Acute pain pathways: protocol for a prospective cohort study.

INTRODUCTION: Opioid analgesics are often used to treat moderate-to-severe acute non-cancer pain; however, there is little high-quality evidence to guide clinician prescribing. An essential element to developing evidence-based guidelines is a better understanding of pain management and pain control among individuals experiencing acute pain for various common diagnoses. METHODS AND ANALYSIS: This multicentre prospective observational study will recruit 1550 opioid-naïve participants with acute pain seen in diverse clinical settings including primary/urgent care, emergency departments and dental clinics. Participants will be followed for 6 months with the aid of a patient-centred health data aggregating platform that consolidates data from study questionnaires, electronic health record data on healthcare services received, prescription fill data from pharmacies, and activity and sleep data from a Fitbit activity tracker. Participants will be enrolled to represent diverse races and ethnicities and pain conditions, as well as geographical diversity. Data analysis will focus on assessing patients' patterns of pain and opioid analgesic use, along with other pain treatments; associations between patient and condition characteristics and patient-centred outcomes including resolution of pain, satisfaction with care and long-term use of opioid analgesics; and descriptive analyses of patient management of leftover opioids. ETHICS AND DISSEMINATION: This study has received approval from IRBs at each site. Results will be made available to participants, funders, the research community and the public. TRIAL REGISTRATION NUMBER: NCT04509115.

Pharmacogenetic Labeling of FDA-Approved Drugs: A Regulatory Retrospective.

The U.S. Food and Drug Administration recently marked 10 years since first updating the labeling for warfarin (often referred to as the "poster child" of pharmacogenomics) to include information regarding the potential impact of CYP2C9 and VKORC1 genetic variation on warfarin dosing requirements and risks. Herein, we opine on the experience updating the warfarin labeling, highlighting more generally the enabling factors and challenges encountered when considering incorporation of pharmacogenomic information into the prescribing recommendations for already approved drugs. We also provide a historical perspective of implemented changes in regulatory policies related to personalized medicine.

Clinical Trial Designs to Support Clinical Utility of Pharmacogenomic Testing.

Advancing the use of biomarkers and pharmacogenomics has been a key priority area for the U.S. Food and Drug Administration (FDA). The FDA offers prescribing recommendations to manage ~100 gene-drug interactions, and multiple institutions around the United States and abroad have incorporated genomic testing into patient care. However, the penetration of pharmacogenomic testing remains incomplete. In this perspective, we summarize the evidence streams to support the clinical utility of pharmacogenomic testing and its transition into clinical practice.

Dosing recommendations for pharmacogenetic interactions related to drug metabolism.

OBJECTIVE: Pharmacogenomic studies have established the important contribution of drug-metabolizing enzyme genotype toward drug toxicity and treatment failure; however, clinical implementation of pharmacogenomics has been slow. The aim of this study was to systematically review the information on drug-metabolizing enzyme pharmacogenomics available in the US drug labeling, practice guidelines, and recommendations. METHODS: Drug-metabolizing enzyme genotype and phenotype information was assessed in US FDA drug labeling, clinical practice guidelines, and independent technology assessors to evaluate the consistency in information sources for healthcare providers. RESULTS: Eighty four gene-drug pairs were identified as having drug-metabolizing enzyme genotype or phenotype information within the label. The manner in which pharmacogenomic information was presented was heterogeneous both within the label and between clinical practice recommendations. CONCLUSION: For proper implementation of pharmacogenomics in clinical practice, information sources for healthcare providers should relay consistent and clear information for the appropriate use of biomarkers.

Identification of Stevens-Johnson syndrome and toxic epidermal necrolysis in electronic health record databases.

BACKGROUND: Stevens-Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN) carry a high mortality risk. While identifying clinical and genetic risk factors for these conditions has been hindered by their rarity, large electronic health databases hold promise for identifying large numbers of cases for study, especially with the introduction in 2008 of ICD-9 codes more specific for these conditions. OBJECTIVE: The objective of this study is to estimate the validity of ICD-9 codes for ascertaining SJS/TEN in 12 collaborating research units in the USA, covering almost 60 million lives. METHODS: From the electronic databases at each site, we ascertained potential cases of SJS/TEN using ICD-9 codes. At five sites, a subset of medical records was abstracted and standardized criteria applied by board-certified dermatologists to adjudicate diagnoses. Multivariate logistic regression was used to identify factors independently associated with validated SJS/TEN cases. RESULTS: A total of 56 591 potential cases of SJS/TEN were identified. A subset of 276 charts was selected for adjudication and 39 (of the 276) were confirmed as SJS/TEN. Patients with the ICD-9 codes introduced after 2008 were more likely to be confirmed as cases (OR 3.32; 95%CI 0.82, 13.47) than those identified in earlier years. Likelihood of case status increased with length of hospitalization. Applying the probability of case status to the 56 591 potential cases, we estimated 475-875 to be valid SJS/TEN cases. CONCLUSION: Newer ICD-9 codes, along with length of hospitalization, identified patients with a high likelihood of SJS/TEN. This is important for identification of subjects for future pharmacogenomics studies.

Effectiveness of clopidogrel dose escalation to normalize active metabolite exposure and antiplatelet effects in CYP2C19 poor metabolizers.

Carriers of two copies of the loss-of-function CYP2C19*2 variant convert less clopidogrel into its active metabolite, resulting in diminished antiplatelet responses and higher cardiovascular event rates. To evaluate whether increasing the daily clopidogrel dose in poor metabolizers (PM) overcomes the effect of the CYP2C19 * 2 variant, we enrolled 18 healthy participants in a genotype-stratified, multi-dose, three-period, fixed-sequence crossover study. Six participants with the *1/*1 extensive (EM), *1/*2 intermediate (IM), and *2/*2 poor metabolizer genotypes each received 75 mg, 150 mg, and 300 mg each for 8 days. In each period, maximal platelet aggregation 4 hours post-dose (MPA4) and active metabolite area under the curve (AUC) differed among genotype groups (P < .05 for all). At day 8, PMs needed 300 mg daily and IMs needed 150 mg daily to attain a similar MPA4 as EMs on the 75 mg dose (32.6%, 33.2%, 31.3%, respectively). Similarly, PMs needed 300 mg daily to achieve active metabolite concentrations that were similar to EMs on 75 mg (AUC 37.7 and 33.5 ng h/mL, respectively). These results suggest that quadrupling the usual clopidogrel dose might be necessary to overcome the effect of poor CYP2C19 metabolism.

Impact of TCF7L2 single nucleotide polymorphisms on hydrochlorothiazide-induced diabetes.

OBJECTIVE: Thiazide diuretics have been associated with increased risk for new onset diabetes (NOD), but pharmacogenetic markers of thiazide-induced NOD are not well studied. Single nucleotide polymorphisms (SNPs) in the transcription factor 7-like 2 gene (TCF7L2) represent the strongest and most reproducible genetic associations with diabetes. We investigated the association of tag SNPs in TCF7L2 with thiazide-induced NOD. METHODS: We identified cases that developed NOD and age, sex, and race/ethnicity-matched controls from the INternational VErapamil SR-Trandolapril STudy (INVEST). INVEST compared cardiovascular outcomes between two antihypertensive treatment strategies in ethnically diverse patients with hypertension and coronary artery disease. We genotyped 101 TCF7L2 tag SNPs and used logistic regression to test for pharmacogenetic (SNP×hydrochlorothiazide treatment) interactions. Permuted interaction P values were corrected with the PACT test and adjusted for diabetes-related variables. RESULTS: In INVEST whites, we observed three TCF7L2 SNPs with significant SNP×treatment interactions for NOD. The strongest pharmacogenetic interaction was observed for rs7917983 [synergy index 3.37 (95% CI 1.72-6.59), P=5.0×10, PACT=0.03], which was associated with increased NOD risk in hydrochlorothiazide-treated patients [odds ratio 1.53 (1.04-2.25), P=0.03] and decreased NOD risk in non hydrochlorothiazide-treated patients [odds ratio 0.48 (0.27-0.86), P=0.02]. The TCF7L2 SNP rs4506565, previously associated with diabetes, showed a similar, significant pharmacogenetic association. CONCLUSION: Our results suggest that hydrochlorothiazide treatment is an environmental risk factor that increases diabetes risk beyond that attributed to TCF7L2 variation in white, hypertensive patients. Further study and replication of our results is needed to confirm pharmacogenetic influences of TCF7L2 SNPs on thiazide-induced NOD.

Consistency of drug-drug and gene-drug interaction information in US FDA-approved drug labels.

AIM: To characterize concordance between clinically relevant drug-drug interactions (DDIs) related to CYP2C19, CYP2D6 and CYP2C9 and their analogous gene-drug interactions (GDIs) in US FDA-approved drug labeling. METHODS: We selected prototypical CYP2C19, CYP2D6 and CYP2C9 inhibitors and abstracted all respective interacting drugs via a tertiary resource used in the clinical setting. We then selected only CYP2C19, CYP2D6 and CYP2C9 metabolism-related DDIs requiring enhanced clinical monitoring, dose adjustment or use of alternative drugs. Labeling and management strategies on DDIs and GDIs were compared. RESULTS: Among the drug labels with DDI information, 73% of them describe the analogous GDI. Of the 65 drug labels, 43 and 17% had specific management recommendations for DDIs and GDIs, respectively. In general, GDI management recommendations were concordant with DDI management recommendations in terms of specific dose adjustments or use of alternative drugs. CONCLUSION: The FDA has recognized genetic differences in drug metabolism where clinically relevant DDIs trigger dose adjustment or use of alternative drugs.

The functional G143E variant of carboxylesterase 1 is associated with increased clopidogrel active metabolite levels and greater clopidogrel response.

INTRODUCTION: Carboxylesterase 1 (CES1) is the primary enzyme responsible for converting clopidogrel into biologically inactive carboxylic acid metabolites. METHODS: We genotyped a functional variant in CES1, G143E, in participants of the Pharmacogenomics of Anti-Platelet Intervention (PAPI) study (n=566) and in 350 patients with coronary heart disease treated with clopidogrel, and carried out an association analysis of bioactive metabolite levels, on-clopidogrel ADP-stimulated platelet aggregation, and cardiovascular outcomes. RESULTS: The levels of clopidogrel active metabolite were significantly greater in CES1 143E-allele carriers (P=0.001). Consistent with these findings, individuals who carried the CES1 143E-allele showed a better clopidogrel response as measured by ADP-stimulated platelet aggregation in both participants of the PAPI study (P=0.003) and clopidogrel-treated coronary heart disease patients (P=0.03). No association was found between this single nucleotide polymorphism and baseline measures of platelet aggregation in either cohort. CONCLUSION: Taken together, these findings suggest, for the first time, that genetic variation in CES1 may be an important determinant of the efficacy of clopidogrel.

A sensitive and rapid ultra HPLC-MS/MS method for the simultaneous detection of clopidogrel and its derivatized active thiol metabolite in human plasma.

A sensitive, selective, and rapid ultra-high performance liquid chromatography-tandem mass spectrometry (uHPLC-MS/MS) was developed for the simultaneous quantification of clopidogrel (Plavix(®)) and its derivatized active metabolite (CAMD) in human plasma. Derivatization of the active metabolite in blood with 2-bromo-3'-methoxy acetophenone (MPB) immediately after collection ensured metabolite stability during sample handling and storage. Following addition of ticlopidine as an internal standard and simple protein precipitation, the analytes were separated on a Waters Acquity UPLC™ sub-2 µm-C(18) column via gradient elution before detection on a triple-quadrupole MS with multiple-reaction-monitoring via electrospray ionization. The method was validated across the clinically relevant concentration range of 0.01-50 ng/mL for parent clopidogrel and 0.1-150 ng/mL (r(2)=0.99) for CAMD, with a fast run time of 1.5 min to support pharmacokinetic studies using 75, 150, or 300 mg oral doses of clopidogrel. The analytical method measured concentrations of clopidogrel and CAMD with accuracy (%DEV) <±12% and precision (%CV) of <±6%. The method was successfully applied to measure the plasma concentrations of clopidogrel and CAMD in three subjects administered single oral doses of 75, 150, and 300 mg clopidogrel. It was further demonstrated that the derivatizing agent (MPB) does not affect clopidogrel levels, thus from one aliquot of blood drawn clinically, this method can simultaneously quantify both clopidogrel and CAMD with sensitivity in the picogram per mL range.

Allopurinol pharmacogenetics: assessment of potential clinical usefulness.

Use of pharmacogenetics to inform treatment decisions remains a priority for clinicians, patients and public health agencies. We previously developed a framework for systematically assessing whether pharmacogenetic test information would likely bring value to clinical decision-making and enjoy practical uptake. We applied this tool to allopurinol to determine potential usefulness of HLA genetic information in assessing risk for allopurinol-induced severe cutaneous adverse reactions. We quantified allopurinol use data and the magnitude of adverse event signals using US FDA databases, reviewed reported cases of allopurinol-associated severe cutaneous adverse reactions to assess whether clinical subtypes of patients could be identified, performed pooled analyses of associations between HLA variation and allopurinol-induced severe cutaneous adverse reactions and described considerations in clinical implementation of allopurinol pharmacogenetics.

Pharmacogenomics in the assessment of therapeutic risks versus benefits: inside the United States Food and Drug Administration.

Pharmacogenomics is the study of how genetic variations influence responses to drugs, diagnostics, or biologic agents. The field of pharmacogenomics has significant potential to enhance drug development and aid in making regulatory decisions. The United States Food and Drug Administration (FDA) has supported pharmacogenomics for nearly a decade by providing regulatory advice and reviewing applications, with the intent of discovering and applying genetic determinants of treatment effects. The FDA will continue to develop policies and processes centered on genomics and individualized therapeutics to guide rational drug development. It will also continue to inform the public of clinically relevant pharmacogenomic issues through various mechanisms of communication, such as drug labeling. In this review, we provide a perspective on several pharmacogenomic activities at the FDA. In addition, we attempt to clarify what we believe are several misperceptions regarding the FDA's pharmacogenomic initiatives. We hope this perspective provides a window into some ways in which the FDA is enabling individualized therapeutics through its mission-critical activities.

Effect of cytochrome P450 3A5 genotype on atorvastatin pharmacokinetics and its interaction with clarithromycin.

Abstract Study Objective. To assess the effects of the cytochrome P450 (CYP) 3A genotype, CYP3A5, on atorvastatin pharmacokinetics and its interaction with clarithromycin. Design. Prospective, two-phase, randomized-sequence, open-label pharmacokinetic study. Setting. Clinical research center at a teaching hospital. Subjects. Twenty-three healthy volunteers who were screened for genotype: 10 subjects carried the CYP3A5*1 allele (expressors) and 13 subjects did not (nonexpressors). Intervention. In one phase, subjects received a single oral dose of atorvastatin 20 mg. In the other phase, subjects received clarithromycin 500 mg twice/day for 5 days; on day 4 after the morning dose, subjects also received a single oral dose of atorvastatin 20 mg. All subjects participated in both phases of the study, which were separated by at least 14 days. Measurements and Main Results. Pharmacokinetic parameters of both forms of atorvastatin-atorvastatin acid and atorvastatin lactone-were compared between CYP3A5 expressors and nonexpressors, both in the absence and presence of clarithromycin, a strong CYP3A inhibitor. The acid form is pharmacologically active, and the lactone form has been associated with the atorvastatin's muscle-related adverse effects. Atorvastatin acid exposure did not differ significantly between CYP3A5 genotype groups. When subjects had not received clarithromycin pretreatment, the area under the concentration-time curve from time zero extrapolated to infinity (AUC(0-∞)) of atorvastatin lactone was 36% higher in nonexpressors than in expressors (median 47.6 ng•hr/ml [interquartile range (IQR) 37.8-64.3 ng•hr/ml] vs 34.9 ng•hr/ml [IQR 21.6-42.2 ng•hr/ml], p=0.038). After clarithromycin pretreatment, changes in the pharmacokinetic parameters of atorvastatin acid and lactone were not significantly different between the nonexpressors versus the expressors; however, the increase in the AUC(0-∞) of atorvastatin lactone was 37% greater in expressors than in nonexpressors (geometric mean ± SD 3.59 ± 0.57 vs 2.62 ± 0.35, p=0.049). Conclusion. Our data suggest that the CYP3A5 genotype has minimal effects on the pharmacokinetic parameters of atorvastatin and its interaction with clarithromycin; these effects are unlikely to be clinically significant.

Liver X receptor α gene polymorphisms and variable cardiovascular outcomes in patients treated with antihypertensive therapy: results from the INVEST-GENES study.

BACKGROUND/AIMS: Liver X receptor-α (LXRA) is a nuclear receptor that regulates genes important in cholesterol homeostasis and inflammation. Several single nucleotide polymorphisms (SNPs) in the LXRA gene (NR1H3) have been earlier associated with metabolic phenotypes (dyslipidemia and elevated body mass index). Metabolic dysregulation is a major contributor to coronary disease; therefore, we assessed LXRA in International Verapamil Sustained Release SR Trandolapril Study Genetic Substudy (INVEST-GENES), a genetic-substudy of a large clinical trial in patients with hypertension and coronary artery disease. METHODS: Seven tag SNPs in the LXRA gene region (NR1H3) were selected for study: rs11039149, rs12221497, rs2279238, rs7120118, rs326213, rs11039159, and rs10501321. One thousand fifty-nine patients were genotyped from the INVEST-GENES case-control set (verapamil-sustained release-based or atenolol-based treatment strategies) that comprised of 297 cases frequency matched (approximately 2.5:1) with that of event-free controls by sex and race. The primary outcome was defined as first occurrence of all-cause death, nonfatal myocardial infarction, or nonfatal stroke. Adjusted odds ratios (ORs) were calculated using logistic regression. RESULTS: Three of the seven SNPs were associated with significant effects on the primary outcome in nonBlacks. The variant G allele of rs11039149 and the variant A allele of rs12221497 were associated with reduced risk of experiencing the primary outcome [OR: 0.62, confidence interval (CI): 0.45-0.85, P=0.003 and OR: 0.60, CI: 0.39-0.91, P=0.016, respectively]. The rs2279238 genotype was associated with a significant increase in risk for the primary outcome (OR: 1.42, CI: 1.03-1.95, P=0.03). Furthermore, there was a significant genotype-treatment strategy interaction for carriers of the variant T allele of rs2279238 (OR for verapamil-sustained release strategy compared with atenolol strategy: 2.86, CI: 1.50-5.46, P=0.0015). Diplotype analyses showed that the SNPs are rarely coinherited and support the directionally opposite effects of the SNPs on the primary outcome. CONCLUSION: LXRA genotypes were associated with variable risk for cardiovascular outcomes and pharmacogenetic effect in INVEST-GENES. These novel findings suggest that LXRA is a genetic/pharmacogenetic target that should be further explored.

Learning from product labels and label changes: how to build pharmacogenomics into drug-development programs.

The 2010 US FDA-Drug Industry Association (DIA) Pharmacogenomics (PGx) Workshop follows a series that began in 2002 bringing together multidisciplinary experts spanning regulatory authorities, medical research, healthcare and industry. This report summarizes the 'Building PGx into Labels' sessions from the workshop, which discussed the critical elements in developing PGx outcomes leading to product labels that inform efficacy and/or safety. Examples were drawn from US prescribing information, which integrated PGx knowledge into medical decisions (e.g., panitumumab, warfarin and clopidogrel). Attendees indicated the need for broader dialog and for guidelines on evidentiary considerations for PGx to be included into product labels. Also discussed was the understanding of appropriate PGx placement on labels; how to encourage adoption by medical communities of label recommendations on PGx tests; and, given the global nature of drug development, worldwide considerations including European Summary of Product Characteristics.

Development and regulatory strategies for drug and diagnostic co-development.

At the 5th FDA-Drug Industry Association (DIA) Workshop on 'Pharmacogenomics in Drug Development and Regulatory Decision Making', track four focused on the current thinking and issues in the co-development of therapeutic drugs or biologics, and their companion diagnostic products. Identification and validation of genomic and other biomarkers are becoming important components of drug-development strategies, and recent successes show the power of personalized approaches to change the benefit-risk paradigm for new drugs.

High-dose atorvastatin causes a rapid sustained increase in human serum PCSK9 and disrupts its correlation with LDL cholesterol.

Proprotein convertase subtilisin kexin type 9 (PCSK9) is a key regulator of serum LDL-cholesterol (LDL-C) levels. PCSK9 is secreted by the liver into the plasma and binds the hepatic LDL receptor (LDLR), causing its subsequent degradation. We first demonstrated that a moderate dose of atorvastatin (40 mg) increases PCSK9 serum levels, suggesting why increasing statin doses may have diminished efficacy with regard to further LDL-C lowering. Since that initial observation, at least two other groups have reported statin-induced PCSK9 increases. To date, no analysis of the effect of high-dose atorvastatin (80 mg) on PCSK9 over time has been conducted. Therefore, we studied the time course of atorvastatin (80 mg) in human subjects. We measured PCSK9 and lipid levels during a 2-week lead-in baseline period and every 4 weeks thereafter for 16 weeks. We observed that atorvastatin (80 mg) caused a rapid 47% increase in serum PCSK9 at 4 weeks that was sustained throughout 16 weeks of dosing. Importantly, while PCSK9 levels were highly correlated with total cholesterol (TC), LDL-C, and triglyceride (TG) levels at baseline, atorvastatin (80 mg) completely abolished all of these correlations. Together, these results further suggest an explanation for why increasing doses of statins fail to achieve proportional LDL-C lowering.

Biomarkers to improve the benefit/risk balance for approved therapeutics: a US FDA perspective on personalized medicine.

This article highlights a current US FDA perspective concerning the use of biomarker-based diagnostics for personalized medicine. Specifically, current biomarkers that have application for improving the benefit/risk profile of already approved drugs are discussed. The success of biomarkers for use in personalized medicine depends on many factors, including proper evaluation of the usefulness of the biomarker for assessing the event of interest, and the safety and effectiveness of the diagnostic device used to measure the biomarker, which includes appropriate analytical and clinical validation. These points along with the many regulatory concerns regarding co-labeling of drugs and devices and future aspects, such as co-development, will be discussed in this regulatory science focus.