Estimating cost savings of pharmacogenetic testing for depression in real-world clinical settings

Precision pharmacotherapy of atomoxetine in children with ADHD: how to ensure the right dose for the right person?

Non-stimulant atomoxetine is recognized in various current clinical guidelines as an important alternative to stimulants for the pharmacological treatment of attention deficit/hyperactivity disorder (ADHD) in children. While its efficacy and tolerability for core symptoms are established, there is considerable inter-individual variability in response and exposure, highlighting the need for personalized dosing. In this review, we evaluated existing studies and summarized comprehensive evidence supporting the clinical implementation of therapeutic drug monitoring (TDM) and personalized dosing of atomoxetine, organized around a series of logically structured questions. Although there are notable gaps in achieving personalized dosing across multiple critical elements, the available evidence is helpful to endorse personalized dose adjustments based on TDM and CYP2D6 genotyping "whenever possible." We advocate for ongoing improvement and enhancement in clinical practice. Future advancements will rely on a deeper understanding of ADHD, facilitating more precise diagnoses and personalized treatment strategies.

Implementing a Pharmacist-Led Primary Care Pharmacogenomics Medication Management Service

Background: Pharmacogenomics (PGx) is a tool to guide optimal medication selection. Increased demand for personalized medicine and the growing occurrence of chronic diseases are drivers for pharmacogenomic medication management services. A review of implementation models identified a paucity of models delivering these services utilizing pharmacists in primary care. Lack of standardization of this process remains a barrier to widespread implementation within health systems. Purpose: Describe the process of developing an institutional guidance document and applying it to implement a pharmacogenomics medication management service at clinic sites within an integrated health system in the United States. Measure the growth in the number of PGx visits completed. Method: A task force of pharmacists reviewed literature, guidelines, and institutional policies to create a comprehensive guidance document. The document included six minimum practice requirements for implementation in the primary care setting, and six additional recommendations. A retrospective chart review of all face to face, phone and eConsult PGx visit types occurring from January 1, 2022 through September 30, 2022 was conducted. Results: A pharmacist-led pharmacogenomics medication management service is now offered at all primary care sites within the health system. During the study timeframe, 1378 patients had a PGx visit, resulting in 1939 PGx visits. Of those visits, 1777 (92%) were referred by a primary care provider and 1675 (86.7%) were conducted by a primary care pharmacist. Twenty-nine primary care pharmacists offered the PGX service and 25 (89%) completed at least one visit. Patients were referred by providers from 56 of the 64 (87.5%) primary care departments. Conclusions: Developing an institutional process and guidance document for the implementation of a new pharmacist-led pharmacogenomics medication management service at clinic sites within an integrated health system was beneficial in developing and standardizing the workflow. Dissemination of workflow expectations to the primary care providers and pharmacists resulted in adoption of the service.

Cost Effectiveness of Pharmacogenetic Testing for Drugs with Clinical Pharmacogenetics Implementation Consortium (CPIC) Guidelines: A Systematic Review

The objective of this study was to evaluate the evidence on cost-effectiveness of pharmacogenetic (PGx)-guided treatment for drugs with Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines. A systematic review was conducted using multiple biomedical literature databases from inception to June 2021. Full articles comparing PGx-guided with nonguided treatment were included for data extraction. Quality of Health Economic Studies (QHES) was used to assess robustness of each study (0-100). Data are reported using descriptive statistics. Of 108 studies evaluating 39 drugs, 77 (71%) showed PGx testing was cost-effective (CE) (N = 48) or cost-saving (CS) (N = 29); 21 (20%) were not CE; 10 (9%) were uncertain. Clopidogrel had the most articles (N = 23), of which 22 demonstrated CE or CS, followed by warfarin (N = 16), of which 7 demonstrated CE or CS. Of 26 studies evaluating human leukocyte antigen (HLA) testing for abacavir (N = 8), allopurinol (N = 10), or carbamazepine/phenytoin (N = 8), 15 demonstrated CE or CS. Nine of 11 antidepressant articles demonstrated CE or CS. The median QHES score reflected high-quality studies (91; range 48-100). Most studies evaluating cost-effectiveness favored PGx testing. Limited data exist on cost-effectiveness of preemptive and multigene testing across disease states.

Role of Pharmacogenomics in Comprehensive Medication Management: Considerations for Employers

Rising prescription costs, poor medication adherence, and safety issues pose persistent challenges to employer-sponsored health care plans and their beneficiaries. Comprehensive medication management (CMM), a patient-centered approach to medication optimization, enriched by pharmacogenomics (PGx), has been shown to improve the efficacy and safety of pharmaceutical regimens. This has contributed to improved health care outcomes, reduced costs of treatments, better adherence, shorter durations of treatment, and fewer adverse effects from drug therapy. Despite compelling clinical and economic evidence to justify the application of CMM guided by PGx, implementation in clinical settings remains sparse; notable barriers include limited physician adoption and health insurance coverage. Ultimately, these challenges may be overcome through comprehensive programs that include clinical decision support systems and education through employer-sponsored population health management channels to the benefit of the employees, employers, health care providers, and health care systems. This article discusses benefits, considerations, and barriers of scalable PGx-enriched CMM programs in the context of self-insured employers.

Approaches and hurdles of implementing pharmacogenetic testing in the psychiatric clinic

Pharmacogenetic (PGx) testing has emerged as a tool for predicting a person's ability to process and react to drugs. Despite the growing evidence-base, enthusiasm, and successful efforts to implement PGx testing in psychiatry, a consensus on how best to implement PGx testing into practice has not been established and numerous hurdles to widespread adoption remain to be overcome. In this article, we summarize the most used approaches and commonly encountered hurdles when implementing PGx testing into routine psychiatric care. We also highlight effective strategies that have been used to overcome hurdles. These strategies include the development of user-friendly clinical workflows for test ordering, use, and communication of results, establishment of test standardization and reimbursement policies, and development of tailored curriculums for educating health-care providers and the public. Although knowledge and awareness of these approaches and strategies to overcome hurdles alone may not be sufficient for successful implementation, they are necessary to ensure the effective spread, scale, and sustainability of PGx testing in psychiatry and other areas of medicine.

Sub-Analysis of CYP-GUIDES Data: Assessing the Prevalence and Impact of Drug-Gene Interactions in an Ethnically Diverse Cohort of Depressed Individuals

Introduction: Minority groups are underrepresented in pharmacogenomics (PGx) research. Recent sub-analysis of CYP-GUIDES showed reduced length of stay (LOS) in depressed patients with CYP2D6 sub-functional status. Our primary objective was to determine whether PGx guided (G) versus standard treatment (S) influenced LOS among different race/ethnic groups. Secondary objectives included prevalence of drug-gene interactions (DGIs) and readmission rates (RAR).

Methods: Retrospective sub-analysis of CYP-GUIDES data comprising CYP2D6 phenotypes was reclassified using standardized CYP2D6 genotype to phenotype recommendations from the Clinical Pharmacogenetics Implementation Consortium (CPIC) and Dutch Pharmacogenetics Working Group (DPWG). The Mann-Whitney test was used to determine differences in LOS between groups G and S and Kruskal Wallis test to compare LOS among different race/ethnic groups. Logistic regression was used to determine covariates associated with RAR.

Results: This study included 1,459 patients with 67.3% in G group (n = 982). The majority of patients were White (57.5%), followed by Latinos (25.6%) and Blacks (12.3%). Although there were no differences in LOS between G and S groups, Latinos had significant shorter LOS than Whites (p = 0.002). LOS was significantly reduced by 5.6 days in poor metabolizers in group G compared to S (p = 0.002). The proportion of supra functional and ultra-rapid metabolizers (UMs) were 6 and 20.3% using CYP-GUIDES and CPIC/DPWG definitions, respectively. Prevalence of DGIs was 40% with significantly fewer DGIs in Blacks (p < 0.001). Race/ethnicity was significantly associated with RAR (aOR 1.30; p = 0.003).

Conclusion: A greater number of patients were classified as CYP2D6 UMs using CPIC/DPWG definitions as compared to CYP-GUIDES definitions. This finding may have clinical implications for using psychotropics metabolized by CYP2D6.

Metabolizing status of CYP2C19 in response and side effects to medications for depression: Results from a naturalistic study

Major depressive disorder (MDD) is one of the leading causes of disability worldwide. Polymorphisms in cytochrome P450 genes (CYP450) were demonstrated to play a significant role in antidepressant response and side effects, but their effect in real-world clinical practice is poorly known. We determined the metabolic status of CYP2C19 based on the combination of *1, *2, *3 and *17 alleles extracted from genome-wide data in 1239 patients with MDD, pharmacologically treated in a naturalistic setting. Symptom improvement and side effects were assessed using the Montgomery and Åsberg Depression Rating Scale and the Udvalg for Kliniske Undersøgelse scale, respectively. We tested if symptom improvement, response and side effects were associated with CYP2C19 metabolic status adjusting for potential confounders. We considered patients treated with drugs for depression having CYP2C19 genotyping recommended by guidelines (T1 Drugs); secondarily, with all psychotropic drugs having CYP2C19 as relevant metabolic path (T2 Drugs). In the group treated with T1 drugs (n = 540), poor metabolizers (PMs) showed higher response and higher symptom improvement compared to normal metabolizers (p = 0.023 and p = 0.009, respectively), but also higher risk of autonomic and neurological side effects (p = 0.022 and p = 0.022 respectively). In patients treated with T2 drugs (n = 801), similar results were found. No associations between metabolizer status and other types of side effects were found (psychic and other side effects). Our study suggests potential advantages of CYP2C19 pharmacogenetic testing to guide treatment prescription, that may not be limited to the drugs currently recommended by guidelines.

Gene-drug pairings for antidepressants and antipsychotics: level of evidence and clinical application

Substantial inter-individual discrepancies exist in both therapeutic effectiveness and adverse effects of antidepressant and antipsychotic medications, which can, in part, be explained by genetic variation. Here, we searched the Pharmacogenomics Knowledge Base for gene-antidepressant and gene-antipsychotic pairs with the highest level of evidence. We then extracted and compared the associated prescribing recommendations for these pairs developed by the Clinical Pharmacogenomics Implementation Consortium, the Dutch Pharmacogenetics Working Group or approved product labels in the US, Canada, Europe, and Asia. Finally, we highlight key economical, educational, regulatory, and ethical issues that, if not appropriately considered, can hinder the implementation of these recommendations in clinical practice. Our review indicates that evidence-based guidelines are available to assist with the implementation of pharmacogenetic-guided antidepressant and antipsychotic prescribing, although the maximum impact of these guidelines on patient care will not be realized until key barriers are minimized or eliminated.

Multi-gene Pharmacogenomic Testing That Includes Decision-Support Tools to Guide Medication Selection for Major Depression: A Health Technology Assessment

BACKGROUND

Major depression is a substantial public health concern that can affect personal relationships, reduce people's ability to go to school or work, and lead to social isolation. Multi-gene pharmacogenomic testing that includes decision-support tools can help predict which depression medications and dosages are most likely to result in a strong response to treatment or to have the lowest risk of adverse events on the basis of people's genes.We conducted a health technology assessment of multi-gene pharmacogenomic testing that includes decision-support tools for people with major depression. Our assessment evaluated effectiveness, safety, cost-effectiveness, the budget impact of publicly funding multi-gene pharmacogenomic testing, and patient preferences and values.

METHODS

We performed a systematic literature search of the clinical evidence. We assessed the risk of bias of each included study using the Cochrane Risk of Bias Tool and the Risk of Bias Assessment Tool for Nonrandomized studies (RoBANS) and the quality of the body of evidence according to the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) Working Group criteria.We performed a systematic literature search of the economic evidence to review published cost-effectiveness studies on multi-gene pharmacogenomic testing that includes a decision-support tool in people with major depression. We developed a state-transition model and conducted a probabilistic analysis to determine the incremental cost of multi-gene pharmacogenomic testing versus treatment as usual per quality-adjusted life-year (QALY) gained for people with major depression who had inadequate response to one or more antidepressant medications. In the reference case (with GeneSight-guided care), we considered a 1-year time horizon with an Ontario Ministry of Health perspective. We also estimated the 5-year budget impact of publicly funding multi-gene pharmacogenomic testing for people with major depression in Ontario.To contextualize the potential value of multi-gene pharmacogenomic testing that includes decision-support tools, we spoke with people who have major depression and their families.

RESULTS

We included 14 studies in the clinical evidence review that evaluated six multi-gene pharmacogenomic tests. Although all tests included decision-support tools, they otherwise differed greatly, as did study design, populations included in studies, and outcomes reported. Little or no improvement was observed on change in HAM-D17 depression score compared with treatment as usual for any test evaluated (GRADE: Low-Very Low). GeneSight- and NeuroIDgenetix-guided medication selection led to statistically significant improvements in response (GRADE: Low-Very Low) and remission (GRADE: Low-Very Low), while treatment guided by CNSdose led to significant improvement in remission rates (GRADE: Low), but the study did not report on response. Results were inconsistent and uncertain for the impact of Neuropharmagen, and no significant improvement was observed for Genecept or another unspecified test for either response or remission (GRADE: Low-Very Low). Neuropharmagen may reduce adverse events and CNSDose may reduce intolerability to medication, while no difference was observed in adverse events with GeneSight, Genecept, or another unspecified test (GRADE: Moderate-Very Low). No studies reported data on suicide, treatment adherence, relapse, recovery, or recurrence of depression symptoms.Our review included four model-based economic studies and found that multi-gene pharmacogenomic testing was associated with greater effectiveness and cost savings than treatment as usual, over long-term (i.e., 3-,5-year and lifetime) time horizons. Since none of the included studies was fully applicable to the Ontario health care system, we conducted a primary economic evaluation.Our reference case analysis over the 1-year time horizon found that multi-gene pharmacogenomic testing (with GeneSight) was associated with additional QALYs (0.03, 95% credible interval [CrI]: 0.005; 0.072) and additional costs ($1,906, 95% Crl: $688; $3,360). An incremental cost-effectiveness ratio was $60,564 per QALY gained. The probability of the intervention being cost-effective (vs. treatment as usual) was 36.8% at a willingness-to-pay amount of $50,000 per QALY (i.e., moderately likely not to be cost-effective), rising to 70.7% at a willingness-to-pay amount of $100,000 per QALY (i.e., moderately likely to be cost-effective). Evidence informing economic modeling of the reference case with GeneSight and other multi-gene pharmacogenomic tests was of low to very low quality, implying considerable uncertainty or low confidence in the effectiveness estimates. The price of the test, efficacy of the intervention on remission, time horizon, and analytic perspective were major determinants of the cost-effectiveness results. If the test price were assumed to be $2,162 (compared with $2,500 in the reference case), the intervention would be cost-effective at a willingness-to-pay amount of $50,000 per QALY; moreover, if the price decreased to $595, the intervention would be cost saving (or dominant) compared with treatment as usual.At an increasing uptake of 1% per year and a test price of $2,500, the annual budget impact of publicly funding multi-gene pharmacogenomic testing in Ontario over the next 5 years ranged from an additional $3.5 million in year 1 (at uptake of 1%) to $16.8 million in year 5. The 5-year budget impact was estimated at about $52 million.People with major depression and caregivers generally supported multi-gene pharmacogenomic testing because they believed it could provide guidance that fit their values. They hoped such guidance would speed symptom relief, would reduce side effects and help inform their medication choices. Some patients expressed concerns over maintaining confidentiality of test results and the possibility that physicians would sacrifice patient-centred care to follow pharmacogenomic guidance.

CONCLUSIONS

Multi-gene pharmacogenomic testing that includes decision-support tools to guide medication selection for depression varies widely. Differences between individual tests must be considered, as clinical utility observed with one test might not apply to other tests. Overall, effectiveness was inconsistent among the six multi-gene pharmacogenomic tests we identified. Multi-gene pharmacogenomic tests may result in little or no difference in improvement in depression scores compared with treatment as usual, but some tests may improve response to treatment or remission from depression. The impact on adverse events is uncertain. The evidence, however, is uncertain, and therefore our confidence that these observed effects reflect the true effects is low to very low.For the management of major depression in people who had inadequate response to at least one medication, some multi-gene pharmacogenomic tests that include decision support tools are associated with additional costs and QALYs over the 1-year time horizon, and maybe be cost-effective at the willingness-to-pay amount of $100,000 per QALY. Publicly funding multi-gene pharmacogenomic testing in Ontario would result in additional annual costs of between $3.5 million and $16.8 million, with a total budget impact of about $52 million over the next 5 years.People with major depression and caregivers generally supported multi-gene pharmacogenomic testing because they believed it could provide guidance that fit their values. They hoped such guidance would speed symptom relief, would reduce side and help inform their medication choices. Some patients expressed concerns over maintaining confidentiality of test results and the possibility that physicians would sacrifice patient-centred care to follow pharmacogenomic guidance.

The impact of pharmacogenetic testing in patients exposed to polypharmacy: a scoping review

Polypharmacy poses a significant risk for adverse reactions. While there are clinical decision support tools to assist clinicians in medication management, pharmacogenetic testing to identify potential drug-gene or drug-drug-gene interactions is not widely implemented in the clinical setting. A PRISMA-compliant scoping review was performed to determine if pharmacogenetic testing for absorption, distribution, metabolism, and excretion (ADME)-related genetic variants is associated with improved clinical outcomes in patients with polypharmacy. Six studies were reviewed. Five reported improved clinical outcomes, reduced side effects, reduction in the number of drugs used, or reduced healthcare utilization. The reviewed studies varied in methodological quality, risk of bias, and outcome measures. Age, diet, disease state, and treatment adherence also influence drug response, and may confound the relationship between genetic polymorphisms and treatment outcomes. Further studies using a randomized control design are needed. We conclude that pharmacogenetic testing represents an opportunity to improve health outcomes in patients exposed to polypharmacy, particularly in patients with psychiatric disorders and the elderly.

Economic evaluation in psychiatric pharmacogenomics: a systematic review

Nowadays, many relevant drug-gene associations have been discovered, but pharmacogenomics (PGx)-guided treatment needs to be cost-effective as well as clinically beneficial to be incorporated into standard health care. To address current challenges, this systematic review provides an update regarding previously published studies, which assessed the cost-effectiveness of PGx testing for the prescription of antidepressants and antipsychotics. From a total of 1159 studies initially identified by literature database querying, and after manual assessment and curation of all of them, a mere 18 studies met our inclusion criteria. Of the 18 studies evaluations, 16 studies (88.89%) drew conclusions in favor of PGx testing, of which 9 (50%) genome-guided interventions were cost-effective and 7 (38.9%) were less costly compared to standard treatment based on cost analysis. More precisely, supportive evidence exists for CYP2D6 and CYP2C19 drug-gene associations and for combinatorial PGx panels, but evidence is limited for many other drug-gene combinations. Amongst the limitations of the field are the unclear explanation of perspective and cost inputs, as well as the underreporting of study design elements, which can influence though the economic evaluation. Overall, the findings of this article demonstrate that although there is growing evidence on the cost-effectiveness of genome-guided interventions in psychiatric diseases, there is still a need for performing additional research on economic evaluations of PGx implementation with an emphasis on psychiatric disorders.

Acceptability of Pharmacogenetic Testing among French Psychiatrists, a National Survey

Psychiatric disorder management is based on the prescription of psychotropic drugs. Response to them remains often insufficient and varies from one patient to another. Pharmacogenetics explain part of this variability. Pharmacogenetic testing is likely to optimize the choice of treatment and thus improve patients’ care, even if concerns and limitations persist. This practice of personalized medicine is not very widespread in France. We conducted a national survey to evaluate the acceptability of this tool by psychiatrists and psychiatry residents in France, and to identify factors associated with acceptability and previous use. The analysis included 397 observations. The mean acceptability score was 10.70, on a scale from 4 to 16. Overall acceptability score was considered as low for 3.0% of responders, intermediate for 80.1% and high for 16.9%. After regression, the remaining factors influencing acceptability independently of the others were prescription and training history and theoretical approach. The attitude of our population seems to be rather favorable, however, obvious deficiencies have emerged regarding perceived skills and received training. Concerns about the cost and delays of tests results also emerged. According to our survey, one of the keys to overcoming the barriers encountered in the integration of pharmacogenetics seems to be the improvement of training and the provision of information to practitioners.

Clinical pharmacogenomics in action: design, assessment and implementation of a novel pharmacogenetic panel supporting drug selection for diseases of the central nervous system (CNS)

Background

Pharmacogenomics describes the link between gene variations (polymorphisms) and drug responses. In view of the implementation of precision medicine in personalized healthcare, pharmacogenetic tests have recently been introduced in the clinical practice. However, the translational aspects of such tests have been limited due to the lack of robust population-based evidence.

Materials

In this paper we present a novel pharmacogenetic panel (iDNA Genomics-PGx–CNS or PGx–CNS), consisting of 24 single nucleotide polymorphisms (SNPs) on 13 genes involved in the signaling or/and the metabolism of 28 approved drugs currently administered to treat diseases of the Central Nervous System (CNS). We have tested the PGx–CNS panel on 501 patient-derived DNA samples from a southeastern European population and applied biostatistical analyses on the pharmacogenetic associations involving drug selection, dosing and the risk of adverse drug events (ADEs).

Results

Results reveal the occurrences of each SNP in the sample and a strong correlation with the European population. Nonlinear principal component analysis strongly indicates co-occurrences of certain variants. The metabolization efficiency (poor, intermediate, extensive, ultra-rapid) and the frequency of clinical useful pharmacogenetic, associations in the population (drug relevance), are also described, along with four exemplar clinical cases illustrating the strong potential of the PGx–CNS panel, as a companion diagnostic assay. It is noted that pharmacogenetic associations involving copy number variations (CNVs) or the HLA gene were not included in this analysis.

Conclusions

Overall, results illustrate that the PGx–CNS panel is a valuable tool supporting therapeutic medical decisions, urging its broad clinical implementation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-021-02816-3.

Identification of high-impact gene-drug pairs for pharmacogenetic testing in Alberta, Canada

OBJECTIVES

To facilitate decision-making and priority-setting related to Alberta's Pharmacogenomics (PGx) testing implementation strategy by identifying gene-drug pairs with the highest potential impact on prescribing practices in Alberta.

PATIENTS AND METHODS

Annual drug dispensing data for Alberta from 2012 to 2016 for 57 medications with PGx-based prescribing guidelines were obtained, along with population estimates and demographics (age and ethnicity). Frequencies of actionable PGx genotypes by ethnicity were obtained from the Pharmacogenomics Knowledgebase (PharmGKB). Annual dispensing activity for each of the 57 medications was calculated for the full population (all ages) and children/youth (0-19 years). Alberta ethnicity data were cross-referenced with genetic frequency data for each of the main ethnic groups from PharmGKB to estimate the proportion of individuals with actionable genotypes. Actionable genotype proportions and drug dispensing frequencies were collectively used to identify high impact gene-drug pairs.

RESULTS

We found (a) half of the drugs with PGx-based prescribing guidelines, namely, analgesics, proton pump inhibitors, psychotropics, and cardiovascular drugs, were dispensed at high frequencies (>1% of the entire population), (b) the dispensing rate for about one-third of these drugs increased over the 5-year study period, (c) between 1.1 and 45% of recipients of these drugs carried actionable genotypes, and (d) the gene-drug pairs with greatest impact in Alberta predominatly included CYP2C19 or CYP2D6.

CONCLUSIONS

We uncovered specific patterns in drug dispensing and identified important gene-drug pairs that will inform the planning and development of an evidenced-based PGx testing service in Alberta, Canada. Adaptation of our approach may facilitate the process of evidence-based PGx testing implementation in other jurisdictions.

Cost-effectiveness of genetic and clinical predictors for choosing combined psychotherapy and pharmacotherapy in major depression

BACKGROUND

Predictors of treatment outcome in major depressive disorder (MDD) could contribute to evidence-based therapeutic choices. Combined pharmacotherapy and psychotherapy show increased efficacy but higher cost compared with antidepressant pharmacotherapy; baseline predictors of pharmacotherapy resistance could be used to identify patients more likely to benefit from combined treatment.

METHODS

We performed a proof-of-principle study of the cost-effectiveness of using previously identified pharmacogenetic and clinical risk factors (PGx-CL-R) of antidepressant resistance or clinical risk factors alone (CL-R) to guide the prescription of combined pharmacotherapy and psychotherapy vs pharmacotherapy. The cost-effectiveness of these two strategies was compared with standard care (ST, pharmacotherapy to all subjects) using a three-year Markov model. Model parameters were literature-based estimates of response to pharmacotherapy and combined treatment, costs (UK National Health System) and benefits (quality-adjusted life years [QALYs], one QALY=one year lived in perfect health).

RESULTS

CL-R was more cost-effective than PGx-CL-R: the cost of one-QALY improvement was £2341 for CL-R and £3937 for PGx-CL-R compared to ST. PGx-CL-R had similar or better cost-effectiveness compared to CL-R when 1) the cost of genotyping was £100 per subject or less or 2) the PGx-CL-R test had sensitivity ≥ 0.90 and specificity ≥ 0.85. The cost of one-QALY improvement for CL-R was £3664 and of £4110 in two independent samples.

LIMITATIONS

lack of validation in large samples from the general population.

CONCLUSIONS

Using clinical risk factors to predict pharmacotherapy resistance and guide the prescription of pharmacotherapy combined with psychotherapy could be a cost-effective strategy.

Review and Consensus on Pharmacogenomic Testing in Psychiatry

The implementation of pharmacogenomic (PGx) testing in psychiatry remains modest, in part due to divergent perceptions of the quality and completeness of the evidence base and diverse perspectives on the clinical utility of PGx testing among psychiatrists and other healthcare providers. Recognizing the current lack of consensus within the field, the International Society of Psychiatric Genetics assembled a group of experts to conduct a narrative synthesis of the PGx literature, prescribing guidelines, and product labels related to psychotropic medications as well as the key considerations and limitations related to the use of PGx testing in psychiatry. The group concluded that to inform medication selection and dosing of several commonly-used antidepressant and antipsychotic medications, current published evidence, prescribing guidelines, and product labels support the use of PGx testing for 2 cytochrome P450 genes (CYP2D6, CYP2C19). In addition, the evidence supports testing for human leukocyte antigen genes when using the mood stabilizers carbamazepine (HLA-A and HLA-B), oxcarbazepine (HLA-B), and phenytoin (CYP2C9, HLA-B). For valproate, screening for variants in certain genes (POLG, OTC, CSP1) is recommended when a mitochondrial disorder or a urea cycle disorder is suspected. Although barriers to implementing PGx testing remain to be fully resolved, the current trajectory of discovery and innovation in the field suggests these barriers will be overcome and testing will become an important tool in psychiatry.

Digital Microfluidics-Enabled Analysis of Individual Variation in Liver Cytochrome P450 Activity

The superfamily of hepatic cytochrome P450 (CYP) enzymes is responsible for the intrinsic clearance of the majority of therapeutic drugs in humans. However, the kinetics of drug clearance via CYPs varies significantly among individuals due to both genetic and external factors, and the enzyme amount and function are also largely impacted by many liver diseases. In this study, we developed a new methodology, based on digital microfluidics (DMF), for rapid determination of individual alterations in CYP activity from human-derived liver samples in biopsy-scale. The assay employs human liver microsomes (HLMs), immobilized on magnetic beads to facilitate determination of the activity of microsomal CYP enzymes in a parallelized system at physiological temperature. The thermal control is achieved with the help of a custom-designed, inkjet-printed microheater array modularly integrated with the DMF platform. The CYP activities are determined with the help of prefluorescent, enzyme-selective model compounds by quantifying the respective fluorescent metabolites based on optical readout in situ. The selectivity and sensitivity of the assay was established for four different CYP model reactions, and the diagnostic concept was validated by determining the interindividual variation in one of the four model reaction activities, that is, ethoxyresorufin O-deethylation (CYP1A1/2), between five donors. Overall, the developed protocol consumes only about 15 μg microsomal protein per assay. It is thus technically adaptable to screening of individual differences in CYP enzyme function from biopsy-scale liver samples in an automated fashion, so as to support tailoring of medical therapies, for example, in the context of liver disease diagnosis.

Costing Methods as a Means to Measure the Costs of Pharmacogenomics Testing

Clinical implementation of pharmacogenomics and personalized medicine interventions relies on addressing important financial aspects of the delivery of genetic testing to the patients, be it from public or private providers. Details on how to determine the cost items of the genetic testing are often limited. The goal of this study is to present a costing methodology in order to estimate and measure the costs as far as the technical process of pharmacogenomics testing is concerned. Moreover, an overall cost mindset strategy based on the selective genotyping workflow to guide specialized laboratories of interest effectively is provided. We particularly accounted for the resources consumed within the laboratory premises such as cost of reagents for DNA isolation, cost of consumables, cost of personnel, while costs associated with patient recruitment, blood sample collection and maintenance, administration costs in the hospital, and costs of blood sample shipment were not taken into consideration. Our article presents the first-time detailed information on a costing framework for pharmacogenomic testing that could be employed to laboratories involved in routine clinical implementation of pharmacogenomics.

Pharmacogenetics in Psychiatry: An Update on Clinical Usability

Using pharmacogenetics in guiding drug therapy experiences a steady increase in uptake, although still leads to discussions as to its clinical use. Psychiatry constitutes a field where pharmacogenomic testing might help in guiding drug therapy. To address current challenges, this minireview provides an update regarding genotyping (SNP analysis/arrays/NGS), structural variant detection (star-alleles/CNVs/hybrid alleles), genotype-to-phenotype translations, cost-effectiveness, and actionability of results (FDA/CPIC/PharmGKB) regarding clinical importance of pre-emptive pharmacogenomic testing for prescription of antidepressants and antipsychotics.

Literature Review Concerning the Challenges of Implementing Pharmacogenetics in Primary Care Practice

Since President Obama signed the Precision Medicine Initiative in 2015, endeavors to integrate pharmacogenetics in clinical practice and psychiatric care have been evolving rapidly. The nature of general practice and psychiatric medicine, including psychopharmacotherapy and the long-term care necessary for chronic diseases, renders these fields in desperate need of the implementation of pharmacogenetics. This article presents some of the challenges facing pharmacogenetics implementation in family medicine and psychiatric care. Reputable research websites were used to extract papers, data, and lectures concerning this topic. The results reveal that three main challenges are facing this integration: the evaluation of pharmacogenetic testing in general and psychiatric practice, cost-effectiveness, and regulatory burdens. Although considerable advances are being made to address these issues, it is time to gather these efforts under one umbrella to create guidelines based on previous and upcoming research.

Cost avoidance related to a pharmacist-led pharmacogenomics service for the Program of All-inclusive Care for the Elderly

Aim: Estimate cost avoidance of pharmacist recommendations for participants enrolled in the Program of All-inclusive Care for the Elderly. Materials & methods: Convenience sample of 200 pharmacogenomics consultations from the PHARM-GENOME-PACE study. Genetic variants, drug-gene interactions, drug-drug-gene interactions and phenoconversions were interrogated. Cost avoidance was estimated and adjusted for inflation. Results: In total, 165 participants had at least one actionable drug-gene pair totaling 429 drug-gene pairs, of which 158 (36.8%) were clinically actionable. Most (70.5%) pharmacists' recommendations were accepted. Estimated cost avoidance was $233,945 when all recommendations were included but conservatively $162,031 based on acceptance rates. Overall mean cost avoidance per actionable drug-gene pair was $1063 or $1983 per participant. Conclusion: Pharmacist-led pharmacogenomics services added to the traditional medication review can avoid substantial costs for payers. Clinical trial registration number: NCT03257605.

Genetics of Treatment Outcomes in Major Depressive Disorder: Present and Future

Pharmacogenetic testing is a useful and increasingly widespread tool to assist in antidepressant prescription. More than ten antidepressants (including tricyclics, selective serotonin reuptake inhibitors and venlafaxine) have already genetic biomarkers of response/side effects in clinical guidelines and drug labels. These are represented by functional genetic variants in genes coding for cytochrome enzymes (CYP2D6 and CYP2C19). Depending on the predicted metabolic activity, guidelines provide recommendations on drug choice and dosing. Despite not conclusive, the current evidence suggests that testing can be useful in patients who did not respond or tolerate at least one previous pharmacotherapy. However, the current recommendations are based on pharmacokinetic genes only (CYP450 enzymes), while pharmacodynamic genes (modulating antidepressant mechanisms of action in the brain) are still being studied because of their greater complexity. This may be captured by polygenic risk scores, which reflect the cumulative contribution of many genetic variants to a trait, and they may provide future clinical applications of pharmacogenetics. A more extensive use of genotyping in clinical practice may lead to improvement in treatment outcomes thanks to personalized treatments, but possible ethical issues and disparities should be taken into account and prevented.

[Perspectives of the use of pharmacogenetic tests in neurology and psychiatry]

The review is devoted to the analysis of the current state of pharmacogenetic research and their use in psychiatric practice. The main genes responsible for the pharmacodynamics and pharmacokinetics of drugs used in psychiatry are listed. Foreign pharmacogenetic clinical recommendations and progress on their implementation in medical practice in various countries of Europe and the USA are analyzed. The need to create Russian clinical guidelines on pharmacogenomics to improve the effectiveness of patient care and to implement a personalized approach to therapy is discussed.

Pharmacogenomics at the center of precision medicine: challenges and perspective in an era of Big Data

Pharmacogenomics (PGx) is one of the core elements of personalized medicine. PGx information reduces the likelihood of adverse drug reactions and optimizes therapeutic efficacy. St Catherine Specialty Hospital in Zagreb/Zabok, Croatia has implemented a personalized patient approach using the RightMed^® Comprehensive PGx panel of 25 pharmacogenes plus Facor V Leiden, Factor II and MTHFR genes, which is interpreted by a special counseling team to offer the best quality of care. With the advent of significant technological advances comes another challenge: how can we harness the data to inform clinically actionable measures and how can we use it to develop better predictive risk models? We propose to apply the principles artificial intelligence to develop a medication optimization platform to prevent, manage and treat different diseases.

Concepts Driving Pharmacogenomics Implementation Into Everyday Healthcare

Pharmacogenomics (PGx) is often promoted as the domain of precision medicine with the greatest potential to readily impact everyday healthcare. Rapid advances in PGx knowledge derived from extensive basic and clinical research along with decreasing costs of laboratory testing have led to an increased interest in PGx and expectations of imminent clinical translation with substantial clinical impact. However, the implementation of PGx into clinical workflows is neither simple nor straightforward, and comprehensive processes and multidisciplinary collaboration are required. Several national and international institutions have pioneered models for implementing clinical PGx, and these initial models have led to a better understanding of unresolved challenges. In this review, we have categorized and explored the most relevant of these challenges to highlight potential gaps and present possible solutions. We describe the ongoing need for basic and clinical research to drive further developments in evidence-based medicine. Integration into daily clinical workflows introduces new challenges requiring innovative solutions; specifically those related to the electronic health record and embedded clinical decision support. We describe advances in PGx testing and result reporting and describe the critical need for increased standardization in these areas across laboratories. We also explore the complexity of the PGx knowledge required for clinical practice and the need for educational strategies to ensure adequate understanding among members of current and future healthcare teams. Finally, we evaluate knowledge obtained from previous implementation efforts and discuss how to best apply these learnings to future projects. Despite these challenges, the future of precision medicine appears promising due to the rapidity of recent advances in the field and current multidisciplinary efforts to effectively translate PGx to everyday clinical practice.

Translating pharmacogenomics into clinical decisions: do not let the perfect be the enemy of the good

The field of pharmacogenomics (PGx) is gradually shifting from the reactive testing of single genes toward the proactive testing of multiple genes to improve treatment outcomes, reduce adverse events, and decrease the burden of unnecessary costs for healthcare systems. Despite the progress in the field of pharmacogenomics, its implementation into routine care has been slow due to several barriers. However, in recent years, the number of studies on the implementation of PGx has increased, all providing a wealth of knowledge on different solutions for overcoming the obstacles that have been emphasized over the past years. This review focuses on some of the challenges faced by these initiatives, the solutions and different approaches for testing that they suggest, and the evidence that they provide regarding the benefits of preemptive PGx testing.

Impact of pharmacogenomics on clinical outcomes in major depressive disorder in the GUIDED trial: A large, patient- and rater-blinded, randomized, controlled study

Current prescribing practices for major depressive disorder (MDD) produce limited treatment success. Although pharmacogenomics may improve outcomes by identifying genetically inappropriate medications, studies to date were limited in scope. Outpatients (N = 1167) diagnosed with MDD and with a patient- or clinician-reported inadequate response to at least one antidepressant were enrolled in the Genomics Used to Improve DEpression Decisions (GUIDED) trial - a rater- and patient-blind randomized controlled trial. Patients were randomized to treatment as usual (TAU) or a pharmacogenomics-guided intervention arm in which clinicians had access to a pharmacogenomic test report to inform medication selections (guided-care). Medications were considered congruent ('use as directed' or 'use with caution' test categories) or incongruent ('use with increased caution and with more frequent monitoring' test category) with test results. Unblinding occurred after week 8. Primary outcome was symptom improvement [change in 17-item Hamilton Depression Rating Scale (HAM-D17)] at week 8; secondary outcomes were response (≥50% decrease in HAM-D17) and remission (HAM-D17 ≤ 7) at week 8. At week 8, symptom improvement for guided-care was not significantly different than TAU (27.2% versus 24.4%, p = 0.107); however, improvements in response (26.0% versus 19.9%, p = 0.013) and remission (15.3% versus 10.1%, p = 0.007) were statistically significant. Patients taking incongruent medications prior to baseline who switched to congruent medications by week 8 experienced greater symptom improvement (33.5% versus 21.1%, p = 0.002), response (28.5% versus 16.7%, p = 0.036), and remission (21.5% versus 8.5%, p = 0.007) compared to those remaining incongruent. Pharmacogenomic testing did not significantly improve mean symptoms but did significantly improve response and remission rates for difficult-to-treat depression patients over standard of care (ClinicalTrials.gov NCT02109939).

Influence of CYP2C19 Metabolizer Status on Escitalopram/Citalopram Tolerability and Response in Youth With Anxiety and Depressive Disorders

In pediatric patients, the selective serotonin reuptake inhibitors (SSRIs) escitalopram and citalopram (es/citalopram) are commonly prescribed for anxiety and depressive disorders. However, pharmacogenetic studies examining CYP2C19 metabolizer status and es/citalopram treatment outcomes have largely focused on adults. We report a retrospective study of electronic medical record data from 263 youth < 19 years of age with anxiety and/or depressive disorders prescribed escitalopram or citalopram who underwent routine clinical CYP2C19 genotyping. Slower CYP2C19 metabolizers experienced more untoward effects than faster metabolizers (p = 0.015), including activation symptoms (p = 0.029) and had more rapid weight gain (p = 0.018). A larger proportion of slower metabolizers discontinued treatment with es/citalopram than normal metabolizers (p = 0.007). Meanwhile, faster metabolizers responded more quickly to es/citalopram (p = 0.005) and trended toward less time spent in subsequent hospitalizations (p = 0.06). These results highlight a disparity in treatment outcomes with es/citalopram treatment in youth with anxiety and/or depressive disorders when standardized dosing strategies were used without consideration of CYP2C19 metabolizer status. Larger, prospective trials are warranted to assess whether tailored dosing of es/citalopram based on CYP2C19 metabolizer status improves treatment outcomes in this patient population.

Translating genotype data of 44,000 biobank participants into clinical pharmacogenetic recommendations: challenges and solutions

PURPOSE

Biomedical databases combining electronic medical records and phenotypic and genomic data constitute a powerful resource for the personalization of treatment. To leverage the wealth of information provided, algorithms are required that systematically translate the contained information into treatment recommendations based on existing genotype-phenotype associations.

METHODS

We developed and tested algorithms for translation of preexisting genotype data of over 44,000 participants of the Estonian biobank into pharmacogenetic recommendations. We compared the results obtained by genome sequencing, exome sequencing, and genotyping using microarrays, and evaluated the impact of pharmacogenetic reporting based on drug prescription statistics in the Nordic countries and Estonia.

RESULTS

Our most striking result was that the performance of genotyping arrays is similar to that of genome sequencing, whereas exome sequencing is not suitable for pharmacogenetic predictions. Interestingly, 99.8% of all assessed individuals had a genotype associated with increased risks to at least one medication, and thereby the implementation of pharmacogenetic recommendations based on genotyping affects at least 50 daily drug doses per 1000 inhabitants.

CONCLUSION

We find that microarrays are a cost-effective solution for creating preemptive pharmacogenetic reports, and with slight modifications, existing databases can be applied for automated pharmacogenetic decision support for clinicians.