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Clinical Trial
. 2025 Mar;18(3):e70178.
doi: 10.1111/cts.70178.

Evaluation of Innate Immune System, Body Habitus, and Sex on the Pharmacokinetics and Pharmacodynamics of Anetumab Ravtansine in Patients With Cancer

Affiliations
Clinical Trial

Evaluation of Innate Immune System, Body Habitus, and Sex on the Pharmacokinetics and Pharmacodynamics of Anetumab Ravtansine in Patients With Cancer

Li Chen et al. Clin Transl Sci. 2025 Mar.

Abstract

Anetumab ravtansine, like other ADC drugs, has high inter-patient variability in its pharmacokinetic (PK) and pharmacodynamic (PD) outcomes, which raises concerns about whether current dosing regimens are optimal for patients. The objective of this study was to evaluate covariates, especially body habitus and the innate immune system (IIS), which may affect anetumab ravtansine PK and PD as part of two clinical trials in patients with ovarian cancer and mesothelioma. Biomarkers of Fcγ receptors(FcγR) CD64 on IIS cells, total body weight (TBW), body surface area (BSA), and other covariates, such as sex and age, were analyzed for an association with anetumab ravtansine PK. Higher FcγR CD64, TBW, and BSA were associated with higher clearance (CL) of anetumab ravtansine (p < 0.05). However, there was no relationship between TBW or BSA and FcγR CD64. Female patients had a lower anetumab ravtansine CL (0.030 ± 0.007 L/h) compared to male patients (0.042 ± 0.006 L/h) (p < 0.05). In both studies, patients with stable disease (SD) and partial response (PR) had higher anetumab ravtansine AUC0-inf compared to patients with progressive disease (PD). Individualizing the dose of anetumab ravtansine and potentially other ADCs based only on TBW is not optimal, whereas precision dosing of an ADC based on the inclusion of novel metrics of IIS biomarkers, body habitus, and sex may be more appropriate to reduce variability in PK exposure, reduce toxicity, and improve response.

Keywords: anetumab ravtansine; antibody‐drug conjugate; body habitus; innate immune system; pharmacodynamics; pharmacokinetics; precision dosing.

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Conflict of interest statement

William Zamboni is the founder and CSO of Glolytics LLC, which plans to commercialize biomarkers of the innate immune system. He has also received the following funding related to this study: (1) Duke‐UNC‐Wash NCI UM1 Partnership for Early Phase Clinical Trials in Cancer (UNC Subaward 2036079/5UM1CA186704–05; REVISED PSID 5113372 IPF ID19‐2156); (2) Duke‐UNC‐Wash NCI UM1 Partnership for Early Phase Clinical Trials in Cancer—Biomarker Supplements for Assay Development/Validation and Analysis of Samples (5UM1‐CA186704‐05; PSID 5115121 IPF no. 19‐5629); and (3) UNC Lineberger Comprehensive Cancer Center Developmental Award, which is supported in part by P30 CA016086 Cancer Center Core Support Grant. Aaron Mansfield reports receiving support from Genentech and Janssen for manuscript publication; receiving research support to the institution from Novartis and Verily; receiving honoraria to the institution for participation on advisory boards for AbbVie, AstraZeneca, Bristol‐Myers Squibb, Genentech, Janssen, and Takeda Oncology; serving as a steering committee member for Janssen and Johnson & Johnson Global Services; having speaking engagements from Chugai Pharmaceutical Co. Ltd. (Roche); serving as a grant reviewer for Rising Tide; having expert think tank participation in TRIPTYCH Health Partners; serving as a moderator for Ideology Health LLC (formerly Nexus Health Media); having CME presentation for Intellisphere LLC (OncLive Summit Series) and Answers in CME; having a presentation for Immunocore; serving on the advisory board for Sanofi Genzyme; receiving honoraria to self for CME presentation for Antoni van Leeuwenhoek Kanker Instituut and MJH Life Sciences (OncLive); having presented to the University of Miami International Mesothelioma Symposium; receiving travel support from Roche; serving as a nonremunerated director of the Mesothelioma Applied Research Foundation and a member of the Friends of Patan Hospital Board of Directors; and receiving study funding and article process charges from Bristol‐Myers Squibb. He has been supported by a Mark Foundation ASPIRE Award, Thymic Carcinoma Center Research Award, Department of Defense Concept Award W81XWH‐22‐1‐0021, NCI R21 (CA251923), NCI R33 (CA272271), and NCI U24 (CA283479). The trial 10107 was supported by the NCI grants UM1 CA186709 and UM1 CA186686.

Andrew T. Lucas contributed to this manuscript while employed at the University of North Carolina, Chapel Hill. This manuscript reflects the views of the author and should not be construed to represent his new employer, PumasAI's, views or policies.

Figures

FIGURE 1
FIGURE 1
Relationships between biomarkers of the IIS and metrics of body habitus and anetumab ravtansine plasma CL and Vd in all patients and in study 10107 in patients with mesothelioma, and in study 10150 in patients with ovarian cancer. Panels A and B include the relationships between CD64 and CL and Vd, respectively. Panels C and D include the relationships between TBW and CL and Vd, respectively. Panels E and F include the relationships between TBW and CL and Vd, respectively. The red line represents the linear regression for all patients. The green line and symbols represent linear regression and patients in study 10,107, respectively. The blue line and symbols represent linear regression and patients in study 10150, respectively. Higher FcγR CD64, TBW, and BSA are associated with higher CL and Vd of anetumab ravtansine (p < 0.05).
FIGURE 2
FIGURE 2
The relationship between biomarkers of the IIS and metrics of body habitus and anetumab ravtansine PK exposure in plasma in all patients and in study 10107 in patients with mesothelioma, and in study 10150 in patients with ovarian cancer. Panels A, B, and C include the relationships between CD64 and measured AUC (top = study 10150; bottom = study 10107), AUC dose normalized by mg/kg, and AUC dose normalized by mg, respectively. Panels D, E, and F include the relationships between TBW and measured AUC (top = study 10150; bottom = study 10107), AUC dose normalized by mg/kg, and AUC dose normalized by mg, respectively. Panels G, H, and I include the relationships between BSA and measured AUC (top = study 10150; bottom = study 10107), AUC dose normalized by mg/kg, and AUC dose normalized by mg, respectively. In panels A, D, and G, the top figure is for study 10150, and the bottom figure is for study 10107. In panel A, the results for individual patients (symbols) and the regression line for cycle 1 day 1 and day 8 are presented in red and blue, respectively. In panels D and G top, the individual patient results (symbols) and regression lines for all patients, patients with high TBW (≥ 80 kg), and patients with low TBW (< 80 kg) are presented in black, red, and blue, respectively. In panels D and G bottom, the individual patient results (symbols) and regression lines for all patients and patients with and without capping of the dose are presented in black, blue, and red. In panels B, C, E, F, H, and I, the red line represents the linear regression for all patients. The green line and symbols represent linear regression and patients in study 10107, respectively. The blue line and symbols represent linear regression and patients in study 10150, respectively. There is high PK variability in Anetumab ravtansine AUC when the dose is based on TBW (mg/kg dosing) and in general, patients with higher TBW have higher measured AUC. However, exposure based on administered unit dose (mg) is inversely related to TBW, which suggests larger patients achieve less exposure per administered ADC.
FIGURE 3
FIGURE 3
Relationships between TBW or BSA, FcγR CD64, and anetumab ravtansine CL in all patients and in study 10107 in patients with mesothelioma, and in study 10150 in patients with ovarian cancer. In panels (A) and (C) evaluating the relationship between CD64 and TBW or BSA, the red line represents the linear regression for all patients, the green line and symbols represent linear regression and patients in study 10107, and the blue line and symbols represent the linear regression and patients in study 10150. In these patient groups, there is no relationship between CD64 and TBW or BSA. In panels (B) and (D), the green and blue symbols represent patients in studies 10107 and 10150, respectively. The size of the symbol represents the rank order of anetumab ravtansine CL with larger symbols representing higher CL and smaller symbols representing lower CL. Solid symbol represents female and open symbol represents male. Patients with higher CD64 and higher TBW or higher BSA had higher anetumab ravtansine CL. Around the median TBW or BSA, male patients had higher CL compared to Female patients.
FIGURE 4
FIGURE 4
Relationship between anetumab ravtansine AUC0‐inf and best antitumor response for patients with ovarian cancer (study 10150) and patients with mesothelioma (study 10107). Individual patient results are presented as the open circles. Mean and SD results are presented as the black solid circle and whiskers, respectively. Panel A shows in study 10150, patients with partial response (PR) had higher mean anetumab ravtansine AUC0‐inf than patients with stable disease (SD) and progressive disease (PD) (p = 0.12). Panel B shows in study 10107, patients with PR and SD had higher mean anetumab ravtansine AUC0‐inf than patients with PD (p = 0.27).

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