A mechanistic model of ADC-induced thrombocytopenia for predicting therapeutic index



  • Off-target hematotoxicity has been reported in the clinic for many antibody-drug conjugates (ADCs); toxicity can limit the maximum tolerated dose in the clinic.
  • A mechanistic model of hematopoiesis was developed to describe thrombocytopenia post Trastuzumab-emtansine (T-DM1) administration, but could be generalized to other hematopoietic diseases and other therapeutics.
  • Combining efficacy (see our other poster) and toxicity models allows us to explore common therapeutic metrics, such as therapeutic window and indexes.

Conclusions & Future Directions


  • A mechanistic model of hematopoiesis can simulate variable platelet dynamics in response to ADC administration. Variabilty could be due to patients' diesease status or previous therapeutic administration. 
  • Our model uses parameters informed by biological measurements rather than emperical parameters, like in the semi-mechanistic “Friberg” model.
  • A therapeutic window can be predicted by combining efficacy and toxicity models, which can be used to explore different outputs that act on different time scales.
  • While T-DM1 has a high TI index, our studies show the importance of strategically selecting particular time points for evaluating efcacy and toxicity to understand the full picture.

The model is built so that different drug effect mechanisms can be included!

Next Steps:

  • Create a virtual population of patients to identify subpopulations that could benefit from fractionated or alternative dosing regimens.
  • Validate model on larger datasets (hundreds to thousands of patients)
  • Assess the model’s ability to scale from in vitro → cyno → human.


Download the Poster