Population Pharmacokinetics of Inotuzumab Ozogamicin in Pediatric Relapsed/Refractory B-Cell Precursor Acute Lymphoblastic Leukemia: Results of Study ITCC-059.

BACKGROUND AND OBJECTIVE: Inotuzumab ozogamicin is an antibody-drug conjugate approved for treating relapsed/refractory B-cell precursor acute lymphoblastic leukemia (BCP-ALL) in adults. Pediatric pharmacokinetic data of inotuzumab ozogamicin are lacking. This study is the first to examine the population pharmacokinetics of inotuzumab ozogamicin in pediatric patients with relapsed/refractory BCP-ALL. METHODS: From 531 adult patients with B-cell non-Hodgkin's lymphoma, 234 adult patients with BCP-ALL, and 53 pediatric patients with BCP-ALL, 8924 inotuzumab ozogamicin serum concentrations were analyzed using non-linear mixed-effects modeling. A published adult inotuzumab ozogamicin population-pharmacokinetic model, a two-compartment model with linear and time-dependent clearance, was adapted to describe the pediatric data. RESULTS: Modifications in this analysis, compared to the published adult model, included: (i) re-estimating pharmacokinetic parameters and covariate effects; (ii) modifying covariate representation; and (iii) introducing relevant pediatric covariate effects (age on the decay coefficient of time-dependent clearance and ALL effect (disease type and/or different bioanalytical analysis methods) on initial values of time-dependent clearance). For patients with relapsed/refractory BCP-ALL, increasing age was associated with a decreasing decay coefficient of time-dependent clearance, reflecting that the target-mediated drug clearance declines more rapidly in children. In pediatric BCP-ALL, the median [interquartile range] cumulative area under the concentration-time curve was significantly higher among responders (n = 42) versus non-responders (n = 10) at the end of the first cycle (26.1 [18.9-35.0] vs 10.1 [9.19-16.1], × 103 ng*h/mL, p < 0.001). From simulations performed at the recommended pediatric phase II dose, inotuzumab ozogamicin exposure reached a similar level as observed in responding pediatric trial participants. CONCLUSIONS: The pharmacokinetic profile of inotuzumab ozogamicin in pediatric patients with relapsed/refractory BCP-ALL was well described in this study. No dose adjustment is required clinically for pediatric patients with BCP-ALL based on the simulated inotuzumab ozogamicin exposure at the recommended pediatric phase II dose, promising efficacy and acceptable tolerability.

Population modeling of bosutinib exposure-response in patients with newly diagnosed chronic phase chronic myeloid leukemia.

BACKGROUND: The BELA and BFORE trials compared bosutinib starting doses of 500 mg once daily (QD) and 400 mg QD, respectively, with imatinib in adults with newly diagnosed chronic phase chronic myeloid leukemia (CP-CML). The B1871048 trial evaluated bosutinib 400 mg QD in Japanese patients with newly diagnosed CP-CML. AIM: This analysis assessed the impact of a lower bosutinib starting dose on key efficacy and safety outcomes. MATERIALS & METHODS: A pharmacokinetic model was used to estimate metrics of bosutinib exposure, and logistic regression was used to investigate relationships with efficacy (cumulative major molecular response [MMR] and cumulative complete cytogenetic response [CCyR]) and safety outcomes (eight prespecified adverse events). RESULTS: Totals of 573 and 574 patients were included in the efficacy and safety endpoint analyses, respectively. Cumulative MMR and CCyR were similar across studies. Log(Ctrough ) and log(Cavg ) were significant predictors of MMR and CCyR, and the probability of achieving MMR or CCyR increased 1.3-fold or 2.7-fold for every 1 unit increase in log(Ctrough ) or log(Cavg ), respectively. An exposure-response relationship was identified between time-to-event and risk of diarrhea, nausea, and vomiting. Significant relationships were also observed between time-to-event and log(Cavg ), Ctrough , and Cavg with diarrhea, nausea, and vomiting, respectively. DISCUSSION: A bosutinib exposure-response relationship with safety and efficacy was observed. CONCLUSION: Compared with 500 mg QD, a bosutinib starting dose of 400 mg QD improved tolerability in some patients with newly diagnosed CP-CML without compromising efficacy. CLINICALTRIALS: gov identifiers: NCT00574873; NCT02130557; NCT03128411.

Population pharmacokinetics of inotuzumab ozogamicin in relapsed/refractory acute lymphoblastic leukemia and non-Hodgkin lymphoma.

This population pharmacokinetics analysis evaluated the target-mediated drug disposition of inotuzumab ozogamicin (InO) through an empirical time-dependent clearance (CLt) term and identified potential covariates that may be important predictors of variability in InO distribution and elimination. This analysis was conducted by pooling data from 2 studies of single-agent InO in patients with relapsed or refractory (R/R) B cell acute lymphoblastic leukemia (ALL), 3 studies of single-agent InO, 5 studies of InO plus rituximab (R-InO), and 1 study of R-InO plus chemotherapy in patients with R/R B-cell non-Hodgkin lymphoma (NHL). Pharmacokinetic data included 8361 InO concentration-time observations that were modeled using nonlinear mixed-effects analysis. Covariate relations were identified using generalized additive modeling on base model parameters and then tested in a stepwise manner via covariate modeling. InO concentration was described with a 2-compartment model with linear and time-dependent clearance components. Based on the final model, baseline body surface area was a covariate of the linear and time-dependent clearance components and volume of distribution in the central compartment; baseline percentage of blasts in the peripheral blood was a covariate of the decay coefficient of the time-dependent clearance term (CLt); and concomitant rituximab treatment was a covariate of the linear clearance component (CL1). The magnitude of change of each pharmacokinetic parameter due to these covariates was not considered clinically relevant. Therefore, no dose adjustment of InO for the treatment of patients with R/R B-cell ALL or NHL is needed on the basis of selected covariates.

Lack of effect of smoking status on axitinib pharmacokinetics in patients with non-small-cell lung cancer.

PURPOSE: Axitinib, a tyrosine kinase inhibitor targeting vascular endothelial growth factor receptors 1-3, is approved for second-line treatment of advanced renal cell carcinoma. Axitinib is partially metabolized by cytochrome P450 1A2, which is induced by chronic heavy smoking. The effect of smoking on axitinib pharmacokinetics was evaluated in a non-small-cell lung cancer (NSCLC) patient population with a large number of active and ex-smokers. METHODS: Data were pooled from six clinical studies-serial pharmacokinetics from two healthy volunteer studies (n = 58) and sparse pharmacokinetics from four NSCLC studies (n = 152)-for a nonlinear mixed effects modeling (NONMEM v7.2) analysis. Demographics, smoking status, liver and renal function status, and Eastern Cooperative Oncology Group performance status were tested as covariates. RESULTS: There were 83 (40%) active smokers and 56 (27%) ex-smokers in the pooled dataset. Axitinib pharmacokinetics was adequately described with a linear, two-compartment model with a lagged first-order absorption. Final parameter estimates (inter-individual variability) were 16.1 L/h (59.1%) and 45.3 L (54.4%) for systemic clearance (CL) and central volume of distribution (Vc), respectively. Smoking status was found not to alter CL or Vc. Asian ethnicity and body weight were significant covariates for Vc, but were not considered clinically relevant since individual values of Vc for Asians were within the range of non-Asians. CONCLUSIONS: Based on this analysis, smoking status does not affect area under plasma concentration-time curve, and thus no dose adjustment is required for smokers.

Effect of Renal Impairment on the Pharmacokinetics and Safety of Axitinib.

BACKGROUND: Axitinib, an inhibitor of vascular endothelial growth factor (VEGF) receptors, is approved as second-line treatment for advanced renal cell carcinoma (RCC). Agents targeting the VEGF pathway may induce renal toxicities, which may be influenced by pre-existing renal dysfunction. OBJECTIVE: The objective was to characterize axitinib pharmacokinetics and safety in patients with renal impairment. PATIENTS AND METHODS: Effect of renal function (baseline creatinine clearance [CrCL]) on axitinib clearance was evaluated in a population pharmacokinetic model in 207 patients with advanced solid tumors who received a standard axitinib starting dose, and in 383 healthy volunteers. Axitinib safety according to baseline CrCL was assessed in previously treated patients with RCC (n = 350) who received axitinib in the phase 3 AXIS study. RESULTS: Median axitinib clearance was 14.0, 10.7, 12.3, 7.81, and 12.6 L/h, respectively, in individuals with normal renal function (≥90 ml/min; n = 381), mild renal impairment (60-89 ml/min; n = 139), moderate renal impairment (30-59 ml/min; n = 64), severe renal impairment (15-29 ml/min; n = 5), and end-stage renal disease (<15 ml/min; n = 1). The population pharmacokinetic model adequately predicted axitinib clearance in individuals with severe renal impairment or end-stage renal disease. Grade ≥3 adverse events (AEs) were reported in 63 % of patients with normal renal function or mild impairment, 77 % with moderate impairment, and 50 % with severe impairment; study discontinuations due to AEs were 10 %, 11 %, and 0 %, respectively. CONCLUSIONS: Axitinib pharmacokinetics and safety were similar regardless of baseline renal function; no starting-dose adjustment is needed for patients with pre-existing mild to severe renal impairment.

Axitinib plasma pharmacokinetics and ethnic differences.

Axitinib, a potent and selective tyrosine kinase inhibitor of vascular endothelial growth factor receptors 1, 2, and 3, showed improved progression-free survival over sorafenib in patients previously treated for advanced renal cell carcinoma in the AXIS trial. Although a few studies had established the efficacy and safety of axitinib in Asian patients, additional evaluation was necessary to obtain regulatory approval in several Asian countries, especially in light of ethnic differences that are known to exist in genetic polymorphisms for metabolizing enzymes such as cytochrome P450 (CYP) 3A5, CYP2C19 and uridine diphosphate glucuronosyltransferase (UGT) 1A1, which are involved in axitinib metabolism. Axitinib plasma pharmacokinetics following single or multiple administration of oral axitinib in Asian (Japanese or Chinese) healthy subjects as well as Asian patients with advanced solid tumors was compared with that obtained in Caucasians. Upon review, the data demonstrated that axitinib can be characterized as not sensitive to ethnic factors based on its pharmacokinetic and pharmacodynamic properties. Axitinib exhibited similar pharmacokinetics in Asian and non-Asian subjects. A pooled population pharmacokinetic analysis indicated lack of a clinically meaningful effect of ethnicity on axitinib disposition. Therefore, dose adjustment for axitinib on the basis of ethnicity is not currently warranted.

Pharmacokinetics of single-agent axitinib across multiple solid tumor types.

PURPOSE: Axitinib, a potent and selective inhibitor of vascular endothelial growth factor receptors, showed antitumor activity as a single agent against several solid tumor types in Phase II and III trials. This study was conducted to evaluate axitinib pharmacokinetics across a variety of solid tumors. METHODS: The current study analyzed the pharmacokinetics of axitinib in 110 patients with non-small cell lung cancer (NSCLC), thyroid cancer, or melanoma from three Phase II trials plus 127 healthy volunteers, using nonlinear mixed-effects modeling. Boxplots of maximum observed plasma concentration (C max) and area under the plasma concentration-time curve (AUC) of data from these tumor populations was compared to C max and AUC from the final population pharmacokinetic model developed for metastatic renal cell carcinoma (mRCC) to compare axitinib pharmacokinetics across different tumor types. RESULTS: Axitinib disposition based on data from 237 subjects was best described using a two-compartment model with first-order absorption and lag time. Population estimates for systemic clearance, central volume of distribution, absorption rate constant, absolute bioavailability, and lag time were 20.1 L/h, 56.2 L, 1.26/h(-1), 0.663, and 0.448 h, respectively. Statistically significant covariates included gender on clearance, and body weight on central volume of distribution. However, predicted changes due to gender and body weight were found not clinically meaningful. The final analysis indicated that the pharmacokinetic model for mRCC was able to successfully describe axitinib pharmacokinetics in patients with NSCLC, thyroid cancer, and melanoma. CONCLUSION: The pharmacokinetics of axitinib appears to be similar across a variety of tumor types.

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 (Vc ), absorption rate constant (ka ) 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, ka 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 Vc , but the effect was within the estimated interindividual variability for Vc . CONCLUSIONS: The analysis established a model that adequately characterizes axitinib pharmacokinetics in healthy volunteers. Vc 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.

Clinical pharmacology of axitinib.

Axitinib is a potent and selective second-generation inhibitor of vascular endothelial growth factor receptors 1, 2, and 3 that is approved in the US and several other countries for treatment of patients with advanced renal cell carcinoma after failure of one prior systemic therapy. The recommended clinical starting dose of axitinib is 5 mg twice daily, taken with or without food. Dose increase (up to a maximum of 10 mg twice daily) or reduction is permitted based on individual tolerability. Axitinib pharmacokinetics are dose-proportional within 1-20 mg twice daily, which includes the clinical dose range. Axitinib has a short effective plasma half-life (range 2.5-6.1 h), and the plasma accumulation of axitinib is in agreement with what is expected based on the plasma half-life of the drug. Axitinib is absorbed relatively rapidly, reaching maximum observed plasma concentrations (C max) within 4 h of oral administration. The mean absolute bioavailability of axitinib is 58 %. Axitinib is highly (>99 %) bound to human plasma proteins with preferential binding to albumin and moderate binding to α1-acid glycoprotein. In patients with advanced renal cell carcinoma, at the 5-mg twice-daily dose in the fed state, the geometric mean (% coefficient of variation) C max and area under the plasma concentration-time curve (AUC) from time 0-24 h (AUC24) were 27.8 ng/mL (79 %) and 265 ng·h/mL (77 %), respectively. Axitinib is metabolized primarily in the liver by cytochrome P450 (CYP) 3A4/5 and, to a lesser extent (<10 % each), by CYP1A2, CYP2C19, and uridine diphosphate glucuronosyltransferase (UGT) 1A1. The two major human plasma metabolites, M12 (sulfoxide product) and M7 (glucuronide product), are considered pharmacologically inactive. Axitinib is eliminated via hepatobiliary excretion with negligible urinary excretion. Although mild hepatic impairment does not affect axitinib plasma exposures compared with subjects with normal hepatic function, there was a 2-fold increase in AUC from time zero to infinity (AUC∞) following a single 5-mg dose in subjects with moderate hepatic impairment. In the presence of ketoconazole, a strong CYP3A4/5 inhibitor, axitinib C max and AUC∞ increased by 1.5- and 2-fold, respectively, whereas co-administration of rifampin, a strong CYP3A4/5 inducer, resulted in a 71 and 79 % decrease in the C max and AUC∞, respectively. Axitinib does not inhibit CYP3A4/5, CYP1A2, CYP2C8, CYP2A6, CYP2C9, CYP2C19, CYP2D6, CYP2E1, or UGT1A1 at concentrations obtained with the clinical doses and is not expected to have major interactions with drugs that are metabolized by these enzymes. Axitinib is an inhibitor of the efflux transporter P-glycoprotein (P-gp) in vitro, but is not expected to inhibit P-gp at therapeutic plasma concentrations. A two-compartment population pharmacokinetic model with first-order absorption and lag time was used to describe axitinib pharmacokinetics. No clinically relevant effects of age, sex, body weight, race, renal function, UGT1A1 genotype, or CYP2C19 inferred phenotype on the clearance of axitinib were identified.

Axitinib in metastatic renal cell carcinoma: results of a pharmacokinetic and pharmacodynamic analysis.

Axitinib is a potent and selective inhibitor of vascular endothelial growth factor receptors 1, 2, and 3, approved for second-line therapy for advanced renal cell carcinoma (RCC). Axitinib population pharmacokinetic and pharmacokinetic/pharmacodynamic relationships were evaluated. Using nonlinear mixed effects modeling with pooled data from 383 healthy volunteers, 181 patients with metastatic RCC, and 26 patients with other solid tumors in 17 trials, the disposition of axitinib was best described by a 2-compartment model with first-order absorption and a lag time, with estimated mean systemic clearance (CL) of 14.6 L/h and central volume of distribution (V(c)) of 47.3 L. Of 12 covariates tested, age over 60 years and Japanese ethnicity were associated with decreased CL, whereas V(c) increased with body weight. However, the magnitude of predicted changes in exposure based on these covariates does not warrant dose adjustments. Multivariate Cox proportional hazard regression and logistic regression analyses showed that higher exposure and diastolic blood pressure were independently associated with longer progression-free and overall survivals and higher probability of partial response in metastatic RCC patients. These findings support axitinib dose titration to increase plasma exposure in patients who tolerate axitinib, and also demonstrate diastolic blood pressure as a potential marker of efficacy.

Evaluation of the effect of food on the pharmacokinetics of axitinib in healthy volunteers.

PURPOSE: To evaluate the effect of food on axitinib pharmacokinetics in healthy volunteers with two different crystal polymorphs. METHODS: Two separate open-label, randomized, single-dose, three-period, crossover trials were conducted. Study I, conducted first using 5-mg axitinib Form IV film-coated immediate-release (FCIR) tablets, enrolled 18 subjects to compare fed versus fasted states and 24 subjects to evaluate the effect of timing of food consumption on axitinib pharmacokinetics. Study II enrolled 30 subjects to assess the effect of food using 5-mg axitinib Form XLI FCIR tablets. Subjects received axitinib after overnight fasting, with limited fasting or, depending on the study design, after consuming high-fat, high-calorie or moderate-fat, standard-calorie meals. RESULTS: For Form IV FCIR, compared with overnight fasting, axitinib plasma exposure [area under the concentration curve (AUC)] was decreased 23 % when administered with food. For Form XLI FCIR, mean axitinib plasma AUC and maximum plasma concentration (C(max)) were 19 and 11 % higher, respectively, with a high-fat, high-calorie meal compared with overnight fasting. When Form XLI FCIR was administered with moderate-fat, standard-calorie meal, AUC and C(max) were 10 and 16 % lower compared with overnight fasting. Both formulations were well tolerated. Adverse events, mostly gastrointestinal (7 % with Form IV FCIR and 13 % with Form XLI FCIR), were mild to moderate in both studies. CONCLUSIONS: While axitinib Form IV FCIR was associated with higher plasma exposure after overnight fasting, axitinib Form XLI FCIR can be administered with or without food as differences in axitinib pharmacokinetics under the two conditions were not clinically meaningful.

Effect of ketoconazole on the pharmacokinetics of axitinib in healthy volunteers.

OBJECTIVE: Axitinib (AG-013736), an oral, potent, and selective inhibitor of vascular endothelial growth factor receptors 1, 2, and 3, is metabolized primarily by cytochrome P450 (CYP) 3A with minor contributions from CYP1A2, CYP2C19, and glucuronidation. Co-administration with CYP inhibitors may increase systemic exposure to axitinib and alter its safety profile. This study evaluated changes in axitinib plasma pharmacokinetic parameters and assessed safety and tolerability in healthy subjects, following axitinib co-administration with the potent CYP3A inhibitor ketoconazole. METHODS: In this randomized, single-blind, two-way crossover study, 32 healthy volunteers received placebo, followed by a single 5-mg oral dose of axitinib, administered either alone or on the fourth day of dosing with oral ketoconazole (400 mg/day for 7 days). RESULTS: Axitinib exposure was significantly increased in the presence of ketoconazole, with a geometric mean ratio for area under the plasma concentration-time curve from time zero to infinity of 2.06 (90% confidence interval [CI]: 1.84-2.30) and a geometric mean ratio for maximum plasma concentration (C(max)) of 1.50 (90% CI: 1.33-1.70). For axitinib alone or with ketoconazole, C(max) occurred 1.5 and 2.0 h after dosing, respectively. Adverse events were predominantly mild; the most commonly reported treatment-related adverse events were headache and nausea. CONCLUSIONS: Axitinib plasma exposures and peak concentrations were increased following concurrent administration of axitinib and ketoconazole in healthy volunteers. Axitinib alone and in combination with ketoconazole was well tolerated. These findings provide an upper exposure for expected axitinib plasma concentrations in the presence of potent metabolic inhibition.

Pharmacokinetics of sunitinib malate in subjects with hepatic impairment.

This study evaluated the effect of hepatic impairment on the pharmacokinetics of sunitinib and its active metabolite, SU12662. This open-label study enrolled subjects with normal hepatic function (n = 8), mild (Child-Pugh [CP]-A; n = 8), or moderate (CP-B; n = 8) hepatic impairment. Subjects received sunitinib 50 mg as a single oral dose. Mild or moderate hepatic impairment did not significantly alter sunitinib, SU12662, or total drug (TD) systemic exposure. In subjects with normal hepatic function, mild, or moderate hepatic impairment, respectively, TD AUC(0-infinity) was 1,938, 2,002, and 1,999 ng h/ml, TD AUC(0-last) was 1,913, 1,956, and 1,958 ng h/ml, and TD C (max) was 26.0, 27.3, and 26.7 ng/ml. There were no other notable pharmacokinetic differences and sunitinib was well tolerated. The pharmacokinetic findings of this study do not indicate a need to adjust the currently approved starting dose of sunitinib (50 mg daily on Schedule 4/2) for cancer patients with mild to moderate liver impairment.