A Physiologically-Based Pharmacokinetic (PBPK) Model Network for the Prediction of CYP1A2 and CYP2C19 Drug-Drug-Gene Interactions with Fluvoxamine, Omeprazole, S-mephenytoin, Moclobemide, Tizanidine, Mexiletine, Ethinylestradiol, and Caffeine.

Physiologically-based pharmacokinetic (PBPK) modeling is a well-recognized method for quantitatively predicting the effect of intrinsic/extrinsic factors on drug exposure. However, there are only few verified, freely accessible, modifiable, and comprehensive drug-drug interaction (DDI) PBPK models. We developed a qualified whole-body PBPK DDI network for cytochrome P450 (CYP) CYP2C19 and CYP1A2 interactions. Template PBPK models were developed for interactions between fluvoxamine, S-mephenytoin, moclobemide, omeprazole, mexiletine, tizanidine, and ethinylestradiol as the perpetrators or victims. Predicted concentration-time profiles accurately described a validation dataset, including data from patients with genetic polymorphisms, demonstrating that the models characterized the CYP2C19 and CYP1A2 network over the whole range of DDI studies investigated. The models are provided on GitHub (GitHub Inc., San Francisco, CA, USA), expanding the library of publicly available qualified whole-body PBPK models for DDI predictions, and they are thereby available to support potential recommendations for dose adaptations, support labeling, inform the design of clinical DDI trials, and potentially waive those.

Population pharmacokinetics of nintedanib, an inhibitor of tyrosine kinases, in patients with non-small cell lung cancer or idiopathic pulmonary fibrosis.

PURPOSE: A population pharmacokinetic model was developed for nintedanib in patients with non-small cell lung cancer (NSCLC) or idiopathic pulmonary fibrosis (IPF). The effects of intrinsic and extrinsic patient factors on exposure of nintedanib and its main metabolite BIBF 1202 were studied. METHODS: Data from 1191 patients with NSCLC (n = 849) or IPF (n = 342) treated with oral nintedanib (once- or twice-daily, dose range 50-250 mg) in 4 Phase II or III studies were combined. Plasma concentrations of nintedanib (n = 5611) and BIBF 1202 (n = 5376) were analyzed using non-linear mixed-effects modeling. RESULTS: Pharmacokinetics of nintedanib were described by a one-compartment model with linear elimination, first-order absorption, and absorption lag time. For a typical patient, the absorption rate was 0.0827 h-1, apparent total clearance was 897 L/h, apparent volume of distribution at steady state was 465 L, and lag time was 25 min. Age, weight, smoking, and Asian race were statistically significant covariates influencing nintedanib exposure, but no individual covariate at extreme values (5th and 95th percentiles of baseline values for continuous covariates) resulted in a change of more than 33% relative to a typical patient. Pharmacokinetics and covariate effects for BIBF 1202 were similar to nintedanib. Mild or moderate renal impairment and mild hepatic impairment (classified by transaminase or bilirubin increase above the upper limit of normal) or underlying disease had no significant effects on nintedanib pharmacokinetics. CONCLUSIONS: This model adequately described the pharmacokinetic profile of nintedanib in NSCLC and IPF populations and can be used for simulations exploring covariate effects and exposure-response analyses.

Population Pharmacokinetics of Volasertib Administered in Patients with Acute Myeloid Leukaemia as a Single Agent or in Combination with Cytarabine.

BACKGROUND: Volasertib, a potent and selective polo-like kinase inhibitor, has shown to increase response rates and improve survival with a clinically manageable safety profile, administered alone and in combination with cytarabine in patients with acute myeloid leukaemia. OBJECTIVES: The objectives of this analysis were to describe the pharmacokinetics of volasertib and cytarabine, administered as single agents or in combination. METHODS: Three thousand, six hundred and six plasma volasertib concentrations from 501 patients receiving either volasertib alone, or in combination with cytarabine, and 826 plasma cytarabine concentrations from 650 patients receiving cytarabine as multiple subcutaneous injections per cycle either alone, or in combination with volasertib, were analysed using NONMEM Version 7.3. Covariates evaluated included demographic and disease-related parameters. RESULTS: The pharmacokinetics of volasertib were found to be dose independent from 150 to 550 mg. Body surface area and ethnicity showed significant effects in all the patients. This is reflected as an increase in drug exposure for Japanese patients, although this finding has to be interpreted with caution because only 7% of patients were part of that population group. Volasertib showed low-to-mild inter-individual variability in total clearance. For the case of cytarabine, its pharmacokinetics was affected by body surface area. Finally, volasertib and cytarabine did not influence the pharmacokinetic characteristics of each other. CONCLUSIONS: The pharmacokinetics of volasertib in patients with acute myeloid leukaemia alone or in combination with cytarabine is predictable and associated with low-to-mild patient variability with the exception of the high variability associated with the volume of distribution of the central compartment, having no effect on the area under the plasma concentration-time curve.

Population pharmacokinetics of afatinib, an irreversible ErbB family blocker, in patients with various solid tumors.

PURPOSE: This population pharmacokinetic model was developed to characterize the pharmacokinetics of the oral irreversible ErbB family blocker afatinib in patients with solid tumors and to investigate the impact of selected intrinsic and extrinsic factors. METHODS: Data from 927 patients (4,460 plasma concentrations) with advanced solid tumors in 7 Phase II or III studies were analyzed. Afatinib was administered orally in continuous 3 or 4 week cycles (starting dose 20, 40 or 50 mg once-daily). Plasma concentration-time data for up to 7 months dosing were analyzed using nonlinear mixed-effects modeling. RESULTS: The pharmacokinetic profile of afatinib was best described by a two-compartment disposition model with first-order absorption and linear elimination. There was a slightly more than proportional increase in exposure with increasing dose, accounted for by a dose-dependent relative bioavailability. For the therapeutic dose of 40 mg, the estimated apparent total clearance and distribution volume at steady state were 734 mL/min and 2,370 L, respectively. While food intake, body weight, gender, Eastern Cooperative Oncology Group performance score, renal function, and the level of alkaline phosphatase, lactate dehydrogenase or total protein were statistically significant covariates influencing afatinib exposure, none resulted in a proportional change in exposure of more than 27.8 % in a typical patient at model extremes (2.5th and 97.5th percentiles of baseline values for continuous covariates). In simulations of the individual covariate effects, none caused a change in the typical profile exceeding the observed variability range (90 % prediction interval) of afatinib. CONCLUSION: This population pharmacokinetic model adequately described the pharmacokinetics of afatinib in different cancer patient populations and therefore can be used for simulations exploring covariate effects and possible dose adaptations. The effect size for each of the individual covariates is not considered clinically relevant.

A pharmacokinetic-pharmacodynamic model for cardiovascular safety assessment of R1551.

INTRODUCTION: Pharmacokinetic-pharmacodynamic relationships are crucial in understanding a drug's arrhythmogenic potential. Models assist to quantitatively relate parent and metabolite concentrations to adverse electrocardiographic effects, including an apparent delay between effect and circulating parent species concentration. Here, we used an effect compartment model to investigate PR and QRS prolongation previously observed in preclinical studies with the NK1-NK3 antagonist R1551. METHOD: Using a cross-over design, beagle dogs received a single oral dose of R1551 (0-100mg/kg), and cynomolgus monkeys received oral doses of 0-30 mg/kg once daily for 5 days. PR and QRS intervals and heart rate were measured by telemetry, for ≥ 24h after each dose in dogs, and on treatment days 1, 3, and 5 in monkeys. Pharmacokinetic parameters were estimated by fitting a two-compartment model to the data. For each species, a linear effect compartment model was used to relate PR and QRS intervals to effect compartment concentrations. RESULTS: The effect compartment model provided a good fit to the observed data for both ECG parameters in dogs, and for QRS interval in monkeys (PR(0)=95.1 ms ± 2.74 and 64.9 ms ± 1.46, QRS(0)=42.5 ms ± 1.24 and 46.5 ms ± 1.11 in dog and monkey, respectively). For PR interval in monkeys, the fit was improved by adding a placebo effect compartment to the linear model. R1551 effects on intervals in dogs suggested the presence of responder and non-responder sub-populations. In monkeys, only the highest R1551 dose prolonged PR intervals. Effect slope factors were similar between dog and monkey for both intervals (S(PR)=0.00930 ms mg(-1)kg(-1)l(-1) ± 0.00133 in dog and 0.00934 ms mg(-1)kg(-1)l(-1) ± 0.00141 in monkey; S(QRS)=0.00274 ms mg(-1)kg(-1)l(-1) ± 0.00101 in dog and 0.00200 ms mg(-1)kg(-1)l(-1) ± 0.000552 in monkey). DISCUSSION: Our results indicate a non-linear relationship between R1551 plasma kinetics and electrophysiological effects and suggest that the parent was not responsible for the observed ECG effects. In addition, the population based approach allows exploitation of sparse PK data in dog and monkey, analysis throughout the complete effect time course, and assessment of inter-individual variability, all in a single comprehensive model.