Personalizing oncology treatments by predicting drug efficacy, side-effects, and improved therapy: mathematics, statistics, and their integration, Wiley interdisciplinary reviews. Systems biology and medicine, vol.6, pp.239-253, 2014. ,
Integrating intracellular dynamics using compucell3d and bionetsolver: Applications to multiscale modelling of cancer cell growth and invasion, PLOS ONE, vol.7, issue.3, pp.1-17, 2012. ,
, Mathematical oncology. Bulletin of mathematical biology, vol.80, pp.945-953, 2018.
From patient-specific mathematical neuro-oncology to precision medicine, Frontiers in oncology, vol.3, p.62, 2013. ,
Multiscale design of cell-type?specific pharmacokinetic/pharmacodynamic models for personalized medicine: Application to temozolomide in brain tumors, CPT Pharmacometrics Syst. Pharmacol, vol.3, p.112, 2014. ,
Physiologically based mathematical models to optimize therapies against metastatic colorectal cancer: a mini-review, Current pharmaceutical design, vol.20, pp.37-48, 2014. ,
URL : https://hal.archives-ouvertes.fr/hal-00849018
, Systems chronotherapeutics. Pharmacological reviews, vol.69, pp.161-199, 2017.
SimCells, an advanced software for multicellular modeling Application to tumoral and blood vessel codevelopment, 2018. ,
URL : https://hal.archives-ouvertes.fr/hal-01853293
Fabrice Barl??si, and Nicolas Andr?? Computational oncologymathematical modelling of drug regimens for precision medicine, Nature reviews. Clinical oncology, vol.13, pp.242-254, 2016. ,
Homeostasis back and forth: An ecoevolutionary perspective of cancer. Cold Spring Harbor perspectives in medicine, vol.7, 2017. ,
Smt or toft? how the two main theories of carcinogenesis are made (artificially) incompatible, Acta biotheoretica, vol.63, pp.257-267, 2015. ,
Smt and toft integrable after all: A reply to bizzarri and cucina, Acta biotheoretica, vol.65, pp.81-85, 2017. ,
Smt and toft: Why and how they are opposite and incompatible paradigms, Acta biotheoretica, vol.64, pp.221-239, 2016. ,
Physiologically based pharmacokinetic and pharmacodynamic modeling in cancer drug development: status, potential and gaps. Expert opinion on drug metabolism & toxicology, vol.11, pp.743-756, 2015. ,
Combining radiation with hyperthermia: a multiscale model informed by , javax.xml.bind.jaxbelement@346894c0, experiments, Journal of the Royal Society, Interface, p.15, 2018. ,
Towards the design of a patient-specific virtual tumour. Computational and mathematical methods in medicine, p.7851789, 2016. ,
URL : https://hal.archives-ouvertes.fr/hal-01975976
Current mathematical models for cancer drug discovery, Expert opinion on drug discovery, vol.12, pp.785-799, 2017. ,
The mathematical modelling of tumour angiogenesis and invasion, Acta Biotheoretica, vol.43, issue.4, pp.387-402, 1995. ,
Patient specific image driven evaluation of the aggressiveness of metastases to the lung, Med Image Comput Comput Assist Interv, vol.17, issue.1, pp.553-60, 2014. ,
URL : https://hal.archives-ouvertes.fr/hal-01038074
Predictive computational modeling to define effective treatment strategies for bone metastatic prostate cancer, Scientific reports, vol.6, p.29384, 2016. ,
Availability of evidence of benefits on overall survival and quality of life of cancer drugs approved by european medicines agency: retrospective cohort study of drug approvals 2009-13, BMJ, vol.359, p.4530, 2017. ,
Simulating cancer: computational models in oncology, Frontiers in oncology, vol.3, p.233, 2013. ,
Organs-on-chips at the frontiers of drug discovery, Nature Reviews Drug Discovery, vol.14, pp.248-260, 2015. ,
Evolution of acquired resistance to anti-cancer therapy, Journal of theoretical biology, vol.355, pp.10-20, 2014. ,
Spatial heterogeneity and evolutionary dynamics modulate time to recurrence in continuous and adaptive cancer therapies, Cancer research, vol.78, pp.2127-2139, 2018. ,
Pharmacokinetic/pharmacodynamic modeling for drug development in oncology, Annual Meeting, vol.37, pp.210-215, 2017. ,
Evolution of cell motility in an individual-based model of tumour growth, Journal of theoretical biology, vol.259, pp.67-83, 2009. ,
URL : https://hal.archives-ouvertes.fr/hal-00554584
PhysiCell: an open source physics-based cell simulator for 3-D multicellular systems, PLoS Comput. Biol, vol.14, issue.2, p.1005991, 2018. ,
Le vivant discret et continu-Modes de représentation en biologie théorique, 2013. ,
Simulation of biological cell sorting using a two-dimensional extended potts model, Phys. Rev. Lett, vol.69, pp.2013-2016, 1992. ,
Microvessel chaste: An open library for spatial modeling of vascularized tissue, Biophysical Journal, 2017. ,
What does not kill a tumour may make it stronger: In silico insights into chemotherapeutic drug resistance, Journal of theoretical biology, vol.454, pp.253-267, 2018. ,
High drug attrition rates: where are we going wrong?, Nature Review in Clinical Oncology, vol.8, pp.189-190, 2011. ,
Patient-specific mathematical neuro-oncology: using a simple proliferation and invasion tumor model to inform clinical practice, Bulletin of mathematical biology, vol.77, pp.846-856, 2015. ,
Mathematical models of tumor cell proliferation: A review of the literature, Expert review of anticancer therapy, pp.1-16, 2018. ,
Mathematical and computational modeling in complex biological systems, BioMed research international, p.5958321, 2017. ,
Targeting ligand specificity linked to tumor tissue topological heterogeneity via single-cell micro-pharmacological modeling, Scientific reports, vol.8, p.3638, 2018. ,
Towards personalized computational oncology: from spatial models of tumour spheroids, to organoids, to tissues, Journal of the Royal Society, Interface, p.15, 2018. ,
Strategies of eradicating glioma cells: a multi-scale mathematical model with mir-451-ampk-mtor control, PloS one, vol.10, p.114370, 2015. ,
Can the pharmaceutical industry reduce the attrition rates?, Nature Review in Drug Discovery, vol.3, pp.711-716, 2004. ,
Predicting outcomes of prostate cancer immunotherapy by personalized mathematical models, PLOS ONE, vol.5, issue.12, p.2010 ,
Dynamics of tumor growth, British journal of cancer, vol.13, pp.490-502, 1964. ,
On the importance of the submicrovascular network in a computational model of tumour growth, Microvascular research, vol.84, pp.188-204, 2012. ,
URL : https://hal.archives-ouvertes.fr/inserm-00738177
Solid tumor models for the assessment of different treatment modalities: I. radiation-induced changes in growth rate characteristics of a solid tumor model, Proceediings of the National Academy of Sciences U.S.A, vol.72, issue.7, pp.2662-2668, 1975. ,
Patient-calibrated agent-based modelling of ductal carcinoma in situ (dcis): from microscopic measurements to macroscopic predictions of clinical progression, Journal of theoretical biology, vol.301, pp.122-140, 2012. ,
Progress towards computational 3-d multicellular systems biology, Advances in experimental medicine and biology, vol.936, pp.225-246, 2016. ,
Simulating pdgf-driven glioma growth and invasion in an anatomically accurate brain domain, Bulletin of mathematical biology, vol.80, pp.1292-1309, 2018. ,
Chaste: An open source c++ library for computational physiology and biology, PLOS Computational Biology, vol.9, issue.3, pp.1-8, 2013. ,
URL : https://hal.archives-ouvertes.fr/hal-00956373
Computational screening of tip and stalk cell behavior proposes a role for apelin signaling in sprout progression, PLOS ONE, vol.11, issue.11, pp.1-31, 2016. ,
Microfluidic organ/body-on-a-chip devices at the convergence of biology and microengineering, Sensors, vol.15, pp.31142-31170, 2015. ,
, Computational oncology. Journal of oncopathology and clinical research, vol.2, 2018.
,
40 YEARS OF CPC: A celebratory issue focused on quality software for high performance, Computer Physics Communications, vol.180, issue.12, pp.2452-2471, 2009. ,
Predicting patientspecific radiotherapy protocols based on mathematical model choice for proliferation saturation index, Bulletin of mathematical biology, vol.80, pp.1195-1206, 2018. ,
A computational framework to assess the efficacy of cytotoxic molecules and vascular disrupting agents against solid tumours, Math. Model. Nat. Phenom, vol.7, issue.1, pp.49-77, 2012. ,
URL : https://hal.archives-ouvertes.fr/hal-00847022
Bystander effects and their implications for clinical radiation therapy: Insights from multiscale in silico experiments, Journal of theoretical biology, vol.401, pp.1-14, 2016. ,
Systems oncology: towards patient-specific treatment regimes informed by multiscale mathematical modelling, Seminars in cancer biology, vol.30, pp.13-20, 2015. ,
A proliferation saturation index to predict radiation response and personalize radiotherapy fractionation, Radiation oncology, vol.10, p.159, 2015. ,
The tissue organization field theory of cancer: a testable replacement for the somatic mutation theory, BioEssays : news and reviews in molecular, cellular and developmental biology, vol.33, pp.332-340, 2011. ,
How tumour-induced vascular changes alter angiogenesis: Insights from a computational model, Journal of theoretical biology, vol.419, pp.211-226, 2017. ,
Systems biology, systems medicine, systems pharmacology: The what and the why, Acta biotheoretica, 2018. ,
Mathematical modelling of flow in 2d and 3d vascular networks: applications to antiangiogenic and chemotherapeutic drug stategies, Mathematical and Computer Modelling, vol.41, pp.1137-56, 2005. ,
Chapter 13-multi-scale modeling of tissues using compucell3d, Computational Methods in Cell Biology, vol.110, pp.325-366, 2012. ,
An integrative computational model for intestinal tissue renewal, Cell Proliferation, vol.42, issue.5, pp.617-636 ,
Prognostic significance of growth kinetics in newly diagnosed glioblastomas revealed by combining serial imaging with a novel biomathematical model, Cancer Research, vol.69, issue.23, pp.9133-9173, 2009. ,
Spatial modeling of drug delivery routes for treatment of disseminated ovarian cancer, Cancer Research, vol.76, issue.6, pp.1320-1334, 2016. ,
Integrating imaging data into predictive biomathematical and biophysical models of cancer, ISRN biomathematics, 2012. ,
Quantitative multimodality imaging in cancer research and therapy, Nature reviews. Clinical oncology, vol.11, pp.670-680, 2014. ,
Multi-scale modeling in clinical oncology: Opportunities and barriers to success, Annals of biomedical engineering, vol.44, pp.2626-2641, 2016. ,