Towards a platform quantitative systems pharmacology (QSP) model for preclinical to clinical translation of antibody drug conjugates (ADCs)

A next generation multiscale quantitative systems pharmacology (QSP) model for antibody drug conjugates (ADCs) is presented, for preclinical to clinical translation of ADC efficacy. Two HER2 ADCs (trastuzumab-DM1 and trastuzumab-DXd) were used for model development, calibration, and validation. The...

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Bibliographic Details
Published in:	Journal of pharmacokinetics and pharmacodynamics Vol. 51; no. 5; pp. 429 - 447
Main Authors:	Scheuher, Bruna, Ghusinga, Khem Raj, McGirr, Kimiko, Nowak, Maksymilian, Panday, Sheetal, Apgar, Joshua, Subramanian, Kalyanasundaram, Betts, Alison
Format:	Journal Article
Language:	English
Published:	New York Springer US 01-10-2024 Springer Nature B.V
Subjects:	Antibodies Biochemistry Biomedical and Life Sciences Biomedical Engineering and Bioengineering Biomedicine ErbB-2 protein Metastases Original Paper Pharmacokinetics Pharmacology/Toxicology Pharmacy Translation Trastuzumab Tumors Veterinary Medicine/Veterinary Science Kadcyla Enhertu Oncology HER2 Quantitative systems pharmacology Antibody drug conjugate
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Summary:	A next generation multiscale quantitative systems pharmacology (QSP) model for antibody drug conjugates (ADCs) is presented, for preclinical to clinical translation of ADC efficacy. Two HER2 ADCs (trastuzumab-DM1 and trastuzumab-DXd) were used for model development, calibration, and validation. The model integrates drug specific experimental data including in vitro cellular disposition data, pharmacokinetic (PK) and tumor growth inhibition (TGI) data for T-DM1 and T-DXd, as well as system specific data such as properties of HER2, tumor growth rates, and volumes. The model incorporates mechanistic detail at the intracellular level, to account for different mechanisms of ADC processing and payload release. It describes the disposition of the ADC, antibody, and payload inside and outside of the tumor, including binding to off-tumor, on-target sinks. The resulting multiscale PK model predicts plasma and tumor concentrations of ADC and payload. Tumor payload concentrations predicted by the model were linked to a TGI model and used to describe responses following ADC administration to xenograft mice. The model was translated to humans and virtual clinical trial simulations were performed that successfully predicted progression free survival response for T-DM1 and T-DXd for the treatment of HER2+ metastatic breast cancer, including differential efficacy based upon HER2 expression status. In conclusion, the presented model is a step toward a platform QSP model and strategy for ADCs, integrating multiple types of data and knowledge to predict ADC efficacy. The model has potential application to facilitate ADC design, lead candidate selection, and clinical dosing schedule optimization.
Bibliography:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23
ISSN:	1567-567X 1573-8744 1573-8744
DOI:	10.1007/s10928-023-09884-6