Prediction of CYP Down Regulation after Tusamitamab Ravtansine Administration (a DM4-Conjugate), Based on an In Vitro-In Vivo Extrapolation Approach.

Tusamitamab ravtansine is an antibody-drug conjugate (ADC) composed of a humanized monoclonal antibody (IgG1) and DM4 payload. Even if DM4 and its main metabolite methyl-DM4 (Me-DM4) circulate at low concentrations after ADC administration, their potential as perpetrators of cytochrome P450 mediated drug-drug interaction was assessed. In vitro studies in human hepatocytes indicated that Me-DM4 elicited a clear concentration-dependent down regulation of cytochrome P450 enzymes (CYP3A4, 1A2, and 2B6). Because DM4 was unstable under the incubation conditions studied, the in vitro constants could not be determined for this entity. Thus, to predict the clinical relevance of this observed downregulation, an in vitro-in vivo extrapolation (IVIVE) pharmacokinetic (PK) based approach was developed. To mitigate model prediction errors and because of their similar inhibitory effect on tubulin polymerization, the same downregulation constants were used for DM4 and Me-DM4. This approach describes the time course of decreasing CYP3A4, 1A2, and 2B6 enzyme amounts as a function of circulating concentrations of DM4 and Me-DM4 predicted from a population PK model. The developed IVIVE-PK model showed that the highest CYP abundance decrease was observed for CYP3A4, with a transient reduction of < 10% from baseline. The impact on midazolam exposure, as probe substrate of CYP3A, was then simulated based on a physiologically-based PK static method. The maximal CYP3A4 abundance reduction was associated with a predicted midazolam area under the curve (AUC) ratio of 1.14. To conclude, the observed in vitro downregulation of CYPs by Me-DM4 is not expected to have relevant clinical impact.

A multi-model approach to predict efficacious clinical dose for an anti-TGF-ß antibody (GC2008) in the treatment of osteogenesis imperfecta.

Osteogenesis imperfecta (OI) is a heterogeneous group of inherited bone dysplasias characterized by reduced skeletal mass and bone fragility. Although the primary manifestation of the disease involves the skeleton, OI is a generalized connective tissue disorder that requires a multidisciplinary treatment approach. Recent studies indicate that application of a transforming growth factor beta (TGF-ß) neutralizing antibody increased bone volume fraction (BVF) and strength in an OI mouse model and improved bone mineral density (BMD) in a small cohort of patients with OI. In this work, we have developed a multitiered quantitative pharmacology approach to predict human efficacious dose of a new anti-TGF-ß antibody drug candidate (GC2008). This method aims to translate GC2008 pharmacokinetic/pharmacodynamic (PK/PD) relationship in patients, using a number of appropriate mathematical models and available preclinical and clinical data. Compartmental PK linked with an indirect PD effect model was used to characterize both pre-clinical and clinical PK/PD data and predict a GC2008 dose that would significantly increase BMD or BVF in patients with OI. Furthermore, a physiologically-based pharmacokinetic model incorporating GC2008 and the body's physiological properties was developed and used to predict a GC2008 dose that would decrease the TGF-ß level in bone to that of healthy individuals. By using multiple models, we aim to reveal information for different aspects of OI disease that will ultimately lead to a more informed dose projection of GC2008 in humans. The different modeling efforts predicted a similar range of pharmacologically relevant doses in patients with OI providing an informed approach for an early clinical dose setting.

Covariate analysis of tusamitamab ravtansine, a DM4 anti-CEACAM5 antibody-drug conjugate, based on first-in-human study.

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.

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.