Modeling the efficacy of trastuzumab-DM1, an antibody drug conjugate, in mice

Jumbe, Nelson L.; Xin, Yan; Leipold, Douglas D.; Crocker, Lisa; Dugger, Debra; Mai, Elaine; Sliwkowski, Mark X.; Fielder, Paul J.; Tibbitts, Jay

doi:10.1007/s10928-010-9156-2

Cited by 119HER2/EGFR in Cancer ResearchMonoclonal and Polyclonal Antibodies ResearchMathematical Biology Tumor Growth

Modeling the efficacy of trastuzumab-DM1, an antibody drug conjugate, in mice

Jumbe, Nelson L., Xin, Yan, Leipold, Douglas D., Crocker, Lisa, Dugger, Debra, Mai, Elaine, Sliwkowski, Mark X., Fielder, Paul J. +1 more·2010·Journal of Pharmacokinetics and Pharmacodynamics

DOI 10.1007/s10928-010-9156-2

Open this paper in CoChat — free account

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.

Integrity signals

Registry

Crossref · 10.1007/s10928-010-9156-2

Cites

35 of 35 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Jumbe et al. developed a population-based semi-mechanistic PK/PD model to describe T-DM1 antitumor activity by consolidating the exposure-effect relationship determined across multiple animal models.
“The authors developed a population‐based semi‐mechanistic PK/PD model to describe the T‐DM1 antitumor activity by consolidating the exposure–effect relationship determined across multiple animal models.”
From Tutorial on monoclonal antibody pharmacokinetics and its considerations in early development (2018) · cites this paper as [79]
The treatment regimen, targeted exposure parameters, and tumoristatic concentration for T-DM1 were derived from the model to support early clinical trial design.
“Subsequently, the treatment regimen, targeted exposure parameters (AUC, Cmax, or time above minimal concentration threshold), and tumoristatic concentration were derived from the model to support early clinical trial design.”
From Tutorial on monoclonal antibody pharmacokinetics and its considerations in early development (2018) · cites this paper as [79]

Radiobiology for the Radiologist.
(1974) · Annals of Internal Medicine · doi:10.7326/0003-4819-80-3-438_1 · Cited by 3,498 · see citing works
Efficacy and Safety of Trastuzumab as a Single Agent in First-Line Treatment of HER2-Overexpressing Metastatic Breast Cancer
Vogel, C. L., Cobleigh, M., Tripathy, D., Gutheil, J. C., Harris, L. N., Fehrenbacher, L., Slamon, D. J., Murphy, M., Novotny, W. F., Burchmore, M., et al. (2002) · Journal of Clinical Oncology · doi:10.1200/jco.20.3.719 · Cited by 3,240 · see citing works
Physiological Parameters in Laboratory Animals and Humans
Davies, B., & Morris, T. (1993) · Pharmaceutical Research · doi:10.1023/a:1018943613122 · Cited by 2,930 · see citing works
Efficacy and Safety of Trastuzumab as a Single Agent in First-Line Treatment of <i>HER2</i>-Overexpressing Metastatic Breast Cancer
Vogel, C. L., Cobleigh, M. A., Tripathy, D., Gutheil, J. C., Harris, L. N., Fehrenbacher, L., Slamon, D. J., Murphy, M., Novotny, W. F., Burchmore, M., et al. (2002) · Journal of Clinical Oncology · doi:10.1200/jco.2002.20.3.719 · Cited by 1,860 · see citing works
Targeting HER2-Positive Breast Cancer with Trastuzumab-DM1, an Antibody–Cytotoxic Drug Conjugate
Phillips, G. D. L., Li, G., Dugger, D. L., Crocker, L., Parsons, K. L., Mai, E., Blättler, W. A., Lambert, J. M., Chari, R. V. J., Lutz, R. J., et al. (2008) · Cancer Research · doi:10.1158/0008-5472.can-08-1776 · Cited by 1,679 · see citing works
Self-citation
Radiobiology for the Radiologist
Fry, R. J. M., & Hall, E. J. (1995) · Radiation Research · doi:10.2307/3579017 · Cited by 1,351 · see citing works
Mechanisms of Disease: understanding resistance to HER2-targeted therapy in human breast cancer
Nahta, R., Yu, D., Hung, M., Hortobágyi, G. N., & Esteva, F. J. (2006) · Nature Clinical Practice Oncology · doi:10.1038/ncponc0509 · Cited by 916 · see citing works
Predictive Pharmacokinetic-Pharmacodynamic Modeling of Tumor Growth Kinetics in Xenograft Models after Administration of Anticancer Agents
Simeoni, M., Magni, P., Cammia, C., Nicolao, G. D., Croci, V., Pesenti, E. A., Germani, M., Poggesi, I., & Rocchetti, M. (2004) · Cancer Research · doi:10.1158/0008-5472.can-03-2524 · Cited by 509 · see citing works
Resistance to Trastuzumab in Breast Cancer
Pohlmann, P. R., Mayer, I. A., & Mernaugh, R. L. (2009) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-09-0636 · Cited by 506 · see citing works
Understanding the Mechanisms Behind Trastuzumab Therapy for Human Epidermal Growth Factor Receptor 2–Positive Breast Cancer
Spector, N. L., & Blackwell, K. (2009) · Journal of Clinical Oncology · doi:10.1200/jco.2009.22.1507 · Cited by 497 · see citing works
Simultaneous vs. Sequential Analysis for Population PK/PD Data I: Best-Case Performance
Zhang, L., Beal, S. L., & Sheiner, L. B. (2003) · Journal of Pharmacokinetics and Pharmacodynamics · doi:10.1023/b:jopa.0000012998.04442.1f · Cited by 372 · see citing works
Results of Two Open-Label, Multicenter Phase II Studies of Docetaxel, Platinum Salts, and Trastuzumab in HER2-Positive Advanced Breast Cancer
Pegram, M. D., Pieńkowski, T., Northfelt, D., EIERMANN, W., Patel, R., Fumoleau, P., Quan, E., Crown, J. P., Toppmeyer, D., Smylie, M., et al. (2004) · JNCI Journal of the National Cancer Institute · doi:10.1093/jnci/djh133 · Cited by 270 · see citing works
Immunoconjugates containing novel maytansinoids: promising anticancer drugs.
CHARI, R. V. J., Martell, B., Gross, J. L., Cook, S., Shah, S. A., Blättler, W. A., McKenzie, S. J., & Goldmacher, V. S. (1992) · PubMed · Cited by 266 · see citing works
Sentinel Node Tumor Burden According to the Rotterdam Criteria Is the Most Important Prognostic Factor for Survival in Melanoma Patients
van Akkooi, A. C. J., Nowecki, Z. I., Voit, C. A., Schäfer-Hesterberg, G., Michej, W., de Wilt, J. H. W., Rutkowski, P. L., Verhoef, C. K., & Eggermont, A. M. M. (2008) · Annals of Surgery · doi:10.1097/sla.0b013e31818fefe0 · Cited by 253 · see citing works
Integrating pharmacology and in vivo cancer models in preclinical and clinical drug development
Peterson, J. K., & Houghton, P. J. (2004) · European Journal of Cancer · doi:10.1016/j.ejca.2004.01.003 · Cited by 223 · see citing works
Azithromycin: 3-Day Versus 5-Day Course in the Treatment of Respiratory Tract Infections in Children
Ficnar, B., Huzjak, N., Oreskovic, K., Matrapazovski, M., & Klinar, I. (1997) · Journal of Chemotherapy · doi:10.1179/joc.1997.9.1.38 · Cited by 202 · see citing works
Pharmacodynamic modeling of time-dependent transduction systems
Mager, D. E. (2001) · Clinical Pharmacology & Therapeutics · doi:10.1067/mcp.2001.118244 · Cited by 144 · see citing works
Pharmacodynamic modeling of chemotherapeutic effects: Application of a transit compartment model to characterize methotrexate effects in vitro
Lobo, E. D., & Balthasar, J. P. (2002) · AAPS PharmSci · doi:10.1208/ps040442 · Cited by 127 · see citing works
Simultaneous vs. Sequential Analysis for Population PK/PD Data II: Robustness of Methods
Zhang, L., Beal, S. L., & Sheiner, L. B. (2003) · Journal of Pharmacokinetics and Pharmacodynamics · doi:10.1023/b:jopa.0000012999.36063.4e · Cited by 109 · see citing works
What Do We Really Know About Antibiotic Pharmacodynamics?
Gunderson, B. W., Ross, G. H., Ibrahim, K. H., & Rotschafer, J. C. (2001) · Pharmacotherapy The Journal of Human Pharmacology and Drug Therapy · doi:10.1592/phco.21.18.302s.33905 · Cited by 102 · see citing works
Predicting the active doses in humans from animal studies: A novel approach in oncology
Rocchetti, M., Simeoni, M., Pesenti, E. A., Nicolao, G. D., & Poggesi, I. (2007) · European Journal of Cancer · doi:10.1016/j.ejca.2007.05.011 · Cited by 101 · see citing works
A mathematical model of breast and ovarian cancer treated with paclitaxel
Panetta, J. C. (1997) · Mathematical Biosciences · doi:10.1016/s0025-5564(97)00077-1 · Cited by 95 · see citing works
A mathematical model to study the effects of drugs administration on tumor growth dynamics
Magni, P., Simeoni, M., Poggesi, I., Rocchetti, M., & Nicolao, G. D. (2006) · Mathematical Biosciences · doi:10.1016/j.mbs.2005.12.028 · Cited by 85 · see citing works
Stochastic Gompertz model of tumour cell growth
Lo, C. (2007) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2007.04.024 · Cited by 66 · see citing works
A phase II study of trastuzumab-DM1 (T-DM1), a HER2 antibody-drug conjugate (ADC), in patients (pts) with HER2+ metastatic breast cancer (MBC): Final results
Vogel, C. L., Burris, H. A., Limentani, S. A., Borson, R. A., O’Shaughnessy, J., Vukelja, S. J., Agresta, S., Klencke, B. J., Birkner, M., & Rugo, H. S. (2009) · Journal of Clinical Oncology · doi:10.1200/jco.2009.27.15_suppl.1017 · Cited by 63 · see citing works
Phase II Trial of Gemcitabine plus Trastuzumab in Metastatic Breast Cancer Patients Previously Treated with Chemotherapy: Preliminary Results
O’Shaughnessy, J., Vukelja, S. J., Marsland, T., Kimmel, G. T., Ratnam, S., & Pippen, J. (2002) · Clinical Breast Cancer · doi:10.3816/cbc.2002.s.004 · Cited by 53 · see citing works
Investigation of various growth mechanisms of solid tumour growth within the linear-quadratic model for radiotherapy
McAneney, H., & O'Rourke, S. F. C. (2007) · Physics in Medicine and Biology · doi:10.1088/0031-9155/52/4/012 · Cited by 49 · see citing works
A phase I study of trastuzumab-DM1 (T-DM1), a first-in-class HER2 antibody-drug conjugate (ADC), in patients (pts) with advanced HER2+ breast cancer (BC)
Beeram, M., Burris, H. A., Modi, S., Birkner, M., Girish, S., Tibbitts, J., Holden, S. N., Lutzker, S. G., & Krop, I. E. (2008) · Journal of Clinical Oncology · doi:10.1200/jco.2008.26.15_suppl.1028 · Cited by 48 · see citing works
Self-citation
A unified model of sigmoid tumour growth based on cell proliferation and quiescence
Kozusko, F., & Bourdeau, M. (2007) · Cell Proliferation · doi:10.1111/j.1365-2184.2007.00474.x · Cited by 44 · see citing works
Blood volume in inbred strain BALB/c, CBA/J and C57BL/10 mice determined by means of 59Fe-labelled red cells and 59Fe bound to transferrin.
Vácha, J. (1975) · PubMed · Cited by 35 · see citing works
A Pharmacokinetic‐Pharmacodynamic Model for Predicting Tumour Growth Inhibition in Mice: A Useful Tool in Oncology Drug Development
Rocchetti, M., Poggesi, I., Germani, M., Fiorentini, F., Pellizzoni, C., Zugnoni, P., Pesenti, E. A., Simeoni, M., & Nicolao, G. D. (2005) · Basic & Clinical Pharmacology & Toxicology · doi:10.1111/j.1742-7843.2005.pto960325.x · Cited by 32 · see citing works
Sentinel Node Tumor Burden According to the Rotterdam Criteria Is the Most Important Prognostic Factor for Survival in Melanoma Patients
Hatef, D. A., & Hollier, L. H. (2009) · Journal of Craniofacial Surgery · doi:10.1097/scs.0b013e3181b17655 · Cited by 22 · see citing works
A phase I study of weekly dosing of trastuzumab-DM1 (T-DM1) in patients with advanced HER2+ breast cancer.
Krop, I. E., Mita, M. M., Burris, H., Birkner, M., Girish, S., Tibbitts, J., Holden, S. N., Lutzker, S. G., & Modi, S. (2009) · Cancer Research · doi:10.1158/0008-5472.sabcs-3136 · Cited by 12 · see citing works
Self-citation
Prognostic Role of Tumor Size in Childhood Cancer
Favini, F., Sultan, I. Y., Meazza, C., Casanova, M., & Ferrari, A. (2009) · Future Oncology · doi:10.2217/fon.09.124 · Cited by 5 · see citing works
Long-Term Outcomes in Stage IIIB Breast Cancer Patients Who Achieved Less Than a Pathological Complete Response (<pCR) After Primary Chemotherapy
Ionta, M. T., Atzori, F., Deidda, M. C., Pusceddu, V., PALMERI, S., Frau, B., Murgia, M., Barca, M., Minerba, L., & Massidda, B. (2009) · The Oncologist · doi:10.1634/theoncologist.2009-0077 · Cited by 4 · see citing works

Flagged first, then by citations

Sorted by citations

Efficacy and safety of neoadjuvant pertuzumab and trastuzumab in women with locally advanced, inflammatory, or early HER2-positive breast cancer (NeoSphere): a randomised multicentre, open-label, phase 2 trial
Gianni, L., Pieńkowski, T., Im, Y., Roman, L., Tseng, L., Liu, M.-C., Lluch, A. M., Starosławska, E., de la Haba-Rodríguez, J., Im, S., et al. (2011) · The Lancet Oncology · doi:10.1016/s1470-2045(11)70336-9 · Cited by 2,387 · see citing works
Ado-trastuzumab Emtansine (T-DM1): An Antibody–Drug Conjugate (ADC) for HER2-Positive Breast Cancer
Lambert, J. M., & Chari, R. V. J. (2014) · Journal of Medicinal Chemistry · doi:10.1021/jm500766w · Cited by 545 · see citing works
Tutorial on monoclonal antibody pharmacokinetics and its considerations in early development
Ovacik, M., & Lin, K. (2018) · Clinical and Translational Science · doi:10.1111/cts.12567 · Cited by 299 · see citing works
New developments for antibody-drug conjugate-based therapeutic approaches
de Goeij, B. E., & Lambert, J. M. (2016) · Current Opinion in Immunology · doi:10.1016/j.coi.2016.02.008 · Cited by 254 · see citing works
Implementation of pharmacokinetic and pharmacodynamic strategies in early research phases of drug discovery and development at Novartis Institute of Biomedical Research
Tuntland, T., Ethell, B., Kosaka, T., Blasco, F., Zang, R. X., Jain, M., Gould, T., & Hoffmaster, K. (2014) · Frontiers in Pharmacology · doi:10.3389/fphar.2014.00174 · Cited by 239 · see citing works
Pharmacokinetics, Pharmacodynamics and Physiologically-Based Pharmacokinetic Modelling of Monoclonal Antibodies
Dostálek, M., Gardner, I. B., Gurbaxani, B. M., Rose, R. H., & Chetty, M. (2013) · Clinical Pharmacokinetics · doi:10.1007/s40262-012-0027-4 · Cited by 231 · see citing works
The Preclinical Profile of the Duocarmycin-Based HER2-Targeting ADC SYD985 Predicts for Clinical Benefit in Low HER2-Expressing Breast Cancers
van der Lee, M. M. C., Groothuis, P. G., Ubink, R., van der Vleuten, M. A. J., van Achterberg, T. A. E., Loosveld, E. M., Damming, D., Jacobs, D. C. H., Rouwette, M., Egging, D. F., et al. (2015) · Molecular Cancer Therapeutics · doi:10.1158/1535-7163.mct-14-0881-t · Cited by 201 · see citing works
The Effect of Different Linkers on Target Cell Catabolism and Pharmacokinetics/Pharmacodynamics of Trastuzumab Maytansinoid Conjugates
Erickson, H. K., Phillips, G. D. L., Leipold, D. D., Provenzano, C. A., Mai, E., Johnson, H. A., Gunter, B., Audette, C. A., Gupta, M., Pinkas, J., et al. (2012) · Molecular Cancer Therapeutics · doi:10.1158/1535-7163.mct-11-0727 · Cited by 194 · see citing works
Self-citation
Preclinical Profile of the HER2-Targeting ADC SYD983/SYD985: Introduction of a New Duocarmycin-Based Linker-Drug Platform
Dokter, W. H. A., Ubink, R., van der Lee, M. M. C., van der Vleuten, M. A. J., van Achterberg, T. A. E., Jacobs, D. C. H., Loosveld, E. M., van den Dobbelsteen, D., Egging, D. F., Mattaar, E., et al. (2014) · Molecular Cancer Therapeutics · doi:10.1158/1535-7163.mct-14-0040-t · Cited by 165 · see citing works
Bench to bedside translation of antibody drug conjugates using a multiscale mechanistic PK/PD model: a case study with brentuximab-vedotin
Shah, D. K., Haddish‐Berhane, N., & Betts, A. M. (2012) · Journal of Pharmacokinetics and Pharmacodynamics · doi:10.1007/s10928-012-9276-y · Cited by 160 · see citing works
Pharmacokinetic Considerations for Antibody Drug Conjugates
Lin, K., & Tibbitts, J. (2012) · Pharmaceutical Research · doi:10.1007/s11095-012-0800-y · Cited by 136 · see citing works
Self-citation
CDK4/6 inhibition provides a potent adjunct to Her2-targeted therapies in preclinical breast cancer models
Witkiewicz, A. K., Cox, D., & Knudsen, E. S. (2014) · Genes & Cancer · doi:10.18632/genesandcancer.24 · Cited by 121 · see citing works
Antibody–Drug Conjugates: Pharmacokinetic/Pharmacodynamic Modeling, Preclinical Characterization, Clinical Studies, and Lessons Learned
Hedrich, W. D., Fandy, T. E., Ashour, H. M., Wang, H., & Hassan, H. E. (2017) · Clinical Pharmacokinetics · doi:10.1007/s40262-017-0619-0 · Cited by 102 · see citing works
The antibody-drug conjugate: an enabling modality for natural product-based cancer therapeutics
Gerber, H., Koehn, F. E., & Abraham, R. T. (2013) · Natural Product Reports · doi:10.1039/c3np20113a · Cited by 97 · see citing works
Correction: CDK4/ 6 inhibition provides a potent adjunct to Her2- targeted therapies in preclinical breast cancer models
Witkiewicz, A. K., Cox, D., & Knudsen, E. S. (2021) · Genes & Cancer · doi:10.18632/genesandcancer.211 · Cited by 93 · see citing works
A Mechanistic Pharmacokinetic Model Elucidating the Disposition of Trastuzumab Emtansine (T-DM1), an Antibody–Drug Conjugate (ADC) for Treatment of Metastatic Breast Cancer
Bender, B. C., Leipold, D. D., Xu, K., Shen, B., Tibbitts, J., & Friberg, L. E. (2014) · The AAPS Journal · doi:10.1208/s12248-014-9618-3 · Cited by 85 · see citing works
Self-citation
Determination of Cellular Processing Rates for a Trastuzumab-Maytansinoid Antibody-Drug Conjugate (ADC) Highlights Key Parameters for ADC Design
Maass, K. F., Kulkarni, C., Betts, A. M., & Wittrup, K. D. (2016) · The AAPS Journal · doi:10.1208/s12248-016-9892-3 · Cited by 85 · see citing works
On translation of antibody drug conjugates efficacy from mouse experimental tumors to the clinic: a PK/PD approach
Haddish‐Berhane, N., Shah, D. K., Ma, D., Leal, M., Gerber, H., Sapra, P., Barton, H. A., & Betts, A. M. (2013) · Journal of Pharmacokinetics and Pharmacodynamics · doi:10.1007/s10928-013-9329-x · Cited by 79 · see citing works
Developing Exposure/Response Models for Anticancer Drug Treatment: Special Considerations
Mould, D., Walz, A., Lavé, T., Gibbs, J., & Frame, B. (2015) · CPT Pharmacometrics & Systems Pharmacology · doi:10.1002/psp4.16 · Cited by 75 · see citing works
Pharmacokinetic and Immunological Considerations for Expanding the Therapeutic Window of Next-Generation Antibody–Drug Conjugates
Khera, E., & Thurber, G. M. (2018) · BioDrugs · doi:10.1007/s40259-018-0302-5 · Cited by 72 · see citing works
Clinical Implications of Pathophysiological and Demographic Covariates on the Population Pharmacokinetics of Trastuzumab Emtansine, a HER2‐Targeted Antibody‐Drug Conjugate, in Patients With HER2‐Positive Metastatic Breast Cancer
Gupta, M., LoRusso, P. M., Wang, B., Yi, J., Burris, H. A., Beeram, M., Modi, S., Chu, Y., Agresta, S. V., Klencke, B. J., et al. (2011) · The Journal of Clinical Pharmacology · doi:10.1177/0091270011403742 · Cited by 71 · see citing works
Application of Pharmacokinetic-Pharmacodynamic Modeling and Simulation for Antibody-Drug Conjugate Development
Singh, A. P., Shin, Y. G., & Shah, D. K. (2015) · Pharmaceutical Research · doi:10.1007/s11095-015-1626-1 · Cited by 70 · see citing works
Preclinical to Clinical Translation of Antibody-Drug Conjugates Using PK/PD Modeling: a Retrospective Analysis of Inotuzumab Ozogamicin
Betts, A. M., Haddish‐Berhane, N., Tolsma, J., Jasper, P., King, L. E., Sun, Y. S., Subramanyam, C., Shor, B., Boni, J. P., & Johnson, T. R. (2016) · The AAPS Journal · doi:10.1208/s12248-016-9929-7 · Cited by 64 · see citing works
Bioorthogonal strategies for site-directed decoration of biomaterials with therapeutic proteins
Braun, A. C., Gutmann, M., Lühmann, T. C., & Meinel, L. (2018) · Journal of Controlled Release · doi:10.1016/j.jconrel.2018.01.018 · Cited by 57 · see citing works
Cardio-oncology in targeting the HER receptor family: the puzzle of different cardiotoxicities of HER2 inhibitors.
Albini, A., Cesana, E., Donatelli, F., Cammarota, R., Bucci, E., Baravelli, M., Anza', C., & Noonan, D. (2011) · Future Cardiology · doi:10.2217/fca.11.54 · Cited by 47 · see citing works
Mathematical modeling of tumor growth and tumor growth inhibition in oncology drug development
Bernard, A., Kimko, H. H. C., Mital, D. P., & Poggesi, I. (2012) · Expert Opinion on Drug Metabolism & Toxicology · doi:10.1517/17425255.2012.693480 · Cited by 53 · see citing works
Altering Antibody–Drug Conjugate Binding to the Neonatal Fc Receptor Impacts Efficacy and Tolerability
Hamblett, K. J., Le, T., Rock, B. M., Rock, D. A., Siu, S., Huard, J. N., Conner, K. P., Milburn, R. R., O’Neill, J., Tometsko, M. E., et al. (2016) · Molecular Pharmaceutics · doi:10.1021/acs.molpharmaceut.6b00153 · Cited by 52 · see citing works
Application of a PK-PD Modeling and Simulation-Based Strategy for Clinical Translation of Antibody-Drug Conjugates: a Case Study with Trastuzumab Emtansine (T-DM1)
Singh, A. P., & Shah, D. K. (2017) · The AAPS Journal · doi:10.1208/s12248-017-0071-y · Cited by 48 · see citing works
Fractionated Dosing Improves Preclinical Therapeutic Index of Pyrrolobenzodiazepine-Containing Antibody Drug Conjugates
Hinrichs, M. J., Ryan, P. M., Zheng, B., Afif-Rider, S., Xiang, Y., Gunsior, M., Zhong, H., Harper, J. W., Bezabeh, B. Z., Vashisht, K., et al. (2017) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-17-0219 · Cited by 48 · see citing works
Evolution of Antibody-Drug Conjugate Tumor Disposition Model to Predict Preclinical Tumor Pharmacokinetics of Trastuzumab-Emtansine (T-DM1)
Singh, A. P., Maass, K. F., Betts, A. M., Wittrup, K. D., Kulkarni, C., King, L. E., Khot, A., & Shah, D. K. (2016) · The AAPS Journal · doi:10.1208/s12248-016-9904-3 · Cited by 44 · see citing works
Controlled pharmacokinetic anti-cancer drug concentration profiles lead to growth inhibition of colorectal cancer cells in a microfluidic device
Komen, J., Westerbeek, E. Y., Kolkman, R. W., Roesthuis, J., Lievens, C., van den Berg, A., & van der Meer, A. D. (2020) · Lab on a Chip · doi:10.1039/d0lc00419g · Cited by 45 · see citing works
Modeling of human tumor xenografts and dose rationale in oncology
Simeoni, M., Nicolao, G. D., Magni, P., Rocchetti, M., & Poggesi, I. (2012) · Drug Discovery Today Technologies · doi:10.1016/j.ddtec.2012.07.004 · Cited by 41 · see citing works
Multiscale modeling of tumor growth and angiogenesis: Evaluation of tumor-targeted therapy
Nivlouei, S. J., Soltani, M., Carvalho, J., Travasso, R. D. M., Salimpour, M. R., & Shirani, E. (2021) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1009081 · Cited by 42 · see citing works
Towards a platform quantitative systems pharmacology (QSP) model for preclinical to clinical translation of antibody drug conjugates (ADCs)
Scheuher, B., Ghusinga, K. R., McGirr, K., Nowak, M., Panday, S., Apgar, J. F., Subramanian, K., & Betts, A. M. (2023) · Journal of Pharmacokinetics and Pharmacodynamics · doi:10.1007/s10928-023-09884-6 · Cited by 39 · see citing works
Model‐Informed Development and Registration of a Once‐Daily Regimen of Extended‐Release Tofacitinib
Lamba, M., Hutmacher, M., Furst, D. E., Dikranian, A. H., Dowty, M. E., Conrado, D. J., Stock, T. B., Nduaka, C. I., Cook, J., & Krishnaswami, S. (2016) · Clinical Pharmacology & Therapeutics · doi:10.1002/cpt.576 · Cited by 38 · see citing works
Key metrics to expanding the pipeline of successful antibody–drug conjugates
Nessler, I., Menezes, B., & Thurber, G. M. (2021) · Trends in Pharmacological Sciences · doi:10.1016/j.tips.2021.07.005 · Cited by 36 · see citing works
Onartuzumab (MetMAb): Using Nonclinical Pharmacokinetic and Concentration–Effect Data to Support Clinical Development
Xiang, H., Bender, B. C., Reyes, A. E., Merchant, M. A., Jumbe, N. L. ‘., Romero, M., Davancaze, T., Nijem, I., Mai, E., Young, J. C., et al. (2013) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-13-0260 · Cited by 35 · see citing works
Self-citation
Using the Lessons Learned From the Clinic to Improve the Preclinical Development of Antibody Drug Conjugates
Jackson, D., & Stover, D. R. (2014) · Pharmaceutical Research · doi:10.1007/s11095-014-1536-7 · Cited by 34 · see citing works
Recent Advances in Translational Pharmacokinetics and Pharmacodynamics Prediction of Therapeutic Antibodies Using Modeling and Simulation
Haraya, K., Tsutsui, H., Komori, Y., & Tachibana, T. (2022) · Pharmaceuticals · doi:10.3390/ph15050508 · Cited by 35 · see citing works
Increment in Drug Loading on an Antibody–Drug Conjugate Increases Its Binding to the Human Neonatal Fc Receptor in Vitro
Brachet, G., Respaud, R., Arnoult, C., Henriquet, C., Dhommée, C., Viaud‐Massuard, M., Heuzé‐Vourc'h, N., Joubert, N., Pugnière, M., & Gouilleux‐Gruart, V. (2016) · Molecular Pharmaceutics · doi:10.1021/acs.molpharmaceut.6b00082 · Cited by 33 · see citing works
An Agent-Based Systems Pharmacology Model of the Antibody-Drug Conjugate Kadcyla to Predict Efficacy of Different Dosing Regimens
Menezes, B., Cilliers, C., Wessler, T., Thurber, G. M., & Linderman, J. J. (2020) · The AAPS Journal · doi:10.1208/s12248-019-0391-1 · Cited by 33 · see citing works
Efficacy of Anti-RON Antibody Zt/g4–Drug Maytansinoid Conjugation (Anti-RON ADC) as a Novel Therapeutics for Targeted Colorectal Cancer Therapy
Feng, L., Yao, H., Wang, W., Zhou, Y.-Q., Zhou, J., Zhang, R., & Wang, M. (2014) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-14-0898 · Cited by 33 · see citing works
Quantitative Translational Modeling to Facilitate Preclinical to Clinical Efficacy & Toxicity Translation in Oncology
Zhu, A. (2018) · Future Science OA · doi:10.4155/fsoa-2017-0152 · Cited by 33 · see citing works
Mechanistic pharmacokinetic/pharmacodynamic modeling of in vivo tumor uptake, catabolism, and tumor response of trastuzumab maytansinoid conjugates
Wada, R., Erickson, H. K., Phillips, G. D. L., Provenzano, C. A., Leipold, D. D., Mai, E., Johnson, H. A., & Tibbitts, J. (2014) · Cancer Chemotherapy and Pharmacology · doi:10.1007/s00280-014-2561-2 · Cited by 30 · see citing works
Self-citation
Preclinical and clinical pharmacokinetic/pharmacodynamic considerations for antibody–drug conjugates
Sapra, P., Betts, A. M., & Boni, J. P. (2013) · Expert Review of Clinical Pharmacology · doi:10.1586/17512433.2013.827405 · Cited by 30 · see citing works
Development and Translational Application of an Integrated, Mechanistic Model of Antibody-Drug Conjugate Pharmacokinetics
Sukumaran, S., Zhang, C., Leipold, D. D., Saad, O. M., Xu, K., Gadkar, K. G., Samineni, D., Wang, B., Milojic-Blair, M., Carrasco‐Triguero, M., et al. (2016) · The AAPS Journal · doi:10.1208/s12248-016-9993-z · Cited by 27 · see citing works
Self-citation
Preclinical Efficacy of Anti-RON Antibody–Drug Conjugate Zt/g4-MMAE for Targeted Therapy of Pancreatic Cancer Overexpressing RON Receptor Tyrosine Kinase
Yao, H., Feng, L., Weng, T.-H., Hu, C. W., Suthe, S. R., Mostofa, A., Chen, L., Wu, Z., Wang, W., & Wang, M. (2018) · Molecular Pharmaceutics · doi:10.1021/acs.molpharmaceut.8b00298 · Cited by 26 · see citing works
Preclinical Efficacy and Safety Assessment of an Antibody–Drug Conjugate Targeting the c-RET Proto-Oncogene for Breast Carcinoma
Nguyen, M., Miyakawa, S., Kato, J., Mori, T., Arai, T., Armanini, M. P., Gelmon, K. A., Yerushalmi, R., Leung, S. C. Y., Gao, D., et al. (2015) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-15-0468 · Cited by 26 · see citing works
Therapeutic efficacy, pharmacokinetic profiles, and toxicological activities of humanized antibody-drug conjugate Zt/g4-MMAE targeting RON receptor tyrosine kinase for cancer therapy
Yao, H., Feng, L., Suthe, S. R., Chen, L., Weng, T.-H., Hu, C. W., Jun, E. S., Wu, Z., Wang, W., Kim, S. C., et al. (2019) · Journal for ImmunoTherapy of Cancer · doi:10.1186/s40425-019-0525-0 · Cited by 25 · see citing works
A Mechanism-Based PK/PD Model for Hematological Toxicities Induced by Antibody-Drug Conjugates
Ait‐Oudhia, S., Zhang, W., & Mager, D. E. (2017) · The AAPS Journal · doi:10.1208/s12248-017-0113-5 · Cited by 24 · see citing works
Use of translational modeling and simulation for quantitative comparison of PF-06804103, a new generation HER2 ADC, with Trastuzumab-DM1
Betts, A. M., Clark, T. H., Jasper, P., Tolsma, J., van der Graaf, P. H., Graziani, E. I., Rosfjord, E. C., Sung, M. S., Ma, D., & Barletta, F. (2020) · Journal of Pharmacokinetics and Pharmacodynamics · doi:10.1007/s10928-020-09702-3 · Cited by 24 · see citing works
Modeling Tumor Growth in Oncology
Bonate, P. L. (2011) · Springer eBooks · doi:10.1007/978-1-4419-7937-7_1 · Cited by 23 · see citing works
Antibody-Drug Conjugates
Kumar, A., White, J. B., Christie, R. J., Dimasi, N., & Gao, C. (2017) · Annual reports in medicinal chemistry · doi:10.1016/bs.armc.2017.08.002 · Cited by 22 · see citing works
Tumor Static Concentration Curves in Combination Therapy
Cardilin, T., Almquist, J. O., Jirstrand, M., Sostelly, A., Amendt, C., Bawab, S. E., & Gabrielsson, J. (2016) · The AAPS Journal · doi:10.1208/s12248-016-9991-1 · Cited by 21 · see citing works
Current mathematical models for cancer drug discovery
Carrara, L., Lavezzi, S. M., Borella, E., Nicolao, G. D., Magni, P., & Poggesi, I. (2017) · Expert Opinion on Drug Discovery · doi:10.1080/17460441.2017.1340271 · Cited by 21 · see citing works
Analytical techniques for the characterization of Antibody Drug Conjugates: Challenges and prospects
Neupane, R., & Bergquist, J. (2017) · European Journal of Mass Spectrometry · doi:10.1177/1469066717733919 · Cited by 21 · see citing works
Aberrant RON and MET Co-overexpression as Novel Prognostic Biomarkers of Shortened Patient Survival and Therapeutic Targets of Tyrosine Kinase Inhibitors in Pancreatic Cancer
Hu, C. W., Xu, X., Hong, B., Wu, Z., Qian, Y., Weng, T.-H., Liu, Y., Tang, T.-M., Wang, M., & Yao, H. (2019) · Frontiers in Oncology · doi:10.3389/fonc.2019.01377 · Cited by 20 · see citing works
DHA Affects Microtubule Dynamics Through Reduction of Phospho-TCTP Levels and Enhances the Antiproliferative Effect of T-DM1 in Trastuzumab-Resistant HER2-Positive Breast Cancer Cell Lines
D’Amico, S., Krasnowska, E. K., Manni, I., Toietta, G., Baldari, S., Piaggio, G., Ranalli, M., Gambacurta, A., Vernieri, C., Giacinto, F. D., et al. (2020) · Cells · doi:10.3390/cells9051260 · Cited by 20 · see citing works
Therapeutic evaluation of monoclonal antibody-maytansinoid conjugate as a model of RON-targeted drug delivery for pancreatic cancer treatment.
Yao, H., Feng, L., Zhou, J., Zhang, R., & Wang, M. (2016) · PubMed Central · Cited by 19 · see citing works
PK/PD Mediated Dose Optimization of Emactuzumab, a CSF1R Inhibitor, in Patients With Advanced Solid Tumors and Diffuse‐Type Tenosynovial Giant Cell Tumor
Smart, K. A., Bröske, A.-M. E., Rüttinger, D., Mueller, C., Phipps, A., Walz, A., Ries, C. H., Baehner, M., Cannarile, M. A., & Meneses‐Lorente, G. (2020) · Clinical Pharmacology & Therapeutics · doi:10.1002/cpt.1964 · Cited by 19 · see citing works
Modelling of tumour growth and cytotoxic effect of docetaxel in xenografts
Evans, N. D., Dimelow, R. J., & Yates, J. W. T. (2013) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2013.06.014 · Cited by 19 · see citing works
Biological evaluation of antibody-maytansinoid conjugates as a strategy of RON targeted drug delivery for treatment of non-small cell lung cancer
Feng, L., Yao, H., Sharma, S., Zhou, Y.-Q., Zhou, J., Zhang, R., & Wang, M. (2016) · Journal of Experimental & Clinical Cancer Research · doi:10.1186/s13046-016-0347-6 · Cited by 19 · see citing works
Correction to: Therapeutic efficacy, pharmacokinetic profiles, and toxicological activities of humanized antibody-drug conjugate Zt/g4-MMAE targeting RON receptor tyrosine kinase for cancer therapy
Yao, H., Feng, L., Suthe, S. R., Chen, L., Weng, T.-H., Hu, C. W., Jun, E. S., Wu, Z., Wang, W., Kim, S. C., et al. (2019) · Journal for ImmunoTherapy of Cancer · doi:10.1186/s40425-019-0571-7 · Cited by 19 · see citing works
Recent advances in physiologically based pharmacokinetic and pharmacodynamic models for anticancer nanomedicines
Byun, J. H., Han, D., Cho, H., Yoon, I., & Jung, I. H. (2020) · Archives of Pharmacal Research · doi:10.1007/s12272-020-01209-2 · Cited by 18 · see citing works
Integration of Bioanalytical Measurements Using PK–PD Modeling and Simulation: Implications for Antibody–Drug Conjugate Development
Khot, A., Sharma, S., & Shah, D. K. (2015) · Bioanalysis · doi:10.4155/bio.15.85 · Cited by 16 · see citing works
A multiscale cell‐based model of tumor growth for chemotherapy assessment and tumor‐targeted therapy through a 3D computational approach
Nivlouei, S. J., Soltani, M., Shirani, E., Salimpour, M. R., Travasso, R. D. M., & Carvalho, J. (2022) · Cell Proliferation · doi:10.1111/cpr.13187 · Cited by 17 · see citing works
Issues, challenges, and opportunities in model-based drug development for monoclonal antibodies
Hu, L., & Hansen, R. J. (2013) · Journal of Pharmaceutical Sciences · doi:10.1002/jps.23504 · Cited by 16 · see citing works
Translational PK/PD framework for antibody-drug conjugates to inform drug discovery and development
Liao, M. Z., Leipold, D. D., Chen, S., Li, Z., Kamath, A. V., & Li, C. (2024) · Xenobiotica · doi:10.1080/00498254.2024.2351044 · Cited by 15 · see citing works
Self-citation
Translational Model-Based Strategy to Guide the Choice of Clinical Doses for Antibody-Drug Conjugates
Bouillon‐Pichault, M., Brillac, C., Amara, C., Nicolazzi, C., Fagniez, N., Fau, J., Koiwai, K., Ziti‐Ljajic, S., & Veyrat‐Follet, C. (2017) · The Journal of Clinical Pharmacology · doi:10.1002/jcph.869 · Cited by 15 · see citing works
Humanized dual-targeting antibody–drug conjugates specific to MET and RON receptors as a pharmaceutical strategy for the treatment of cancers exhibiting phenotypic heterogeneity
Wang, M., Ma, Q., Suthe, S. R., Hudson, R. E., Pan, J.-Y., Mikelis, C. M., Zhu, M., Wu, Z., Shi, D., & Yao, H. (2025) · Acta Pharmacologica Sinica · doi:10.1038/s41401-024-01458-7 · Cited by 14 · see citing works
Systems pharmacology and enhanced pharmacodynamic models for understanding antibody-based drug action and toxicity
Ait‐Oudhia, S., Ovacik, M., & Mager, D. E. (2016) · mAbs · doi:10.1080/19420862.2016.1238995 · Cited by 14 · see citing works
Comparison of classical tumour growth models for patient derived and cell-line derived xenografts using the nonlinear mixed-effects framework
Voulgarelis, D., Bulusu, K. C., & Yates, J. W. T. (2022) · Journal of Biological Dynamics · doi:10.1080/17513758.2022.2061615 · Cited by 14 · see citing works
Pattern Recognition in Pharmacodynamic Data Analysis
Gabrielsson, J., & Hjorth, S. (2015) · The AAPS Journal · doi:10.1208/s12248-015-9842-5 · Cited by 14 · see citing works
Modeling long-term tumor growth and kill after combinations of radiation and radiosensitizing agents
Cardilin, T., Almquist, J., Jirstrand, M., Zimmermann, A., Lignet, F., el Bawab, S., & Gabrielsson, J. (2019) · Cancer Chemotherapy and Pharmacology · doi:10.1007/s00280-019-03829-y · Cited by 11 · see citing works
Opportunities for Quantitative Translational Modeling in Oncology
Yates, J. W. T., Byrne, H. M., Chapman, S. C., Chen, T., Cucurull-Sanchez, L., Delgado-SanMartin, J. A., Veroli, G. Y. D., Dovedi, S. J., Dunlop, C. M., Jena, R., et al. (2020) · Clinical Pharmacology & Therapeutics · doi:10.1002/cpt.1963 · Cited by 12 · see citing works
Mixture dynamics: Combination therapy in oncology
Gabrielsson, J., Gibbons, F. D., & Peletier, L. A. (2016) · European Journal of Pharmaceutical Sciences · doi:10.1016/j.ejps.2016.02.020 · Cited by 13 · see citing works
ADME and DMPK considerations for the discovery and development of antibody drug conjugates (ADCs)
Beaumont, K. C., Pike, A., Davies, M., Savoca, A., Vasalou, C., Harlfinger, S., Ramsden, D., Ferguson, D., Hariparsad, N., Jones, O., et al. (2022) · Xenobiotica · doi:10.1080/00498254.2022.2141667 · Cited by 12 · see citing works
Death receptor 5 agonistic antibody PRO95780: preclinical pharmacokinetics and concentration–effect relationship support clinical dose and regimen selection
Xiang, H., Reyes, A. E., Eppler, S., Kelley, S. K., & Damico‐Beyer, L. A. (2013) · Cancer Chemotherapy and Pharmacology · doi:10.1007/s00280-013-2200-3 · Cited by 12 · see citing works
Typical Antibody–Drug Conjugates
Lambert, J. M. (2016) · doi:10.1002/9781119060727.ch1 · Cited by 12 · see citing works
Trastuzumab emtansine in advanced human epidermal growth factor receptor 2-positive breast cancer
den Mooter, T. V., Teuwen, L.-A. M. N., Rutten, A., & Dirix, L. Y. (2015) · Expert Opinion on Biological Therapy · doi:10.1517/14712598.2015.1036026 · Cited by 9 · see citing works
Trastuzumab emtansine in breast cancer
Dirix, L. Y., Rutten, A., Huget, P., & Dirix, M. (2013) · Expert Opinion on Biological Therapy · doi:10.1517/14712598.2013.778238 · Cited by 8 · see citing works
Translation of the efficacy of antibody–drug conjugates from preclinical to clinical using a semimechanistic PK / PD model: A case study with RC88
Li, Q., Wang, L., Zhang, J., Zhao, G., Liu, Z., Ma, X., & Jiang, J. (2023) · Clinical and Translational Science · doi:10.1111/cts.13526 · Cited by 7 · see citing works
Mathematical modeling of antibody drug conjugates with the target and tubulin dynamics to predict AUC
Byun, J. H., & Jung, I. H. (2018) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2018.01.028 · Cited by 7 · see citing works
How translational modeling in oncology needs to get the mechanism just right
Yates, J. W. T., & Fairman, D. A. (2021) · Clinical and Translational Science · doi:10.1111/cts.13183 · Cited by 6 · see citing works
Dose finding by concentration-response versus dose-response: a simulation-based comparison
Berges, A., & Chen, C. (2013) · European Journal of Clinical Pharmacology · doi:10.1007/s00228-013-1474-z · Cited by 7 · see citing works
Lifespan Based Pharmacokinetic-Pharmacodynamic Model of Tumor Growth Inhibition by Anticancer Therapeutics
Mo, G., Gibbons, F., Schroeder, P. E., & Krzyżański, W. (2014) · PLoS ONE · doi:10.1371/journal.pone.0109747 · Cited by 7 · see citing works
QSP modeling of a transiently inactivating antibody-drug conjugate highlights benefit of short antibody half life
Khera, E., Dharmarajan, L., Hainzl, D., Engelhardt, V., Vostiarova, H., Davis, J., Ebel, N., Wuersch, K., Romanet, V., Sharaby, S., et al. (2024) · Journal of Pharmacokinetics and Pharmacodynamics · doi:10.1007/s10928-024-09956-1 · Cited by 6 · see citing works
Translational PK/PD Modeling of Tumor Growth Inhibition and Target Inhibition to Support Dose Range Selection of the LMP7 Inhibitor M3258 in Relapsed/Refractory Multiple Myeloma
Lignet, F., Esdar, C., Walter-Bausch, G., Friese‐Hamim, M., Stinchi, S., Drouin, E. E., Bawab, S. E., Becker, A. D., Gimmi, C. D., Sanderson, M. P., et al. (2022) · Journal of Pharmacology and Experimental Therapeutics · doi:10.1124/jpet.122.001355 · Cited by 6 · see citing works
Evaluation and translation of combination therapies in oncology – A quantitative approach
Cardilin, T., Almquist, J. O., Jirstrand, M., & Gabrielsson, J. (2018) · European Journal of Pharmacology · doi:10.1016/j.ejphar.2018.07.041 · Cited by 6 · see citing works
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
Ahad, A., Saeed, H. K., del Solar, V., López‐Hernández, J. E., Michel, A. L., Mathew, J., Lewis, J. S., & Contel, M. (2023) · ACS Pharmacology & Translational Science · doi:10.1021/acsptsci.3c00270 · Cited by 5 · see citing works
Utility of PK-PD Modeling and Simulation to Improve Decision Making for Antibody-Drug Conjugate Development
Singh, A. P., & Shah, D. K. (2018) · Cancer drug discovery and develogment/Cancer drug discovery and development · doi:10.1007/978-3-319-78154-9_4 · Cited by 5 · see citing works
Optimized scaling of translational factors in oncology: from xenografts to RECIST
Baaz, M., Cardilin, T., Lignet, F., & Jirstrand, M. (2022) · Cancer Chemotherapy and Pharmacology · doi:10.1007/s00280-022-04458-8 · Cited by 5 · see citing works
Nucleic acid–triggered tumoral immunity propagates pH ‐selective therapeutic antibodies through tumor‐driven epitope spreading
Furuya, G., Katoh, H., Atsumi, S., Hashimoto, I., Komura, D., Hatanaka, R., Senga, S., Hayashi, S., Akita, S., Matsumura, H., et al. (2022) · Cancer Science · doi:10.1111/cas.15596 · Cited by 3 · see citing works
Nonclinical Pharmacology and Mechanistic Modeling of Antibody–Drug Conjugates in Support of Human Clinical Trials
Schmidt, B. J., Pan, C., Vezina, H. E., Sun, H., Leipold, D. D., & Gupta, M. (2016) · Wiley eBooks · doi:10.1002/9781119060727.ch9 · Cited by 4 · see citing works
Self-citation
Technologies for Antibody‐Drug Conjugation
Holder, P. G., & Rabuka, D. (2016) · Wiley eBooks · doi:10.1002/9781118940648.ch22 · Cited by 4 · see citing works
Applications of Pharmacometrics in Antibody–Drug Conjugate Development
Cheng, X., Ji, S., Lee, Y., & Dong, H. (2026) · Pharmaceutics · doi:10.3390/pharmaceutics18030354 · Cited by 4 · see citing works
A novel semi‐mechanistic tumor growth fraction model for translation of preclinical efficacy of anti‐glypican 3 antibody drug conjugate to human
Singh, R., Kozhich, A. T., Pan, C., Lee, F. Y., Cardarelli, P. M., Vangipuram, R., Iyer, R., & Marathe, P. (2020) · Biopharmaceutics & Drug Disposition · doi:10.1002/bdd.2249 · Cited by 3 · see citing works
Understanding tumour growth variability in breast cancer xenograft models identifies PARP inhibition resistance biomarkers
Voulgarelis, D., Forment, J. V., Herencia-Ropero, A., Polychronopoulos, D., Cohen-Setton, J., Bender, A., Serra, V., O’Connor, M. J., Yates, J. W. T., & Bulusu, K. C. (2024) · npj Precision Oncology · doi:10.1038/s41698-024-00702-x · Cited by 3 · see citing works
Genetically Engineered Mouse Models in Preclinical Anti-Cancer Drug Development
Sergio, Y., & Melinda, G. (2011) · InTech eBooks · doi:10.5772/30666 · Cited by 3 · see citing works
Survival Prolongation Index as a Novel Metric to Assess Anti-Tumor Activity in Xenograft Models
Chandra, F. A., Zaks, L., & Zhu, A. Z. X. (2019) · The AAPS Journal · doi:10.1208/s12248-018-0284-8 · Cited by 2 · see citing works

Choosing the right dose and regimen PK/PD modeling of tumor response of trastuzumab-MCC-DM1 using mouse models
Jumbe, N. L. ‘., Tibbitts, J., Leipold, D., Sliwkowski, M. X., Dugger, D. L., Crocker, L., Reich, M., & Fielder, P. J. (2007) · Cancer Research
Self-citation
Population Pharmacokinetics of Trastuzumab-DM1, a First-in-Class HER2 Antibody-Drug Conjugate Given Every 3 Weeks (q3w) and Weekly (qw) to Patients with HER2-Positive Metastatic Breast Cancer (MBC).
LoRusso, P. M., Girish, S., Burris, H. A., Beeram, M., Vukelja, S. J., Modi, S., Yi, J., Wang, B., Saad, O. M., & Gupta, M. (2009) · Cancer Research · doi:10.1158/0008-5472.sabcs-09-5099 · Cited by 3 · see citing works
P1-12-13: Comparative Pharmacokinetics (PK) of Trastuzumab Emtansine (T-DM1) in Patients Who Have or Who Have Not Received Prior Treatment for Human Epidermal Growth Factor 2 (HER2)-Positive Metastatic Breast Cancer (MBC).
Wang, B., Conte, P., Casanova, L., da Fonseca, V. J., Saad, O., Yi, J.-H., Gupta, M., Song, C., Olsen, S., Perez, E. A., et al. (2011) · Cancer Research · doi:10.1158/0008-5472.sabcs11-p1-12-13 · Cited by 1 · see citing works
Pharmacometric Models for Antibody Drug Conjugates and Taxanes in HER2+ and HER2- Breast Cancer
Bender, B. C. (2016) · KTH Publication Database DiVA (KTH Royal Institute of Technology) · Cited by 3 · see citing works
Evaluation and PK/PD modeling of the dose regimen chronomodulation of Trastuzumab-MC-vc-PAB-MMAF (Tmab-vc-MMAF) in tumor bearing mouse models
Bender, B. C., Leipold, D., Li, D., Crocker, L., Parsons, K. L., Ross, S., Tibbitts, J., & Jumbe, N. L. ‘. (2007) · Molecular Cancer Therapeutics
Self-citation

Authors: Jumbe, N. L., Xin, Y., Leipold, D. D., Crocker, L., Dugger, D., Mai, E., Sliwkowski, M. X., Fielder, P. J., & Tibbitts, J.
Affiliations: Genentech (US)
Corresponding author: Tibbitts, Jay
ORCID: Jumbe, Nelson L.
Leipold, Douglas D.
Dugger, Debra
Sliwkowski, Mark X.
Venue: Journal of Pharmacokinetics and Pharmacodynamics
Publisher: Springer Science and Business Media LLC
Published: 2010-04-28
Volume: 37
Issue: 3
Pages: 221-242
ISSN: 1567-567X (ISSN-L)
1573-8744
DOI: 10.1007/s10928-010-9156-2
OpenAlex: W1987301058
Cited by: 119
References: 35
Citations by year: 2026: 4 · 2025: 2 · 2024: 5 · 2023: 5 · 2022: 8 · 2021: 6 · 2020: 9 · 2019: 5 · 2018: 9 · 2017: 9 · 2016: 17 · 2015: 10 · 2014: 9 · 2013: 11 · 2012: 5
FWCI: 3.30
Type: journal article
Language: en
Open access: closed
Licence: www.springer.com/tdm (tdm)
Locations: Journal of Pharmacokinetics and Pharmacodynamics (publishedVersion)
PubMed (publishedVersion)
Topics: Health Sciences › Medicine › Oncology › HER2/EGFR in Cancer Research
Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Monoclonal and Polyclonal Antibodies Research
Physical Sciences › Mathematics › Modeling and Simulation › Mathematical Biology Tumor Growth
Keywords: antibody-drug conjugates, HER2-positive breast cancer, pharmacokinetic-pharmacodynamic modeling, dosing regimen optimization, tumor growth modeling, tumor growth rate, time-dose-fractionation, mouse pharmacokinetics
MeSH terms: Trastuzumab, Ado-Trastuzumab Emtansine, Animals, Antibodies, Monoclonal, Immunotoxins, Antineoplastic Agents, Dose-Response Relationship, Drug, Drug Administration Schedule, Female, Humans, Maytansine, Mice, Nude, Models, Biological, Neoplasms, Time Factors, Xenograft Model Antitumor Assays, Cell Line, Tumor, Mice, Antibodies, Monoclonal, Humanized

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Modeling the efficacy of trastuzumab-DM1, an antibody drug conjugate, in mice

Abstract

Integrity signals

Claims the paper makes

Claims other papers make about this one

Cites

Cited by

Related

Record

About these checks