Yuri Kogan
Yuri Kogan holds a BA degree in Theoretical Mathematics from the TelAviv University (TAU). Over many years of scientific research at IMBM, he has been involved in biomathematical modelling of several cancer indications, as well as in researching cancer stem cells, intracellular signal transduction, immune system functioning and clinical immunotherapy.
Scientific activity in 2022
During the recent year, Yuri lead the development of the novel algorithm for individual prediction of the immediate deterioration for the hospitalized Covid19 patients, based on their blood test results. For this project, we have established cooperation with Covid19 divisions in Sheba Hospital and in Barzilai Hospital, and have obtained realword patient data for the analysis and model development. Our model employs advanced Machine Learning methods and has retrospectively evaluated ROC AUC metric of 0.750.8 tested by crossvalidation and independent external validation.
Scientific activity in 2023
Yuri will focus on modelling the dynamics of immune system, in response to disease. The model will be applied to study response to viral infection, sepsis, and cancer immunotherapy. We will start by creating a population model of the longitudinal dynamics of immune response to Covid19 infection.
Publications


 Kogan Y, Robinson A, Itelman E, BarNur Y, Jakobson DJ, Segal G, et al. Developing and validating a machine learning prognostic model for alerting to imminent deterioration of hospitalized patients with COVID19. Sci Rep (2022) 12(1):19220

Albrecht M, Kogan Y, Kulms D, Sauter T. Mechanistically Coupled PK (MCPK) Model to Describe Enzyme Induction and Occupancy Dependent DDI of Dabrafenib Metabolism. Pharmaceutics 2022, 14, 310. https://doi.org/10.3390/pharmaceutics14020310

Agur Z, Elishmereni M, Foryś U, Kogan Y. Accelerating the Development of Personalized Cancer Immunotherapy by Integrating Molecular Patients’ Profiles with Dynamic Mathematical Models. Clinical Pharmacology & Therapeutics 2020. doi: https://doi.org/10.1002/CPT.1942

Perlstein D, Shlagman O, Kogan Y, et al. Personal response to immune checkpoint inhibitors of patients with advanced melanoma explained by a computational model of cellular immunity, tumor growth, and drug. Plos One. 2019;14(12):e0226869

Tsur N, Kogan Y, Rehm M, Agur Z. Response of Patients with Melanoma to Immune Checkpoint Blockade – Insights Gleaned from Analysis of a New Mathematical Mechanistic Model.Journal of Theoretical Biology 2019:110033. doi: 10.1016/j.jtbi.2019.110033. PubMed PMID: 31580835.

Tsur N, Kogan Y, AvizovKhodak E, Vaeth D, Vogler N, Utikal J, Lotem M, Agur Z. Predicting response to pembrolizumab in metastatic melanoma by a new personalization algorithm.Journal of Translational Medicine 2019;17(1):338. doi: 10.1186/s1296701920812. PubMed PMID: 31590677.

Hochman G, HaleviTobias K, Kogan Y, Agur Z. Extracellular inhibitors can attenuate tumorigenic Wnt pathway activity in adenomatous polyposis coli mutants: Predictions of a validated mathematical model. PLoS One 2017 Jul 14;12(7):e0179888.

Agur Z, HaleviTobias K, Kogan Y, et al. Employing Dynamical Computational Models for Personalizing Cancer Immunotherapy. J Expert Opinion on Biological Therapy , 2016.

Forys U, Bodnar M, Kogan Y.Asymptotic dynamics of some tperiodic onedimensional model with application to prostate cancer immunotherapy. J Math Biol 2016.

Kogan Y, Agur Z, Elishmereni M. A mathematical model for the immunotherapeutic control of the Th1/Th2 imbalance in melanoma. Discrete and Continuous Dynamics – Series B 2013, 18(4) pp. 10171030.

Kogan Y, HaleviTobias K, Elishmereni M, VukPavlović S, Agur Z. 2012. Reconsidering the Paradigm of Cancer Immunotherapy by Computationally Aided RealTime Personalization. Cancer Research, Published OnlineFirst March 15, 2012; doi: 10.1158/00085472.
 Kogan Y, HaleviTobias KE, Hochman G, Baczmanska AK, Leyns L, Agur, Z. A new validated mathematical model of the Wnt signaling pathway predicts effective combinational therapy by sFRP and Dkk Biochem J 2012, 443, doi:10.1042/BJ20111887.
 Vainstein V, Kirnasovsky O, Kogan Y, Agur Z, Strategies for cancer stem cell elimination: Insights from mathematical modeling. J Theor Bol 2012, vol. 298, pp. 32–41.
 Kronik N, Kogan Y, Schlegel PG, Wölfl M. Improving Tcell Immunotherapy for Melanoma Through a Mathematically Motivated Strategy: Efficacy in Numbers? J of Immunotherapy 2012 35(2).
 Agur Z, Bloch N, Gorelik B, Kleiman M, Kogan Y, Sagi Y, Sidreansky D, Ronen Y. Developing Oncology Drugs Using Virtual Patients of Vascular Tumor Diseases. In Systems Biology in Drug Discovery and Development, Young DL, Michelson S. (eds). Wiley, 2011, pp 203231.
 Agur Z, Kirnasovsky OU, Vasserman G, TencerHershkowicz L, Kogan Y, Harrison H, et al. Dickkopf1 regulates fate decision and drives breast cancer stem cells to differentiation: an experimentally supported mathematical model. PLoS One 2011 6(9) e24225.
 Kronik N., Kogan Y., Elishmereni M., HaleviTobias K., Vuk Pavlović S., Agur Z. Predicting Effect of Prostate Cancer Immunotherapy by Personalized Mathematical Models PLoS One 2010 5(12) e15482.
 Agur Z., Kogan Y., Levi L., Harrison H., Lamb R., Kirnasovsky O.U., Clarke R.B. Disruption of a Quorum Sensing Mechanism Triggers Tumorigenesis: a Simple Discrete Model Corroborated by Experiments in Mammary Cancer Stem Cells. Biol Direct 2010 5(1) pp.2041.
 Kogan Y., Forys U., Shukron O., Kronik N., Agur Z. Cellular immunotherapy for high grade Gliomas: mathematical analysis deriving efficacious infusion rates based on patient requirements. SIAM J. Appl. Math. 2010 70(6) pp. 19531976.
 Agur Z, Elishmereni M, Kogan Y, Kheiffetz Y, Ziv I, Shoham M, Vainstein V. Mathematical modeling as a new approach for improving the efficacy/toxicity profile of drugs: the thrombocytopenia case study, Preclinical Development Handbook, Shayne Gad Ed., John Wiley and Sons, USA. 2008, pp 12291266.
 Kirnasovsky O, Kogan Y, Agur Z. Analysis of a Mathematical Model for the Molecular Mechanism of Fate Decision in Mammary Stem Cells, Mathematical Modelling of Natural Phenomena. 2008 3(7) pp. 7889.
 Kirnasovsky OU, Kogan Y, Agur Z. Resilience in stem cell renewal: development of the Agur–Daniel–Ginosar model. Discrete and Continuous Dynamical Systems – Series B (DCDSB), Volume: 10, Number: 1, July 2008
 Kronik N, Kogan Y, Vainstein V, Agur Z, Improving alloreactive CTL immunotherapy for malignant gliomas by a computerized model. Cancer Immunology, Immunotherapy, Vol. 57, pp.424439, 2008.
 Agur Z, Elishmereni M, Kogan Y, Kheifetz Y, Ziv I, Shoham M, Vainstein V, Mathematical modeling as a new approach for improving the efficacy/toxicity profile of drugs: the thrombocytopenia case study. In: Preclinical Development Handbook, John Wiley and Sons. 2008.
 Kogan Y, Ribba B, Marron K, Dahan N, Vainshtein V, Agur Z. 2004. Intensified DoxorubicinBased Regimen Efficacy in Residual NonHodgkin’s Limphoma Disease: Towards a Computationally Supported Treatment Improvement. Mathematical Modelling of Natural PhenomenaVol. 2, No. 3, 2007, pp. 4768.
 Vainstein V., Ginosar Y., Shoham M., Ianovski A., Rabinovich A., Kogan Y., Selitser V., Agur Z. Improving cancer therapy by Doxorubicin and Granulocyte colonystimulating factor: Insights from a Computerized Model of Human Granulopoiesis. Mathematical Modelling of Natural Phenomena 2006 1(2), pp.7080.
 Kheifetz Y, Kogan Y, Agur Z, Longrange predictability in models of cell populations subjected to phasespecific drugs: growthrate approximation using properties of positive compact operators, M3AS, 16(7) Supp, July 20061115
 Forys U, Kheiffez Y, Kogan Y, Critical point analysis for threedimensional cancer angiogenesis models, Mathematical Biosciences and Engineering, vol.2 num.3, August 2005.
 Kheiffez Y, Kogan Y, Agur Z., 2004. Matrix and compact operator description of resonance and antiresonance in cell populations subjected to phasespecific drugs. Journal of medical informatics and technologies. Vol. 8, 2004, MM11MM29
 Arakelyan L, Merbl Y, Daugulis P, Ginosar Y, Vainstain V, Kogan Y, Selitser V, Harpak H and Agur Z. 2002. Using multiscale mathematical modeling in antiangiogenic therapy, Chap. 7 in Cancer Modeling and Simulation Mathematical Biology and Medicine Series, Chapman & Hall/CRC
