
Sebastien Benzekry
- Méthodes computationnelles pour la prise en charge thérapeutique en oncologie : Optimisation des stratégies par modélisation mécaniste et statistique (COMPO)
Présentation
Sebastien Benzekry is a scientific researcher (PhD, HDR) at Inria, the french institute for applied mathematics, computer science and their applications. He has created (in 2021) and heads the Inria – Inserm (French national institute for biomedical research) project-team COMPO (COMPutational pharmacology and clinical Oncology), affiliated to both Inria and the Center for Research on Cancer of Marseille (Inserm U1068, CNRS UMR7258, Institut Paoli-Calmettes Institute, Aix-Marseille University, Faculty of Pharmacy). The objective of his research is to model data arising from (clinical) oncology in order to 1) bring clinical decision tools to enhance therapeutic management, 2) better inform and design clinical trials and 3) test biological hypotheses. To do so, he combines mechanistic (i.e., simulation models of the pharmaco-patho-physiological processes in cancer) and statistical learning through an approach termed 'mechanistic learning'. He has fifteen years of experience in trans-disciplinary projects in oncology, with a strong track record of publications in high impact journals (Cancer Res, PLoS Comp Biol, Clin Pharmacol Ther,...). His main topics of research are modeling metastatic development and immuno-oncology, integrating longitudinal data. These are implemented into code libraries developed with a focus on software development standards.
Dr Benzekry has an initial training in applied mathematics (Ecole Normale Supérieure) followed by a PhD at Aix-Marseille University and further training in computational / systems biology as a postdoc in the Center for Cancer and Systems Biology, Tufts Univ, Boston, MA.
Citations: 2095, h-index 24 (11/2011 – 03/2024), 50 research articles, 24 book chapters, editorials and proceedings.
https://team.inria.fr/compo/ https://www-sop.inria.fr/members/Sebastien.Benzekry/index.html https://scholar.google.fr/citations?user=xsLpdFAAAAAJ&hl=fr&oi=ao
Publications
Publications
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Mechanistic Modeling of Joint Circulating Cell-free DNA Concentration—Tumor Size Kinetics under Immune-Checkpoint Inhibitors in Advanced CancerPAGE 2025 - 33th Annual meeting of the Population Approach Group of Europe, Jun 2025, Thessalokini, Greece
Communication dans un congrès
hal-05241536
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Integrating tumor kinetics and circulating cell-free DNA markers through mechanistic modeling for early prediction of immunotherapy responseKSMB-SMB 2024 - Joint annual meeting of the Korean Society for Mathematical Biology and the Society for Mathematical Biology, Jul 2024, Seoul, South Korea
Communication dans un congrès
hal-04665038
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Mechanistic modelling of tumor kinetics coupled with biomarker dynamics for survival prediction in non-small cell lung cancer patientsPAGE meeting XXXII - 2024 Population approach group meeting, 2024, Roma, France
Communication dans un congrès
hal-04880274
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Precision Immuno-Oncology in NSCLC: Challenges in machine learning biomarkers researchEORTC PAMM 2024 - 44th Meeting of the European Organization of Research and Treatment of Cancer (EORTC) – Pharmacology and Molecular Mechanisms (PAMM) Group, Feb 2024, Marseille, France
Communication dans un congrès
hal-04990474
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Mechanistic Learning to predict the results of clinical trialsAMLD 2024 - Applied Machine Learning Days, Mar 2024, Lausanne, Switzerland
Communication dans un congrès
hal-04990478
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Integrating kinetics and machine learning modeling for prediction of outcome following immunotherapy in lung cancerECMTB 2024 - European Conference on Theoretical and Mathematical Biology, Jul 2024, Toledo (Spain), Spain
Communication dans un congrès
hal-04990489
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Integrative kinetics and machine learning modeling for prediction of outcome following immunotherapy in lung cancerKSMB-SMB 2024 - Joint annual meeting of the Korean Society for Mathematical Biology and the Society for Mathematical Biology, Jun 2024, Seoul, South Korea
Communication dans un congrès
hal-04990485
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Machine Learning to Predict Survival and Resistance to Immune Checkpoint InhibitionTwelfth International Workshop on Pharmacodynamics of Anticancer Agents, Sep 2024, Ponta Delgada (Açores), Portugal
Communication dans un congrès
hal-04990492
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Une comparaison des algorithmes d'apprentissage pour la survie avec données manquantesJDS 2023 - 54e Journées de Statistique de la SFds, SFdS, Jul 2023, Bruxelles (BEL), Belgique. ⟨10.48550/arXiv.2303.13590⟩
Communication dans un congrès
hal-04384220
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Artificial intelligence in healthcare data warehousesAnnual congress of the French group of clinical pneumo-oncology (GPCO), Jun 2023, Toulon, France
Communication dans un congrès
hal-04388413
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Using statistical learning for clinical trialsAnnual meeting of the APHM center for early phase clinical trials in oncology, Jun 2023, Marseille, France
Communication dans un congrès
hal-04388605
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Integrative kinetics and machine learning modeling for prediction of outcome following immunotherapy in lung cancerSMAI 2023 congress - 11th French Biennial of Applied and Industrial Mathematics, May 2023, Le Gosier (Guadeloupe), France
Communication dans un congrès
hal-04388478
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Integrative kinetics and machine learning modeling for prediction of outcome following immunotherapy in lung cancerCARe graduate school workshop, Jan 2023, Toulouse, France
Communication dans un congrès
hal-04388750
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Integrative kinetics and machine learning modeling for prediction of outcome following immunotherapy in lung cancerWorkshop for young researchers in Cancer 2023, Cancéropôle PACA, Oct 2023, Porquerolles, France
Communication dans un congrès
hal-04388572
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Mechanistic modeling of the longitudinal tumor and biological markers combined with quantitative cell-free DNA2023 SMB annual meeting - Annual Meeting of the Society for Mathematical Biology, Society for Mathematical Biology, Jul 2023, Columbus (Ohio), United States
Communication dans un congrès
hal-04388020
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Integrative kinetics and machine learning modeling for prediction of outcome following immunotherapy in lung cancerAnnual congress of the French society of pharmacology and therapeutics (SFPT), Jun 2023, Limoges, France
Communication dans un congrès
hal-04388499
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3MO - Comprehensive biomarkers (BMs) analysis to predict efficacy of PD1/L1 immune checkpoint inhibitors (ICIs) in combination with chemotherapy: a subgroup analysis of the Precision Immuno-Oncology for advanced Non-Small CEll Lung CancER (PIONeeR) trial2022 ESMO Immuno-Oncology Congress, Dec 2022, Geneva, Switzerland
Communication dans un congrès
hal-03928784
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Supporting decision making and early prediction of survival for oncology drug development using a pharmacometrics-machine learning based modelPAGE - Population Approach Group Europe, Jun 2022, Ljubljana, Slovenia
Communication dans un congrès
hal-03921394
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Mechanistic modeling of the combination between cytotoxics and anti-angiogenics for sequence optimizationQuantitative Systems Pharmacology, Leiden University, Apr 2022, Leiden (Netherlands), Netherlands
Communication dans un congrès
hal-05239911
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Quantitative modeling of metastasis: cancer at the organism scale8th international conference on Systems Biology of Mammalian Cells: From Systems Medicine towards Digital Health, May 2022, Heidelberg (Germany), Germany
Communication dans un congrès
hal-05239921
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Quantitative modeling of metastasis: cancer at the organism scaleMini-symposium "Mathematical approaches to advance clinical studies in oncology", Annual conference of the Society of Mathematical Biology (SMB), 2021, Virtual conference, United States
Communication dans un congrès
hal-05239934
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Machine learning versus mechanistic modeling for prediction of metastatic relapse in breast cancer2019 CSBC-PSON Mathematical Oncology Meeting, May 2019, Portland, United States
Communication dans un congrès
hal-02424419
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Data-driven mechanistic modeling of metastasis: cancer at the organism scaleRITS conference (Recherche en Imagerie et Technologies pour la Sante) of the French Society of Biomedical Engineering (SFGBM), May 2019, Tours, France
Communication dans un congrès
hal-02424452
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Mechanistic modeling of metastasis: cancer at the organism scaleInternational Society of Pharmacometrics (ISoP) workshop, Jul 2019, Paris, France
Communication dans un congrès
hal-02424424
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Mathematical Modeling of Tumor-Tumor Distant Interactions Supports a Systemic Control of Tumor Growth3rd Mathematical Biology Modeling days of Besançon, Jun 2018, Besançon, France
Communication dans un congrès
hal-01969102
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Optimization of sequential administration of bevacizumab plus cytotoxics in non-small cell lung cancer by combining in vivo experiments and mathematical modelingMathematical perspectives in the biology and therapeutics of cancer, Jul 2018, Marseille, France
Communication dans un congrès
hal-01969142
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Mathematical Modeling and Prediction of Clinical MetastasisMathematical Challenges in the Analysis of Continuum Models for Cancer Growth, Evolution and Therapy, Nov 2018, Oaxaca, Mexico
Communication dans un congrès
hal-01969108
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Optimized radiotherapy protocols delay the malignant transformation of low-grade gliomas in-silico5th Quadrennial Meeting of the World Federation of Neuro-Oncology Societies, May 2017, Zurich, Switzerland. pp.iii12 - iii12, ⟨10.1093/neuonc/nox036.040⟩
Communication dans un congrès
hal-01517899
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Abstract 2099: Model-driven optimization of anti-angiogenics combined with chemotherapy: application to bevacizumab + pemetrexed/cisplatin doublet in NSCLC-bearing mice107th Annual Meeting of the American Association for Cancer Research, 2016, New Orleans, France. pp.20, ⟨10.1158/1538-7445.AM2016-2099⟩
Communication dans un congrès
hal-01404637
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On the growth and dissemination laws in a mathematical model of metastatic growthWorkshop on Multiscale and Hybrid Modelling in Cell and Cell Population Biology, Mar 2015, Paris, France. ⟨10.1051/itmconf/20150500007⟩
Communication dans un congrès
hal-01222088
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A mathematical model of systemic inhibition of angiogenesis in metastatic developmentCongres SMAI 2013, May 2013, Seignosse, France. pp.75-87, ⟨10.1051/proc/201445008⟩
Communication dans un congrès
hal-00867992
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Model-based optimization of combined antiangiogenic + cytotoxics modalities: application to the bevacizumab-paclitaxel association in breast cancer modelsAACR Annual Meeting 2014, Apr 2014, San Diego, United States. ⟨10.1158/1538-7445.AM2014-3677⟩
Communication dans un congrès
hal-01090883
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Population Modeling of Tumor Growth Curves, the Reduced Gompertz Model and Prediction of the Age of a TumorMathematical and Computational Oncology, pp.87-97, 2019, ⟨10.1007/978-3-030-35210-3_7⟩
Chapitre d'ouvrage
hal-02383995
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A Mathematical Model for Growing Metastases on Oncologists’s ServiceComputational Surgery and Dual Training, Springer, pp.331 - 338, 2014, ⟨10.1007/978-1-4614-8648-0_21⟩
Chapitre d'ouvrage
hal-01087708
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<a href="https://mathematical-oncology.org/blog/mechanistic-learning-in-action-at-compo.html">Mechanistic learning in action at COMPO</a>blog post. 2025
Rapport
hal-05243544
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Mathematical modeling of tumor and metastatic growth when treated with sunitinib[Research Report] Inria Bordeaux Sud-Ouest. 2016
Rapport
(rapport de recherche)
hal-01377994
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Around a mathematical model of the concomitant tumor resistance phenomenon[Research Report] INRIA Bordeaux; Equipe MONC; INSA Toulouse. 2016
Rapport
(rapport de recherche)
hal-01420449
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Modeling, mathematical and numerical analysis of anti-cancerous therapies for metastatic cancersAnalysis of PDEs [math.AP]. Université Aix-Marseille 1 – Université de Provence, 2011. English. ⟨NNT : ⟩
Thèse
tel-01658210
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Contributions in Mathematical Oncology: When Theory Meets RealityMathematics [math]. Université de Bordeaux, 2017
HDR
tel-01658070
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Mechanistic learning to predict response and survival in immuno-oncology: A modeling journey in immuno-oncologyDoctoral. BIOMAT 2024 - 19th International Summer School, Granada (Spain), Spain. 2024
Cours
hal-04990482
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Quantitative modeling of metastasis: cancer at the organism scaleDoctoral. United States. 2021
Cours
hal-03261886
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