Optimisation of cancer drug treatments using cell population dynamics
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A. Friedman | H. Schättler | U. Ledzewicz | Eugene | Kashdan
[1] A. Kirsch. An Introduction to the Mathematical Theory of Inverse Problems , 1996, Applied Mathematical Sciences.
[2] Thomas B. L. Kirkwood,et al. Deciphering death: a commentary on Gompertz (1825) ‘On the nature of the function expressive of the law of human mortality, and on a new mode of determining the value of life contingencies’ , 2015, Philosophical Transactions of the Royal Society B: Biological Sciences.
[3] Stéphane Gaubert,et al. Synchronisation and control of proliferation in cycling cell population models with age structure , 2014, Math. Comput. Simul..
[4] K. Aziz,et al. Molecular markers for cancer prognosis and treatment: have we struck gold? , 2012, Cancer letters.
[5] Marie Doumic,et al. Nonparametric Estimation of the Division Rate of a Size-Structured Population , 2011, SIAM J. Numer. Anal..
[6] W. Marsden. I and J , 2012 .
[7] Karyn L. Sutton,et al. A new model for the estimation of cell proliferation dynamics using CFSE data. , 2011, Journal of immunological methods.
[8] S. Gaubert,et al. Proliferation in Cell Population Models with Age Structure , 2011 .
[9] Annabelle Ballesta,et al. A Combined Experimental and Mathematical Approach for Molecular-based Optimization of Irinotecan Circadian Delivery , 2011, PLoS Comput. Biol..
[10] Annabelle Ballesta,et al. Theoretical optimization of Irinotecan-based anticancer strategies in the case of drug-induced efflux , 2011, Appl. Math. Lett..
[11] Urszula Ledzewicz,et al. Optimal and suboptimal protocols for a mathematical model for tumor anti-angiogenesis in combination with chemotherapy. , 2011, Mathematical biosciences and engineering : MBE.
[12] Benoît You,et al. A model of vascular tumour growth in mice combining longitudinal tumour size data with histological biomarkers. , 2011, European journal of cancer.
[13] Stéphane Gaubert,et al. Circadian rhythm and cell population growth , 2010, Math. Comput. Model..
[14] Albert Goldbeter,et al. An automaton model for the cell cycle , 2011, Interface Focus.
[15] Gabriela Ochoa,et al. Modeling and optimization of combined cytostatic and cytotoxic cancer chemotherapy , 2010, Artif. Intell. Medicine.
[16] S. Tejpar,et al. New Strategies for Treatment of KRAS Mutant Metastatic Colorectal Cancer , 2010, Clinical Cancer Research.
[17] Samuel Bernard,et al. Tumor Growth Rate Determines the Timing of Optimal Chronomodulated Treatment Schedules , 2010, PLoS Comput. Biol..
[18] Jean Clairambault,et al. Circadian timing in cancer treatments. , 2010, Annual review of pharmacology and toxicology.
[19] D. Bresch,et al. Computational Modeling of Solid Tumor Growth: The Avascular Stage , 2010, SIAM J. Sci. Comput..
[20] On the Calibration of a Size-Structured Population Model from Experimental Data , 2009, Acta biotheoretica.
[21] H. Schättler,et al. On optimal delivery of combination therapy for tumors. , 2009, Mathematical biosciences.
[22] Didier Bresch,et al. A pharmacologically based multiscale mathematical model of angiogenesis and its use in investigating the efficacy of a new cancer treatment strategy. , 2009, Journal of theoretical biology.
[23] Paolo Ubezio,et al. Quantitative assessment of the complex dynamics of G1, S, and G2-M checkpoint activities. , 2009, Cancer research.
[24] R. Gatenby. A change of strategy in the war on cancer , 2009, Nature.
[25] Mauro Ferrari,et al. Prediction of drug response in breast cancer using integrative experimental/computational modeling. , 2009, Cancer research.
[26] Assia Benabdallah,et al. Mathematical and numerical analysis for a model of growing metastatic tumors. , 2009, Mathematical biosciences.
[27] Albert Goldbeter,et al. Identifying mechanisms of chronotolerance and chronoefficacy for the anticancer drugs 5-fluorouracil and oxaliplatin by computational modeling. , 2009, European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences.
[28] Jean Clairambault,et al. Comparison of Perron and Floquet Eigenvalues in Age Structured Cell Division Cycle Models , 2008, 0812.0803.
[29] Alberto Gandolfi,et al. A family of models of angiogenesis and anti-angiogenesis anti-cancer therapy. , 2008, Mathematical medicine and biology : a journal of the IMA.
[30] Jorge P. Zubelli,et al. Numerical solution of an inverse problem in size-structured population dynamics , 2008, 0810.1381.
[31] M. Ferrari,et al. Predicting drug pharmacokinetics and effect in vascularized tumors using computer simulation , 2006, Journal of mathematical biology.
[32] B. Frieden,et al. Adaptive therapy. , 2009, Cancer research.
[33] Jean Clairambault,et al. Modelling Physiological and Pharmacological Control on Cell Proliferation to Optimise Cancer Treatments , 2009 .
[34] Didier Bresch,et al. A viscoelastic model for avascular tumor growth , 2009 .
[35] Atsushi Miyawaki,et al. Tracing the silhouette of individual cells in S/G2/M phases with fluorescence. , 2008, Chemistry & biology.
[36] Albert Goldbeter,et al. Implications of circadian clocks for the rhythmic delivery of cancer therapeutics , 2008, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.
[37] Jean Clairambault,et al. An age-and-cyclin-structured cell population model for healthy and tumoral tissues , 2008, Journal of mathematical biology.
[38] Jean Clairambault,et al. A Step Toward Optimization of Cancer Therapeutics , 2008 .
[39] J. Clairambault. A step toward optimization of cancer therapeutics. Physiologically based modeling of circadian control on cell proliferation. , 2008, IEEE engineering in medicine and biology magazine : the quarterly magazine of the Engineering in Medicine & Biology Society.
[40] Efstratios N. Pistikopoulos,et al. Optimal delivery of chemotherapeutic agents in cancer , 2008, Comput. Chem. Eng..
[41] T. Haferlach. Molecular genetic pathways as therapeutic targets in acute myeloid leukemia. , 2008, Hematology. American Society of Hematology. Education Program.
[42] Alberto d'Onofrio,et al. Rapidly acting antitumoral antiangiogenic therapies. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.
[43] Akif Uzman,et al. The cell cycle: Principles of control (Primers in Biology series) , 2007 .
[44] M. Crosby,et al. Cell Cycle: Principles of Control , 2007, The Yale Journal of Biology and Medicine.
[45] Jean Clairambault,et al. Modeling oxaliplatin drug delivery to circadian rhythms in drug metabolism and host tolerance. , 2007, Advanced drug delivery reviews.
[46] Albert Goldbeter,et al. A cell cycle automaton model for probing circadian patterns of anticancer drug delivery. , 2007, Advanced drug delivery reviews.
[47] M Kardar,et al. Dynamics of tumor growth and combination of anti-angiogenic and cytotoxic therapies , 2007, Physics in medicine and biology.
[48] Glenn F Webb,et al. A mathematical model separates quantitatively the cytostatic and cytotoxic effects of a HER2 tyrosine kinase inhibitor , 2007, Theoretical Biology and Medical Modelling.
[49] Urszula Ledzewicz,et al. Optimal controls for a model with pharmacokinetics maximizing bone marrow in cancer chemotherapy. , 2007, Mathematical biosciences.
[50] Paolo Ubezio,et al. A Generalised Age- and Phase-Structured Model of Human Tumour Cell Populations Both Unperturbed and Exposed to a Range of Cancer Therapies , 2007, Bulletin of mathematical biology.
[51] H. Kitano. A robustness-based approach to systems-oriented drug design , 2007, Nature Reviews Drug Discovery.
[52] Ueli Schibler,et al. Circadian rhythms: mechanisms and therapeutic implications. , 2007, Annual review of pharmacology and toxicology.
[53] B. Perthame,et al. On the inverse problem for a size-structured population model , 2006, math/0611052.
[54] A. Goldbeter,et al. Optimizing Temporal Patterns of Anticancer Drug Delivery by Simulations of a Cell Cycle Automaton , 2007 .
[55] B Ribba,et al. A multiscale mathematical model of avascular tumor growth to investigate the therapeutic benefit of anti-invasive agents. , 2006, Journal of theoretical biology.
[56] B. Perthame. Transport Equations in Biology , 2006 .
[57] Refael Hassin,et al. Optimizing Chemotherapy Scheduling Using Local Search Heuristics , 2006, Oper. Res..
[58] Alessandro Torricelli,et al. Modelling the balance between quiescence and cell death in normal and tumour cell populations. , 2006, Mathematical biosciences.
[59] Z. Agur,et al. LONG-RANGE PREDICTABILITY IN MODELS OF CELL POPULATIONS SUBJECTED TO PHASE-SPECIFIC DRUGS: GROWTH-RATE APPROXIMATION USING PROPERTIES OF POSITIVE COMPACT OPERATORS , 2006 .
[60] P. Maini,et al. Modelling aspects of cancer dynamics: a review , 2006, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.
[61] Helen M. Byrne,et al. Modelling the response of spatially structured tumours to chemotherapy: Drug kinetics , 2006, Math. Comput. Model..
[62] W. Evans,et al. Mechanistic mathematical modelling of mercaptopurine effects on cell cycle of human acute lymphoblastic leukaemia cells , 2005, British Journal of Cancer.
[63] Andrzej Swierniak,et al. Control Theory Approach to Cancer Chemotherapy: Benefiting from Phase Dependence and Overcoming Drug Resistance , 2006 .
[64] Nikolaus Hansen,et al. The CMA Evolution Strategy: A Comparing Review , 2006, Towards a New Evolutionary Computation.
[65] F. Lévi,et al. The circadian timing system, a coordinator of life processes. implications for the rhythmic delivery of cancer therapeutics , 2006, 2006 International Conference of the IEEE Engineering in Medicine and Biology Society.
[66] Francis Lévi,et al. Chronotherapeutics: The Relevance of Timing in Cancer Therapy , 2006, Cancer Causes & Control.
[67] Paolo Ubezio,et al. Interpreting cell cycle effects of drugs: the case of melphalan , 2006, Cancer Chemotherapy and Pharmacology.
[68] Claude Basdevant,et al. Optimisation of time-scheduled regimen for anti-cancer drug infusion , 2005 .
[69] Graeme C. Wake,et al. Modelling the flow cytometric data obtained from unperturbed human tumour cell lines: Parameter fitting and comparison , 2005 .
[70] H. Maurer,et al. Optimization methods for the verification of second order sufficient conditions for bang–bang controls , 2005 .
[71] V. Cristini,et al. Nonlinear simulation of tumor necrosis, neo-vascularization and tissue invasion via an adaptive finite-element/level-set method , 2005, Bulletin of mathematical biology.
[72] Helen M. Byrne,et al. A Multiple Scale Model for Tumor Growth , 2005, Multiscale Model. Simul..
[73] Alberto Gandolfi,et al. Tumour eradication by antiangiogenic therapy: analysis and extensions of the model by Hahnfeldt et al. (1999). , 2004, Mathematical biosciences.
[74] Tim Hesterberg,et al. Introduction to Stochastic Search and Optimization: Estimation, Simulation, and Control , 2004, Technometrics.
[75] Armando Santoro,et al. Cetuximab monotherapy and cetuximab plus irinotecan in irinotecan-refractory metastatic colorectal cancer. , 2004, The New England journal of medicine.
[76] Ping Chen,et al. Overriding Imatinib Resistance with a Novel ABL Kinase Inhibitor , 2004, Science.
[77] Britta Basse,et al. Modelling cell population growth with applications to cancer therapy in human tumour cell lines. , 2004, Progress in biophysics and molecular biology.
[78] Paolo Ubezio,et al. Cytostatic and cytotoxic effects of topotecan decoded by a novel mathematical simulation approach. , 2004, Cancer research.
[79] H. Kitano. Cancer as a robust system: implications for anticancer therapy , 2004, Nature Reviews Cancer.
[80] Graeme Wake,et al. Modelling cell death in human tumour cell lines exposed to the anticancer drug paclitaxel , 2004, Journal of mathematical biology.
[81] John Carl Panetta,et al. A mechanistic mathematical model of temozolomide myelosuppression in children with high-grade gliomas. , 2003, Mathematical biosciences.
[82] Graeme Wake,et al. A mathematical model for analysis of the cell cycle in cell lines derived from human tumors , 2003, Journal of mathematical biology.
[83] L. Wein,et al. Optimal scheduling of radiotherapy and angiogenic inhibitors , 2003, Bulletin of mathematical biology.
[84] Jean Charles Gilbert,et al. Numerical Optimization: Theoretical and Practical Aspects , 2003 .
[85] Trachette L. Jackson,et al. Intracellular accumulation and mechanism of action of doxorubicin in a spatio-temporal tumor model. , 2003, Journal of theoretical biology.
[86] Jean Clairambault,et al. A mathematical model of the cell cycle and its control , 2003 .
[87] Mats Gyllenberg,et al. The inverse problem of linear age-structured population dynamics , 2002 .
[88] Robert A. Gatenby,et al. Analysis of tumor as an inverse problem provides a novel theoretical framework for understanding tumor biology and therapy , 2002, Appl. Math. Lett..
[89] J. Murray,et al. Virtual brain tumours (gliomas) enhance the reality of medical imaging and highlight inadequacies of current therapy , 2002, British Journal of Cancer.
[90] J. Murray,et al. Quantifying Efficacy of Chemotherapy of Brain Tumors with Homogeneous and Heterogeneous Drug Delivery , 2002, Acta biotheoretica.
[91] B. Druker,et al. STI571: a paradigm of new agents for cancer therapeutics. , 2002, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.
[92] Dominique Barbolosi,et al. Optimizing drug regimens in cancer chemotherapy: a simulation study using a PK-PD model , 2001, Comput. Biol. Medicine.
[93] C. Sawyers,et al. Efficacy and safety of a specific inhibitor of the BCR-ABL tyrosine kinase in chronic myeloid leukemia. , 2001, The New England journal of medicine.
[94] S G Grant,et al. A mathematical model of in vitro cancer cell growth and treatment with the antimitotic agent curacin A. , 2001, Mathematical biosciences.
[95] D K Smith,et al. Numerical Optimization , 2001, J. Oper. Res. Soc..
[96] J. Murray,et al. A quantitative model for differential motility of gliomas in grey and white matter , 2000, Cell proliferation.
[97] Dominique Barbolosi,et al. Optimizing Drug Regimens in Cancer Chemotherapy by an Efficacy-Toxicity Mathematical Model , 2000, Comput. Biomed. Res..
[98] N. Shigesada,et al. A dynamical model for the growth and size distribution of multiple metastatic tumors. , 2000, Journal of theoretical biology.
[99] H M Byrne,et al. A mathematical model to study the effects of drug resistance and vasculature on the response of solid tumors to chemotherapy. , 2000, Mathematical biosciences.
[100] John Carl Panetta,et al. Optimal Control Applied to Cell-Cycle-Specific Cancer Chemotherapy , 2000, SIAM J. Appl. Math..
[101] P. Hahnfeldt,et al. Tumor development under angiogenic signaling: a dynamical theory of tumor growth, treatment response, and postvascular dormancy. , 1999, Cancer research.
[102] Francis Levi. Cancer chronotherapeutics , 1998 .
[103] Paolo Ubezio,et al. Simulating cancer-cell kinetics after drug treatment: Application to cisplatin on ovarian carcinoma , 1998 .
[104] M. Mackey,et al. Chaos, Fractals, and Noise: Stochastic Aspects of Dynamics , 1998 .
[105] J. M. Murray,et al. The optimal scheduling of two drugs with simple resistance for a problem in cancer chemotherapy. , 1997, IMA journal of mathematics applied in medicine and biology.
[106] J C Panetta,et al. A mathematical model of breast and ovarian cancer treated with paclitaxel. , 1997, Mathematical biosciences.
[107] Eric Walter,et al. Identification of Parametric Models: from Experimental Data , 1997 .
[108] O. Arino,et al. A Survey of Cell Population Dynamics , 1997 .
[109] E. T. Gawlinski,et al. A reaction-diffusion model of cancer invasion. , 1996, Cancer research.
[110] A Swierniak,et al. Optimal control problems arising in cell‐cycle‐specific cancer chemotherapy , 1996, Cell proliferation.
[111] H M Byrne,et al. Growth of necrotic tumors in the presence and absence of inhibitors. , 1996, Mathematical biosciences.
[112] H M Byrne,et al. Growth of nonnecrotic tumors in the presence and absence of inhibitors. , 1995, Mathematical biosciences.
[113] Ovide Arino,et al. A survey of structured cell population dynamics , 1995, Acta biotheoretica.
[114] F L Pereira,et al. A new optimization based approach to experimental combination chemotherapy. , 1995, Frontiers of medical and biological engineering : the international journal of the Japan Society of Medical Electronics and Biological Engineering.
[115] Marek Kimmel,et al. Comparison of Approaches to Modeling of Cell Population Dynamics , 1993, SIAM J. Appl. Math..
[116] R. B. Martin,et al. Optimal control drug scheduling of cancer chemotherapy , 1992, Autom..
[117] M E Fisher,et al. Optimal control of tumor size used to maximize survival time when cells are resistant to chemotherapy. , 1992, Mathematical biosciences.
[118] M E Fisher,et al. Low-intensity combination chemotherapy maximizes host survival time for tumors containing drug-resistant cells. , 1992, Mathematical biosciences.
[119] G. F. Webb,et al. A NONLINEAR CELL POPULATION MODEL OF PERIODIC CHEMOTHERAPY TREATMENT , 1992 .
[120] G. F. Webb,et al. Resonance phenomena in cell population chemotherapy models , 1990 .
[121] J. M. Murray,et al. Some optimal control problems in cancer chemotherapy with a toxicity limit. , 1990, Mathematical biosciences.
[122] J. M. Murray,et al. Optimal control for a cancer chemotherapy problem with general growth and loss functions. , 1990, Mathematical biosciences.
[123] G. Webb,et al. A nonlinear structured population model of tumor growth with quiescence , 1990, Journal of mathematical biology.
[124] Lennart Ljung,et al. System Identification: Theory for the User , 1987 .
[125] S. Bittanti,et al. Optimal periodic control and periodic systems analysis: An overview , 1986, 1986 25th IEEE Conference on Decision and Control.
[126] O. Diekmann,et al. The Dynamics of Physiologically Structured Populations , 1986 .
[127] P. J. Ponzo,et al. A model for the growth of a solid tumor with non-uniform oxygen consumption , 1977 .
[128] R. Shymko,et al. Cellular and geometric control of tissue growth and mitotic instability. , 1976, Journal of theoretical biology.
[129] A S Deakin,et al. Model for the growth of a solid in vitro tumor. , 1975, Growth.
[130] H. Greenspan. Models for the Growth of a Solid Tumor by Diffusion , 1972 .
[131] M. L. Chambers. The Mathematical Theory of Optimal Processes , 1965 .
[132] A. K. Laird. Dynamics of Tumour Growth , 1964, British Journal of Cancer.
[133] N. Rashevsky,et al. Mathematical biology , 1961, Connecticut medicine.
[134] E. L. Lehmann,et al. Theory of point estimation , 1950 .
[135] Kendrick,et al. Applications of Mathematics to Medical Problems , 1925, Proceedings of the Edinburgh Mathematical Society.
[136] K. Schittkowski,et al. NONLINEAR PROGRAMMING , 2022 .