Towards a platform quantitative systems pharmacology (QSP) model for preclinical to clinical translation of antibody-drug conjugates (ADCs)
Abstract
Background
ADCs form a therapeutic class that has demonstrated immense potential for transformative clinical responses in several types of cancers. Due to their complexity, however, predicting clinical properties remains a challenge. The mAb, linker, and payload all need to be optimized for a particular tumor target, indication, and patient population.. More importantly, traditional approaches can be misleading when considered in isolation, and several notable clinical ADC failures have been reported in recent years.
A mechanistic model of ADC-induced thrombocytopenia for predicting therapeutic index
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Abstract
Background
- 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 therapeut
A platform quantitative systems pharmacology (QSP) model for preclinical to clinical translation of ADCs and clinical evaluation of thrombocytopenia
Abstract
Background
- Predicting clinical ADC efficacy and toxicity is a challenge.
Towards a platform quantitative systems pharmacology (QSP) model for preclinical to clinical translation of antibody drug conjugates (ADCs)
Published in Journal of Pharmacokinetics and Pharmacodynamics