barriers to the implementation of precision psychiatry in the clinical setting, as well as possible solutions and future perspectives, will be presented.