Tusamitamab
目录号 : GC68358Tusamitamab 是一种靶向 CEACAM5 的 IgG1 单克隆抗体。Tusamitamab 可用于合成 Tusamitamab ravtansine (SAR408701),Tusamitamab ravtansine 是首创的人源化抗体药物偶联物 (ADC),结合了 Tusamitamab 和 DM4 (一种强效美登素衍生物)。
Cas No.:2349294-95-5
Sample solution is provided at 25 µL, 10mM.
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Tusamitamab is an IgG1 monoclonal antibody that targets CEACAM5. Tusamitamab can be used to synthesize Tusamitamab ravtansine (SAR408701), which is a first-in-class humanized antibody-drug conjugate (ADC) that combines Tusamitamab and DM4 (a potent maytansine derivative)[1].
[1]. Clemence Pouzin, et al. Covariate analysis of tusamitamab ravtansine, a DM4 anti-CEACAM5 antibody-drug conjugate, based on first-in-human study. CPT Pharmacometrics Syst Pharmacol. 2022 Mar;11(3):384-394.
Cas No. | 2349294-95-5 | SDF | Download SDF |
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Safety, pharmacokinetics, and antitumor activity of the anti-CEACAM5-DM4 antibody-drug conjugate Tusamitamab ravtansine (SAR408701) in patients with advanced solid tumors: first-in-human dose-escalation study
Ann Oncol 2022 Apr;33(4):416-425.PMID:35026412DOI:10.1016/j.annonc.2021.12.012.
Background: Tusamitamab ravtansine (SAR408701) is an antibody-drug conjugate composed of a humanized monoclonal antibody that binds carcinoembryonic antigen-related cell adhesion molecule-5 (CEACAM5) and a cytotoxic maytansinoid that selectively targets CEACAM5-expressing tumor cells. In this phase I dose-escalation study, we evaluated the safety, pharmacokinetics, and preliminary antitumor activity of Tusamitamab ravtansine in patients with solid tumors. Patients and methods: Eligible patients were aged ≥18 years, had locally advanced/metastatic solid tumors that expressed or were likely to express CEACAM5, and had an Eastern Cooperative Oncology Group Performance Status of 0 or 1. Patients were treated with ascending doses of Tusamitamab ravtansine intravenously every 2 weeks (Q2W). The first three dose levels (5, 10, and 20 mg/m2) were evaluated using an accelerated escalation protocol, after which an adaptive Bayesian procedure was used. The primary endpoint was the incidence of dose-limiting toxicities (DLTs) during the first two cycles, graded using National Cancer Institute Common Terminology Criteria for Adverse Events (NCI CTCAE) v4.03 criteria. Results: Thirty-one patients received Tusamitamab ravtansine (range 5-150 mg/m2). The DLT population comprised 28 patients; DLTs (reversible grade 3 microcystic keratopathy) occurred in three of eight patients treated with Tusamitamab ravtansine 120 mg/m2 and in two of three patients treated with 150 mg/m2. The maximum tolerated dose was identified as 100 mg/m2. Twenty-two patients (71%) experienced ≥1 treatment-related treatment-emergent adverse event (TEAE), seven patients (22.6%) experienced ≥1 treatment-related grade ≥3 TEAE, and three patients (9.7%) discontinued treatment due to TEAEs. The most common TEAEs were asthenia, decreased appetite, keratopathy, and nausea. Three patients had confirmed partial responses. The mean plasma exposure of Tusamitamab ravtansine increased in a dose-proportional manner from 10 to 150 mg/m2. Conclusions: Tusamitamab ravtansine had a favorable safety profile with reversible, dose-related keratopathy as the DLT. Based on the overall safety profile, pharmacokinetic data, and Bayesian model recommendations, the maximum tolerated dose of Tusamitamab ravtansine was defined as 100 mg/m2 Q2W.
Antibodies to watch in 2023
MAbs 2023 Jan-Dec;15(1):2153410.PMID:36472472DOI:10.1080/19420862.2022.2153410.
In this 14th installment of the annual Antibodies to Watch article series, we discuss key events in commercial monoclonal antibody therapeutics development that occurred in 2022 and forecast events that might occur in 2023. As of mid-November, 12 antibody therapeutics had been granted first approvals in either the United States or European Union (tebentafusp (Kimmtrak), faricimab (Vabysmo), sutimlimab (Enjaymo), relatlimab (Opdualag), tixagevimab/cilgavimab (Evusheld), mosunetuzumab (Lunsumio), teclistamab (TECVAYLI), spesolimab (SPEVIGO), tremelimumab (Imjudo; combo with durvalumab), nirsevimab (Beyfortus), mirvetuximab soravtansine (ELAHERE™), and teplizumab (TZIELD)), including 4 bispecific antibodies and 1 ADC. Based on FDA action dates, several additional product candidates could be approved by the end of 2022. An additional seven were first approved in China or Japan in 2022, including two bispecific antibodies (cadonilimab and ozoralizumab). Globally, at least 24 investigational antibody therapeutics are undergoing review by regulatory agencies as of mid-November 2022. Our data show that, with antibodies for COVID-19 excluded, the late-stage commercial clinical pipeline grew by ~20% in the past year to include nearly 140 investigational antibody therapeutics that were designed using a wide variety of formats and engineering techniques. Of those in late-stage development, marketing application submissions for at least 23 may occur by the end of 2023, of which 5 are bispecific (odronextamab, erfonrilimab, linvoseltamab, zanidatamab, and talquetamab) and 2 are ADCs (datopotamab deruxtecan, and Tusamitamab ravtansine).
Covariate analysis of Tusamitamab ravtansine, a DM4 anti-CEACAM5 antibody-drug conjugate, based on first-in-human study
CPT Pharmacometrics Syst Pharmacol 2022 Mar;11(3):384-394.PMID:35191618DOI:10.1002/psp4.12769.
Tusamitamab ravtansine is an anti-CEACAM5 antibody-drug conjugate indicated in patients with solid tumors. Based on a previous developed semimechanistic model describing simultaneously pharmacokinetic (PK) of SAR408701, two of its active metabolites: DM4 and methyl-DM4 and naked antibody, with integration of drug-to-antibody data, the main objective of the present analysis was to evaluate covariate's impact in patients from phase I/II study (n = 254). Demographic and pathophysiologic baseline covariates were explored to explain interindividual variability on each entity PK parameter. Model parameters were estimated with good precision. Five covariates were included in the final PK model: body surface area (BSA), tumor burden, albumin, circulating target, and gender. Comparison of BSA-adjusted dosing and flat dosing supported the current BSA-based dosing regimen, to limit under and over exposure in patients with extreme BSA. Overall, this model characterized accurately the PKs of all entities and highlighted sources of PK variability. By integrating mechanistic considerations, this model aimed to improve understanding of the SAR408701 complex disposition while supporting key steps of clinical development.
Integrated multiple analytes and semi-mechanistic population pharmacokinetic model of Tusamitamab ravtansine, a DM4 anti-CEACAM5 antibody-drug conjugate
J Pharmacokinet Pharmacodyn 2022 Jun;49(3):381-394.PMID:35166967DOI:10.1007/s10928-021-09799-0.
Tusamitamab ravtansine (SAR408701) is an antibody-drug conjugate (ADC), combining a humanized monoclonal antibody (IgG1) targeting carcinoembryonic antigen-related cell adhesion molecule 5 (CEACAM5) and a potent cytotoxic maytansinoid derivative, DM4, inhibiting microtubule assembly. SAR408701 is currently in clinical development for the treatment of advanced solid tumors expressing CEACAM5. It is administered intravenously as a conjugated antibody with an average Drug Antibody Ratio (DAR) of 3.8. During SAR408701 clinical development, four entities were measured in plasma: conjugated antibody (SAR408701), naked antibody (NAB), DM4 and its methylated metabolite (MeDM4), both being active. Average DAR and proportions of individual DAR species were also assessed in a subset of patients. An integrated and semi-mechanistic population pharmacokinetic model describing the time-course of all entities in plasma and DAR measurements has been developed. All DAR moieties were assumed to share the same drug disposition parameters, excepted for clearance which differed for DAR0 (i.e. NAB entity). The conversion of higher DAR to lower DAR resulted in a DAR-dependent ADC deconjugation and was represented as an irreversible first-order process. Each conjugated antibody was assumed to contribute to DM4 formation. All data were fitted simultaneously and the model developed was successful in describing the pharmacokinetic profile of each entity. Such a structural model could be translated to other ADCs and gives insight of mechanistic processes governing ADC disposition. This framework will further be expanded to evaluate covariates impact on SAR408701 pharmacokinetics and its derivatives, and thus can help identifying sources of pharmacokinetic variability and potential efficacy and safety pharmacokinetic drivers.