Population pharmacokinetics of bevacizumab in cancer patients with external validation

Han, Kelong; Peyret, Thomas; Marchand, Mathilde; Quartino, Angelica; Gosselin, Nathalie; Girish, Sandhya; Allison, David E.; Jin, Jin

doi:10.1007/s00280-016-3079-6

Cited by 55 publications

(46 citation statements)

References 29 publications

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“…All covariates included in the final PopPK model for 23 mAbs, including the PK structural model, were summarized from the literature review (Table ) . The effect of covariates was evaluated specifically for the linear portion of CL for mAbs exhibiting linear or parallel linear and nonlinear CL.…”

Section: Resultsmentioning

confidence: 99%

Evaluation of covariate effects on pharmacokinetics of monoclonal antibodies in oncology

Bajaj

Suryawanshi

Roy

et al. 2019

Brit J Clinical Pharma

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Aims The development of monoclonal antibodies (mAbs) requires an understanding of the interindividual variability (IIV) in pharmacokinetics (PK) at the population level facilitated by population PK (PopPK) modelling. However, there is no clear rationale for selecting which covariates to screen during PopPK model development. Here, we compare the effect of covariates on PK parameters for mAbs in oncology and identify the most commonly used covariates affecting PK parameters. Methods All 25 mAbs approved for therapeutic use in oncology until December 2017 by the Food and Drug Administration and the European Medicines Agency were selected for study. Literature searches revealed 23 available PopPK models for these mAbs. To understand the magnitude and types of covariate effect on PK parameters, all covariates included in the final PopPK model for each mAb were summarized. Results The most commonly identified covariates were baseline body weight (BW; 17 mAbs), baseline serum albumin (8 mAbs), and sex (7 mAbs) on clearance; and BW (16 mAbs) and sex (12 mAbs) on central volume of distribution. A reduced PopPK model was developed for nivolumab and ipilimumab using these covariates, and the percentage of explained IIV from the reduced model (20.3% and 16.8%, respectively) was compared with that from the full model (24.5% and 27.9%, respectively). Conclusions This analysis provides a uniform platform for selecting covariates and suggests that the effect of BW, albumin and sex should be included during the development of PopPK models for mAbs in oncology. The reduced model was able to explain IIV to a similar extent as the full model.

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Section: Resultsmentioning

confidence: 99%

Evaluation of covariate effects on pharmacokinetics of monoclonal antibodies in oncology

Bajaj

Suryawanshi

Roy

et al. 2019

Brit J Clinical Pharma

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“…Sex differences in pharmacokinetics have also been noted for monoclonal antibodies, e.g. panitumumab or bevacizumab, with the clearance being reduced by roughly 20% in women [48,64] and for some tyrosine kinase inhibitors, such as sunitinib and imatinib [65,66]. For other molecules, the absence of acknowledged sex differences in pharmacokinetics may be the consequence of either insufficient investigation or lack of statistical power in available studies rather than true non-existence.…”

Section: Sex Differences In the Pharmacology Of Anticancer Drugsmentioning

confidence: 99%

Gender medicine and oncology: report and consensus of an ESMO workshop

et al. 2019

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Background: The importance of sex and gender as modulators of disease biology and treatment outcomes is well known in other disciplines of medicine, such as cardiology, but remains an undervalued issue in oncology. Considering the increasing evidence for their relevance, European Society for Medical Oncology decided to address this topic and organized a multidisciplinary workshop in Lausanne, Switzerland, on 30 November and 1 December 2018. Design: Twenty invited faculty members and 40 selected physicians/scientists participated. Relevant content was presented by faculty members on the basis of a literature review conducted by each speaker. Following a moderated consensus session, the final consensus statements are reported here. Results: Clinically relevant sex differences include tumour biology, immune system activity, body composition and drug disposition and effects. The main differences between male and female cells are sex chromosomes and the level of sexual hormones they are exposed to. They influence both local and systemic determinants of carcinogenesis. Their effect on carcinogenesis in non-reproductive organs is largely unknown. Recent evidence also suggests differences in tumour biology and molecular markers. Regarding body composition, the difference in metabolically active, fat-free body mass is one of the most prominent: in a man and a woman of equal weight and height, it accounts for 80% of the man's and 65% of the woman's body mass, and is not taken into account in body-surface area based dosing of chemotherapy. Conclusion: Sex differences in cancer biology and treatment deserve more attention and systematic investigation. Interventional clinical trials evaluating sex-specific dosing regimens are necessary to improve the balance between efficacy and toxicity for drugs with significant pharmacokinetic differences. Especially in diseases or disease subgroups with significant differences in epidemiology or outcomes, men and women with non-sex-related cancers should be considered as biologically distinct groups of patients, for whom specific treatment approaches merit consideration.

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“…Based on reported population PK analyses of reference bevacizumab [11,12] and the observed bi-exponential serum concentration-time profiles of PF-06439535 and reference bevacizumab in Study B7391001 [7], a two-compartment structural PK model with zero-order input (constant-rate IV infusion) and first-order elimination from the central compartment was used as the starting structural model. Since body weight was a significant covariate impacting both clearance (CL) and central volume of distribution (V 1 ) in previous analyses of reference bevacizumab [11,12], and administration of PF-06439535 or bevacizumab-EU was normalized for body weight (i.e., 15 mg/kg in Study B7391003), the effect of body weight on CL and V 1 was incorporated into the structural model to improve model stability.…”

Section: Base Model and Random-effects Model Developmentmentioning

confidence: 99%

Population pharmacokinetic modeling of PF-06439535 (a bevacizumab biosimilar) and reference bevacizumab (Avastin®) in patients with advanced non-squamous non-small cell lung cancer

Sweeney

Cronenberger

2019

Cancer Chemother Pharmacol

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The objectives of this analysis were to characterize the population pharmacokinetics (PK) of PF-06439535 (a bevacizumab biosimilar) and reference bevacizumab (Avastin ®) sourced from the European Union (bevacizumab-EU) in patients with advanced non-squamous non-small cell lung cancer (NSCLC), and to quantify the difference in PK parameters between the two drug products via covariate analysis. Methods Pooled PF-06439535 and bevacizumab-EU serum concentration data from a comparative clinical efficacy and safety study (NCT02364999) in patients with NSCLC (N = 719) were analyzed using a non-linear mixed-effects modeling approach. Patients received PF-06439535 plus chemotherapy or bevacizumab-EU plus chemotherapy every 21 days for 4-6 cycles, followed by monotherapy with PF-06439535 or bevacizumab-EU. PF-06439535 or bevacizumab-EU was administered intravenously at a dose of 15 mg/kg. Effects of patient and disease covariates, as well as the drug product (PF-06439535 versus bevacizumab-EU), on PK were investigated. Results Overall, 8632 serum bevacizumab concentrations from 351 patients in the PF-06439535 group and 354 patients in the bevacizumab-EU group were included in the analysis. A two-compartment model adequately described the combined data. Clearance (CL) and central volume of distribution (V 1) estimates were 0.0113 L/h and 2.99 L for a typical 71-kg female patient with NSCLC administered bevacizumab-EU. CL and V 1 increased with body weight and were higher in males than females even after accounting for differences in body weight. The 95% confidence intervals for the effect of drug product on CL and V 1 encompassed unity. Conclusions The population PK of PF-06439535 and bevacizumab-EU were well characterized by a two-compartment model. Covariate analysis did not reveal any appreciable differences between PK parameters for PF-06439535 and bevacizumab-EU in patients with NSCLC. Clinical trial registration ClinicalTrials.gov, NCT02364999.

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Population pharmacokinetics of bevacizumab in cancer patients with external validation

Cited by 55 publications

References 29 publications

Evaluation of covariate effects on pharmacokinetics of monoclonal antibodies in oncology

Evaluation of covariate effects on pharmacokinetics of monoclonal antibodies in oncology

Gender medicine and oncology: report and consensus of an ESMO workshop

Population pharmacokinetic modeling of PF-06439535 (a bevacizumab biosimilar) and reference bevacizumab (Avastin®) in patients with advanced non-squamous non-small cell lung cancer

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