Population pharmacokinetic and exposure simulation analysis for cediranib (AZD2171) in pooled Phase I/II studies in patients with cancer.

AIMS: A population pharmacokinetic (PK) model was developed for cediranib to simulate cediranib exposure for different doses, including comedication with strong uridine glucuronosyl transferase/P-glycoprotein inducers such as rifampicin, in cancer patients. METHODS: Plasma concentrations and covariates from 625 cancer patients after single or multiple oral cediranib administrations ranging from 0.5 to 90 mg in 19 Phase I and II studies were included in the analysis. Stepwise covariate modelling was used to develop the population PK model. The final model was used to simulate cediranib exposure in cancer patients to evaluate cediranib target coverage and the need for dose adjustment for covariates or coadministration with rifampicin. RESULTS: A two-compartment model with sequential zero- and first-order absorption and first-order elimination adequately described the cediranib concentration-time courses. Body weight and age were identified as having statistically significant impact on cediranib PK, but only <21% impact on AUC and maximum concentrations. Simulated lower bounds of 90% prediction interval or median of unbound cediranib concentrations after cediranib 15 or 20 mg exceeded the IC50 for vascular endothelial growth factor receptors-1, -2 and -3. Exposures of cediranib 20 or 30 mg with coadministration of rifampicin were comparable to those of 15 or 20 mg, respectively, without coadministration. CONCLUSIONS: No covariate was identified to require dose adjustment for cediranib. Cediranib exposure following 15 or 20 mg daily dose administration is adequate overall for inhibition of in vitro estimated vascular endothelial growth factor receptor-1, -2 and -3 activities. An increase in cediranib dose may be needed for cediranib coadministered with strong uridine glucuronosyl transferase/P-glycoprotein inducers such as rifampicin.

Allopregnanolone Concentrations in Breast Milk and Plasma from Healthy Volunteers Receiving Brexanolone Injection, With Population Pharmacokinetic Modeling of Potential Relative Infant Dose.

BACKGROUND AND OBJECTIVE: Women with postpartum depression (PPD) may expose their infants to antidepressants via breast milk. Brexanolone is the only FDA-approved antidepressant specifically indicated for the treatment of PPD. This open-label, phase Ib study of healthy lactating volunteers assessed pharmacokinetic (PK) properties of brexanolone and a population PK (PopPK) model determined the relative infant dose (RID) in breastfeeding mothers. METHODS: Twelve participants received a 60-h infusion of brexanolone (titration up to 90 µg/kg/h). Allopregnanolone concentration was measured in breast milk and plasma. The RID was computed using a nonlinear mixed-effects PopPK model of patients with PPD and healthy women (N = 156). Model results were extended across an integrated dataset of participants through day 7. RESULTS: Allopregnanolone concentration-time profiles were similar between breast milk and plasma (partition coefficient for concentration gradient [milk : plasma] 1.36). Mean (95% CI) Cmax was 89.7 ng/mL (74.19-108.39), and median (95% CI) tmax was 47.8 h (47.8-55.8) in plasma. The overall PK profile was best described by a two-compartment model with linear elimination and distribution. Body weight was the only significant covariate identified. There were no apparent differences in PopPK AUC and Cmax between participants with or without concomitant antidepressant treatment. Maximum RID was 1.3%. CONCLUSION: The PopPK model successfully described the variability and concentration-time profiles of allopregnanolone in breast milk and plasma in healthy participants and in the plasma of brexanolone-treated patients with PPD. The rapid elimination of allopregnanolone from plasma and breast milk, and low RID, suggests the appropriateness of brexanolone weight-based dosing and supports other PK-related labeling recommendations.

Population pharmacokinetic-pharmacodynamic model for neutropenia with patient subgroup identification: comparison across anticancer drugs.

PURPOSE: Cancer chemotherapy, although based on body surface area, often causes unpredictable myelosuppression, especially severe neutropenia. The aim of this study was to evaluate qualitatively and quantitatively the influence of patient-specific characteristics on the neutrophil concentration-time course, to identify patient subgroups, and to compare covariates on system-related pharmacodynamic variable between drugs. EXPERIMENTAL DESIGN: Drug and neutrophil concentration, demographic, and clinical chemistry data of several trials with docetaxel (637 patients), paclitaxel (45 patients), etoposide (71 patients), or topotecan (191 patients) were included in the covariate analysis of a physiology-based pharmacokinetic-pharmacodynamic neutropenia model. Comparisons of covariate relations across drugs were made. RESULTS: A population model incorporating four to five relevant patient factors for each drug to explain variability in the degree and duration of neutropenia has been developed. Sex, previous anticancer therapy, performance status, height, binding partners, or liver enzymes influenced system-related variables and alpha1-acid glycoprotein, albumin, bilirubin, concomitant cytotoxic agents, or administration route changed drug-specific variables. Overall, female and pretreated patients had a lower baseline neutrophil concentration. Across-drug comparison revealed that several covariates (e.g., age) had minor (clinically irrelevant) influences but consistently shifted the pharmacodynamic variable in the same direction. CONCLUSIONS: These mechanistic models, including patient characteristics that influence drug-specific parameters, form the rationale basis for more tailored dosing of individual patients or subgroups to minimize the risk of infection and thus might contribute to a more successful therapy. In addition, nonsignificant or clinically irrelevant relations on system-related parameters suggest that these covariates could be negligible in clinical trails and daily use.

Association of CYP2C8, CYP3A4, CYP3A5, and ABCB1 polymorphisms with the pharmacokinetics of paclitaxel.

PURPOSE: To retrospectively evaluate the effects of six known allelic variants in the CYP2C8, CYP3A4, CYP3A5, and ABCB1 genes on the pharmacokinetics of the anticancer agent paclitaxel (Taxol). EXPERIMENTAL DESIGN: A cohort of 97 Caucasian patients with cancer (median age, 57 years) received paclitaxel as an i.v. infusion (dose range, 80-225 mg/m(2)). Genomic DNA was analyzed using PCR RFLP or using Pyrosequencing. Pharmacokinetic variables for unbound paclitaxel were estimated using nonlinear mixed effect modeling. The effects of genotypes on typical value of clearance were evaluated with the likelihood ratio test within NONMEM. In addition, relations between genotype and individual pharmacokinetic variable estimates were evaluated with one-way ANOVA. RESULTS: The allele frequencies for the CYP2C8*2, CYP2C8*3, CYP2C8*4, CYP3A4*3, CYP3A5*3C, and ABCB1 3435C>T variants were 0.7%, 9.2%, 2.1%, 0.5%, 93.2%, and 47.1%, respectively, and all were in Hardy-Weinberg equilibrium. The population typical value of clearance of unbound paclitaxel was 301 L/h (individual clearance range, 83.7-1055 L/h). The CYP2C8 or CYP3A4/5 genotypes were not statistically significantly associated with unbound clearance of paclitaxel. Likewise, no statistically significant association was observed between the ABCB1 3435C>T variant and any of the studied pharmacokinetic variables. CONCLUSIONS: This study indicates that the presently evaluated variant alleles in the CYP2C8, CYP3A4, CYP3A5, and ABCB1 genes do not explain the substantial interindividual variability in paclitaxel pharmacokinetics.

Model of chemotherapy-induced myelosuppression with parameter consistency across drugs.

PURPOSE: To develop a semimechanistic pharmacokinetic-pharmacodynamic model describing chemotherapy-induced myelosuppression through drug-specific parameters and system-related parameters, which are common to all drugs. PATIENTS AND METHODS: Patient leukocyte and neutrophil data after administration of docetaxel, paclitaxel, and etoposide were used to develop the model, which was also applied to myelosuppression data from 2'-deoxy-2'-methylidenecytidine (DMDC), irinotecan (CPT-11), and vinflunine administrations. The model consisted of a proliferating compartment that was sensitive to drugs, three transit compartments that represented maturation, and a compartment of circulating blood cells. Three system-related parameters were estimated: baseline, mean transit time, and a feedback parameter. Drug concentration-time profiles affected the proliferation of sensitive cells by either an inhibitory linear model or an inhibitory E(max) model. To evaluate the model, system-related parameters were fixed to the same values for all drugs, which were based on the results from the estimations, and only drug-specific parameters were estimated. All modeling was performed using NONMEM software. RESULTS: For all investigated drugs, the model successfully described myelosuppression. Consecutive courses and different schedules of administration were also well characterized. Similar system-related parameter estimates were obtained for the different drugs and also for leukocytes compared with neutrophils. In addition, when system-related parameters were fixed, the model well characterized chemotherapy-induced myelosuppression for the different drugs. CONCLUSION: This model predicted myelosuppression after administration of one of several different chemotherapeutic drugs. In addition, with fixed system-related parameters to proposed values, and only drug-related parameters estimated, myelosuppression can be predicted. We propose that this model can be a useful tool in the development of anticancer drugs and therapies.

Pharmacokinetic/pharmacodynamic modelling in oncological drug development.

For many oncological agents, myelosuppression is the dose-limiting toxicity and the quantitative characterisation of the relationship between drug dose, plasma concentration and haematological toxicity is of importance in the drug development. Mechanism-based population pharmacokinetic-pharmacodynamic models have been developed for this purpose and the applications of these in candidate selection, first-in-man studies, prodrug and formulation development, dose finding, schedule optimisation, assessing influence of modifying agents, drug combination studies, subgroup identification and feedback individualisation are reviewed.

Population pharmacokinetics of TC-5214, a nicotinic channel modulator, in phase I and II clinical studies.

TC-5214 (dexmecamylamine) is a nicotinic channel modulator that has previously been evaluated for treatment of major depression disorder (MDD) and is currently being evaluated by Targacept as a treatment for overactive bladder. A comprehensive population pharmacokinetic (POP PK) model of TC-5214 was developed using nonlinear mixed-effects modeling of pooled plasma concentration data from 6 early phase I studies in 179 healthy participants or patients with non-MDD and 1 phase II study in 68 MDD patients. Concentration-time profiles of TC-5214 after either single or multiple oral doses of TC-5214 was described by a one-compartment model with first-order absorption with lag time and first-order elimination. Covariate analysis revealed that creatinine clearance was a significant covariate on clearance and that body weight significantly influenced the central volume of distribution. The final model (with identified covariates) was used to simulate steady-state exposure for patients with impaired renal function. Results from forest plots reveal that patients with moderate to severe renal impairment or end stage renal disease are associated with significantly higher Cssmax and AUC compared to patients with normal renal function. The proposed final POP PK model could be employed in defining a TC-5214 dosage regimen in patients with impaired renal function.

Role of modelling and simulation: a European regulatory perspective.

Modelling and simulation (M&S) of clinical data, e.g. pharmacokinetic, pharmacodynamic and clinical endpoints, is a useful approach for more efficient interpretation of collected data and for extrapolation of knowledge to the entire target population. This type of documentation is included in the majority of marketing authorization applications for new medicinal products. This article summarizes the current status of regulatory review with respect to the role of M&S in Europe from the perspective of the Swedish Medical Products Agency. At present, regulatory bodies in Europe encourage the application of the M&S approach during drug development. However, there is a lack of consensus and transparent guidance documents. The main regulatory usage is in the evaluation of dose choices in sub-populations and as support for the dosing regimen in general. The regulatory review of conestat alfa illustrates how the dose recommendation was revised during the approval procedure based on M&S information. A survey of marketing authorization applications for new medicinal products approved in 2010 revealed that the use of the information gained from M&S documentation varies with respect to both regulatory review and the applicants' presentation of the data in the submitted dossier. Increased utilization and broadened application of M&S is anticipated in pharmaceutical development, where one area of focus is medicines for paediatric patients. Accordingly, the regulatory agencies will need to increase their capability to assess and utilize this type of information, and an interactive process among regulatory agencies is warranted to provide more unified regulatory assessment and guidance. Moreover, applicants are encouraged to expand on the usage of exposure-response models to map the systemic exposure range that yields safe and efficacious treatment and to improve the presentation of the gained knowledge in summary documents of the marketing authorization applications.