Polypharmacy: a healthcare conundrum with a pharmacogenetic solution

Use of drugs with pharmacogenomics (PGx)-based dosing guidelines in a Danish cohort of persons with chronic kidney disease, both on dialysis and not on dialysis: Perspectives for prescribing optimization

AIM

The objective of this registry study is to assess the utilization of pharmacogenomic (PGx) drugs among patients with chronic kidney disease (CKD).

METHODS

This study was a retrospective study of patients affiliated with the Department of Nephrology, Aalborg University Hospital, Denmark in 2021. Patients diagnosed with CKD were divided into CKD without dialysis and CKD with dialysis. PGx prescription drugs were retrieved from the Patient Administration System. Actionable dosing guidelines (AG) for specific drug-gene pairs for CYP2D6, CYP2C9, CYP2C19 and SLCO1B1 were retrieved from the PharmGKB homepage.

RESULTS

Out of 1241 individuals, 25.5% were on dialysis. The median number of medications for each patient was 9 within the non-dialysis group and 16 within the dialysis group. Thirty-one distinct PGx drugs were prescribed. Altogether, 76.0% (943 individuals) were prescribed at least one PGx drug and the prevalence of prescriptions of PGx drugs was higher in the dialysis group compared to the non-dialysis group. The most frequently prescribed drugs with AG were metoprolol, pantoprazole, atorvastatin, simvastatin and warfarin.

CONCLUSION

This study demonstrated that a substantial proportion of patients with CKD are exposed to drugs or drug combinations for which there exists AG related to PGx of CYP2D6, CYP2C19, CYP2C9 and SLCO1B1.

Binder jetting 3D printing in fabricating pharmaceutical solid products for precision medicine

Current treatment strategies are moving towards patient-centricity, which emphasizes the need for new solutions allowing for medication tailored to a patient. This can be realized by precision medicine where patient diversity is considered during treatment. However, the broader use of precision medicine is restricted by the current technological solutions and rigid manufacturing of pharmaceutical products by mass production principles. Additive manufacturing of pharmaceutical products can provide a feasible solution to this challenge. In this review, a particular subtype of additive manufacturing, that is, binder jetting 3D printing, is introduced as a solution for fabricating pharmaceutical solid products that can be considered as precision medicine. Technical aspects, practical applications, unique advantages and challenges related to this technique are discussed, indicating that binder jetting 3D printing possesses the potential for fabricating already new product prototypes, where diversity in patient treatment in terms of the needs for specific drug type, dose and drug release can be accounted. To further advance this type of mass customization of pharmaceuticals, multidisciplinary research initiatives are needed not only to cover the engineering aspects but also to bridge these innovations with patient-centric perspectives.

Implementation of pharmacogenomics testing for precision medicine

Great strides have been made in the past decade to lower barriers to clinical pharmacogenomics implementation. Nevertheless, PGx consultation prior to prescribing therapeutics is not yet mainstream. This review addresses the current climate surrounding PGx implementation, focusing primarily on strategies for implementation at academic institutions, particularly at The University of Chicago, and provides an up-to-date guide of resources supporting the development of PGx programs. Remaining challenges and recent strategies for overcoming these challenges to implementation are discussed.

A precision medicine approach to personalized prescribing using genetic and nongenetic factors for clinical decision-making

Screening potential drug-drug interactions, drug-gene interactions, contraindications, and other factors is crucial in clinical practice. However, implementing these screening concepts in real-world settings poses challenges. This work proposes an approach towards precision medicine that combines genetic and nongenetic factors to facilitate clinical decision-making. The approach focuses on raising the performance of four potential interaction screenings in the prescribing process, including drug-drug interactions, drug-gene interactions, drug-herb interactions, drug-social lifestyle interactions, and two potential considerations for patients with liver or renal impairment. The work describes the design of a curated knowledge-based model called the knowledge model for potential interaction and consideration screening, the screening logic for both the detection module and inference module, and the personalized prescribing report. Three case studies have demonstrated the proof-of-concept and effectiveness of this approach. The proposed approach aims to reduce decision-making processes for healthcare professionals, reduce medication-related harm, and enhance treatment effectiveness. Additionally, the recommendation with a semantic network is suggested to assist in risk-benefit analysis when health professionals plan therapeutic interventions with new medicines that have insufficient evidence to establish explicit recommendations. This approach offers a promising solution to implementing precision medicine in clinical practice.

Clinical Pharmacist Transition of Care Model Improves Hospital System Practice by Reducing Readmissions

PURPOSE

A primary cause of hospital readmission is medication-related problems (MRPs). Polypharmacy patients taking multiple medications concurrently experience an increased likelihood of MRPs and high occurrence of readmissions to the hospital within 30 days. This study assessed the ability of a pharmacist-led transition of care program to decrease readmissions in polypharmacy patients by evaluating and rectifying MRPs.

METHODS

Over 16 months, patients admitted onto the medicine ward service with ≥10 home medications ( n = 536) received medication management interventions from a clinical pharmacist including admission interview, medication reconciliation and consultation, and postdischarge phone follow-up. Admitted patients taking fewer than 10 home medications during the same time served as the control group and received routine standard of care ( n = 2317).

RESULTS

The polypharmacy group who received the pharmacist-led intervention had a statistically significantly lower 30-day readmission rate (8.8%) compared with patients in the control group (12.4%; X 2 = 5.63, p = .01). Patients receiving pharmacist intervention were 33% less likely to be readmitted within 30 days of discharge compared with the control group (odds ratio = 0.67, 95% CI = 0.49-0.94). All patients had at least one medication-related discrepancy.

CONCLUSION

This pharmacy-led transition of care program can effectively reduce readmission rates through resolution of medication-related problems.

Pharmacogenetics and phenoconversion: the influence on side effects experienced by psychiatric patients

Introduction: Preventing side effects is important to ensure optimal psychopharmacotherapy and therapeutic adherence among psychiatric patients. Obtaining the pharmacogenetic profile of CYP2C19 and CYP2D6 can play an important role in this. When the genotype-predicted phenotype shifts because of the use of co-medication, this is called phenoconversion. The aim was to study the influence of the pharmacogenetic (PGx) profile and phenoconversion on side effects experienced by psychiatric patients. Methods: A retrospective cohort study was performed using data from 117 patients from a psychiatric outpatient clinic. Patients were genotyped with a psychiatric PGx panel and side effects were evaluated using the Udvalg for Kliniske Undersølgelser side effects rating scale (UKU). Results: Of all patients, 10.3% and 9.4% underwent phenoconversion (any shift in predicted phenotype) for CYP2C19 and CYP2D6 respectively. No significant associations were found between the phenotype and UKU-score. 75% of the patients with an Intermediate metabolizer (IM) or Poor metabolizer (PM) phenoconverted phenotype of CYP2C19 experienced nausea and vomiting compared to 9.1% of the Normal metabolizer (NM) and Ultrarapid metabolizer (UM) patients (p = 0.033). 64% of the patients with an IM or PM phenoconverted phenotype of CYP2D6 experienced the side effect depression compared to 30.4% NMs and UMs (p = 0.020). CYP2D6 IM and PM patients had a higher concentration-dose ratio than NM patients (p < 0.05). Discussion: This study underlines the importance to consider phenoconversion when looking at a patient's genotype. This is important for a better prediction of the phenotype and preventing possible side effects under a specific psychopharmacotherapy.

Case Report: Performing a Medication Safety Review Assisted by Pharmacogenomics to Explain a Prescribing Cascade Resulting in a Patient Fall

Pharmacotherapy for major depressive disorder (MDD) typically consists of trial-and-error and clinician preference approaches, where patients often fail one or more antidepressants before finding an optimal regimen. Pharmacogenomics (PGx) can assist in prescribing appropriate antidepressants, thereby reducing the time to MDD remission and occurrence of adverse drug events. Since many antidepressants are metabolized by and/or inhibit cytochrome P450 enzymes (e.g., CYP2C19 or CYP2D6), drug-induced phenoconversion is common in patients on antidepressant combinations. This condition influences the interpretation of a patient's PGx results, overall risk of ineffective/adverse medication response due to multi-drug interactions, and the recommendations. This complex case describes a patient with MDD, generalized anxiety disorder, and chronic pain who experienced a fall due to excessive sedation following a prescribing cascade of fluoxetine, bupropion, and doxepin. These antidepressants delivered a significant additive sedative effect and interacted with the patient's hydrocodone, potentially contributing to uncontrolled pain, upward dose titration of hydrocodone, and a higher overall sedative burden. The PGx results and drug-induced phenoconversion described in this case report explain the patient's excessive sedation and possibly ineffective/toxic antidepressant and opioid treatment. This case report also illustrates how a more timely multi-drug interaction assessment (preferably in conjunction with preemptive PGx testing) may have informed a different prescribing pattern, reduced/avoided a prescribing cascade, and potentially prevented a drug-related fall.

Readiness to Accept Genetic Testing for Personalized Medicine: Survey Findings on the Role of Socio-Demographic Characteristics, Health Vulnerabilities, Perceived Genetic Risk and Personality Factors

Studies from various countries have shown that majorities would accept genetic testing for personalization of treatment, but little is known about differences among population subgroups. The present study investigated whether readiness to accept a hypothetical cost-free offer of genetic testing to personalize treatment depends on socio-demographic characteristics, health-related vulnerabilities, personal dispositions, and prior awareness about personalized medicine. The study was based on a cross-sectional survey design. Out of a representative initial sample of 50-80-year-old Danish citizens (n = 15,072), n = 6807 returned a fully answered web-based questionnaire. Socio-demographic data were added from a national registry. Data were analyzed by multivariable logistic regression. A large majority of respondents (78.3%) expressed their readiness to be tested. Rates were higher in men, younger persons, and those with higher income. Additionally, ex-smokers and obese persons as well as those less satisfied with their health and respondents who perceived a personal genetic risk were more interested, as were those with higher internal health control, higher extraversion, higher emotional stability, and those who had not heard about this option before. Further research should investigate the specific concerns among population subgroups which need being addressed by systematic communication efforts in a clinical but also a broader public health context.

Population-based pattern of medication use and prevalence of polypharmacy among patients with cardiovascular diseases: results of the Pars cohort study from Iran

Background

Polypharmacy in patients with cardiovascular diseases (CVDs) has been linked to several adverse outcomes. This study aimed to investigate the pattern of medication use and prevalence of polypharmacy among CVDs patients in Iran.

Method

We used the baseline data of the Pars cohort study (PCS). The participants were asked to bring their medication bags; then, the medications were classified using the Anatomical Therapeutic Chemical classification. Polypharmacy was defined as using five or more medications concurrently. Poisson regression modeling was applied. The adjusted prevalence ratios (PR) and its 95% confidence interval (CI) were estimated.

Results

Totally, 9262 participants were enrolled in the PCS, of whom 961 had CVDs. The prevalence of polypharmacy in participants with and without CVDs was 38.9% and 7.1%, respectively. The highest prevalence of polypharmacy (51.5%) was among obese patients. Abnormal waist-hip ratio (PR: 2.79; 95% CI 1.57–4.94), high socioeconomic status (PR: 1.65; 95% CI 1.07–2.54), tobacco-smoking (PR: 1.35; 95% CI 1.00–1.81), patients with more than three co-morbidities (PR: 1.41; 95% CI 1.30–1.53), high physical activity (PR: 0.66; 95% CI 0.45–0.95), use of opiate ever (PR: 0.46; 95% CI 0.26–0.82), and healthy overweight subjects (PR: 0.22; 95% CI 0.12–0.39) were associated with polypharmacy. Cardiovascular drugs (76.1%), drugs acting on blood and blood-forming organs (50.4%), and alimentary tract and metabolism drugs (33.9%) were the most frequently used drugs. Agents acting on the renin-angiotensin system were the mostly used cardiovascular system drugs among men and those above 60 years old, while beta-blocking agents were mostly prevalent among cardiovascular system drugs in women with CVDs.

Conclusion

Given the high prevalence of polypharmacy among CVDs patients, and subsequent complications, programs to educate both physicians and patients to prevent this issue is crucial.

Idiopathic Symptoms Resolved by Pharmacogenomics-Enriched Comprehensive Medication Management: A Case Report

Clinical manifestations of biological aging can be remarkably similar to the side effects of frequently used medications. Fatigue, muscle pain, and confusion are common and often not shared as part of proper geriatric patient history. When patients report them, a root cause is usually confounding. These symptoms not only negatively impact health and wellness outcomes, patient quality of life, and increase costs to the healthcare system, but also may be a limitation on provider best practices. The patient, a 71-year-old female of European descent, enrolled in pharmacogenomics-enriched comprehensive medication management (PGx+CMM) program through her retirement benefit. At the time of testing, she was approximately 18 months post cerebrovascular accident and was being observed by her primary care provider for common chronic conditions. Of interest, she had been manifesting unreported clinical symptoms of fatigue, hypotension, and myalgia. Addressing these patient concerns and specifically focusing on an individual's goals, fears, and basic needs, rather than concentrating merely on the absence of disease, is the crux of personalized medicine and programs that address the notion of healthy aging. The patient's therapeutic regimen was adjusted based on PGx+CMM pharmacist review, use of a clinical decision support system (CDSS), and communication of recommendations to the prescribing physician. The patient saw rapid improvements in symptoms, suggesting they were caused by medication side effects. Her blood pressure and cholesterol levels remained controlled while noticeable side effects were eliminated. This case study demonstrates the positive impacts of personalized medicine and shows how pharmacists can be empowered with a CDSS to positively impact healthcare.

The pattern of medication use, and determinants of the prevalence of polypharmacy among patients with a recent history of depressive disorder: results from the pars cohort study

BACKGROUND

Inappropriate medication use among individuals with depressive disorders (DD) is a rising public health challenge. We aimed to investigate the polypharmacy and its determinants among individuals with DD in a less developed region, and evaluate the pattern of medication use in this population.

METHODS

Data was extracted from Pars Cohort Study (PCS) between 2016 and 2019. Participants were asked to bring all the medication they were using regularly, and history of DD during the last 12 months prior to study was obtained. The Anatomical Therapeutic Chemical classification was applied and polypharmacy was defined as concurrent use of five or more medications. Logistic regression models were developed to estimate the associations between polypharmacy and DD, adjusted for relevant covariates. The prevalence of consumption of each drug class was estimated among males, females, and elders. Logistic regression was applied and the adjusted odds ratio (OR) and its 95% confidence interval (CI) were estimated.

RESULTS

A total of 9264 participants with a mean age of 52.6 (SD: 9.7) were enrolled. The prevalence of polypharmacy was 22.6% [95% CI (20.7-24.6)]. The most common drug classes were genitourinary system (55.4%) and nervous system (29.1%) medication, respectively. Recent history of DD was reported among 19.4% (n = 1795) participants, the majority of whom were females. Factors associated with polypharmacy include female gender (OR: 1.51), Fars ethnicity (OR: 1.52), lower physical activity (OR: 1.74), and higher socioeconomic status (OR: 1.40). The prevalence of antidepressant use among males was higher than females (P < 0.001).

CONCLUSION

The prevalence of polypharmacy is high among patients with a recent history of depressive disorder. Females, individuals with higher socioeconomic status and lower physical activity, and those who use tobacco are more likely to be polymedicated. Surveillance measures need to be established to monitor the patterns of medication use among individuals with depressive disorders.

Comparison of Multidrug Use in the General Population and among Persons with Diabetes in Denmark for Drugs Having Pharmacogenomics (PGx) Based Dosing Guidelines

Background: This study measures the use of drugs within the therapeutic areas of antithrombotic agents (B01), the cardiovascular system (C), analgesics (N02), psycholeptics (N05), and psychoanaleptics (N06) among the general population (GP) in comparison to persons with diabetes in Denmark. The study focuses on drugs having pharmacogenomics (PGx) based dosing guidelines for CYP2D6, CYP2C19, and SLCO1B1 to explore the potential of applying PGx-based decision-making into clinical practice taking drug–drug interactions (DDI) and drug–gene interactions (DGI) into account. Methods: This study is cross-sectional, using The Danish Register of Medicinal Product Statistics as the source to retrieve drug consumption data. Results: The prevalence of use in particular for antithrombotic agents (B01) and cardiovascular drugs (C) increases significantly by 4 to 6 times for diabetic users compared to the GP, whereas the increase for analgesics (N02), psycoleptics, and psychoanaleptics (N06) was somewhat less (2–3 times). The five most used PGx drugs, both in the GP and among persons with diabetes, were pantoprazole, simvastatin, atorvastatin, metoprolol, and tramadol. The prevalence of use for persons with diabetes compared to the GP (prevalence ratio) increased by an average factor of 2.9 for all PGx drugs measured. In addition, the prevalence of use of combinations of PGx drugs was 4.6 times higher for persons with diabetes compared to GP. In conclusion, the findings of this study clearly show that a large fraction of persons with diabetes are exposed to drugs or drug combinations for which there exist PGx-based dosing guidelines related to CYP2D6, CYP2C19, and SLCO1B1. This further supports the notion of accessing and accounting for not only DDI but also DGI and phenoconversion in clinical decision-making, with a particular focus on persons with diabetes.

An Analysis of Pharmacogenomic-Guided Pathways and Their Effect on Medication Changes and Hospital Admissions: A Systematic Review and Meta-Analysis

Ninety-five percent of the population are estimated to carry at least one genetic variant that is discordant with at least one medication. Pharmacogenomic (PGx) testing has the potential to identify patients with genetic variants that puts them at risk of adverse drug reactions and sub-optimal therapy. Predicting a patient's response to medications could support the safe management of medications and reduce hospitalization. These benefits can only be realized if prescribing clinicians make the medication changes prompted by PGx test results. This review examines the current evidence on the impact PGx testing has on hospital admissions and whether it prompts medication changes. A systematic search was performed in three databases (Medline, CINAHL and EMBASE) to search all the relevant studies published up to the year 2020, comparing hospitalization rates and medication changes amongst PGx tested patients with patients receiving treatment-as-usual (TAU). Data extracted from full texts were narratively synthesized using a process model developed from the included studies, to derive themes associated to a suggested workflow for PGx-guided care and its expected benefit for medications optimization and hospitalization. A meta-analysis was undertaken on all the studies that report the number of PGx tested patients that had medication change(s) and the number of PGx tested patients that were hospitalized, compared to participants that received TAU. The search strategy identified 5 hospitalization themed studies and 5 medication change themed studies for analysis. The meta-analysis showed that medication changes occurred significantly more frequently in the PGx tested arm across 4 of 5 studies. Meta-analysis showed that all-cause hospitalization occurred significantly less frequently in the PGx tested arm than the TAU. The results show proof of concept for the use of PGx in prescribing that produces patient benefit. However, the review also highlights the opportunities and evidence gaps that are important when considering the introduction of PGx into health systems; namely patient involvement in PGx prescribing decisions, thus a better understanding of the perspective of patients and prescribers. We highlight the opportunities and evidence gaps that are important when considering the introduction of PGx into health systems.

Sociodemographic factors and beliefs about medicines in the uptake of pharmacogenomic testing in older adults

Aim: To assess the impact of sociodemographic factors and beliefs about medicines on the uptake of pharmacogenomic testing in older adults in a public healthcare system. Materials & methods: Data are based on a sample of 347 primary care older adults. Results: Most respondents (90%) were willing to provide a saliva sample and 47% were willing to pay for it. Increased age (odds ratio: 0.91; p = 0.04) and negative beliefs about the harmfulness of medicines (odds ratio: 0.68; p = 0.02) were associated with a decreased willingness to provide a sample. Lower education (less than university, odds ratio: 0.54; p = 0.04) was associated with a decreased willingness to pay. Conclusion: Education and beliefs about medicines are important factors in the acceptability of pharmacogenomic testing in older adults.

Pharmacogenomics for Primary Care: An Overview

Most of the prescribing and dispensing of medicines happens in primary care. Pharmacogenomics (PGx) is the study and clinical application of the role of genetic variation on drug response. Mounting evidence suggests PGx can improve the safety and/or efficacy of several medications commonly prescribed in primary care. However, implementation of PGx has generally been limited to a relatively few academic hospital centres, with little adoption in primary care. Despite this, many primary healthcare providers are optimistic about the role of PGx in their future practice. The increasing prevalence of direct-to-consumer genetic testing and primary care PGx studies herald the plausible gradual introduction of PGx into primary care and highlight the changes needed for optimal translation. In this article, the potential utility of PGx in primary care will be explored and on-going barriers to implementation discussed. The evidence base of several drug-gene pairs relevant to primary care will be outlined with a focus on antidepressants, codeine and tramadol, statins, clopidogrel, warfarin, metoprolol and allopurinol. This review is intended to provide both a general introduction to PGx with a more in-depth overview of elements relevant to primary care.

Drug Use among Nursing Home Residents in Denmark for Drugs Having Pharmacogenomics Based (PGx) Dosing Guidelines: Potential for Preemptive PGx Testing

BACKGROUND

Polypharmacy is most prevalent among the elderly population and in particular among nursing home residents. The frequency of the use of drugs with pharmacogenomics (PGx)-based dosing guidelines for CYP2D6, CYP2C9, CYP2C19 and SLCO1B1 were measured among nursing home residents in the Capital Region of Denmark as well as drug-drug interactions. The aim was to evaluate the potential of applying PGx-test as a supportive tool in medication reviews.

METHODS

Drug use among nursing home residents during 2017-2018 in the Capital Region of Copenhagen, for drugs with PGx-based dosing guidelines available through the PharmGKB website, were measured. Drug-drug interactions were scored in severity by using drug interaction checkers.

RESULTS

The number of residents using drugs with PGx-based actionable dosing guidelines (AG) were 119 out of 141 residents (84.3%). Of these 119 residents, 87 residents used drugs with AG for CYP2C19, 47 residents for CYP2D6, and 42 residents for SLCO1B1. In addition, 30 residents used two drugs with an AG for CYP2C19, and for CYP2D6, it was only seven residents. The most used drugs with AG were clopidogrel (42), pantoprazole (32), simvastatin (30), metoprolol (25), and citalopram (24). The most frequent drug interactions found with warnings were combinations of proton pump inhibitors and clopidogrel underscoring the potential for phenoconversion.

CONCLUSION

this study clearly showed that the majority of the nursing home residents were exposed to drugs or drug combinations for which there exist PGx-based AG. This indeed supports the notion of accessing and accounting for not only drug-gene but also drug-drug-gene interactions as a supplement to medication review.