Mathematical modeling of tumor growth and tumor growth inhibition in oncology drug development

Bibliography

• Kola I, Landis J. Can the pharmaceutical industry reduce attrition rates? Nat Rev Drug Discov 2004;3:711-16
   PubMed Web of Science ®Google Scholar
• Adams CP, Brantner VV. Estimating the cost of new drug development: is it really $802 million? Health Aff 2006;25:420-8
   PubMed Web of Science ®Google Scholar
• Cockburn IM. Is the pharmaceutical industry in a productivity crisis? In: Lerner J, Stern S, editors. Innovation policy and the economy. Volume 7, MIT Press, Cambridge, MA; 2007
   Google Scholar
• Innovation or stagnation? Challenge and opportunity on the critical path to new medical products. Food and drug administration, March 2004. Available from: http://www.fda.gov/downloads/ScienceResearch/SpecialTopics/CriticalPathInitiative/CriticalPathOpportunitiesReports/ucm113411.pdf [Last accessed 28 Dec 2011]
   Google Scholar
• Shepard T. Role of modelling and simulation in regulatory decision making in Europe. EMA-EFPIA Modelling and Simulation Workshop, London 2011. Available from: http://www.ema.europa.eu/docs/en_GB/document_library/Presentation/2011/11/WC500118262.pdf [Last accessed 28 Dec 2011]
   Google Scholar
• Lalonde RL, Kowalski KG, Hutmacher MM, Model-based drug development. Clin Pharmacol Ther 2007;82:21-32
   PubMed Web of Science ®Google Scholar
• Zhang L, Pfister M, Meibohm B. Concepts and challenges in quantitative pharmacology and model-based drug development. AAPS J 2008;10:552-9
   PubMed Web of Science ®Google Scholar
• Barrett JS, Gupta M, Mondick JT. Model-based drug development applied to oncology. Expert Opin Drug Discov 2007;2:185-209
   PubMed Web of Science ®Google Scholar
• Nucci G, Gomeni R, Poggesi I. Model-based approaches to increase efficiency of drug development in schizophrenia: a can't miss opportunity. Expert Opin Drug Discov 2009;4:837-85
   PubMed Web of Science ®Google Scholar
• Santen G, van Zwet E, Danhof M, Della Pasqua O. From trial and error to trial simulation. Part 1: the importance of model-based drug development for antidepressant drugs. Clin Pharmacol Ther 2009;86:248-54
   PubMed Web of Science ®Google Scholar
• Santen G, Horrigan J, Danhof M, Della Pasqua O. From trial and error to trial simulation. Part 2: an appraisal of current beliefs in the design and analysis of clinical trials for antidepressant drugs. Clin Pharmacol Ther 2009;86:255-62
   PubMed Web of Science ®Google Scholar
• Samtani MN, Farnum M, Lobanov V, An improved model for disease progression in patients from the Alzheimer's Disease neuroimaging initiative. J Clin Pharmacol 2011; published online 9 June 2011; DOI: 10.1177/0091270011405497.
   PubMed Web of Science ®Google Scholar
• Kimko HHC, Peck CC, editors. Clinical trial simulations. Applications and trends. AAPS Press, New York; 2011
   Google Scholar
• Zhou Q, Gallo JM. The pharmacokinetic/pharmacodynamic pipeline: translating anticancer drug pharmacology to the clinic. AAPS J 2011;13:111-20
   PubMed Web of Science ®Google Scholar
• Sanga S, Frieboes HB, Zheng X, Predictive oncology: multidisciplinary, multi-scale in-silico modeling linking phenotype, morphology and growth. Neuroimage 2007;37(Suppl 1):S120-34
   PubMed Web of Science ®Google Scholar
• Della Pasqua O. PKPD and disease modeling: concepts and applications to oncology. In: Kimko HHC, Peck CC, editors. Clinical trial simulations. Applications and trends. AAPS Press, New York; 2011
   Google Scholar
• Workman P. Auditing the pharmacological accounts for Hsp90 molecular chaperone inhibitors: unfolding the relationship between pharmacokinetics and pharmacodynamics. Mol Cancer Ther 2003;2:131-8
   PubMed Web of Science ®Google Scholar
• Yap TA, Sandhu SK, Workman P, de Bono JS. Envisioning the future of early anticancer drug development. Nat Rev Cancer 2010;10:514-23
   PubMed Web of Science ®Google Scholar
• Bueno L, de Alwis DP, Pitou C, Semi-mechanistic modelling of the tumour growth inhibitory effects of LY2157299, a new type I receptor TGF-beta kinase antagonist, in mice. Eur J Cancer 2008;44:142-50
   PubMed Web of Science ®Google Scholar
• Yamazaki S, Skaptason J, Romero D, Pharmacokinetic-Pharmacodynamic modeling of biomarker response and tumor growth inhibition to an orally available cMet kinase inhibitor in human tumor xenograft mouse models. Drug Metab Dispos 2008;36:1267-74
   PubMed Web of Science ®Google Scholar
• Yamazaki S, Nguyen L, Vekich S, Pharmacokinetic-Pharmacodynamic modeling of biomarker response and tumor growth inhibition to an orally available Heat Shock Protein 90 inhibitor in a human tumor xenograft mouse model. JPET 2011;338:964-73
   PubMed Web of Science ®Google Scholar
• Salphati L, Wong H, Belvin M, Pharmacokinetic-Pharmacodynamic modeling of tumor growth inhibition and biomarker modulation by the novel phosphatidylinositol 3-kinase inhibitor GDC-0941. Drug Metab Dispos 2010;38:1436-42
   PubMed Web of Science ®Google Scholar
• Luo FR, Yang Z, Camuso A, Dasatinib (BMS-354825) pharmacokinetics and pharmacodynamic biomarkers in animal models predict optimal clinical exposure. Clin Cancer Res 2006;12:7180-6
   PubMed Web of Science ®Google Scholar
• Claret L, Girard P, Hoff PM, Model-based prediction of phase III overall survival in colorectal cancer on the basis of phase II tumor dynamics. J Clin Oncol 2009;27:4103-8
   PubMed Web of Science ®Google Scholar
• Claret L, Lu J-F, Sun Y-N, Bruno R. Development of a modeling framework to simulate efficacy endpoints for motesanib in patients with thyroid cancer. Cancer Chemother Pharmacol 2010;66:1141-9
   PubMed Web of Science ®Google Scholar
• Wang Y, Sung C, Dartois C, Elucidation of relationship between tumor size and survival in non-small-cell lung cancer patients can aid early decision making in clinical drug development. Clin Pharmacol Ther 2009;86:167-74
   PubMed Web of Science ®Google Scholar
• Hollingshead MG. Antitumor efficacy testing in rodents. J Natl Cancer Inst 2008;100:1500-10
   PubMedGoogle Scholar
• Frese KK, Tuveson DA. Maximizing mouse cancer models. Nat Rev Cancer 2008;7:645-58
   Web of Science ®Google Scholar
• Kelland LR. Of mice and men: values and liabilities of the athymic nude mouse model in anticancer drug development. Eur J Cancer 2004;40:827-36
   PubMed Web of Science ®Google Scholar
• Lyons SK. Advances in imaging mouse tumour models in vivo. J Pathol 2005;205:194-205
   PubMed Web of Science ®Google Scholar
• Voscoglu-Nomikos T, Pater JL, Seymour L. Clinical predictive value of in vitro cell line, human xenograft, and mouse allograft preclinical cancer models. Clin Cancer Res 2003;9:4227-39
   PubMed Web of Science ®Google Scholar
• Poggesi I, De Nicolao G, Germani M, Rocchetti M. Re: antitumor efficacy testing in rodents. J Natl Cancer Inst 2009;101:1592-3
   PubMed Web of Science ®Google Scholar
• Rocchetti M, Simeoni M, Pesenti E, Predicting the active doses in humans from animal studies: a novel approach in oncology. Eur J Cancer 2007;12:1862-8
   Web of Science ®Google Scholar
• Wong H, Choo EF, Alicke B, Antitumor activity of targeted and cytotoxic agents in xenograft models correlates with clinical response: a pharmacokinetic-pharmacodynamic analysis. Mol Cancer Ther 2011;10(Suppl 1):abstract TARG-11-A11-AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 12 – 16 Nov 2011; San Francisco, CA
   Google Scholar
• Gorelik B, Ziv I, Shohat R, Efficacy of weekly docetaxel and bevacizumab in mesenchymal chondrosarcoma: a new theranostic method combining xenografted biopsies with a mathematical model. Cancer Res 2008;68:9033-40
   PubMed Web of Science ®Google Scholar
• Therasse P, Arbuck SG, Eisenhauer EA, New guidelines to evaluate the response to treatment in solid tumors. J Natl Cancer Inst 2000;92:205-16
   PubMed Web of Science ®Google Scholar
• Aarons L, Ogungbenro K. Optimal design of pharmacokinetic studies. Basic Clin Pharmacol Toxicol 2010;106:250-5
   PubMed Web of Science ®Google Scholar
• Bajzer Z, Marusic M, Vuk-Pavlovic S. Conceptual frameworks for mathematical modeling of tumor growth dynamics. Math Comput Model 1996;23:31-46
   Web of Science ®Google Scholar
• Nestorov I, Rowland M, Hadjitodorov ST, Petrov I. Empirical versus mechanistic modelling: comparison of an artificial neural network to a mechanistically based model for quantitative structure pharmacokinetic relationships of a homologous series of barbiturates. AAPS PharmSci 1999;1(article 17):1-9
   Google Scholar
• Skipper HE, Schabel FM Jr, Implications of biochemical, cytokinetic, pharmacologic, and toxicologic relationships in the design of optimal therapeutic schedules. Cancer Chemother Rep 1970;54:431-50
   PubMedGoogle Scholar
• Porrata LF, Adjei AA. The pharmacologic basis of high dose chemotherapy with haematopoietic stem cell support for solid tumors. Br J Cancer 2001;85:484-9
   PubMed Web of Science ®Google Scholar
• Norton L, Hudis C. Role of modeling in pharmacotherapeutics. In: Piccart M, Wood WC, Hung M-C, Solin LJ, Cardosa F, editors. Breast cancer and molecular medicine. Springer-Verlag Berlin; Heidelberg: 2006
   Google Scholar
• Norton L. Theoretical concepts and the emerging role of taxanes in adjuvant therapy. Oncologist 2001;6:30-5
   PubMed Web of Science ®Google Scholar
• Jusko WJ. Pharmacodynamics of therapeutic effects: dose-time relationships for phase nonspecific agents. J Pharm Sci 1971;60:892-5
   PubMed Web of Science ®Google Scholar
• Jusko WJ. A pharmacodynamic model for cell-cycle specific chemotherapeutic agents. J Pharmacokinet Pharmacodyn 1973;1:175-200
   Web of Science ®Google Scholar
• Goldie JH, Coldman A. The genetic origin of drug resistance in neoplasms: implications for systemic therapy. Cancer Res 1984;44:3643-53
   PubMed Web of Science ®Google Scholar
• DeVita VT Jr, Chu E. Biology of drug resistance. DeVita, Hellman, and Rosenberg's Cancer: principles & practice of oncology. 8th edition. Lippincott Williams & Wilkins, Philadelphia, PA; 2008
   Google Scholar
• Teicher B. Tumor models for efficacy determination. Mol Cancer Ther 2006;5:2435-43
   PubMed Web of Science ®Google Scholar
• Creton G, Benassi MI, Di Staso M, The time factor in oncology: consequences of tumour volume and therapeutic planning. J Exp Clin Cancer Res 2006;25:557-73
   PubMed Web of Science ®Google Scholar
• 50. Verhulst P-F. Notice sur la loi que la population poursuit dans son accroissement. Correspondance Mathematique et Physique 1838;10:113-21
   Google Scholar
• Gonze D. The logistic equation. Available from: http://homepages.ulb.ac.be/∼dgonze/TEACHING/logistic.pdf [Last accessed 28 Feb 2012]
   Google Scholar
• Von Bertalanffy L. Untersuchungen uber die Gesetzlichkeit des Wachstums. I. Allgemeine Grundlagen der Theorie; mathematische und physiologische Gesetzlichkeiten des Wachstums bei Wassertieren. Arch Entwicklungsmech 1934;131:613-52
   Google Scholar
• Laird AK. Dynamics of tumor growth. Br J Cancer 1964;18:490-502
   Web of Science ®Google Scholar
• Norton L. Conceptual and practical implications of breast tissue geometry: toward a more effective, less toxic therapy. Oncologist 2005;10:370-81
   PubMed Web of Science ®Google Scholar
• Norton L, Simon R. The Norton-Simon hypothesis revisited. Cancer Treat Rep 1986;70:163-9
   PubMedGoogle Scholar
• Traina T, Dugan U, Higgins B, Optimizing chemotherapy dose and schedule by norton-simon mathematical modeling. Breast Dis 2010;31:7-18
   PubMedGoogle Scholar
• Citron ML, Berry DA, Cirrincione C, Randomized trial of dose-dense versus conventionally scheduled and sequential versus concurrent combination chemotherapy as postoperative adjuvant treatment of node-positive primary breast cancer: first report of intergroup Trial C9741/Cancer and Leukemia Group B Trial 9741. J Clin Oncol 2003;21:1431-9
   PubMed Web of Science ®Google Scholar
• Lobo ED, Balthasar JP. Pharmacodynamic modeling of chemotherapeutic effects: application of transit compartmental model to characterize methotrexate effects in vitro. AAPS J 2002;4(article 42):1-11
   Google Scholar
• Yang J, Mager DE, Straubinger RM. Comparison of two pharmacodynamic transduction models for the analysis of tumor therapeutic responses in model systems. AAPS J 2010;12:1-10
   PubMed Web of Science ®Google Scholar
• Simeoni M, Magni P, Cammia C, Predictive pharmacokinetic-pharmacodynamic modeling of tumor growth kinetics in xenograft models after administration of anticancer agents. Cancer Res 2004;64:1094-101
   PubMed Web of Science ®Google Scholar
• Magni P, Germani M, De Nicolao G, A minimal model of tumor growth inhibition. IEEE Trans Biomed Engineer 2008;55:2683-90
   PubMed Web of Science ®Google Scholar
• Jumbe NL, Xin Y, Leipold DD, Modeling the efficacy of trastuzumab-DM1, an antibody drug conjugate, in mice. J Pharmacokinet Pharmacodyn 2010;37:221-42
   PubMed Web of Science ®Google Scholar
• Danhof M, Alvan G, Dahl SG, Mechanism-based pharmacokinetic–pharmacodynamic modeling—a new classification of biomarkers. Pharm Res 2005;22:1432-7
   PubMed Web of Science ®Google Scholar
• Lassere MN, Johnson KR, Boers M, Definitions and validation criteria for biomarkers and surrogate endpoints: development and testing of a quantitative hierarchical levels of evidence schema. J Rheumatol 2007;34:607-15
   PubMed Web of Science ®Google Scholar
• Therasse P. Evaluation of response: new and standard criteria. Ann Oncol 2002;13(Suppl 4):127-9
   PubMed Web of Science ®Google Scholar
• Miller AB, Hogestraeten B, Staquet M, Winkler A. Reporting results of cancer treatment. Cancer 1981;47:207-14
   PubMed Web of Science ®Google Scholar
• Lu J-F, Claret L, Sutjandra L, Population pharmacokinetic/pharmacodynamic modeling for the time course of tumor shrinkage by motesanib in thyroid cancer patients. Cancer Chemother Pharmacol 2010;66:1151-8
   PubMed Web of Science ®Google Scholar
• Houk BE, Bello CL, Poland B, Relationship between exposure to sunitinib and efficacy and tolerability endpoints in patients with cancer: results of a pharmacokinetic/pharmacodynamic meta-analysis. Cancer Chemother Pharmacol 2010;66:357-71
   PubMed Web of Science ®Google Scholar
• An M-W, Mandrekar SJ, Branda ME, Comparison of continuous versus categorical tumor measurement–based metrics to predict overall survival in cancer treatment trials. Clin Cancer Res 2011;17:6592-9
   PubMed Web of Science ®Google Scholar
• Tham L-S, Wang L, Soo RA, A pharmacodynamic model for the time course of tumor shrinkage by gemcytabine + carboplatin in non-small cell lung cancer patients. Clin cancer Res 2008;14:4213-18
   PubMed Web of Science ®Google Scholar
• Bonate PL. Modeling tumor growth in oncology. In: Bonate PL, Howard DR, editors. Pharmacokinetics in drug development. AAPS Press, New York; 2011
   Google Scholar
• Zhang L, Allerheiligen SR, Lalonde RL, Fostering culture and optimizing organizational structure for implementing model-based drug development. J Clin Pharmacol 2010;50:146S-50S
   PubMed Web of Science ®Google Scholar
• Wetherington JD, Pfister M, Banfield C, Model-based drug development: strengths, weaknesses, opportunities, and threats for broad application of pharmacometrics in drug development. J Clin Pharmacol 2010;50:31S-46S
   PubMed Web of Science ®Google Scholar