PRO-1107

Nonsmall cell lung cancer (NSCLC) presents significant therapeutic challenges, causing advancements in targeted therapies. We have developed a site-selective antibody-drug conjugate (ADC), durvalumab-monomethyl auristatin E (MMAE), with a drug-antibody ratio (DAR) of 4, specifically targeting programmed death-ligand 1 (PD-L1), aimed at enhancing NSCLC therapy. Utilizing the innovative AbClick Pro linker, this ADC ensures stable, site-specific conjugation of MMAE to durvalumab, preserving antibody functionality and integrity. In vivo studies demonstrate that durvalumab-MMAE achieves substantial tumor growth inhibition in NSCLC xenograft models, with an impressive tumor growth inhibition rate of over 60% at lower dosages without significant toxicity. These results, combined with a favorable pharmacokinetic profile featuring extended half-life and low clearance, highlight the potential of durvalumab-MMAE (DAR4) as a potent next-generation ADC for treating PD-L1-expressing cancers, offering a promising avenue for improved NSCLC patient outcomes.

The objective of this work was to develop a translational physiologically-based pharmacokinetic (PBPK) model for antibody-drug conjugates (ADCs), using monomethyl auristatin E (MMAE)-based ADCs. A previously established dual-structured whole-body PBPK model for MMAE-based ADCs in mice was scaled to higher species (i.e., rats and monkeys) and humans. Species-specific physiological and drug-related parameters for the payload and antibody backbone of ADCs were obtained from literature. Parameters associated with payload release, including the deconjugation rate, were optimized using an allometric scaling approach, and antibody degradation rate was adjusted to account for the enhanced clearance of ADCs due to conjugation across different species. The translational PBPK model predicted the PK profiles for various ADC analytes in rats, monkeys, and humans reasonably well. The optimized PBPK model suggested decreased rate of deconjugation for ADCs in higher species, whereas the effects of payload conjugation on ADC clearance were more pronounced in higher species and humans. The translational PBPK model presented here may enable prediction of different ADC analyte PK at the site-of-action, offering valuable insights for the development of exposure-response relationships for ADCs. The modeling framework presented here can also serve as a platform for the development of PBPK model for other ADCs.