To address the most appropriate endogenous biomarker for drug–drug interaction risk assessment, eight healthy subjects received an organic anion transporting polypeptide 1B (OATP1B) inhibitor (rifampicin, 150, 300, and 600 mg), and a probe drug cocktail (atorvastatin, pitavastatin, rosuvastatin, and valsartan). In addition to coproporphyrin I, a widely studied OATP1B biomarker, we identified at least 4 out of 28 compounds (direct bilirubin, glycochenodeoxycholate‐3‐glucuronide, glycochenodeoxycholate‐3‐sulfate, and hexadecanedioate) that presented good sensitivity and dynamic range in terms of the rifampicin dose‐dependent change in area under the plasma concentration‐time curve ratio (AUCR). Their suitability as OATP1B biomarkers was also supported by the good correlation of AUC0‐24h between the endogenous compounds and the probe drugs, and by nonlinear regression analysis (AUCR−1 vs. rifampicin plasma Cmax (maximum total concentration in plasma)) to yield an estimate of the inhibition constant of rifampicin. These endogenous substrates can complement existing OATP1B‐mediated drug–drug interaction risk assessment approaches based on agency guidelines in early clinical trials.

Tanezumab was safe and generally well tolerated and may improve pain symptoms in Japanese patients with moderate to severe osteoarthritis of the knee. CLINICALTRIALS.GOV IDENTIFIER: NCT00669409.

Endogenous biomarkers are emerging to advance clinical drug-drug interaction (DDI) risk assessment in drug development. Twelve healthy subjects received a multidrug and toxin exclusion protein (MATE) inhibitor (pyrimethamine, 10, 25, and 75 mg) in a crossover fashion to identify an appropriate endogenous biomarker to assess MATE1/2-K-mediated DDI in the kidneys. Metformin (500 mg) was also given as reference probe drug for MATE1/2-K. In addition to the previously reported endogenous biomarker candidates (creatinine and N 1methylnicotinamide (1-NMN)), N 1-methyladenosine (m 1 A) was included as novel biomarkers. 1-NMN and m 1 A presented as superior MATE1/2-K biomarkers since changes in their renal clearance (CL r) along with pyrimethamine dose were well-correlated with metformin CL r changes. The CL r of creatinine was reduced by pyrimethamine, however, its changes poorly correlated with metformin CL r changes. Nonlinear regression analysis (CL r vs. mean total concentration of pyrimethamine in plasma) yielded an estimate of the inhibition constant (K i) of pyrimethamine and the fraction of the clearance pathway sensitive to pyrimethamine. The in vivo K i value thus obtained was further converted to unbound Ki using plasma unbound fraction of pyrimethamine, which was comparable to the in vitro K i for MATE1 (1-NMN) and MATE2-K (1-NMN and m 1 A). It is concluded that 1-NMN and m 1 A CL r can be leveraged as quantitative MATE1/2-K biomarkers for DDI risk assessment in healthy volunteers.

AIMSThe aims of this study were to develop a population pharmacokinetic (PK) model of ampicillin and sulbactam, to identify patient characteristics influencing the PK, and to explore the relationship between dose regimen and degree of renal impairment with exposure and time above minimum inhibitory concentration (MIC). METHODSThis analysis was performed on PK data for ampicillin and sulbactam and MIC data from a clinical trial in Japanese patients with community acquired pneumonia. Simulations were performed to investigate the effects of different dosing intervals on exposure and time above MIC in various degrees of renal impairment. RESULTSThe plasma concentrations from 47 patients were adequately described by a two compartment model with simultaneous fit of ampicillin and sulbactam PK data, where creatinine clearance on clearance and body weight on volume in the peripheral compartment were identified as covariates for both drugs. Creatinine clearance contributed to reducing inter-individual variability of clearance by 16%. Mean clearance (inter-individual variability) for ampicillin and sulbactam was estimated to be 10.7 l h −1 (14.8%) and 10.4 l h −1 (15.2%), respectively. The time above MIC for each pathogen was generally > 50% of the treatment period. Simulations for exposure and time above MIC supported currently recommended dose adjustments. CONCLUSIONSThis study provided a PK model for ampicillin and sulbactam, the time above MICs for identified pathogens and associated simulation results. These findings provide useful information and augment evidence for the established dosage regimens in patients with various degrees of renal impairment.

A population pharmacokinetic (PK) analysis was conducted to characterize the voriconazole pharmacokinetic profiles in immunocompromised Japanese pediatric subjects and to compare them to those in immunocompromised non-Japanese pediatric subjects. A previously developed two-compartment pharmacokinetic model with first-order absorption and mixed linear and nonlinear elimination adequately described the voriconazole intravenous and oral data from Japanese pediatric subjects with few modifications. Bayesian priors were applied to this analysis by using the NONMEM routine NWPRI, which allowed priors for the fixed-effect parameter vector and variance matrix of the random-effect parameters to be a normal distribution and an inverse Wishart distribution, respectively. Large intersubject variabilities in oral bioavailability and voriconazole exposure were observed in these pediatric subjects. The mean oral bioavailability estimated in Japanese pediatric subjects was 73% (range, 17% to 99%), which is consistent with the reported estimates of 64% in the previous model and less than what was originally estimated for healthy adults-96%. Voriconazole exposures in Japanese pediatric subjects were generally comparable to those in non-Japanese pediatric subjects receiving the same dosing regimens, given the large intersubject variability. Consistent with the previous findings, the CYP2C19 genotyping status did not have a clinically relevant effect on voriconazole exposure in Japanese pediatric subjects, although it was identified as a covariate in the model to help explain the intersubject variability in voriconazole exposure. The CYP2C19 genotyping status alone does not warrant dose adjustment of voriconazole. No other factors besides age and weight were identified to explain the PK variability of voriconazole. Voriconazole is a broad-spectrum triazole antifungal agent for the treatment of patients with opportunistic fungal infections, such as invasive aspergillosis (1). It exhibits potent and wide-ranging in vitro activity, including fungicidal activity against Aspergillus species and other fungi. Immunocompromised children, particularly those with hematological malignancies, are at higher risk for systemic fungal infections, which significantly affect the prognosis of such patients. Voriconazole is suggested as a treatment option for fungal infections in children in Japanese and overseas guidelines.Voriconazole is extensively metabolized by and is also an inhibitor of the cytochrome P450 (CYP) isozymes CYP2C19 (major), CYP2C9, and CYP3A4 (2), which results in extensive drug interactions with concomitant medications. Voriconazole exhibits nonlinear pharmacokinetics (PK), and intersubject variability in voriconazole exposure is high. It has been demonstrated that in healthy adults CYP2C19 genotype, gender, and age are key factors that help explain this variability (3). CYP2C19 exhibits genetic polymorphism, and approximately 3% to 5% of Caucasians and African Americans and up to 20% of Asians are poor metabolizers (PMs) (4, 5)....