Mechanistic pharmacokinetic modelling of ephedrine, norephedrine and caffeine in healthy subjects

AIM: The combination of ephedrine and caffeine has been used in herbal products for weight loss and athletic performance-enhancement, but the pharmacokinetic profiles of these compounds have not been well characterized. This study aimed to develop a mechanistic model describing ephedrine, norephedrine, and caffeine pharmacokinetics and their interactions in healthy subjects. METHODS: The pharmacokinetic model was developed based on the simultaneous modelling using plasma samples gathered from two clinical trials. The treatments consisted of single-doses of pharmaceutical caffeine and ephedrine, given alone or together, and an herbal formulation containing both caffeine and ephedrine. We used a mixed-effect statistical model and the program NONMEM to take account of intersubject variability. RESULTS: Three hundred and seventy-nine ephedrine, 352 norephedrine, 417 caffeine plasma concentrations and 40 ephedrine urine concentrations were obtained from 24 subjects. A one-compartment model with first-order absorption described the caffeine data. Caffeine clearance was 0.083 l min(-1) (CV 38%) and decreased to 0.038 l min(-1) in presence of oral contraceptive therapy, its volume of distribution was 38.6 l (CV 20%) and its absorption rate constant was 0.064 l min(-1) (CV 50%). A four-compartment model described the pharmocokinetics of ephedrine and norephedrine. Ephedrine was eliminated mostly renally, with a clearance of 0.34 l min(-1) (CV 11%), and a volume of distribution of 181 l (CV 19%). Nonlinearity in the conversion of ephedrine to norephedrine was observed. Different models showed that the simultaneous administration of caffeine, or the amount of caffeine in the absorption compartment, was associated with a slower rate of absorption of ephedrine. A 32% greater relative bioavailability of herbal compared with pharmaceutical ephedrine administration was observed. CONCLUSIONS: We describe a mechanistic model for ephedrine, norephedrine and caffeine pharmacokinetics and their interactions. The relative bioavailability of ephedrine differed between the herbal supplement compared with the pharmaceutical formulation. Concomitant ingestion of caffeine slowed the absorption rate of ephedrine, which is mainly related to the amount of the former in the absorption compartment. A saturable process appears to be involved in the metabolism of ephedrine to norephedrine.     

Population pharmacokinetic parameters in patients treated with oral mexiletine

Summary A new data analysis approach, NONMEM, proposed by Sheiner and Beal, has been employed to estimate the population pharmacokinetic parameters of oral mexiletine in patients treated for arrhythmias. 452 serum concentration measurements in 58 patients were available for analysis. 27 patients had congestive heart failure and 8 had abnormal liver function tests at the time of the study. The population averages of the pharmacokinetic parameters and their interindividual variability were: oral total body clearance (Cl) 0.38 l/h/kg±43% (C. V.), apparent volume of distribution (Vd) 5.3 l/kg±40%, absorption rate constant 3.1 h^–1±205%, absorption time-lag 0.3 h. Congestive heart failure and sex did not show a significant effect on Cl and Vd; the number of patients with severe liver function impairment was too small for a definite conclusion. Normalizing Cl and Vd for body weight significantly decreased their interindividual variability. Based on these results, a dosage regimen is recommended which is expected to produce a therapeutic serum concentration (0.8–2 mg/l) in over 60% of patients. Because of its unique features, which allow estimation of pharmacokinetic parameters and their variability from fragmentary patient data, the NONMEM system has great potential applicability to clinical pharmacokinetic studies.Presented in part at the First European Congress on Biopharmaceutics and Pharmacokinetics, Clermont-Ferrand, April 1981     

Recent advances in pharmacokinetic modeling

A major part of the science of pharmacokinetics is the modeling of the underlying processes that contribute to drug disposition. The purpose of pharmacokinetic models is to summarize the knowledge gained in preclinical and clinical studies at various stages in drug development and to rationally guide future studies with the use of adequately predictive models. This review highlights a variety of recent advances in mechanistic pharmacokinetic modeling. It is aimed at a broad audience, and hence, an attempt was made to maintain a balance between technical information and practical applications of pharmacokinetic modeling. It is hoped that drug researchers from all disciplines would be able to get a flavor of the function and capacity of pharmacokinetic modelers and their contribution to drug development. While this review is not intended to be a technical reference on modeling approaches, the roles of statistical applications and population methodologies are discussed where appropriate.     

基于NONMEM法建立紫杉醇群体药动学模型

目的：建立国人紫杉醇（paclitaxel,PTX）群体药动学（population pharmacokinetic,PPK）模型,为制定个体化给药方案提供理论支持。方法：收集138例接受紫杉醇治疗的肿瘤患者（建模组105例,验证组33例）210个血样,HPLC法测定紫杉醇血药浓度,PCR-RFLP法检测MDR1 C3435T。应用非线性混合效应模型（NONMEM）法,考察MDR1 C3435T基因多态性、合并用药及病理生理因素对紫杉醇药动学参数的影响,建立紫杉醇PPK模型。对模型进行拟合优度诊断、自举法（Bootstrap）内部验证,正态预测分布误差法（NPDE）及外部验证考察模型预测能力。结果：紫杉醇清除率（CL）和表观分布容积（V_d）的群体典型值分别为64.7 L·h^-1和1 240 L,患者内生肌酐清除率（CLcr）和给药速率（RATE）显著影响紫杉醇清除率。最终模型Bootstrap法验证结果与模型计算值相符,拟合优度、准确度及精密度均优于最简模型。结论：紫杉醇PPK最终模型稳定、有效,可结合Bayesian反馈法为临床优化给药方案提供科学依据。     

Population pharmacokinetic modelling of gentamicin and vancomycin in patients with unstable renal function following cardiothoracic surgery

AIMS: To describe the population pharmacokinetics of gentamicin and vancomycin in cardiothoracic surgery patients with unstable renal function. METHODS: Data collected during routine care were analyzed using NONMEM. Linear relationships between creatinine clearance (CL(Cr)) and drug clearance (CL) were identified, and two approaches to modelling changing CL(Cr) were examined. The first included baseline (BCOV) and difference from baseline (DCOV) effects and the second allowed the influence of CL(Cr) to vary between individuals. Final model predictive performance was evaluated using independent data. The data sets were then combined and parameters re-estimated. RESULTS: Model building was performed using data from 96 (gentamicin) and 102 (vancomycin) patients, aged 17-87 years. CL(Cr) ranged from 9 to 172 ml min(-1) and changes varied from -76 to 58 ml min(-1) (gentamicin) and -86 to 93 ml min(-1) (vancomycin). Inclusion of BCOV and DCOV improved the fit of the gentamicin data but had little effect on that for vancomycin. Inclusion of interindividual variability (IIV) in the influence of CL(cr) resulted in a poorly characterized model for gentamicin and had no effect on vancomycin modelling. No bias was seen in population compared with individual CL estimates in independent data from 39 (gentamicin) and 37 (vancomycin) patients. Mean (95% CI) differences were 4% (-3, 11%) and 2% (-2, 6%), respectively. Final estimates were: CL(Gent) (l h(-1)) = 2.81 x (1 + 0.015 x (BCOV(CLCr)-BCOV(CLCr Median)) + 0.0174 x DCOV(CLCr)); CL(Vanc) (l h(-1)) = 2.97 x (1 + 0.0205 x (CL(Cr)-CL(Cr Median))). IIV in CL was 27% for both drugs. CONCLUSIONS: A parameter describing individual changes in CL(cr) with time improves population pharmacokinetic modelling of gentamicin but not vancomycin in clinically unstable patients.     

Population pharmacokinetic modelling of Emfilermin (recombinant human leukaemia inhibitory factor, r-hLIF) in healthy postmenopausal women and in infertile patients undergoing in vitro fertilization and embryo transfer

AIMS: The aim of this analysis was to develop a population pharmacokinetic model for Emfilermin (recombinant human leukaemia inhibitory factor, r-hLIF) following subcutaneous administration to healthy postmenopausal women and to infertile patients undergoing in vitro fertilization and embryo transfer (IVF-ET). METHODS: Data from three studies, a single and a repeat dose Phase I study in postmenopausal women as well as a proof of concept study in patients undergoing in vitro fertilization and embryo transfer were combined and analyzed. The structural pharmacokinetic model was developed using the rich data from the Phase I studies and the full pharmacostatistical model was then derived using all the data. RESULTS: The pharmacokinetics of r-hLIF after repeated subcutaneous administration were described by a one-compartment disposition model with a zero order input. The duration of the absorption phase was short (0.8 h) and invariant. The apparent clearance in postmenopausal women was 57 l h(-1) (CV = 17%). In in vitro fertilization and embryo transfer patients, the apparent clearance was decreased by 35% compared with postmenopausal women. The apparent volume of distribution was 235 l (interindividual CV = 28%) and exhibited an interoccasion variability of 23%. It increased (for weight above 62 kg) or decreased (for weight below 62 kg) by 29% for every 10 kg body weight. The median posthoc estimates of apparent clearance and volume of distribution and their variability were consistent with the population estimates. In postmenopausal women, the results were consistent with those obtained by noncompartmental analysis. The residual variability on r-hLIF serum concentrations was 20%. CONCLUSIONS: The pharmacokinetics of r-hLIF after repeated SC administration were described by a one compartment disposition model, with zero order input, in postmenopausal women and those undergoing IVF or intracytoplasmic sperm injection and embryo transfer. Absorption of r-hLIF was rapid as was its subsequent clearance. The apparent volume of distribution of r-hLIF was moderate to high, depended on body weight and showed interoccasion variability.     

Population pharmacokinetic modelling of the enterohepatic recirculation of diclofenac and rofecoxib in rats

BACKGROUND AND PURPOSE: Enterohepatic recirculation (EHC) is a common pharmacokinetic phenomenon that has been poorly modelled in animals. The presence of EHC leads to the appearance of multiple peaks in the concentration-time profile and increased exposure, which may have implications for drug effect and extrapolation across species. The aim of this investigation was to develop a population pharmacokinetic model for diclofenac and rofecoxib that describes EHC and to assess its consequence for the pharmacodynamics of both drugs. EXPERIMENTAL APPROACH: The pharmacokinetics of diclofenac and rofecoxib was characterized in male rats following intravenous, intraperitoneal and oral administration. Blood samples were collected at pre-defined time points after dosing to determine plasma concentrations over time. A parametric approach using nonlinear mixed effects modelling was applied to describe EHC, whilst simulations were used to evaluate its impact on PGE(2) inhibition. KEY RESULTS: For diclofenac, EHC was described by a compartmental model with periodic transfer rate and metabolite formation rate. For rofecoxib, EHC modelling required a conversion compartment with first-order recycling rate and lag time. Based on model predictions, EHC causes an increase of 95% in the systemic exposure to diclofenac and of 15% in the exposure to rofecoxib. In addition, EHC prolongs the inhibition of PGE(2) and increases the duration of the anti-inflammatory effect (24 h for rofecoxib 10 mg kg(-1)) without affecting maximum inhibition. CONCLUSIONS AND IMPLICATIONS: Our findings show the relevance of exploring EHC in a quantitative manner to accurately interpret pharmacodynamic findings in vivo, in particular when scaling across species.     

A population pharmacokinetic study of alminoprofen penetration into synovial fluid

The pharmacokinetics of alminoprofen in plasma and synovial fluid (SF) at steady state (300 mg t.i.d.) was studied in 45 patients with knee effusion. Plasma and SF samples, one each per patient, were obtained. Six groups were made according to the time of sampling after ingestion of the 13th dose: 1h (n = 7), 2h (n = 7), 4h (n = 7), 6h (n = 10), 8h (n = 6), 12h (n = 8). A three-compartment model was used to describe alminoprofen kinetics in plasma and SF, with two parameterizations, a ‘classical’ and a ‘physiological’ one. The non-linear mixed effect model approach was used to estimate the mean and variance of the pharmacokinetic parameters. The mean ±SE of the estimates (coefficient of variation of interindividual variability as a percentage) were volume of distribution, 11.0 ± 1.711 (12%); elimination rate constant, 0.236 ± 0.025 h^?1 (18%); absorption rate constant 2.80 ± 0.31 h^?1 (464%), clearance of influx into SF, 0.29 ± 0.14 mL min^?1; clearance of efflux into plasma, 0.56 ± 0.25 mL min^?1. These two clearances were not significantly different, which indicates that passive diffusion occurs in both directions. The mean ±SD alminoprofen concentration versus time curve in plasma and SF at steady state was simulated and showed that the mean ±SD maximal concentration in SF was 8.1 ± 6.3 mg L^?1 and was obtained 4h after dose administration.     

Evaluation of the autoinduction of ifosfamide metabolism by a population pharmacokinetic approach using NONMEM

AIMS: This study investigated the population pharmacokinetics of ifosfamide in 15 patients treated for soft tissue sarcoma with 9 or 12 g m-2 ifosfamide by means of a 72 h continuous i.v. infusion. METHODS: A model was developed using nonlinear mixed effects modelling (NONMEM) to describe the nonlinear pharmacokinetics of ifosfamide by linking the ifosfamide plasma concentrations to the extent of the autoinduction. RESULTS: The proposed model revealed the effect of autoinduction on the disposition of ifosfamide. The initial clearance, volume of distribution, rate constant for enzyme degradation, induction half-life of the enzyme and the ifosfamide concentration at 50% of the maximum inhibition of enzyme degradation were estimated at 2.94 +/- 0.27 l h-1, 43.5 +/- 2.9 l, 0.0546 +/- 0. 0078 h-1, 12.7 h and 30.7 +/- 4.8 microM, respectively. Interindividual variabilities of initial clearance, volume of distribution, rate constant for enzyme degradation were 24.5, 23.4 and 22.7%, respectively. Proportional and additive variability not explained by the model were 13.6% and 0.0763 microM, respectively. CONCLUSIONS: The absence of a lag time for the autoinduction of ifosfamide metabolism could be the result of an immediate inhibition of the enzymatic degradation of CYP3A4 by ifosfamide. By application of the autoinduction model individual pharmacokinetic profiles of patients were described with adequate precision. This model may therefore be used in the future development of a model to individualize dose selection in patients.     

Population pharmacokinetic/ pharmacodynamic modelling of eltrombopag in healthy volunteers and subjects with chronic liver disease

Aims

To characterize the pharmacokinetics (PK)/pharmacodynamics (PD) of eltrombopag in chronic liver disease (CLD).

Methods

The PK/PD model was developed using data from 79 CLD patients using nonlinear mixed-effects modelling.

Results

The PK of eltrombopag were described by a two-compartment model with dual sequential first-order absorption. Gender, race and severity of CLD were predictors of the apparent clearance of eltrombopag. The PD of eltrombopag in CLD were adequately described by a four-compartment lifespan model, in which eltrombopag stimulated platelet precursor production rate. East Asian CLD patients were less sensitive to the stimulatory effect of eltrombopag. Following a daily dose regimen of 50 mg eltrombopag, the time to achieve peak platelet counts was longer for the CLD population compared with patients who had immune thrombocytopenic purpura, but was comparable to patients with hepatitis C. Likewise, it took a longer time for platelet counts to rebound back to baseline once eltrombopag treatment was discontinued.

Conclusions

The time course of the platelet response in CLD was different from that in immune thrombocytopenic purpura but comparable to that in hepatitis C.     

Population pharmacokinetic analysis of cilostazol in healthy subjects with genetic polymorphisms of CYP3A5, CYP2C19 and ABCB1

AIMS

To investigate the influence of genetic polymorphisms in the CYP3A5, CYP2C19 and ABCB1 genes on the population pharmacokinetics of cilostazol in healthy subjects.

METHODS

Subjects who participated in four separate cilostazol bioequivalence studies with the same protocols were included in this retrospective analysis. One hundred and four healthy Korean volunteers were orally administered a single 50- or 100-mg dose of cilostazol. We estimated the population pharmacokinetics of cilostazol using a nonlinear mixed effects modelling (nonmem) method and explored the possible influence of genetic polymorphisms in CYP3A (CYP3A5*3), CYP2C19 (CYP2C19*2 and CYP2C19*3) and ABCB1 (C1236T, G2677T/A and C3435T) on the population pharmacokinetics of cilostazol.

RESULTS

A two-compartment model with a first-order absorption and lag time described the cilostazol serum concentrations well. The apparent oral clearance (CL/F) was estimated to be 12.8 l h⁻¹. The volumes of the central and the peripheral compartment were characterized as 20.5 l and 73.1 l, respectively. Intercompartmental clearance was estimated at 5.6 l h⁻¹. Absorption rate constant was estimated at 0.24 h⁻¹ and lag time was predicted at 0.57 h. The genetic polymorphisms of CYP3A5 had a significant (P < 0.001) influence on the CL/F of cilostazol. When CYP2C19 was evaluated, a significant difference (P < 0.01) was observed among the three genotypes (extensive metabolizers, intermediate metabolizers and poor metabolizers) for the CL/F. In addition, a combination of CYP3A5 and CYP2C19 genotypes was found to be associated with a significant difference (P < 0.005) in the CL/F. When including these genotypes, the interindividual variability of the CL/F was reduced from 34.1% in the base model to 27.3% in the final model. However, no significant differences between the ABCB1 genotypes and cilostazol pharmacokinetic parameters were observed.

CONCLUSIONS

The results of the present study indicate that CYP3A5 and CYP2C19 polymorphisms explain the substantial interindividual variability that occurs in the metabolism of cilostazol.     

Integration of data from multiple sources for simultaneous modelling analysis: experience from nevirapine population pharmacokinetics

AIMS

To propose a modelling strategy to efficiently integrate data from different sources in one simultaneous analysis, using nevirapine population pharmacokinetic data as an example.

METHODS

Data from three studies including 115 human immunodeficiency virus-infected South African adults were used. Patients were on antiretroviral therapy regimens including 200 mg nevirapine twice daily and sampled at steady state. A development process was suggested, implemented in NONMEM7 and the final model evaluated with an external data set.

RESULTS

A stepwise approach proved efficient. Model development started with the intensively sampled data. Data were added sequentially, using visual predictive checks for inspecting their compatibility with the existing model. Covariate exploration was carried out, and auxiliary regression models were designed for imputation of missing covariates. Nevirapine pharmacokinetics was described by a one-compartment model with absorption through two transit compartments. Body size was accounted for using allometric scaling. The model included a mixture of two subpopulations with different typical values of clearance, namely fast (3.12 l h⁻¹) and slow metabolizers (1.45 l h⁻¹), with 17% probability of belonging to the latter. Absorption displayed large between-occasion variability, and food slowed the absorption mean transit time from 0.6 to 2.5 h. Concomitant antitubercular treatment including rifampicin typically decreased bioavailability by 39%, with significant between-subject variability. Visual predictive checks of external validation data indicated good predictive performance.

CONCLUSIONS

The development strategy succeeded in integrating data from different sources to produce a model with robust parameter estimates. This work paves the way for the creation of a nevirapine mega-model, including additional data from numerous diverse sources.     

Evaluation of Bayesian estimation in comparison to NONMEM for population pharmacokinetic data analysis: Application to pefloxacin in intensive care unit patients

The pharmacokinetics of pefloxacin (PF) were investigated in a population of 74 intensive care unit patients receiving 400 mg bid as 1-hr infusion using (i) Bayesian estimation (BE) of individual patient parameters followed by multiple linear regression (MLR) analysis and (ii) NONMEM analysis. The data consisted of 3 to 9 PF plasma levels per patient measured over 1 to 3 dosage intervals (total 113) according to four different limited (suboptimal) sampling 3-point protocols. Twenty-nine covariates (including 15 comedications) were considered to explain the interpatient variability. Predicted PFCLfor a patient with median covariates values was similar in both BE/ MLR and NONMEM analysis (4.02 and 3.92 L/hr, respectively). Bilirubin level and age were identified as the major determinants of PFCLby both approaches with similar predicted magnitude of effects (about 40 and 30% decrease of median CL,respectively). Confounding effects were observed between creatinine clearance (26% decrease of PF CLin the BE/MLR model), simplified acute physiology score (a global score based on 14 biological and clinical variables) (18% decrease of median CLin the NONMEM model) and age (entered in both models) which were highly correlated in our data base. However, both models predicted similar PF CLfor actual subpopulations by using actual covariate values. Finally, the NONMEM analysis allowed identification of an effect of weight on CL(decrease of CL for weight <65 kg) whereas the BE/MLR analysis predicted an increase of CLin patients treated with phenobarbital. In conclusion, both approaches allowed identification of the major risk factors of PF pharmacokinetics in ICU patients. Their potential use at different stages of drug development is discussed.     

Population pharmacokinetic model of digoxin in older Chinese patients and its application in clinical practice

Aim:

To establish a population pharmacokinetic (PPK) model of digoxin in older Chinese patients to provide a reference for individual medication in clinical practice.

Methods:

Serum concentrations of digoxin and clinically related data including gender, age, weight (WT), serum creatinine (Cr), alanine aminotransferase (ALT), aspartate aminotransferase (AST), blood urea nitrogen (BUN), albumin (ALB), and co-administration were retrospectively collected from 119 older patients taking digoxin orally for more than 7 d. NONMEM software was used to get PPK parameter values, to set up a final model, and to assess the models in clinical practice.

Results:

Spironolactone (SPI), WT, and Cr markedly affected the clearance rate of digoxin. The final model formula is Cl/F=5.9×[1–0.412×SPI]×[1–0.0101×(WT–62.9)]×[1–0.0012×(Cr–126.8)] (L/h); Ka=1.63 (h⁻¹); V_d/F=550 (L). The population estimates for Cl/F and V_d/F were 5.9 L/h and 550 L, respectively. The interindividual variabilities (CV) were 49.0% for Cl/F and 94.3% for V_d/F. The residual variability (SD) between observed and predicted concentrations was 0.365 μg/L. The difference between the objective function value and the primitive function value was less than 3.84 (P>0.05) by intra-validation. Clinical applications indicated that the percent of difference between the predicted concentrations estimated by the PPK final model and the observed concentrations were −4.3%–+25%. Correlation analysis displayed that there was a linear correlation between observated and predicted values (y=1.35x+0.39, r=0.9639, P<0.0001).

Conclusion:

The PPK final model of digoxin in older Chinese patients can be established using the NONMEM software, which can be applied in clinical practice.     

Population pharmacokinetic and pharmacogenetic analysis of 6-mercaptopurine in paediatric patients with acute lymphoblastic leukaemia

WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT

• The cytotoxic effects of 6-mercaptopurine (6-MP) were found to be due to drug-derived intracellular metabolites (mainly 6-thioguanine nucleotides and to some extent 6-methylmercaptopurine nucleotides) rather than the drug itself.
• Current empirical dosing methods for oral 6-MP result in highly variable drug and metabolite concentrations and hence variability in treatment outcome.

WHAT THIS STUDY ADDS

• The first population pharmacokinetic model has been developed for 6-MP active metabolites in paediatric patients with acute lymphoblastic leukaemia and the potential demographic and genetically controlled factors that could lead to interpatient pharmacokinetic variability among this population have been assessed.
• The model shows a large reduction in interindividual variability of pharmacokinetic parameters when body surface area and thiopurine methyltransferase polymorphism are incorporated into the model as covariates.
• The developed model offers a more rational dosing approach for 6-MP than the traditional empirical method (based on body surface area) through combining it with pharmacogenetically guided dosing based on thiopurine methyltransferase genotype.

AIMS

To investigate the population pharmacokinetics of 6-mercaptopurine (6-MP) active metabolites in paediatric patients with acute lymphoblastic leukaemia (ALL) and examine the effects of various genetic polymorphisms on the disposition of these metabolites.

METHODS

Data were collected prospectively from 19 paediatric patients with ALL (n = 75 samples, 150 concentrations) who received 6-MP maintenance chemotherapy (titrated to a target dose of 75 mg m⁻² day⁻¹). All patients were genotyped for polymorphisms in three enzymes involved in 6-MP metabolism. Population pharmacokinetic analysis was performed with the nonlinear mixed effects modelling program (nonmem) to determine the population mean parameter estimate of clearance for the active metabolites.

RESULTS

The developed model revealed considerable interindividual variability (IIV) in the clearance of 6-MP active metabolites [6-thioguanine nucleotides (6-TGNs) and 6-methylmercaptopurine nucleotides (6-mMPNs)]. Body surface area explained a significant part of 6-TGNs clearance IIV when incorporated in the model (IIV reduced from 69.9 to 29.3%). The most influential covariate examined, however, was thiopurine methyltransferase (TPMT) genotype, which resulted in the greatest reduction in the model''s objective function (P < 0.005) when incorporated as a covariate affecting the fractional metabolic transformation of 6-MP into 6-TGNs. The other genetic covariates tested were not statistically significant and therefore were not included in the final model.

CONCLUSIONS

The developed pharmacokinetic model (if successful at external validation) would offer a more rational dosing approach for 6-MP than the traditional empirical method since it combines the current practice of using body surface area in 6-MP dosing with a pharmacogenetically guided dosing based on TPMT genotype.