Population pharmacokinetic modelling for enterohepatic circulation of mycophenolic acid in healthy Chinese and the influence of polymorphisms in UGT1A9

AIMS

To establish a population pharmacokinetic model that describes enterohepatic circulation (EHC) of mycophenolic acid (MPA) based on physiological considerations and to investigate the influence of polymorphisms of UGT1A9 on the pharmacokinetics of MPA.

METHODS

Pharmacokinetic data were obtained from two comparative bioavailability studies of oral mycophenolic mofetil formulations. Nonlinear mixed effects modelling was employed to develop an EHC model including both MPA and its main glucuronide metabolite (MPAG) simultaneously. Demographic characteristics and UGT1A9 polymorphisms were screened as covariates.

RESULTS

In total, 590 MPA and 589 MPAG concentration–time points from 42 healthy male volunteers were employed in this study. The chain compartment model included an intestinal compartment, a gallbladder compartment, a central and a peripheral compartment for MPA and a central compartment for MPAG. The typical population clearance (CL/F) estimates with its relative standard error for MPA and MPAG were 10.2 l h⁻¹ (5.7%) and 1.38 l h⁻¹ (6.9%), respectively. The amount of MPA recycled in the body was estimated to be 29.1% of the total amount absorbed. Covariate analysis showed that body weight was positively correlated with CL/F of MPA, intercompartment CL/F of MPA and distribution volume of MPA peripheral compartment. Polymorphisms of UGT1A9 did not show any effect on the pharmacokinetics of MPA and MPAG. The model evaluation tests indicated that the proposed model can describe the pharmacokinetic profiles of MPA and MPAG in healthy Chinese subjects.

CONCLUSIONS

The proposed model may provide a valuable approach for planning future pharmacokinetic–pharmacodynamic studies and for designing proper dosage regimens of MPA.

WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT

• Mycophenolic acid (MPA) undergoes enterohepatic circulation (EHC) in the body and several population models have been proposed to describe this process using sparse data.
• Recent studies in Whites have found that polymorphism in UGT1A9 could partly explain the large interindividual variability associated with the pharmacokinetics of MPA.

WHAT THIS STUDY ADDS

• A new population pharmacokinetic model for EHC combining MPA and its main glucuronide metabolite (MPAG) simultaneously was established based on physiological aspects of biliary excretion using intensive sampling data.
• Pharmacokinetic profiles of MPA and MPAG with the UGT1A9 polymorphism in healthy Chinese were characterized.

     

Effects of UGT1A1*28 polymorphism on raloxifene pharmacokinetics and pharmacodynamics

AIMS

Raloxifene concentrations were reported to correlate approximately with serum bilirubin levels. Bilirubin is a typical UGT1A1 substrate. Based on these facts, we postulated a hypothesis that UGT1A1 is the key enzyme for metabolic clearance of raloxifene and that the common UGT1A1*28 polymorphism significantly contributes to the large pharmacokinetic variability of raloxifene.

METHODS

Serum samples from postmenopausal osteoporotic patients treated with raloxifene were assayed for the concentrations of raloxifene and its glucuronides by liquid chromatography–mass spectrometry–mass spectrometry. The same samples were also genotyped for the presence of UGT1A1*28 polymorphism by the single-strand conformation polymorphism method. The pharmacodynamic effect was evaluated by measuring the change in bone mineral density (BMD) in femoral neck, hip and lumbar spine after 12 months'' raloxifene therapy.

RESULTS

Patients homozygous for the *28 allele showed significantly, twofold higher raloxifene glucuronide concentrations compared with the hetero- and homozygotes for the wild-type allele: 558 ± 115 nmol l⁻¹ compared with 295 ± 43 nmol l⁻¹, respectively (P = 0.012). This indicates a higher raloxifene exposure in the *28/*28 group. Consequently, a significantly greater increase in hip BMD was observed in subjects homozygous for the *28 allele compared with the group carrying at least one copy of the wild-type allele: 4.4 ± 2.4% compared with 0.3 ± 1.4% (P = 0.035).

CONCLUSIONS

In this study it is shown that a relatively common UGT1A1*28 polymorphism may considerably influence raloxifene pharmacokinetics and pharmacodynamics. Underlying mechanisms and clinical implications of our findings are also discussed.     

Development of population PK model with enterohepatic circulation for mycophenolic acid in patients with childhood-onset systemic lupus erythematosus

AIM

This study aimed to develop a population pharmacokinetic (PK) enterohepatic recycling model for MPA in patients with childhood-onset systemic lupus erythematosus (cSLE).

METHODS

MPA concentration–time data were from outpatients on stable oral mycophenolate mofetil (MMF) and collected under fasting conditions, with standardized meals (1 and 4 h post-dose). Sampling times were pre-dose, 20, 40 min, 1, 1.5, 2, 3, 4, 6 and 9 h, post dose. The population PK analysis simultaneously modelled MPA and 7-O-MPA-β-glucuronide (MPAG) concentrations using nonlinear mixed effect modelling.

RESULTS

PK analysis included 186 MPA and MPAG concentrations (mg l^–1) from 19 patients. cSLE patients, age range 10–28 years, median 16.5 years were included. Mean ± SD disease duration was 3.8 ± 3.7 years. The final PK model included a gallbladder compartment for enterohepatic recycling and bile release time related to meal times, with first order absorption and single series of transit compartments. The PK estimates for MPA were CL₁/F 25.3 l h^–1, V₃/F 20.9 l, V₄/F 234 l and CL₂/F 19.8 l h^–1.

CONCLUSION

The final model fitted the complex processes of absorption and enterohepatic circulation (EHC) in those treated with MMF for cSLE and could be applied in Bayesian dose optimization algorithms.     

Population pharmacokinetics of unbound mycophenolic acid in adult allogeneic haematopoietic cell transplantation: effect of pharmacogenetic factors

Aim

To evaluate pharmacogenetic factors as contributors to the variability of unbound mycophenolic acid (MPA) exposure in adult allogeneic haematopoietic cell transplantation (alloHCT) recipients.

Methods

A population-based pharmacokinetic (PK) model of unbound MPA was developed using non-linear mixed-effects modelling (nonmem). Previously collected intensive unbound MPA PK data from 132 adult alloHCT recipients after oral and intravenous dosing of the prodrug mycophenolate mofetil (MMF) were used. In addition to clinical covariates, genetic polymorphisms in UGT1A8, UGT1A9, UGT2B7 and MRP2 were evaluated for their impact on unbound MPA PK.

Results

Unbound MPA concentration−time data were well described by a two compartment model with first order absorption and linear elimination. For the typical patient (52 years of age, creatinine clearance 86 ml min⁻¹), the median estimated values [coefficient of variation, %, (CV)] of systemic clearance, intercompartmental clearance, central and peripheral volumes of MPA were 1610 l h⁻¹ (37.4%), 541 l h⁻¹ (75.6%), 1230 l (37.5%), and 6140 l (120%), respectively. After oral dosing, bioavailability was low (0.56) and highly variable (CV 46%). No genetic polymorphisms tested significantly explained the variability among individuals. Creatinine clearance was a small but significant predictor of unbound MPA CL. No other clinical covariates impacted unbound MPA PK.

Conclusions

In adult alloHCT recipients, variability in unbound MPA AUC was large and remained largely unexplained even with the inclusion of pharmacogenetic information. Targeting unbound MPA AUC in a patient will require therapeutic drug monitoring.     

A mechanism-based model for the population pharmacokinetics of free and bound aflibercept in healthy subjects

AIM

Aflibercept (VEGF-Trap), a novel anti-angiogenic agent that binds to VEGF, has been investigated for the treatment of cancer. The aim of this study was to develop a mechanism-based pharmacokinetic (PK) model for aflibercept to characterize its binding to VEGF and its PK properties in healthy subjects.

METHODS

Data from two phase I clinical studies with aflibercept administered as a single intravenous infusion were included in the analysis. Free and bound aflibercept concentration−time data were analysed using a nonlinear mixed-effects modelling approach with MONOLIX 3.1.

RESULTS

The best structural model involved two compartments for free aflibercept and one for bound aflibercept, with a Michaelis–Menten type binding of free aflibercept to VEGF from the peripheral compartment. The typical estimated clearances for free and bound aflibercept were 0.88 l day⁻¹ and 0.14 l day⁻¹, respectively. The central volume of distribution of free aflibercept was 4.94 l. The maximum binding capacity was 0.99 mg day⁻¹ and the concentration of aflibercept corresponding to half of maximum binding capacity was 2.91 µg ml⁻¹. Interindividual variability of model parameters was moderate, ranging from 13.6% (V_max) to 49.8% (Q).

CONCLUSION

The present PK model for aflibercept adequately characterizes the underlying mechanism of disposition of aflibercept and its nonlinear binding to VEGF.     

UGT1A6 genotype-related pharmacokinetics of deferiprone (L1) in healthy volunteers

AIMS

To examine the effects of UGT1A6 polymorphisms on the pharmacokinetics of deferiprone in healthy volunteers.

METHODS

Twenty-two healthy volunteers were enrolled and grouped according to UGT1A6 genotype. After an overnight fast, the subjects received a single oral dose of 25 mg kg⁻¹ deferiprone. Blood samples were collected at 0, 15, 30, 45, 60, 90, 120, 180, 240, 300 and 360 min after dosing. Urine output was collected at 0, 0–2, 2–4, 4–8, 8–12 and 12–24 h. Deferiprone (L1) and deferiprone-glucuronide (L1G) concentrations in serum and urine were determined using a validated high-performance liquid chromatography method. UGT1A6 genotypes were determined by polymerase chain reaction-restriction fragment length polymorphism analysis.

RESULTS

No statistically significant differences in any pharmacokinetic parameters of either deferiprone or deferiprone-glucuronide among the genotype groups were noted. Likewise, there were no statistically significant differences in 24-h urinary deferiprone and deferiprone-glucuronide excretion among the genotype groups. Significant differences between men and women were found in AUC_0–∞, V_d/F, and CL/F of deferiprone. Gender differences in 24-h urinary deferiprone and its metabolite excretion, however, failed to reach statistical significance. The V_d/F of deferiprone was found to correlate significantly with serum ferritin (r_s = 0.665; P = 0.001).

CONCLUSION

The studied single nucleotide polymorphisms in UGT1A6 do not appear to exert statistically significant effects on the single-dose pharmacokinetics of deferiprone. Gender appears to influence the serum pharmacokinetics of deferiprone, but not urinary excretion of deferiprone and its metabolite. Body iron stores may have an influence on the extent of extravascular deferiprone distribution.

WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT

• UGT1A6 has been proposed as the predominant isoform responsible for the glucuronidation of deferiprone.
• UGT1A6*2 allele has been associated with the altered enzyme activity.

WHAT THIS STUDY ADDS

• There is no statistically significant effect of UGT1A6 genotype on the single-dose pharmacokinetics of deferiprone in healthy volunteers.
• Gender influences serum pharmacokinetics of deferiprone.
• Body iron stores reflected by serum ferritin levels may have an influence on the extent of extravascular deferiprone distribution.

     

Tobramycin disposition in ICU patients receiving a once daily regimen: population approach and dosage simulations

AIM

The aim of this study was to evaluate the disposition of tobramycin (TOB) in critically ill patients (ICU) by a population pharmacokinetic approach, to determine the covariates involved, and to simulate tobramycin dosage regimens.

METHODS

Forty-nine adult ICU patients received TOB (5 mg kg⁻¹) once daily. NonMem modelling was performed on 32 patients. The 17 other patients were used for the qualification process by normalized prediction distribution error. Then Monte Carlo simulations (MCS) were performed.

RESULTS

A two-compartment model with a proportional error best fitted the data. TOB total clearance (CL_TOB) was significantly correlated with Cockcroft creatinine clearance (COCK) and height. TOB clearance was 4.8 ± 1.9 l h⁻¹ (range 1.22–8.95), the volume of distribution of the central compartment was 24.7 ± 3.7 l (range 17.34–32.83) and that of the peripheral compartment and the inter-compartmental clearance were 30.6 l and 4.74 l h⁻¹, respectively. Only 29% of the patients presented a target AUC between 80 and 125 mg l^–1 h and 61% were lower than 80 mg l⁻¹ h. After considering COCK and height, MCS showed that only 50% of the population could achieve the target AUC for the 375 and 400 mg dosages.

CONCLUSION

Even after taking into account COCK and height, for strains with an MIC ≤ 1 mg l⁻¹, MCS doses evidenced that peak and AUC pharmacodynamic targets could not be reached simultaneously in more than 45% of the ICU patient population. Combination therapy in addition to drug monitoring are required to manage efficacy and toxicity.     

Maraviroc modelling strategy: use of early phase 1 data to support a semi-mechanistic population pharmacokinetic model

AIMS

To model the basic pharmacokinetic (PK) characteristics of maraviroc to construct an integrated semi-mechanistic PK model for use in later population PK analyses.

METHODS

Three analyses were performed utilizing intravenous, oral and radiolabel data. Firstly, a PK disposition model was developed from data from 20 healthy males who received 3, 10 or 30 mg of intravenous maraviroc. Secondly, a sigmoid E_maxvs dose model of dose-normalized non-compartmental AUC from oral dosing in 134 healthy young males and females across five phase 1 studies was constructed. This described absorption dose non-linearities and tested for the influence of food, formulation and dose frequency on model parameters. The third analysis developed a mass balance model for both absorption and disposition of maraviroc with 300 mg solution and predicted the mass balance after administration of 100 mg tablet formulation.

RESULTS

A four-compartment PK model best described the intravenous data and no influence of dose was found on clearance. Total clearance was 48 l h⁻¹ (2.2% SE). The main covariate effect in the non-compartmental analysis reproduced the dose-dependency of food through a five-fold increase in the ED₅₀ of the sigmoid E_max model. The mass balance models calculated that 33.3% and 22.9% of 300 mg solution and 100 mg tablet doses, respectively, are systemically available, and first-pass metabolism extracts 62% of an absorbed dose, estimating a hepatic blood flow of 101 l h⁻¹.

CONCLUSIONS

The analysis demonstrates a novel integration approach to build a maraviroc semi-mechanistic population PK model for further use in volunteers and patients.     

Progressive decline in tacrolimus clearance after renal transplantation is partially explained by decreasing CYP3A4 activity and increasing haematocrit

Aims

The long-term disposition of tacrolimus following kidney transplantation is characterized by a gradual decrease in dose requirements and increase in dose-corrected exposure. This phenomenon has been attributed to a progressive decline in cytochrome P450 3A4 (CYP3A4) activity, although this has never been demonstrated in vivo.

Methods

Sixty-five tacrolimus- and 10 cyclosporine-treated renal transplant recipients underwent pharmacokinetic testing at day 7 and months 1, 3, 6 and 12 after transplantation, including 8-h area under the concentration-time curve (AUC) for tacrolimus or cyclosporine and assessment of CYP3A4 activity using oral and intravenous midazolam (MDZ) drug probes.

Results

Tacrolimus clearance decreased gradually throughout the entire first year but only in CYP3A5*3/*3 homozygous recipients (25.6 ± 11.1 l h^–1 at day 7; 17 ± 9.1 l h^–1 at month 12; P < 0.001). In mixed model analysis, decreasing CYP3A4 activity, measured by apparent oral MDZ clearance (924 ± 443 ml min^–1 at day 7 vs. 730 ± 344 ml min^–1 at month 1; P < 0.001), explained 55.4% of the decline in tacrolimus clearance in the first month. CYP3A4 activity decreased by 18.9 ml min^–1 for every milligram of methylprednisolone dose tapering within the first month; beyond this point it remained stable. A gradual rise in haematocrit throughout the entire first year explained 31.7% of the decrease in tacrolimus clearance in the first month and 23.6% of the decrease between months 1 and 12. Cyclosporine clearance did not change over time.

Conclusions

The maturation of tacrolimus disposition in the first year after renal transplantation observed in CYP3A5*3/*3 homozygous patients can partly be explained by a (steroid tapering-related) decline in CYP3A4 activity and a progressive increase in haematocrit.     

Evidence for oxazepam as an in vivo probe of UGT2B15: oxazepam clearance is reduced by UGT2B15 D85Y polymorphism but unaffected by UGT2B17 deletion

AIMS

Although in vitro studies indicate that oxazepam is an isoform-selective substrate probe for UDP-glucuronosyltransferase 2B15, the utility of this drug as an in vivo probe is uncertain. The main aim of this study was to determine whether common missense polymorphisms in the UGT2B15 gene (D85Y and K523T) are associated with altered oxazepam pharmacokinetics and pharmacodynamics. We also determined the possible influence of a common deletion polymorphism in the gene encoding UGT2B17, which shows substantial substrate specificity overlap with UGT2B15.

METHODS

Thirty healthy male subjects were administered 15 mg of oxazepam by mouth followed by plasma oxazepam concentration monitoring for 36 h, and pharmacodynamic testing for 8 h. Genotypes were determined by genomic polymerase chain reaction and commercial 5′-nuclease assays.

RESULTS

Allele frequencies for D85Y, K523T, UGT2B17del were 47%, 23% and 19%, respectively. Median oxazepam apparent oral clearance was significantly lower in 85YY subjects (1.62 ml min⁻¹ kg⁻¹) compared with 85DD subjects (3.35 ml min⁻¹ kg⁻¹; P= 0.003, Student–Newman–Keuls test), whereas 85DY subjects were intermediate (2.34 ml min⁻¹ kg⁻¹; P= 0.018 vs. 85DD, P= 0.034 vs. 85YY). Regression analysis indicated that UGT2B15 D85Y genotype accounted for 34% of interindividual variability. However, neither UGT2B15 K523T nor UGT2B17del was associated with altered oxazepam disposition. Furthermore, no differences in pharmacodynamic measures, including quantitative electroencephalography, digit-symbol substitution test, self- or observer-rated visual analogue scales, could be demonstrated for any of the polymorphisms evaluated.

CONCLUSIONS

These results identify UGT2B15 D85Y as a major determinant of oxazepam clearance, and indicate that oxazepam may be useful as an in vivo probe for glucuronidation by UGT2B15.     

Mechanistic modelling of tesaglitazar pharmacokinetic data in subjects with various degrees of renal function--evidence of interconversion

AIMS

To develop a mechanistic pharmacokinetic (PK) model for tesaglitazar and its metabolite (an acyl glucuronide) following oral administration of tesaglitazar to subjects with varying renal function, and derive an explanation for the increased plasma exposure of tesaglitazar in subjects with impaired renal function.

METHODS

Data were from a 6-week study in subjects with renal insufficiency and matched controls undergoing repeated oral dosing with tesaglitazar (n = 41). Compartmental population PK modelling was employed to describe the PK of tesaglitazar and its metabolite, in plasma and urine, simultaneously. Two hypotheses were tested to investigate the increased exposure of tesaglitazar in subjects with renal functional impairment: tesaglitazar metabolism is correlated with renal function, or metabolite elimination is reduced in renal insufficiency, leading to increased hydrolysis (interconversion) to the parent compound via biliary circulation.

RESULTS

The hypothesis for interconversion was best supported by the data. The population PK model included first-order absorption, two-compartment disposition and separate renal (0.027 l h⁻¹) and metabolic (1.9 l h⁻¹) clearances for tesaglitazar. The model for the metabolite; one-compartment disposition with renal (saturable, V_max = 0.19 μmol l⁻¹ and K_m = 0.04 μmol l⁻¹) and nonrenal clearances (1.2 l h⁻¹), biliary secretion (12 h⁻¹) to the gut, where interconversion and reabsorption (0.8 h⁻¹) of tesaglitazar occurred.

CONCLUSION

A mechanistic population PK model for tesaglitazar and its metabolite was developed in subjects with varying degrees of renal insufficiency. The model and data give insight into the likely mechanism (interconversion) of the increased tesaglitazar exposure in renally impaired subjects, and separate elimination and interconversion processes without dosing of the metabolite.

WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT

• Tesaglitazar, is predominantly metabolized (to an acyl glucuronide of the parent compound) and 20% of given dose is found unchanged in the urine.
• Acyl glucuronides are know to be unstable and can become hydrolysed back to parent compound, a phenomena called interconversion.

WHAT THIS STUDY ADDS

• A likely mechanism (interconversion) for the cause of the increased exposure of tesaglitazar in subjects with impaired renal function.
• A possible modelling framework to evaluate interconversion without dosing of the metabolite based on the simultaneous analysis of plasma and urine data from a group of subjects with varying renal function.
• A mechanistic understanding of the pharmacokinetic properties of tesaglitazar and its metabolite.

     

Repaglinide-gemfibrozil drug interaction: inhibition of repaglinide glucuronidation as a potential additional contributing mechanism

AIM

To further explore the mechanism underlying the interaction between repaglinide and gemfibrozil, alone or in combination with itraconazole.

METHODS

Repaglinide metabolism was assessed in vitro (human liver subcellular fractions, fresh human hepatocytes, and recombinant enzymes) and the resulting incubates were analyzed, by liquid chromatography-mass spectrometry (LC-MS) and radioactivity counting, to identify and quantify the different metabolites therein. Chemical inhibitors, in addition to a trapping agent, were also employed to elucidate the importance of each metabolic pathway. Finally, a panel of human liver microsomes (genotyped for UGT1A1*28 allele status) was used to determine the importance of UGT1A1 in the direct glucuronidation of repaglinide.

RESULTS

The results of the present study demonstrate that repaglinide can undergo direct glucuronidation, a pathway that can possibly contribute to the interaction with gemfibrozil. For example, [³H]-repaglinide formed glucuronide and oxidative metabolites (M2 and M4) when incubated with primary human hepatocytes. Gemfibrozil effectively inhibited (∼78%) both glucuronide and M4 formation, but had a minor effect on M2 formation. Concomitantly, the overall turnover of repaglinide was also inhibited (∼80%), and was completely abolished when gemfibrozil was co-incubated with itraconazole. These observations are in qualitative agreement with the in vivo findings. UGT1A1 plays a significant role in the glucuronidation of repaglinide. In addition, gemfibrozil and its glucuronide inhibit repaglinide glucuronidation and the inhibition by gemfibrozil glucuronide is time-dependent.

CONCLUSIONS

Inhibition of UGT enzymes, especially UGT1A1, by gemfibrozil and its glucuronide is an additional mechanism to consider when rationalizing the interaction between repaglinide and gemfibrozil.     

Population pharmacokinetics and bioavailability of tacrolimus in kidney transplant patients

What is already known about this subject

• In spite of its success in ensuring graft survival, therapeutic use of tacrolimus is complicated by its narrow therapeutic index and wide intra- and interpatient variability.
• Some studies of population pharmacokinetics have already been conducted in liver transplant recipients and in paediatric patients.

What this study adds

• Our work determined population pharmacokinetic parameters, in particular bioavailability, in kidney transplant recipients and the relative importance of factors influencing the disposition of tacrolimus.
• Clearance was modelled and days postoperation and corticosteroids dose were significant covariates.

Aims

The use of tacrolimus is complicated by its narrow therapeutic index and wide intra- and interpatient variability. Tacrolimus population pharmacokinetics, including bioavailability, were investigated in an adult kidney transplant cohort to identify patient characteristics that influence pharmacokinetics.

Methods

The database (drug monitoring data) included 83 adult kidney transplant recipients and analysis was performed by a population approach with NONMEM. Data were collected during the first months after transplantation. Patients were administered oral or intravenous tacrolimus as part of a triple immunosuppressive regimen that also included mycophenolate mofetil and corticosteroids. Subsequent doses were adjusted on the basis of clinical evidence of efficacy and toxicity as in routine therapeutic drug monitoring.

Results

A one compartment open model with linear absorption and elimination adequately described the data. The typical value of minimal clearance was 1.8 ± 0.2 l h⁻¹. Clearance increased with time post transplantation to reach 50% of maximal value after 3.8 ± 0.5 days, with a maximal value of 5.6 l h⁻¹. Moreover clearance increased by approximately 1.6 fold (range 0.5–1.6) if the dose of prednisone was >25 mg. The typical value for volume of distribution, V, (98 ± 13 l kg⁻¹) was similar to reported values in kidney transplant patients. The oral bioavailability of tacrolimus was poor and ranged from 11.2 to 19.1%. No covariates significantly influenced V or F.

Conclusions

The number of days postoperation and corticosteroid dose were significant covariates influencing tacrolimus clearance.     

Population pharmacokinetic analysis of vancomycin in neonates. A new proposal of initial dosage guideline

AIM

To determine the population pharmacokinetic parameters of vancomycin in neonatal patients with a wide range of gestational age and birth weight, and subsequently to design an initial dosing schedule for vancomycin in neonates.

METHODS

Using nonlinear mixed-effects modelling (NONMEM VI), the pharmacokinetics of vancomycin were investigated in 70 neonates with postmenstrual age and body weight ranging 25.1–48.1 weeks and 0.7–3.7 kg, respectively. A one-compartment linear disposition model with zero order input and first-order elimination was used to describe the data. Nine demographic characteristics and 21 co-administered drugs were evaluated as covariates of clearance (CL) and distribution volume (V_d) of vancomycin.

RESULTS

Weight-normalized clearance of vancomycin was influenced by postmenstrual age (PMA) and co-administration of amoxicillin-clavulanic acid. Weight-normalized volume of distribution was influenced by co-administration of spironolactone. CL and V_d of the typical individual in this study population (PMA = 34.6 weeks, weight = 1.7 kg) were estimated to be 0.066 l h⁻¹ kg⁻¹ (95% CI 0.059, 0.073 l h⁻¹ kg⁻¹) and 0.572 l kg⁻¹ (95% CI 0.505, 0.639 l kg⁻¹), respectively. This model was used to predict a priori serum vancomycin concentrations in a validation group (n= 41), which were compared with observed concentrations to determine the predictive performance of the model. The 95% confidence interval of mean prediction error included zero for both peak and trough vancomycin concentrations.

CONCLUSIONS

Postmenstrual age, co-administration of amoxicillin-clavulanic acid and spironolactone have a significant effect on the weight-normalized CL and V_d. An initial dosage guideline for vancomycin is proposed for preterm and full-term neonates, whereas the population pharmacokinetic model can be used for dosage individualization of vancomycin.     

Dosing equation for tacrolimus using genetic variants and clinical factors

AIM

To develop a dosing equation for tacrolimus, using genetic and clinical factors from a large cohort of kidney transplant recipients. Clinical factors and six genetic variants were screened for importance towards tacrolimus clearance (CL/F).

METHODS

Clinical data, tacrolimus troughs and corresponding doses were collected from 681 kidney transplant recipients in a multicentre observational study in the USA and Canada for the first 6 months post transplant. The patients were genotyped for 2 724 single nucleotide polymorphisms using a customized Affymetrix SNP chip. Clinical factors and the most important SNPs (rs776746, rs12114000, rs3734354, rs4926, rs3135506 and rs2608555) were analysed for their influence on tacrolimus CL/F.

RESULTS

The CYP3A5*1 genotype, days post transplant, age, transplant at a steroid sparing centre and calcium channel blocker (CCB) use significantly influenced tacrolimus CL/F. The final model describing CL/F (l h⁻¹) was: 38.4 ×[(0.86, if days 6–10) or (0.71, if days 11–180)]×[(1.69, if CYP3A5*1/*3 genotype) or (2.00, if CYP3A5*1/*1 genotype)]× (0.70, if receiving a transplant at a steroid sparing centre) × ([age in years/50]^−0.4) × (0.94, if CCB is present). The dose to achieve the desired trough is then prospectively determined using the individuals CL/F estimate.

CONCLUSIONS

The CYP3A5*1 genotype and four clinical factors were important for tacrolimus CL/F. An individualized dose is easily determined from the predicted CL/F. This study is important towards individualization of dosing in the clinical setting and may increase the number of patients achieving the target concentration. This equation requires validation in an independent cohort of kidney transplant recipients.     

Pharmacokinetics, pharmacodynamics and safety of a human anti-IL-6 monoclonal antibody (sirukumab) in healthy subjects in a first-in-human study

AIMS

To assess the safety, tolerability, pharmacokinetics (PK) and immunogenicity of sirukumab (CNTO 136) following intravenous (i.v.) infusion in healthy subjects.

METHODS

Forty-five healthy adult subjects (38 men and seven women) were randomly assigned to receive a single i.v. dose of placebo or sirukumab (0.3, 1, 3, 6 or 10 mg kg⁻¹ in a dose-escalating manner). All treated subjects were observed for 96 h post infusion and underwent 20-week follow-up evaluations. Serum samples were collected to measure sirukumab concentrations, pharmacodynamic biomarkers and antibodies to sirukumab. Non-compartmental analysis and population PK modelling were conducted to characterize the PK of sirukumab.

RESULTS

Adverse events were generally brief in duration, mild or moderate in intensity and non-dose-dependent. No serious adverse events were observed in the sirukumab-treated subjects. Both C_max and AUC(0,∞) increased in an approximately dose-proportional manner. Median terminal half-life ranged from 18.5 to 29.6 days. A two-compartment model adequately described the PK of sirukumab following i.v. administration. Population estimates for the clearance (CL), the central volume of distribution (V₁), the inter-compartmental clearance (Q) and the peripheral volume of distribution (V₂) were 0.364 l day⁻¹, 3.28 l, 0.588 l day⁻¹ and 4.97 l, respectively. Compared with placebo subjects, a sustained decrease from baseline in C-reactive protein was observed in all sirukumab-treated dose groups, although no clear dose–response relationship was observed. No subjects were positive for antibodies to sirukumab.

CONCLUSIONS

Sirukumab had a well-tolerated safety profile, desirable PK characteristics and a low incidence of immunogenicity following an i.v. infusion of 0.3 to 10 mg kg⁻¹ in healthy subjects.     

Population pharmacokinetics and optimal design of paediatric studies for famciclovir

AIMS

To develop a population pharmacokinetic model for penciclovir (famciclovir is a prodrug of penciclovir) in adults and children and suggest an appropriate dose for children. Furthermore, to develop a limited sampling design based on sampling windows for three different paediatric age groups (1–2, 2–5 and 5–12 years) using an adequate number of subjects for future pharmacokinetic studies.

METHODS

Penciclovir plasma data from six different adult and paediatric studies were supplied by Novartis. Population pharmacokinetic modelling was undertaken in NONMEM version VI. Simulations in MATLAB were used to select an oral paediatric dose that gives similar exposure to 500 mg in adults. Optimal sampling times and sampling windows were obtained in MATLAB and simulations in NONMEM were used to select adequate sample sizes for three paediatric age groups.

RESULTS

A two-compartment, first-order absorption model with an absorption lag time, allometric weight models on V₁, V₂ and Q, and an allometric weight model, age and creatinine clearance as covariates on CL adequately describe the pharmacokinetics of penciclovir in adults and children. Estimated CL (l h⁻¹ 70 kg⁻¹) and V_ss (l.70 kg⁻¹) were 31.2 and 83.1, respectively. An oral dose of 10 mg kg⁻¹ body weight in children was predicted to give similar exposure as 500 mg in adults. A single sampling windows design (0.25–0.4, 0.5–1, 1.25–1.75, 2.75–3.5 and 7.25–8 h) for five samples per subject and 10 subjects in each of the paediatric age groups is recommended for future studies.

CONCLUSIONS

A population pharmacokinetic model of penciclovir in adults and children has been developed. A prospective study design, including dose adjustment, cohort size and blood sampling design has been recommended.     

Integrated analysis of preclinical data to support the design of the first in man study of LY2181308, a second generation antisense oligonucleotide

AIMS

To predict the concentration and target inhibition profiles of the survivin inhibitor antisense oligonucleotide LY2181308 in humans.

METHODS

An indirect pharmacokinetic/pharmacodynamic (PK/PD) model was built to predict the inhibition of survivin mRNA and protein in humans following LY2181308 dosing. Plasma and tissue PK data from cynomolgus monkeys were analyzed by non-linear mixed effect modelling techniques. Human PK parameters were predicted using allometric scaling. Assumptions about the pharmacodynamic parameters were made based upon the target and tumour growth inhibition data from mouse xenograft models. This enabled the prediction of the clinical PK/PD profiles.

RESULTS

Following a 750 mg dose, LY2181308 tumour concentrations ranging from 18.8 to 54 µg g⁻¹ were predicted to lead to 50 to 90% target inhibition. In humans, LY2181308 tumour concentrations from 13.9 to 52.8 µg g⁻¹ (n = 4, LY2181308 750 mg) were observed associated with a median survivin mRNA and protein inhibition of 20% ± 34 (SD) (n = 9) and 23% ± 63 (SD) (n = 10), respectively. The human PK parameters were adequately estimated: central V_d, 4.09 l (90% CI, 3.6, 4.95), distribution clearances, 2.54 (2.36, 2.71), 0.0608 (0.033, 0.6) and 1.67 (1.07, 2.00) l h⁻¹, peripheral V_ds, 25 900 (19 070, 37 200), 0.936 (0.745, 2.07) and 2.51 (1.01, 2.922) l, mean elimination clearance 23.1 l h⁻¹ (5.6, 33.4) and mean terminal half-life, 32.7 days (range 22–52 days).

CONCLUSION

The model reasonably predicted LY2181308 PK in humans. Overall, the integration of preclinical PK/PD data enabled to appropriately predict dose and dosing regimen of LY2181308 in humans with pharmacologically relevant survivin inhibition achieved at 750 mg.     

Population pharmacokinetic analysis of axitinib in healthy volunteers

AIMS

Axitinib is a potent and selective second generation inhibitor of vascular endothelial growth factor receptors 1, 2 and 3 approved for second line treatment of advanced renal cell carcinoma. The objectives of this analysis were to assess plasma pharmacokinetics and identify covariates that may explain variability in axitinib disposition following single dose administration in healthy volunteers.

METHODS

Plasma concentration–time data from 337 healthy volunteers in 10 phase I studies were analyzed, using non-linear mixed effects modelling (nonmem) to estimate population pharmacokinetic parameters and evaluate relationships between parameters and food, formulation, demographic factors, measures of renal and hepatic function and metabolic genotypes (UGT1A1*28 and CYP2C19).

RESULTS

A two compartment structural model with first order absorption and lag time best described axitinib pharmacokinetics. Population estimates for systemic clearance (CL), central volume of distribution (V_c), absorption rate constant (k_a) and absolute bioavailability (F) were 17.0 l h⁻¹, 45.3 l, 0.523 h⁻¹ and 46.5%, respectively. With axitinib Form IV, k_a and F increased in the fasted state by 207% and 33.8%, respectively. For Form XLI (marketed formulation), F was 15% lower compared with Form IV. CL was not significantly influenced by any of the covariates studied. Body weight significantly affected V_c, but the effect was within the estimated interindividual variability for V_c.

CONCLUSIONS

The analysis established a model that adequately characterizes axitinib pharmacokinetics in healthy volunteers. V_c was found to increase with body weight. However, no change in plasma exposures is expected with change in body weight; hence no dose adjustment is warranted.     

Population pharmacokinetic analysis of tacrolimus in Mexican paediatric renal transplant patients: role of CYP3A5 genotype and formulation

Aims

The aims of this study were (i) to develop a population pharmacokinetic (PK) model of tacrolimus in a Mexican renal transplant paediatric population (n = 53) and (ii) to test the influence of different covariates on its PK properties to facilitate dose individualization.

Methods

Population PK and variability parameters were estimated from whole blood drug concentration profiles obtained at steady-state using the non-linear mixed effect modelling software NONMEM® Version 7.2.

Results

Tacrolimus PK profiles exhibited high inter-patient variability (IPV). A two compartment model with first order input and elimination described the tacrolimus PK profiles in the studied population. The relationship between CYP3A5 genotype and tacrolimus CL/F was included in the final model. CL/F in CYP3A5*1/*1 and *1/*3 carriers was approximately 2- and 1.5-fold higher than in CYP3A5*3/*3 carriers (non-expressers), respectively, and explained almost the entire IPV in CL/F. Other covariates retained in the final model were the tacrolimus dose and formulation type. Limustin® showed markedly lower concentrations than the rest of the formulations.

Conclusions

Population PK modelling of tacrolimus in paediatric renal transplant recipients identified the tacrolimus formulation type as a significant covariate affecting the blood concentrations and confirmed the previously reported significant effect of CYP3A5 genotype on CL/F. It allowed the design of a proposed dosage based on the final model that is expected to help to improve tacrolimus dosing.