Polypharmacy prescribing guidance - draft: consultation

23. Appendix K: Pharmacogenomics and Polypharmacy

Research Questions

Q1: “What is the role of pharmacogenomics in identifying and improving appropriate prescribing/polypharmacy?

Q2: Is it economically viable? Each genomics test costs over £200 at the moment.

The context is: pharmacogenomics and appropriate prescribing

What were we asked to look at and why?

Population People taking multiple medications one of which is a high-risk medication

Intervention Undertaking review of appropriateness of prescribing using pharmacogenomic testing to maximise efficacy in the use of medications as part of medication review.

Comparator Medication review without pharmacogenomic testing

Outcomes Reduction in inappropriate prescribing and improvement in patient outcomes

Study Design SR/GL

Key words

Polypharmacy and pharmacogenomic testing, high risk medication, medication appropriateness, medicines management and pharmacogenomic testing, economic impact of pharmacogenomic testing in a medication review

The importance of this topic

The term ‘pharmacogenomics’, which is often used interchangeably with its predecessor term ‘pharmacogenetics’, has conventionally been defined as the study of how a person’s genetic make-up affects their response (efficacy and/or safety) to a drug. A broader definition of pharmacogenomics is the study of genomic technologies to enable the discovery and development of novel drugs, and the optimisation of drug dose and choice in individual patients to maximize efficacy and minimise toxicity.

The methodological approach we took

We conducted a systematic literature search was carried out between 23/01/2024 – 24/01/2024 to identify guidelines and systematic reviews. Medline, Embase, and Cochrane databases were searched for systematic reviews. Medline, Embase, and several guideline specific databases and producers’ websites were searched for guidelines, including the Guidelines International Network, SIGN and NICE.

Results were limited to 2021 onwards and English language publications. Concepts used in all searches included: polypharmacy, deprescribing, medication review / artificial intelligence, machine learning, deep learning. One person sifted the titles and abstracts, and then the full papers.

In line with SIGN 50, this Topic Exploration aim was to identify guidelines, Health Technology Assessments (HTAs), Cochrane reviews and other systematic reviews that exist in the topic of interest by searching several different sources. We therefore did not perform a detailed analysis of the reports retrieved, instead conducting a high-level review.

Summary of the evidence

We retrieved eight literature reviews; two scoping reviews; one systematic review; one rapid review; one study that analysed pharmacy claims data; one study that conducted a retrospective program review; one focus group; and one study that performed a proof-of-concept for a clinical care protocol.

Systematic review

O’Shea 2022 sought to establish the efficacy of interventions to inform the implementation of pharmacogenetic (PGx) guided therapy into clinical practice for people with multimorbidity and resulting polypharmacy. The interventions included multi-gene, multidrug, and multi-disease PGx interventions. The review found that the incorporation of PGx testing could have significant benefits for healthcare providers and patients by reducing healthcare utilisation and costs, improving identification of clinically significant drug interactions, and enhancing clinical decision-making. However, because of the lack of robust, high-quality studies, small sample sizes, and short follow-up durations, evidence on the efficacy of PGx interventions to improve outcomes in patients with multimorbidity or prescribed polypharmacy was lacking.

Narrative Reviews

Bellanca 2023 looked in part at PGx/genomic procedures as a means for reducing Adverse Drug Reactions (ADRs). They noted that when multiple drugs are taken, metabolism can also be affected by interactions with CYP450 enzymes.

Fujita 2023 examined precision medicine in polypharmacy. Lastly, they defined a proposed approach to provide precision medicine as part of a medication review for patients with polypharmacy based on screening tools to identify older adults with polypharmacy at high risk of adverse outcomes; a medication review informed by This included PGx testing as part of, DDIs prediction, physiological-pharmacokinetic-pharmacodynamic modelling and routinely used care assessment data stored in the electronic medical record.

Hayward 2021 contended that further increasing polypharmacy in primary care, and need for medicine optimisation, reinforces the value of assessment of multigene variants to assist decisions on the effectiveness of medication. Hence, they identified key issues and recommendations for implementing multigene variants panel testing in primary care. They noted that existing prescribing infrastructure including non-PGx Clinical Decision Support System (CDSS) and the primary care multidisciplinary approach to prescribing can act as a foundation for implementation of PGx testing and data into primary care. Additional considerations include defined clinical pathways, adequate reimbursement and provision of education through CDSS and educational programs.

Implementation of PGx requires further evidence for clinical utility, cost–effectiveness and scalability. Integration of PGx data with other patient data into patient record across all care settings can provide robust prescribing recommendations. They concluded that implementation of PGx testing within Primary Care settings could help address the challenge of polypharmacy and medicines optimisation within a resource-constrained healthcare system.

Marshe 2020 provided a review of genetic associations with antidepressant treatment outcomes, pharmacokinetic (PK) profiles and adverse drug reactions (ADRs) in older adults. They noted that polypharmacy may contribute to the variability observed in PK parameters. This is a concern given the increased risk for drug-drug interactions which may affect antidepressant treatment outcomes and result in ADRs. They noted that concomitant medications can mask genetic variation in CYP enzymes due to phenoconversion. They proposed that PGx studies in adults with late-life depression (LLD) should be conducted while adjusting for clinical heterogeneity, such as polypharmacy and including genome-wide data.

Mitropoulou 2020 provided an overview of the impact of the various personalised medicine interventions on patients’ benefit, from the view of patient management and the economics of these interventions. They noted that genomic medicine (personalised or precision medicine) holds promise to predict the disease onset early in life and to individualise drug prescription, known as pharmacogenomics (PGx), by taking advantage of an individual’s unique genomic profile, and optimising the drug treatment modalities for the benefit of the patient and the national healthcare.

Roman 2020 provided a conceptual framework and a roadmap for the clinical implementation of pharmacogenomics within geriatric ambulatory care settings to optimise patient care. PGx testing can significantly reduce rehospitalisation rates in patients aged 50 years and older taking a six or more concurrent medications. PGx education can enable optimal care for older adults to prevent inappropriate prescribing or the development of polypharmacy.

Sharp 2021 focused on how unnecessary polypharmacy is a national healthcare problem, and how implementing PGx testing into everyday practice could provide a solution. They noted that using PGx to target appropriate medications can decrease the number of prescriptions and reduce polypharmacy associated risks.

PGx testing allows the appropriate selection of medications, by enabling minimisation of potential ADRs/toxicity, reducing dosing adjustments, optimising drug efficacy, avoiding DDIs, and tackling the adverse risk of polypharmacy. The best time to incorporate PGx testing is thus before drugs are prescribed, (the pre-emptive approach). This is used to incorporate PGx information into an individual “drug response profile” to guide selection and dosing of a medication and avoid adverse effects of polypharmacy.

PGx testing can improve the economic burden associated with ADRs that may result from polypharmacy. For example, annual savings of $444,426 have been made on corresponding USA-based Medicare reimbursement rates for diagnosis-related group codes associated with acute coronary syndrome (ACS), and an average cost for PGx testing of $315 per person. The cost was completely offset by estimated total savings accrued from reduction of adverse events related to ACS. The evidence suggested PGx testing addressed polypharmacy, decreased adverse patient outcomes as well as associated economic burden.

Use of PGx-based testing in polypharmacy has the potential to reduce economic burden and adverse effects. However, the need remains for a CDSS that incorporates PGx information with other important clinical factors.

Scoping reviews

Hayashi 2022 sought to comprehensively map evidence of pharmacist-delivered PGx services, and evaluate patterns in the characteristics of pharmacy practices, patients, PGx tests, and clinical indications. For polypharmacy patients, antidepressants were the most common indication for genetic testing.

The emergence of panel-based PGx testing in the more medically complex within pharmacy practice make use of organ function, patient clinical signs and symptoms, and interactions other than drug-gene (e.g. drug-drug, drug-disease).

PGx testing used in the older polypharmacy population might have a greater clinical impact demonstrated by reduced hospitalisations. Genetic testing in pain management and anticoagulation might be beneficial, although the ideal populations and protocols have yet to be defined.

Meaddough 2021 assessed PGx testing for patients with polypharmacy because of the impact on patient care and comorbidities. Pharmacogenetic testing in patients with polypharmacy appears to be beneficial. There are two different approaches to PGx testing: reactive testing administered at the time of drug prescription; and pre-emptive PGx testing, of drug response genes in expectation of future prescription events. Psychiatric patients, elderly oncology and cardiology patients, are often prescribed multiple medications, and so are likely to benefit from pharmacogenetic testing.

There is an estimated annual cost savings of $3,962 per patient for PGx testing in patients diagnosed with major depressive disorder.

Analysis of pharmacy claims data

Jablonski 2019 analysed pharmacy claims data for the subset of 2,168 patients aged 65 years at the time of testing of PGx testing. Patients prescribed medications in concordance with the PGx recommendations saved US$2,774 per member per year (PMPY) and had two fewer total prescriptions PMPY and 10 fewer total medication refills PMPY, compared to contrasting prescribing.

Retrospective Program Review

Keogh 2022 conducted a retrospective program review for a pharmacogenomic medication management program among self-insured employees. Most participants (57.7%) who completed the program had polypharmacy (taking greater than five medications). They found inappropriate polypharmacy generally increased the risks of drug-drug, drug-disease, and drug-gene interactions.

Focus group

Magavern 2023 explored the perspectives of British people of South Asian ancestry on pharmacogenomic implementation and sharing pharmacogenomic clinical data for research. PGx testing was viewed as helpful for polypharmacy by decreasing risk of side effects and drug-drug interactions.

Proof-of-concept for a clinical care protocol

Silva 2021 sought to predict and confirm a subject’s response to their medication based in part on specific medication-associated genomic data. Polypharmacy patients and those with symptoms indicative of possible medication interactions were referred to the Interprofessional Pharmacogenomics clinic for evaluation which provides medication where chronic disease burden and polypharmacy are detrimental to health.

Rapid review

David 2021 sought to see whether prescribers accept PGx-guided recommendations for changes to prescribed medication. They noted that PGx can aid understanding of individual responses to medications, offering personalised approaches to safe and effective management of health conditions and reduce inappropriate polypharmacy, by controlling the selection of appropriate medications. A reactive testing approach on those at most risk of adverse drug reactions, such as older people, can target healthcare systems with finite resources in a more precise manner.

Exploration summary and conclusions

In summary, pharmacogenomic testing has the potential to improve medicines optimisation by providing information the individuals response to treatment, taking a person-centred approach. This will result in less medication related harm and improved patient outcomes. Some studies have shown that this approach is more economically viable. However, more evidence is needed together with a tested framework for implementation.

Retrieved papers:

Bellanca, C.M., Augello, E., Cantone, A.F., Di Mauro, R., Attaguile, G.A., Di Giovanni, V., Condorelli, G.A., Di Benedetto, G., Cantarella, G. and Bernardini, R., 2023. Insight into Risk Factors, Pharmacogenetics/Genomics, and Management of Adverse Drug Reactions in Elderly: A Narrative Review. Pharmaceuticals, 16(11), p.1542.

David, V., Fylan, B., Bryant, E., Smith, H., Sagoo, G.S. and Rattray, M., 2021. An analysis of pharmacogenomic-guided pathways and their effect on medication changes and hospital admissions: a systematic review and meta-analysis. Frontiers in genetics, 12, p.698148.

Fujita, K., Masnoon, N., Mach, J., O’Donnell, L.K. and Hilmer, S.N., 2023. Polypharmacy and precision medicine. Cambridge Prisms: Precision Medicine, 1, p.e22.

Hayashi, M., Hamdy, D.A. and Mahmoud, S.H., 2022. Applications for pharmacogenomics in pharmacy practice: A scoping review. Research in Social and Administrative Pharmacy, 18(7), pp.3094-3118.

Hayward, J., McDermott, J., Qureshi, N. and Newman, W., 2021. Pharmacogenomic testing to support prescribing in primary care: A structured review of implementation models. Pharmacogenomics, 22(12), pp.761-776.

Jablonski, M.R., Lorenz, R., Li, J. and Dechairo, B.M., 2020. Economic outcomes following combinatorial pharmacogenomic testing for elderly psychiatric patients. Journal of Geriatric Psychiatry and Neurology, 33(6), pp.324-332.

Keogh, M., Fragala, M.S., Peter, A.P., Lorenz, R.A., Goldberg, S.E. and Shaman, J.A., 2022. Early insights from a pharmacogenomic-enriched comprehensive medication management program implementation in an adult employee population. Journal of Occupational and Environmental Medicine, 64(12), p.e818.

Magavern, E.F., Durrani, F., Raza, M., Lerner, R., Islam, M.R., Genes & Health Research Team, Clinch, M. and Caulfield, M.J., 2023. British South Asian ancestry participants views of pharmacogenomics clinical implementation and research: a thematic analysis. The Pharmacogenomics Journal, 23(6), pp.185-194.

Marshe, V.S., Islam, F., Maciukiewicz, M., Bousman, C., Eyre, H.A., Lavretsky, H., Mulsant, B.H., Reynolds III, C.F., Lenze, E.J. and Müller, D.J., 2020. Pharmacogenetic implications for antidepressant pharmacotherapy in late-life depression: a systematic review of the literature for response, pharmacokinetics and adverse drug reactions. The American Journal of Geriatric Psychiatry, 28(6), pp.609-629.

Matos, A., Bankes, D.L., Bain, K.T., Ballinghoff, T. and Turgeon, J., 2020. Opioids, polypharmacy, and drug interactions: A technological paradigm shift is needed to ameliorate the ongoing opioid epidemic. Pharmacy, 8(3), p.154.

Meaddough, E.L., Sarasua, S.M., Fasolino, T.K. and Farrell, C.L., 2021. The impact of pharmacogenetic testing in patients exposed to polypharmacy: A scoping review. The Pharmacogenomics Journal, 21(4), pp.409-422.

Mitropoulou, C., Litinski, V., Kabakchiev, B., Rogers, S. and P Patrinos, G., 2020. PARC report: Health outcomes and value of personalized medicine interventions: Impact on patient care. Pharmacogenomics, 21(11), pp.797-807.

O’Shea, J., Ledwidge, M., Gallagher, J., Keenan, C. and Ryan, C., 2022. Pharmacogenetic interventions to improve outcomes in patients with multimorbidity or prescribed polypharmacy: a systematic review. The Pharmacogenomics Journal, 22(2), pp.89-99.

Roman, Y.M., Dixon, D.L., Salgado, T.M., Price, E.T., Zimmerman, K.M., Sargent, L. and Slattum, P.W., 2020. Challenges in pharmacotherapy for older adults: a framework for pharmacogenomics implementation. Pharmacogenomics, 21(9), pp.627-635.

Sharp, C.N., Linder, M.W. and Valdes Jr, R., 2020. Polypharmacy: a healthcare conundrum with a pharmacogenetic solution. Critical reviews in clinical laboratory sciences, 57(3), pp.161-180.

Silva, P., Jacobs, D., Kriak, J., Abu-Baker, A., Udeani, G., Neal, G. and Ramos, K., 2021. Implementation of pharmacogenomics and artificial intelligence tools for chronic disease management in primary care setting. Journal of Personalized Medicine, 11(6), p.443.