Antibody-Drug Conjugate (ADC) Design

Computational Exploration of Antibody-Drug Conjugate Pharmacokinetics

World ADC 2016 Best Poster Award!

The pharmacokinetics (PK) of ADCs typically show a discrepancy between the PK of total antibody (conjugated and unconjugated antibody) and that of conjugated antibody, carrying one or more payload molecules.  This discrepancy is often attributed to deconjugation, however recent evidence suggests that the underlying mechanisms may be more complex

This work employs a computational systems pharmacology approach to understand the impact of drug antibody ratio (DAR) and the resulting changes in molecular properties on overall PK and relative payload disposition as observed in preclinical and clinical studies. Our work establishes the benefit of using computational models to design novel ADCs and to optimize the discovery and development of existing ADCs.

  1. Longer mAb half-life reduces payload delivery after multiple doses


  2. ADC half-life affects the percent of payload delivered through different mechanisms, with deconjugation increasing with longer half-life.

The Model

The systems pharmacology model was based on first principles as a system of elementary mass-action, mechanistic PK/PD, ordinary differential equations.  The model mechanisms include ADC binding to target cells, competitive binding of different DAR forms, internalization of ADC and release of payload, plasma deconjugation leading to lower DAR, and plasma elimination of ADCs and free payload.

ADC Model

Simulation results


  1. The model describes the kinetics of individual DAR species and agrees well with typical ADC PK, individual DAR PK, and average DAR measurements in vivo.

  2. The model quantitatively describes the trade-off between higher drug-antibody ratio and lower exposure

  3. Our results show that longer mAb half-life reduces payload delivery after multiple doses

  4. ADC half-life affects the percent of payload delivered through different mechanisms

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