Capturing the Magic Bullet: Pharmacokinetic Principles and Modeling of Antibody-Drug Conjugates

Over the past two decades, antibody-drug conjugates (ADCs) have emerged as a promising class of drugs for cancer therapy and have expanded to nononcology fields such as inflammatory diseases, atherosclerosis, and bacteremia. Eight ADCs are currently approved by FDA for clinical applications, with more novel ADCs under clinical development. Compared with traditional chemotherapy, ADCs combine the target specificity of antibodies with chemotherapeutic capabilities of cytotoxic drugs. The benefits include reduced systemic toxicity and enhanced therapeutic index for patients. However, the heterogeneous structures of ADCs and their dynamic changes following administration create challenges in their development. The understanding of ADC pharmacokinetics (PK) is crucial for the optimization of clinical dosing regimens when translating from animal to human. In addition, it contributes to the optimization of dose selection and clinical monitoring with regard to safety and efficacy. This manuscript reviews the PK characteristics of ADCs and summarizes the diverse approaches for PK modeling that can be used to evaluate an ADC at the preclinical and clinical stages to support their successful development. Despite the numerous available options, fit-for-purpose modeling approaches for the PK and PD of ADCs should be critically planned and well-thought-out to adequately support the development of an ADC.