Predicting drug-drug and drug-gene interactions in a community pharmacy population.

OBJECTIVES: Drug-drug interactions (DDIs) are among the most common causes of adverse drug reactions and are further complicated by genetic variants of drug-metabolizing enzymes. The aim of this study is to quantify and describe potential DDIs, drug-gene interactions (DGIs), and drug-drug-gene interactions (DDGIs) in a community-based population. STUDY DESIGN: This was an analysis of deidentified retail pharmacy prescription data for 4761 individuals. METHODS: Data were first assessed for DDIs, and individuals were stratified to a risk category using the logic of a commercially available digital DDGI tool. To calculate the frequency of potential DGIs and DDGIs, genotypes were imputed and randomly allocated to the cohort 100 times via Monte Carlo simulation according to each variant's frequency in the general population. RESULTS: The probability of a DDI of any impact was 26.0% and increased to 49.6% (95% CI, 48.4%-50.7%) when drug-metabolizing phenotypes were ascribed according to the distribution of variants of 11 genes as found in a Caucasian population. There was a 7.8% probability of major DDIs, which increased to a 10.1% (95% CI, 9.5%-10.8%) probability with the addition of genetic contributions. The probability of DDGIs of any impact was correlated with the number of medications. Antidepressants, antiemetics, blood products and modifiers, analgesics, and antipsychotics had the highest probability of DDGIs. CONCLUSIONS: The probability of drug interaction risk increased when phenotypes associated with genetic polymorphisms were attributed to the population. These data suggest that pharmacogenomic assessment may be useful in predicting drug interactions and severity when evaluating patient medication profiles.

Use of a consultation service following pharmacogenetic testing in psychiatry.

The emerging discipline of pharmacogenetics (PGx) has the goal of aiding the selection of effective therapies and personalized dosing, decreasing the likelihood of adverse drug reactions and optimizing resource utilization. Simultaneously, the rapid evolution of economically feasible genetic testing technologies has resulted in a raft of commercial entities that provide genetic data to providers for use with their complex patients. The adoption of pharmacogenomics in psychiatry is growing, but it is limited by several factors, including the limitless permutations of drugs, comorbid conditions and concomitant medications and provider understanding of phenomena such as phenoconversion. We established an expert PGx consultation service for psychiatric providers who utilize our commercial PGx assay. To date, this service has provided ∼16,000 consults with extremely high levels of satisfaction; in an anonymous survey, 96% of respondents reported a rating of "very helpful" or "extremely helpful".

Randomized, controlled, participant- and rater-blind trial of pharmacogenomic test-guided treatment versus treatment as usual for major depressive disorder.

BACKGROUND: Cohort and cost-effectiveness studies suggest that measuring variation in genes that influence metabolism of common drugs could improve antidepressant treatment outcomes. Prior randomized trials have yielded inconsistent results. METHOD: Multicenter randomized double-blind (subject and rater), controlled trial of pharmacogenomic testing among outpatients with nonpsychotic major depressive disorder. Study participants (n = 304) were randomized 1:1 to assay-guided treatment (AGT; N = 151) or treatment-as-usual (TAU; N = 153). Participants and raters were blinded to study arm; unblinded clinicians received results of a pharmacogenomic test and adjusted treatment in light of the test report. Primary outcome was change over 8 weeks in Hamilton Depression Rating Scale (SIGH-D-17). RESULTS: For the primary comparison of interest, change in SIGH-D-17, no significant difference was detected between AGT and TAU at Week 8 (p = .53). Rates of study completion also did not differ between the arms (AGT 92.7%, TAU 92.2% (χ2 = 0.03, df = 1, p = .86). Exploratory analyses suggested significantly fewer individuals experienced worsening of depressive symptoms following AGT, and that treatment concordant with assay results was associated with greater likelihood of remission. CONCLUSION: Pharmacogenomic testing using a panel of pharmacokinetic and pharmacodynamic variants was not associated with significant improvement in the primary efficacy outcome when providers were unconstrained by the assay results. Further investigation is needed to understand the discordance with cost-effectiveness results and among randomized trials.

Pharmacogenomics and Psychiatric Clinical Care.

Approximately one in five individuals in the United States experiences mental health issues in any given year, and these disorders are consistently among the leading causes of years lived with disability. Unfortunately, many mental illnesses are lifelong conditions that require medication and therapy to improve quality of life, yet clinical trial data show that many patients fail to achieve remission or require several pharmacological interventions prior to remission. These results indicate a need to address the variability among patients in their response to medication, in addition to developing treatment plans tailored to the individual. One approach that may help explain patient variability in response to medication is pharmacogenetic testing. The current review shows the clinical use of pharmacogenetic testing in a small subset of gene variants and how they pertain to psychiatric illness and treatment. Recent evidence suggests that genetic testing for psychiatric illness can improve patient outcomes in addition to decreasing health care costs. [Journal of Psychosocial Nursing and Mental Health Services, 56(1), 22-31.].