Kinetic Modeling of the Antibody Disulfide Bond Reduction Reaction With Integrated Prediction of the Drug Load...

Antibody-drug conjugates (ADC) constitute a groundbreaking advancement in the field of targeted therapy. In the widely utilized cysteine conjugation, the cytotoxic payload is attached to reduced interchain disulfides which involves a reduction of the native monoclonal antibody (mAb). This reaction needs to be thoroughly understood and controlled as it influences the critical quality attributes (CQAs) of the final ADC product, such as the drug-to-antibody ratio (DAR) and the drug load distribution (DLD). However, existing methodologies lack a mechanistic description of the relationship between process parameters and CQAs. In this context, kinetic modeling provides comprehensive reaction understanding, facilitating the model-based optimization of reduction reaction parameters and potentially reduces the experimental effort needed to develop a robust process. With this study, we introduce an integrated modeling framework consisting of a reduction kinetic model for the species formed during the mAb reduction reaction in combination with a regression model to quantify the number of conjugated drugs by DAR and DLD. The species formed during reduction will be measured by analytical capillary gel electrophoresis (CGE), and the DAR and DLD will be derived from reversed-phase (RP) chromatography. First, we present the development of a reduction kinetic model to describe the impact of reducing agent excess and reaction temperature on the kinetic, by careful investigation of different reaction networks and sets of kinetic rates. Second, we introduce a cross-analytical approach based on multiple linear regression (MLR), wherein CGE data is converted into the RP-derived DAR/DLD. By coupling this with the newly developed reduction kinetic model, an integrated model encompassing the two consecutive reaction steps, reduction and conjugation, is created to predict the final DAR/DLD from initial reduction reaction conditions. The integrated model is finally utilized for an in silico screening to analyze the effect of the reduction conditions, TCEP excess, temperature and reaction time, directly on the final ADC product.