ArticleJournal of pharmacokinetics and pharmacodynamics2024
Towards a platform quantitative systems pharmacology (QSP) model for preclinical to clinical translation of antibody drug conjugates (ADCs).
Article in Journal of pharmacokinetics and pharmacodynamics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
What it found
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
21 citing papers in PubMed, 25 citations in OpenAlex.
- Quantitative Systems Pharmacology Model for TROP-2 Targeted Antibody-Drug Conjugate in Triple-Negative Breast Cancer.bioRxiv : the preprint server for biology · 2026Article
- From Prediction to Decision Making: PBPK and QSP as Regulatory-Grade NAMs.Clinical pharmacology and therapeutics · 2026Review
- Quantitative Systems Pharmacology (QSP): Bridging Biology and Mechanism with Clinical Drug Development Decisions.Journal of clinical pharmacology · 2026Review
- Clinical Pharmacology and Translational Science Considerations in the Development of Dual-Payload Antibody Drug Conjugates.Clinical and translational science · 2026Review
- Antibody-Drug Conjugates in Oncology: Principles, Clinical Development, and Future Directions.MedComm · 2026Review
- OPTIMIS: Optimizing Personalized Therapies through Integrated Multiscale Intelligent Simulation.bioRxiv : the preprint server for biology · 2026Article
- Review
- AI-driven virtual cell models in preclinical research: technical pathways, validation mechanisms, and clinical translation potential.NPJ digital medicine · 2025Review
- Quantitative Approaches to Accelerate MASH Drug Discovery and Development.Clinical pharmacology and therapeutics · 2025Review
- Practical Pharmacokinetic-Pharmacodynamic Models in Oncology.Pharmaceutics · 2025Review
- Antibody-drug conjugates in cancer therapy: current landscape, challenges, and future directions.Molecular cancer · 2025Review
- Antibody-Drug Conjugates in Breast Cancer: Navigating Innovations, Overcoming Resistance, and Shaping Future Therapies.Biomedicines · 2025Review
- Mechanistic modeling suggests stroma-targeting antibody-drug conjugates as an alternative to cancer-targeting in cases of heterogeneous target exspression.PLoS computational biology · 2025Article
- Oncology Dose Optimization: Tailored Approaches to Different Molecular Classes.Clinical pharmacology and therapeutics · 2025Review
- Modernizing Preclinical Drug Development: The Role of New Approach Methodologies.ACS pharmacology & translational science · 2025Review
- Using mathematical modelling and AI to improve delivery and efficacy of therapies in cancer.Nature reviews. Cancer · 2025Review
- The next frontier in antibody-drug conjugates: challenges and opportunities in cancer and autoimmune therapy.Cancer drug resistance (Alhambra, Calif.) · 2025Review
- Virtual patient analysis identifies strategies to improve the performance of predictive biomarkers for PD-1 blockade.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Mathematical Modeling Unveils Optimization Strategies for Targeted Radionuclide Therapy of Blood Cancers.Cancer research communications · 2024Article
- An industry perspective on current QSP trends in drug development.Journal of pharmacokinetics and pharmacodynamics · 2024Article
Corrections and comments
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Authors and funding
8 authors at 2 institutions in 2 countries.
Funding
Abstract
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.