The development and evaluation of dose-prediction tools for allopurinol therapy (Easy-Allo tools).

AIMS: Dose escalation at the initiation of allopurinol therapy can be protracted and resource intensive. Tools to predict the allopurinol doses required to achieve target serum urate concentrations would facilitate the implementation of more efficient dose-escalation strategies. The aim of this research was to develop and externally evaluate allopurinol dosing tools, one for use when the pre-urate-lowering therapy serum urate is known (Easy-Allo1) and one for when it is not known (Easy-Allo2). METHODS: A revised population pharmacokinetic-pharmacodynamic model was developed using data from 653 people with gout. Maintenance doses to achieve the serum urate target of <0.36 mmol L-1 in >80% of individuals were simulated and evaluated against external data. The predicted and observed allopurinol doses were compared using the mean prediction error (MPE) and root mean square error (RMSE). The proportion of Easy-Allo predicted doses within 100 mg of the observed was quantified. RESULTS: Allopurinol doses were predicted by total body weight, baseline urate, ethnicity and creatinine clearance. Easy-Allo1 produced unbiased and suitably precise dose predictions (MPE 2 mg day-1 95% confidence interval [CI] -13-17, RMSE 91%, 90% within 100 mg of the observed dose). Easy-Allo2 was positively biased by about 70 mg day-1 and slightly less precise (MPE 70 mg day-1 95% CI 52-88, RMSE 131%, 71% within 100 mg of the observed dose). CONCLUSIONS: The Easy-Allo tools provide a guide to the allopurinol maintenance dose requirement to achieve the serum urate target of <0.36 mmol L-1 and will aid in the development of novel dose-escalation strategies for allopurinol therapy.

An allopurinol adherence tool using plasma oxypurinol concentrations.

AIMS: This study aimed to develop and evaluate an allopurinol adherence tool based on steady-state oxypurinol plasma concentrations, allopurinol's active metabolite. METHODS: Plasma oxypurinol concentrations were simulated stochastically from an oxypurinol pharmacokinetic model for allopurinol doses of 100-800 mg daily, accounting for differences in renal function, diuretic use and ethnicity. For each scenario, the 20th percentile for peak and trough concentrations defined the adherence threshold, below which imperfect adherence was assumed. Predictive performance was evaluated using both simulated low adherence and against data from 146 individuals with paired oxypurinol plasma concentrations and adherence measures. Sensitivity and specificity (S&S), negative and positive predictive values (NPV, PPV) and receiver operating characteristic (ROC) area under the curve (AUC) were determined. The predictive performance of the tool was evaluated using adherence data from an external study (CKD-FIX). RESULTS: The allopurinol adherence tool produced S&S values for trough thresholds of 89-98% and 76-84%, respectively, and 90%-98% and 76-83% for peak thresholds. PPV and NPV were 79-84% and 88-94%, respectively, for trough and 80-85% and 89-98%, respectively, for peak concentrations. The ROC AUC values ranged from 0.84 to 0.88 and from 0.86 to 0.89 for trough and peak concentrations, respectively. S&S values for the external evaluation were found to be 75.8% and 86.5%, respectively, producing an ROC AUC of 0.8113. CONCLUSION: A tool to identify people with gout who require additional support to maintain adherence using plasma oxypurinol concentrations was developed and evaluated. The predictive performance of the tool is suitable for adherence screening in clinical trials and may have utility in some clinical practice settings.

Population pharmacokinetics, pharmacodynamics and pharmacogenetics modelling of oxypurinol in Hmong adults with gout and/or hyperuricemia.

AIMS: The aim of this study was to quantify identifiable sources of variability, including key pharmacogenetic variants in oxypurinol pharmacokinetics and their pharmacodynamic effect on serum urate (SU). METHODS: Hmong participants (n = 34) received 100 mg allopurinol twice daily for 7 days followed by 150 mg allopurinol twice daily for 7 days. A sequential population pharmacokinetic pharmacodynamics (PKPD) analysis with non-linear mixed effects modelling was performed. Allopurinol maintenance dose to achieve target SU was simulated based on the final PKPD model. RESULTS: A one-compartment model with first-order absorption and elimination best described the oxypurinol concentration-time data. Inhibition of SU by oxypurinol was described with a direct inhibitory Emax model using steady-state oxypurinol concentrations. Fat-free body mass, estimated creatinine clearance and SLC22A12 rs505802 genotype (0.32 per T allele, 95% CI 0.13, 0.55) were found to predict differences in oxypurinol clearance. Oxypurinol concentration required to inhibit 50% of xanthine dehydrogenase activity was affected by PDZK1 rs12129861 genotype (-0.27 per A allele, 95% CI -0.38, -0.13). Most individuals with both PDZK1 rs12129861 AA and SLC22A12 rs505802 CC genotypes achieve target SU (with at least 75% success rate) with allopurinol below the maximum dose, regardless of renal function and body mass. In contrast, individuals with both PDZK1 rs12129861 GG and SLC22A12 rs505802 TT genotypes would require more than the maximum dose, thus requiring selection of alternative medications. CONCLUSIONS: The proposed allopurinol dosing guide uses individuals' fat-free mass, renal function and SLC22A12 rs505802 and PDZK1 rs12129861 genotypes to achieve target SU.

Biopharmaceutical characterization of a novel sustained-release formulation of allopurinol with reduced nephrotoxicity.

The present study was aimed to develop a novel sustained-release formulation for allopurinol (ALP/SR) with the use of a pH-sensitive polymer, hydroxypropyl methylcellulose acetate succinate, to reduce nephrotoxicity. ALP/SR was evaluated in terms of crystallinity, the dissolution profile, pharmacokinetic behavior, and nephrotoxicity in a rat model of nephropathy. Under acidic conditions (pH1.2), sustained release behavior was seen for ALP/SR, although both crystalline ALP and ALP/SR exhibited rapid dissolution at neutral condition. After multiple oral administrations of ALP samples (10 mg-ALP/kg) for 4 days in a rat model of nephropathy, ALP/SR led to a low and sustained plasma concentration of ALP, as evidenced by half the maximum concentration of ALP and a 2.5-fold increase in the half-life of ALP compared with crystalline ALP, possibly due to suppressed dissolution behavior under acidic conditions. Repeated-dosing of ALP/SR resulted in significant reductions in plasma creatinine and blood urea nitrogen levels by 73% and 69%, respectively, in comparison with crystalline ALP, suggesting the low nephrotoxic risk of ALP/SR. From these findings, a strategic SR formulation approach might be an efficacious dosage option for ALP to avoid severe nephrotoxicity in patients with nephropathy.

Prevention of mercaptopurine-induced hypoglycemia using allopurinol to reduce methylated thiopurine metabolites.

Skewing of mercaptopurine (6-MP) metabolism preferentially toward the 6-methylmercaptopurine (6-MMP) metabolite over the antileukemic metabolite 6-thioguanine (6-TGN) is associated with 6-MP-related hepatotoxocity. Allopurinol when coadministered with 6-MP can reduce this skewing and ameliorate the associated adverse effects. The cases we report here demonstrate that aberrant overproduction of 6-MMP is also associated with profound 6-MP-associated hypoglycemia, which can be reversed by administration of allopurinol. This case series contributes to the scant literature on 6-MP-induced hypoglycemia and provides evidence that addition of allopurinol to reduced dose 6-MP can successfully manage this severe toxicity.

pH-Dependent 5-Aminosalicylates Releasing Preparations Do Not Affect Thiopurine Metabolism.

BACKGROUND/AIMS: Thiopurines are key drugs in maintenance therapy for treating inflammatory bowel disease (IBD). Time-dependent 5-aminosalicylates (5-ASA) releasing preparations (time-dependent 5-ASA) increase 6-thioguanine nucleotide (6-TGN), an active metabolite of thiopurines. However, the effects of pH-dependent 5-ASA releasing preparations (pH-dependent 5-ASA) on thiopurine metabolism were not reported. METHODS: We conducted a retrospective study of 134 IBD patients who received thiopurine treatment. The 6-methylmercaptopurine (6-MMP)/6-TGN values after taking the same dose of thiopurine preparations for at least 28 days were included. RESULTS: There was a significant decrease in the 6-MMP/6-TGN ratio in time-dependent 5-ASA compared with group without 5-ASA preparations and the pH-dependent 5-ASA group (p = 0.008 and < 0.001 respectively). Spearman's rank correlation coefficient indicated a negative relationship between the daily oral dose of time-dependent 5-ASA and the 6-MMP/6-TGN ratio (r = -0.362, p = 0.003). Multivariate logistic regression analysis was performed in the groups with 6-MMP/6-TGN ratios of 1 or more and less than 1. The use of time-dependent 5-ASA and concomitant allopurinol negatively affected the independent 6-MMP/6-TGN ratio (p = 0.006 and 0.007 respectively). CONCLUSION: Our study revealed that time-dependent but not pH-dependent 5-ASA decreases the 6-MMP/6-TGN ratio. We also confirmed that concomitant allopurinol results in a low 6-MMP/6TGN ratio.

Individualising the dose of allopurinol in patients with gout.

AIMS: The aims of the study were to: 1) determine if a plasma oxypurinol concentration-response relationship or an allopurinol dose-response relationship best predicts the dose requirements of allopurinol in the treatment of gout; and 2) to construct a nomogram for calculating the optimum maintenance dose of allopurinol to achieve target serum urate (SU) concentrations. METHODS: A nonlinear regression analysis was used to examine the plasma oxypurinol concentration- and allopurinol dose-response relationships with serum urate. In 81 patients (205 samples), creatinine clearance (CLCR ), concomitant diuretic use and SU concentrations before (UP ) and during (UT ) treatment were monitored across a range of allopurinol doses (D, 50-700 mg daily). Plasma concentrations of oxypurinol (C) were measured in 47 patients (98 samples). Models (n = 47 patients) and predictions from each relationship were compared using F-tests, r2 values and paired t-tests. The best model was used to construct a nomogram. RESULTS: The final plasma oxypurinol concentration-response relationship (UT = UP - C*(UP - UR )/(ID50 + C), r2  = 0.64) and allopurinol dose-response relationship (UT = UP - D* (UP - UR )/(ID50 + D), r2  = 0.60) did not include CLCR or diuretic use as covariates. There was no difference (P = 0.87) between the predicted SU concentrations derived from the oxypurinol concentration- and allopurinol dose-response relationships. The nomogram constructed using the allopurinol dose-response relationship for all recruited patients (n = 81 patients) required pretreatment SU as the predictor of allopurinol maintenance dose. CONCLUSIONS: Plasma oxypurinol concentrations, CLCR and diuretic status are not required to predict the maintenance dose of allopurinol. Using the nomogram, the maintenance dose of allopurinol estimated to reach target concentrations can be predicted from UP .

A population pharmacokinetic model to predict oxypurinol exposure in patients on haemodialysis.

PURPOSE: The aims of this study were to characterise the population pharmacokinetics of oxypurinol in patients receiving haemodialysis and to compare oxypurinol exposure in dialysis and non-dialysis patients. METHODS: Oxypurinol plasma concentrations from 6 gout people receiving haemodialysis and 19 people with gout not receiving dialysis were used to develop a population pharmacokinetic model in NONMEM. Deterministic simulations were used to predict the steady-state area under the oxypurinol plasma concentration time curve over 1 week (AUC7days). RESULTS: The pharmacokinetics of oxypurinol were best described by a one-compartment model with a separate parameter for dialytic clearance. Allopurinol 100 mg daily produced an AUC7days of 279 µmol/L h in dialysis patients, a value 50-75 % lower than the AUC7days predicted for patients with normal renal function taking 200 to 400 mg daily (427-855 µmol/L h). Dosing pre-dialysis resulted in about a 25-35 % reduction in exposure compared to post-dialysis. CONCLUSIONS: Oxypurinol is efficiently removed by dialysis. The population dialytic and total (non-dialytic) clearance of oxypurinol were found to be 8.23 and 1.23 L/h, standardised to a fat-free mass of 70 kg and creatinine clearance of 6 L/h, respectively. Our results suggest that if the combination of low-dose allopurinol and haemodialysis does not result in sustained urate lowering below treatment targets (serum urate ≤0.36 mmol/L), then allopurinol doses may be increased to optimise oxypurinol exposure.

Pharmacokinetics and relative bioavailability of two allopurinol tablets in healthy Chinese volunteers
.

OBJECTIVE: To evaluate the pharmacokinetics and relative bioavailability of two allopurinol tablets in healthy Chinese volunteers. METHODS: A single-center, randomized, cross-over, two-period study design was conducted in healthy male subjects who were identified as not carrying the HLA-B*58:01 allele. Under fasting conditions, a single oral dose of 300 mg test or reference tablets was given with a 1-week washout period. The blood samples were collected for up to 12 hours after the administration and the plasma concentrations of allopurinol were determined by high performance liquid chromatography. Subject interviews and physical examinations were done over regular intervals to monitor the adverse events. RESULTS: 18 subjects were enrolled in the study, and none dropped out. The main pharmacokinetic parameters of allopurinol test and reference preparations were as follows: AUC0-tlast was 6,725.1 ± 1,390.0 ng×h×mL-1 and 6,425.6 ± 1,257.6 ng×h×mL-1; AUC0-∞ was 7,069.1 ± 1,503.2 ng×h×mL-1 and 6,750.6 ± 1,347.7 ng×h×mL-1; tmax was 1.3 ± 0.8 hours and 1.3 ± 0.8 hours; Cmax was 2,203.7 ± 557.4 ng×mL-1 and 2,310.8 ± 662.8 ng×mL-1; and T1/2 was 2.0 ± 1.6 hours and 1.7 ± 0.7 hours. The relative bioavailability was 105.1 ± 12.6%. The 90% confidence intervals for the geometric mean ratios (test/reference) of Cmax, AUC0-tlast, and AUC0-∞ of both preparations fell within the bioequivalence acceptance criteria (80 - 125%). No adverse events were found or reported during the study. CONCLUSION: The test allopurinol preparations and the reference preparations are bioequivalent and both are well tolerated.
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[Venous thrombosis, unrecognized complication of DRESS]. / Thrombose veineuse, complication méconnue du DRESS.

BACKGROUND: DRESS (Drug Reaction with Eosinophilia and Systemic Symptoms) is a rare syndrome triggered by an immunological reaction to certain drugs and which may be life-threatening as a result of the onset of severe organ involvement. It is characterised by a long period from the time of drug therapy to the onset of actual signs. Herein, we report the case of 42-year-old female patient who developed DRESS one month after beginning allopurinol treatment. PATIENTS AND METHODS: A 42-year-old woman was hospitalised for febrile exanthema with facial oedema, polyadenopathy, mononucleosis syndrome, major hypereosinophilia and hepatic cytolysis. A diagnosis was made of DRESS with a RegiSCAR score of 5. The implicated drug was allopurinol, which had been initiated one month earlier. HHV-6 IgM serology was positive. Two days after the start of systemic corticosteroids, the patient developed thrombosis of the internal jugular vein. Other than major hypereosinophilia, no other factors favouring thrombosis were detected. A favourable outcome was achieved under effective anticoagulants and corticosteroids. DISCUSSION: They have been rare reports of venous thrombosis during DRESS. Hypereosinophilia can be involved in the onset of this condition. Prophylaxis with systemic anticoagulants may be necessary in DRESS involving major hypereosinophilia.

Benefits of Allopurinol Treatment on Blood Pressure and Renal Function in Patients with Early Stage of Chronic Kidney Disease.

BACKGROUND: Hyperuricemia has been associated with increased risk of endothelial dysfunction, cardiovascular, and renal disease. Allopurinol is a potent xanthine oxidase inhibitor used in hyperuricemic patients. It has been shown to decrease cardiovascular disease and hypertension. However, studies have reported conflicting evidence on its effects on blood pressure (BP) and estimated glomerular filtration rate (GFR) in chronic kidney disease (CKD) patients. OBJECTIVE: To demonstrate the effect of allopurinol on BP and estimated GFR in CKD patients. MATERIAL AND METHOD: Patients with CKD stage II-III were screened for possible study enrollment. All patients received allopurinol 50 mg once daily for 12 weeks. The main outcomes were to observe the changes of BP and GFR after given treatment. RESULTS: Forty-four patients were eligible with mean age of 70.14 ± 8.50 years and mean estimated GFR of 43.22 ± 14.44 mL/ min/1.73 m². Serum uric acid decreased significantly from 8.11 ± 2.68 to 7.05 ± 2.38 mg/dL (p = 0.012) at the end of the study. Allopurinol had also statistically significant lower systolic BP (137.72 ± 14.72 to 131.34 ± 12.10 mmHg, p = 0.019) and diastolic BP (79.63 ± 11.56 to 75.43 ± 9.80 mmHg, p = 0.037) at 12 weeks when compared to baseline. There was significant increased in GFR after treatment (43.22 ± 14.44 vs. 45.34 ± 16.09, mL/min/1.73 m², p = 0.029). No serious adverse effects were noted in any of the treated subjects. Two patients (4.5%) in the treatment group had minor skin reaction. CONCLUSION: The study results confirmed that 12 weeks of allopurinol treatment affects the values of serum uric acid, BP and GFR in early stage of CKD patients who already received standard antihypertensive agents without any significant serious adverse effects.

Understanding the impact of ABCG2 polymorphisms on drug pharmacokinetics: focus on rosuvastatin and allopurinol.

INTRODUCTION: In addition to the well-established understanding of the pharmacogenetics of drug-metabolizing enzymes, there is growing data on the effects of genetic variation in drug transporters, particularly ATP-binding cassette (ABC) transporters. However, the evidence that these genetic variants can be used to predict drug effects and to adjust individual dosing to avoid adverse events is still limited. AREAS COVERED: This review presents a summary of the current literature from the PubMed database as of February 2024 regarding the impact of genetic variants on ABCG2 function and their relevance to the clinical use of the HMG-CoA reductase inhibitor rosuvastatin and the xanthine oxidase inhibitor allopurinol. EXPERT OPINION: Although there are pharmacogenetic guidelines for the ABCG2 missense variant Q141K, there is still some conflicting data regarding the clinical benefits of these recommendations. Some caution appears to be warranted in homozygous ABCG2 Q141K carriers when rosuvastatin is administered at higher doses and such information is already included in the drug label. The benefit of dose adaption to lower possible side effects needs to be evaluated in prospective clinical studies.

An audit of a therapeutic drug monitoring service for allopurinol therapy.

BACKGROUND: Oxypurinol, the active metabolite of allopurinol, is the major determinant of the hypouricemic effect of allopurinol. Monitoring oxypurinol concentrations is undertaken to determine adherence to therapy, to investigate reasons for continuing attacks of acute gout and/or insufficiently low plasma urate concentrations despite allopurinol treatment, and to assess the risk of allopurinol hypersensitivity, an adverse effect that has been putatively associated with elevated plasma oxypurinol concentrations. METHODS: An audit of request forms requesting plasma oxypurinol concentration measurements received by the pathology service (SydPath) at St Vincent's Hospital, Darlinghurst, Sydney was undertaken for the 7-year period January 2005-December 2011. Patient demographics, biochemical data, including plasma creatinine and uric acid concentrations, comorbidities, and concomitant medications were recorded. RESULTS: There were 412 requests for determination of an oxypurinol concentration. On 48% of occasions, the time of allopurinol dosing was recorded, while just 79 (19%) blood samples were collected 6-9 hours postdosing, the time window used to establish the therapeutic range for oxypurinol. For these optimally interpretable concentrations, 32 (8%) were within the putative therapeutic range (5-15 mg/L), while 5 (1%) were below and 41 (10%) above this range. The daily dose of allopurinol was documented on only one-third of the request forms. Individually, plasma urate and creatinine concentrations were requested concomitantly with plasma oxypurinol concentrations in 66% and 58% of the cases, respectively; while plasma oxypurinol, urate, and creatinine concentrations were requested concomitantly in 49% of the cases. CONCLUSIONS: Requesting clinicians and blood specimen collectors often fail to provide relevant information (dose, times of last dose, and blood sample collection) to allow the most useful interpretation of oxypurinol concentrations. Concomitant plasma urate and creatinine concentrations should be requested to allow more complete interpretation of the data.

The population pharmacokinetics of allopurinol and oxypurinol in patients with gout.

PURPOSE: The aims of this study were to develop a population pharmacokinetic model for allopurinol and oxypurinol and to explore the influence of patient characteristics on allopurinol and oxypurinol pharmacokinetics. METHODS: Data from 92 patients with gout and 12 healthy volunteers were available for analysis. A parent-metabolite model with a two-compartment model for allopurinol and a one-compartment model for oxypurinol was fitted to the data using non-linear mixed effects modelling. RESULTS: Renal function, fat-free mass (FFM) and diuretic use were found to predict differences in the pharmacokinetics of oxypurinol. The population estimates for allopurinol clearance, inter-compartmental clearance, central and peripheral volume were 50, 142 L/h/70 kg FFM, 11.4, 91 L/70 kg FFM, respectively, with a between-subject variability of 33 % (coefficient of variance, CV) for allopurinol clearance. Oxypurinol clearance and volume of distribution were estimated to be 0.78 L/h per 6 L/h creatinine clearance/70 kg FFM and 41 L/70 kg FFM in the final model, with a between-subject variability of 28 and 15 % (CV), respectively. CONCLUSIONS: The pharmacokinetic model provides a means of predicting the allopurinol dose required to achieve target oxypurinol plasma concentrations for patients with different magnitudes of renal function, different body mass and with or without concomitant diuretic use. The model provides a basis for the rational dosing of allopurinol in clinical practice.

The impact of genetic variability in urate transporters on oxypurinol pharmacokinetics.

The genetic determinants of the allopurinol dose-concentration relationship have not been extensively studied. We aimed to clarify what factors, including genetic variation in urate transporters, influence oxypurinol pharmacokinetics (PKs). A population PK model for oxypurinol was developed with NONMEM (version 7.3). The influence of urate transporter genetic variants for ABCG2 (rs2231142 and rs10011796), SLC2A9/GLUT9 (rs11942223), SLC17A1/NPT1 (rs1183201), SLC22A12/URAT1 (rs3825018), SLC22A11/OAT4 (rs17300741), and ABCC4/MRP4 (rs4148500), as well as other participant factors on oxypurinol PKs was assessed. Data from 325 people with gout were available. The presence of the T allele for ABCG2 (rs2231142) and SLC17A1/NPT1 (rs1183201) was associated with a 24% and 22% increase in oxypurinol clearance, respectively, in univariate analysis. This effect was not significant in the multivariate analysis. In the final model, oxypurinol PKs were predicted by creatinine clearance, diuretic use, ethnicity, and body weight. We have found that genetic variability in the transporters examined does not appear to influence oxypurinol PKs.

Furosemide increases plasma oxypurinol without lowering serum urate--a complex drug interaction: implications for clinical practice.

OBJECTIVE: To determine the effects of furosemide on serum urate (SU), plasma oxypurinol and urinary urate. METHODS: Twenty-three cases with gout receiving furosemide and allopurinol were recruited. Twenty-three controls with gout receiving allopurinol but no diuretics were matched on age, gender, estimated glomerular filtration rate and allopurinol dose. SU, plasma oxypurinol and urinary urate were assessed on a single occasion. The effects of a single dose of furosemide 40 mg were examined in a separate group of 10 patients receiving allopurinol but not diuretic. RESULTS: Cases had significantly higher SU and plasma oxypurinol compared with controls despite receiving similar doses of allopurinol. There was no difference in urinary urate excretion. There was a significant increase in area under the curve (AUC)(0-24) for oxypurinol after administration of furosemide 40 mg. CONCLUSION: The interaction between allopurinol and furosemide results in increased SU and plasma oxypurinol. The exact mechanisms remain unclear but complex interactions that result in attenuation of the hypouricaemic effects of oxypurinol are likely. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry, www.anzctr.org.au, 12609000529246.

An association study of ABCG2 rs2231142 on the concentrations of allopurinol and its metabolites.

ABCG2 is a gene that codes for the human breast cancer resistance protein (BCRP). It is established that rs2231142 G>T, a single nucleotide polymorphism of the ABCG2 gene, is associated with gout and poor response to allopurinol, a uric acid-lowering agent used to treat this condition. It has also been suggested that oxypurinol, the primary active metabolite of allopurinol, is a substrate of the BCRP. We thus hypothesized that carrying the rs2231142 variant would be associated with decreased oxypurinol concentrations, which would explain the lower reduction in uric acid. We performed a cross-sectional study to investigate the association between the ABCG2 rs2231142 variant and oxypurinol, allopurinol, and allopurinol riboside concentrations in 459 participants from the Montreal Heart Institute Hospital Cohort. Age, sex, weight, use of diuretics, and estimated glomerular filtration rate were all significantly associated with oxypurinol plasma concentration. No association was found between rs2231142 and oxypurinol, allopurinol and allopurinol riboside plasma concentrations. Rs2231142 was not significantly associated with daily allopurinol dose in the overall population, but an association was observed in men, with T carriers receiving higher doses. Our results do not support a major role of ABCG2 in the pharmacokinetics of allopurinol or its metabolites. The underlying mechanism of the association between rs2231142 and allopurinol efficacy requires further investigation.

Lack of effect of hydrochlorothiazide and low-dose aspirin on the renal clearance of urate and oxypurinol after a single dose of allopurinol in normal volunteers.

AIMS: To determine whether low-dose aspirin and hydrochlorothiazide (HCTZ) affect the renal clearance of oxypurinol and/or urate. METHODS: Healthy volunteers (n = 8) were treated with allopurinol (600 mg, control), and allopurinol (600 mg) co-administered with single doses of aspirin (100 mg) or HCTZ (25 mg) or a combination of the two. RESULTS: Hydrochlorothiazide, low-dose aspirin or a combination of the two, when co-administered with allopurinol, did not significantly alter (P > 0.05) the renal clearance of oxypurinol or urate. In particular, aspirin and HCTZ, when taken together and with allopurinol, did not change (P > 0.05) oxypurinol fractional renal clearance (allopurinol alone: 0.217, 0.173-0.262; combined: 0.202, 0.155-0.250) or urate fractional renal clearance (allopurinol alone: 0.066, 0.032-0.099; combined: 0.058, 0.038-0.078). CONCLUSIONS: A single, low-dose of aspirin or an anti-hypertensive dose of hydrochlorothiazide, when administered alone or together with allopurinol, are unlikely to alter the hypouricaemic effect of allopurinol. The effect of chronic aspirin and HCTZ dosing taken together upon the efficacy of chronic allopurinol therapy in patients with hyperuricaemia needs to be investigated.

Combining Model-Based Clinical Trial Simulation, Pharmacoeconomics, and Value of Information to Optimize Trial Design.

The Bayesian decision-analytic approach to trial design uses prior distributions for treatment effects, updated with likelihoods for proposed trial data. Prior distributions for treatment effects based on previous trial results risks sample selection bias and difficulties when a proposed trial differs in terms of patient characteristics, medication adherence, or treatment doses and regimens. The aim of this study was to demonstrate the utility of using pharmacometric-based clinical trial simulation (CTS) to generate prior distributions for use in Bayesian decision-theoretic trial design. The methods consisted of four principal stages: a CTS to predict the distribution of treatment response for a range of trial designs; Bayesian updating for a proposed sample size; a pharmacoeconomic model to represent the perspective of a reimbursement authority in which price is contingent on trial outcome; and a model of the pharmaceutical company return on investment linking drug prices to sales revenue. We used a case study of febuxostat versus allopurinol for the treatment of hyperuricemia in patients with gout. Trial design scenarios studied included alternative treatment doses, inclusion criteria, input uncertainty, and sample size. Optimal trial sample sizes varied depending on the uncertainty of model inputs, trial inclusion criteria, and treatment doses. This interdisciplinary framework for trial design and sample size calculation may have value in supporting decisions during later phases of drug development and in identifying costly sources of uncertainty, and thus inform future research and development strategies.

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.