ArticleJournal of pharmacokinetics and pharmacodynamics2010
Modeling the efficacy of trastuzumab-DM1, an antibody drug conjugate, in mice.
Article in Journal of pharmacokinetics and pharmacodynamics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 56 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
56 citing papers in PubMed, 117 citations in OpenAlex.
- Mechanistic modeling of tumor immune microenvironment reveals strategies to enhance antibody-drug conjugates' efficacy.Journal for immunotherapy of cancer · 2026Article
- PK-PD Modeling Suggests Tumor Heterogeneity Limits Preclinical to Clinical Translation of Enzalutamide in Prostate Cancer.Pharmaceutical research · 2026Article
- A missed synthesis from the 1930s: Teorell, Mayneord, and the origins of physiological PK-TGI modelling.Journal of pharmacokinetics and pharmacodynamics · 2026Article
- Applications of Pharmacometrics in Antibody-Drug Conjugate Development.Pharmaceutics · 2026Review
- Practical Pharmacokinetic-Pharmacodynamic Models in Oncology.Pharmaceutics · 2025Review
- Humanized dual-targeting antibody-drug conjugates specific to MET and RON receptors as a pharmaceutical strategy for the treatment of cancers exhibiting phenotypic heterogeneity.Acta pharmacologica Sinica · 2025Article
- QSP modeling of a transiently inactivating antibody-drug conjugate highlights benefit of short antibody half life.Journal of pharmacokinetics and pharmacodynamics · 2024Article
- Understanding tumour growth variability in breast cancer xenograft models identifies PARP inhibition resistance biomarkers.NPJ precision oncology · 2024Article
- Towards a platform quantitative systems pharmacology (QSP) model for preclinical to clinical translation of antibody drug conjugates (ADCs).Journal of pharmacokinetics and pharmacodynamics · 2024Article
- Shifting the Antibody-Drug Conjugate Paradigm: A Trastuzumab-Gold-Based Conjugate Demonstrates High Efficacy against Human Epidermal Growth Factor Receptor 2-Positive Breast Cancer Mouse Model.ACS pharmacology & translational science · 2023Article
- Translation of the efficacy of antibody-drug conjugates from preclinical to clinical using a semimechanistic PK/PD model: A case study with RC88.Clinical and translational science · 2023Article
- Model-based assessment of combination therapies - ranking of radiosensitizing agents in oncology.BMC cancer · 2023Article
- Nucleic acid-triggered tumoral immunity propagates pH-selective therapeutic antibodies through tumor-driven epitope spreading.Cancer science · 2023Article
- Radius additivity score: a novel combination index for tumour growth inhibition in fixed-dose xenograft studies.Frontiers in pharmacology · 2023Article
- Optimized scaling of translational factors in oncology: from xenografts to RECIST.Cancer chemotherapy and pharmacology · 2022Article
- Recent Advances in Translational Pharmacokinetics and Pharmacodynamics Prediction of Therapeutic Antibodies Using Modeling and Simulation.Pharmaceuticals (Basel, Switzerland) · 2022Review
- Exposure-response modeling improves selection of radiation and radiosensitizer combinations.Journal of pharmacokinetics and pharmacodynamics · 2022Article
- A multiscale cell-based model of tumor growth for chemotherapy assessment and tumor-targeted therapy through a 3D computational approach.Cell proliferation · 2022Article
- How translational modeling in oncology needs to get the mechanism just right.Clinical and translational science · 2022Review
- Key metrics to expanding the pipeline of successful antibody-drug conjugates.Trends in pharmacological sciences · 2021Review
Corrections and comments
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Authors and funding
9 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Trastuzumab-DM1 (T-DM1) is a novel antibody-drug conjugate under investigation for the treatment of human epidermal growth factor receptor 2 (HER2)-positive metastatic breast cancer. One challenge in oncologic drug development is determining the optimal dose and treatment schedule. A novel dose regimen-finding strategy was developed for T-DM1 using experimental data and pharmacokinetic/pharmacodynamic modeling. To characterize the disposition of T-DM1, pharmacokinetic studies were conducted in athymic nude and beige nude mice. The pharmacokinetics of T-DM1 were described well by a two-compartment model. Tumor response data were obtained from single-dose, multiple-dose and time-dose-fractionation studies of T-DM1 in animal models of HER2-positive breast cancer, specifically engineered to be insensitive to trastuzumab. A sequential population-based pharmacokinetic/pharmacodynamic modeling approach was developed to describe the anti-tumor activity of T-DM1. A cell-cycle-phase nonspecific tumor cell kill model incorporating transit compartments captured well the features of tumor growth and the activity of T-DM1. Key findings of the model were that tumor cell growth rate played a significant role in the sensitivity of tumors to T-DM1; anti-tumor activity was schedule independent; and tumor response was linked to the ratio of exposure to a concentration required for tumor stasis.
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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.