CV

I received my PhD in Applied Mathematics for Life and Social Sciences from Arizona State University. My research has been focused on mathematical modeling of cancer as an evolving ecological system, with particular focus on applying insights from ecology and evolution to understanding cancer initiation and progression.

I did my post-doctoral fellowship at Tufts Medical Center in Boston, focusing on mechanisms that enable transition from normal blood vessel formation to pathological angiogenesis using both ODEs and agent-based modeling.

I joined EMD Serono (US business of Merck KGaA) in 2016 and am currently an Associate Director in the Quantitative Pharmacology Department. I have an academic affiliation in Eduardo Sontag's lab at Northeastern University in Boston. I am also passionate about process efficiency and improvement and am a certified Lean Six Sigma green belt.

Education and Training

2020-2021 Harvard Medical School (HMS) Clinical Scholars program, Boston, MA

2018-2019 Harvard Medical School (HMS) High-Impact Cancer Research (HI-CR) program

2017-2020 Master of Business Administration (MBA), Isenberg School of Management, University of Massachusetts, Amherst, MA, USA.

2014-2015 Research Associate, Floating Hospital for Children, Tufts Medical Center, Boston, MA.

2012-2013 Postdoctoral fellow at Center of Cancer Systems Biology (CCSB), St. Elizabeth's Medical Center, Boston, MA.

2009-2011 Ph.D. Applied Mathematics in Life and Social Sciences (AMLSS), Arizona State University, Tempe, AZ

Advisor: Carlos Castillo-Chavez, Co-advisor: John Nagy

Title: “Niche Construction, Sustainability and Evolutionary Ecology of Cancer”

2003-2008 B.S. Mathematics / B.A. Music (Vocal Performance),

University of Maryland, College Park

2004-2005 Universität Wien, Vienna, Austria (study abroad)

Research Papers

1. Kareva I. From hyperinsulinemia to cancer progression: how diminishing glucose storage capacity fuels insulin resistance. Aging and Cancer. 2024.
2. Kareva I, Gevertz JL. Mitigating non-genetic resistance to checkpoint inhibition based on multiple states of immune exhaustion. npj Systems Biology and Applications. 2024 Feb 9;10(1):14.
3. Kareva I, Brown JS. Evolutionary and ecological perspective on the multiple states of T cell exhaustion. InCancer through the Lens of Evolution and Ecology 2024 May 29 (pp. 92-104). CRC Press.
4. Gevertz JL, Kareva I. Minimally sufficient experimental design using identifiability analysis. npj Systems Biology and Applications. 2024 Jan 6;10(1):2.
5. Gevertz JL, Kareva I. Guiding model‐driven combination dose selection using multi‐objective synergy optimization. CPT: Pharmacometrics & Systems Pharmacology. 2023 Jul 6.
6. Kareva I, Gevertz JL. Cytokine storm mitigation for exogenous immune agonists. Mathematics of Control, Signals, and Systems. 2024 Jun;36(2):329-50.
7. Craig M, Gevertz JL, Kareva I, Wilkie KP. A practical guide for the generation of model-based virtual clinical trials. Frontiers in Systems Biology. 2023 Jun 16;3:1174647.
8. Kareva I. Serotonin signaling in the enteric nervous system and connection to autism spectrum disorder: a translational mathematical model. Applied Sciences. 2023 Feb 25;13(5):2970.
9. Kareva I. Understanding Metabolic Alterations in Cancer Cachexia through the Lens of Exercise Physiology. Cells. 2022 Jul 27;11(15):2317.
10. Kareva I. Different costs of therapeutic resistance in cancer: Short-and long-term impact of population heterogeneity. Mathematical Biosciences. 2022 Oct 1;352:108891.
11. Kareva I, Zutshi A, Madrasi K. Mathematical modeling of SARS-CoV-2 viral dynamics and treatment with monoclonal antibodies. Ifac-papersonline. 2022 Jan 1;55(23):175-9
12. Kareva I, Berezovskaya F, Karev G. Mathematical model of a cytokine storm. bioRxiv. 2022 Feb 16:2022-02.
13. Kareva I, Zutshi A, Madrasi K. Mathematical modeling of SARS-CoV-2 viral dynamics and treatment with monoclonal antibodies. Ifac-papersonline. 2022 Jan 1;55(23):175-9.
14. Kareva I, Kabilan S, Zutshi A, Rhoden J. Practical guide to calculating impact of avidity in models of bispecific antibodies with two membrane-bound targets. bioRxiv. 2022:2022-09.
15. Kareva I, Luddy KA, O’Farrelly C, Gatenby RA, Brown JS. Predator-Prey in Tumor-Immune Interactions: A Wrong Model or Just an Incomplete One?. Frontiers in Immunology. 2021:3391.
16. Kareva I, Zutshi A, Gupta P, Kabilan S. Bispecific antibodies: A guide to model informed drug discovery and development. Heliyon. 2021 Jul 1;7(7):e07649.
17. Kareva I, Brown JS. Estrogen as an Essential Resource and the Coexistence of ER+ and ER-Cancer Cells. Frontiers in Ecology and Evolution. 2021 Aug 17:534.
18. Kareva I, Zutshi A, Mateo CV, Papasouliotis O. Identifying Safety Thresholds for Immunosuppressive Drugs: Applying Insights from Primary Antibody Deficiencies to Mitigate Adverse Events in Secondary Antibody Deficiencies Using Mathematical Modeling of Preclinical and Early Clinical Data. European journal of drug metabolism and pharmacokinetics. 2021 Sep;46(5):601-11.
19. Antoine M. Dujon, Athena Aktipis, Catherine Alix-Panabières, Sarah R. Amend, Amy M. Boddy, Joel S. Brown, Jean-Pascal Capp, James DeGregori, Paul Ewald, Robert Gatenby, Marco Gerlinger, Mathieu Giraudeau, Rodrigo K. Hamede, Elsa Hansen, Irina Kareva, Carlo C. Maley, Andriy Marusyk, Nicholas McGranahan, Michael J. Metzger, Aurora M. Nedelcu, Robert Noble, Leonard Nunney, Kenneth J. Pienta, Kornelia Polyak, Pascal Pujol, Andrew F. Read, Benjamin Roche, Susanne Sebens, Eric Solary, Kateřina Staňková, Holly Swain Ewald, Frédéric Thomas, Beata Ujvari. Identifying key questions in the ecology and evolution of cancer. Evolutionary applications. 2021 Apr;14(4):877-92.
20. Beckman RA, Kareva I, Adler FR. How Should Cancer Models Be Constructed?. Cancer Control. 2020 Sep 25;27(1):1073274820962008.
21. Kareva I. Immune Suppression in Pregnancy and Cancer: Parallels and Insights. Translational Oncology. 2020 Jul 1;13(7):100759.
22. Tran AP, Ali Al-Radhawi M, Kareva I, Wu J, Waxman DJ, Sontag ED. Delicate balances in cancer chemotherapy: Modeling immune recruitment and emergence of systemic drug resistance. Frontiers in immunology. 2020 Jun 30;11:1376.
23. Chelliah V, Lazarou G, Bhatnagar S, Gibbs JP, Nijsen M, Ray A, Stoll B, Thompson RA, Gulati A, Soukharev S, Yamada A…Kareva I., …and A.Kierzek. Quantitative Systems Pharmacology approaches for Immuno‐oncology: adding virtual patients to the development paradigm. Clinical Pharmacology & Therapeutics. 2020 Jul 19.
24. Kareva I, Karev G. Linear rather than exponential decay: a mathematical model and underlying mechanisms. arXiv preprint arXiv:2004.05726. 2020 Apr 13.
25. Kareva I. Concise Review: Metabolism and Gut Microbiota in Cancer Immunoediting, CD8/Treg Ratios, Immune Cell Homeostasis, and Cancer (Immuno) Therapy. Stem Cells. 2019 Jul 17.
26. Kareva I. Combining Bifurcation Analysis and Population Heterogeneity to Ask Meaningful Questions. In Advanced Mathematical Methods in Biosciences and Applications, 2019 (pp. 89-110). Springer.
27. Kareva I, Karev G. Natural Selection Between Two Games with Applications to Game Theoretical Models of Cancer. Bulletin of mathematical biology. 2019 Apr 23:1-6.
28. Kareva, I., Zutshi, A. and Kabilan, S. (2018). Guiding principles for mechanistic modeling of bispecific antibodies. Progress in biophysics and molecular biology, https://doi.org/10.1016/j.pbiomolbio.2018.08.011.
29. Thomas, F., Kareva, I., Raven, N., Hamede, R., Pujol, P., Roche, B., & Ujvari, B. (2018). Evolved Dependence in Response to Cancer. Trends in ecology & evolution.
30. Kareva, I., & Karev, G. (2018). From Experiment to Theory: What Can We Learn from Growth Curves?. Bulletin of mathematical biology, 80(1), 151-174.
31. Kareva, I. (2017). A Combination of Immune Checkpoint Inhibition with Metronomic Chemotherapy as a Way of Targeting Therapy-Resistant Cancer Cells. International journal of molecular sciences, 18(10), 2134.
32. Kareva, I. (2016) "Cancer as a disease of homeostasis: an angiogenesis perspective", Ecology and Evolution of Cancer. Eds. Beata Ujvari, Benjamin Roche & Frédéric Thomas, Elsevier, in press.
33. Kareva I., Abou-Slaybi A., Dodd O., Dashevsky O. and G. L. Klement (2016). "Normal wound healing and tumor angiogenesis as a game of competitive inhibition", PLoS ONE, 2016 Dec 9;11(12):e0166655. doi: 10.1371/journal.pone.0166655. PubMed PMID: 27935954.
34. Kareva, I. (2016) "Primary and metastatic tumor dormancy as a result of population heterogeneity", Biology Direct, 11:37, DOI 10.1186/s13062-016-0139-0.
35. Karev, G. and I. Kareva (2016). "Mathematical modeling of extinction of inhomogeneous populations", Bulletin of Mathematical Biology, 78(4): 834-858.
36. Kareva, I. (2016). "Escape from tumor dormancy and time to angiogenic switch as mitigated by tumor-induced stimulation of stroma", Journal of Theoretical Biology, 395:11-22. doi: 10.1016/j.jtbi.2016.01.024. Epub 2016 Jan 27. PubMed PMID: 26826487.
37. Kareva, I. (2015). " Cancer ecology: niche construction, keystone species, ecological succession and ergodic theory", Biological Theory, 10(4), 283-288. DOI: 10.1007/s13752-015-0226-y.
38. Kareva, I. and F. Berezovskaya (2015). "Cancer immunoediting: a process driven by metabolic competition as a predator-prey-shared resource type model", Journal of Theoretical Biology, pii: S0022-5193(15)00286-6. doi: 10.1016/j.jtbi.2015.06.007.
39. Kareva I., Waxman, D. and G. Klement (2015). "Metronomic chemotherapy: an attractive alternative to maximum tolerated dose therapy. Prevention of therapeutic resistance and improved anti-tumor immunity". Cancer Letters 28; 358(2):100-6. doi:10.1016/j.canlet.2014.12.039.
40. Kareva, I. (2015) "Immune Evasion through Competitive Inhibition: the Shielding Effect of non-Stem Cancer Cells", Journal of Theoretical Biology, 364:40-8. doi: 10.1016/j.jtbi.2014.08.035.
41. Kareva I., Morin B. and C. Castillo-Chavez (2015). "Resource consumption, sustainability and cancer", Bulletin of Mathematical Biology, 77(2):319-38.
42. Kareva, I. (2014) “Competition driven cancer immunoediting”, arXiv preprint.
43. Kareva, I. and G. Karev (2014) Replicator equations and models of biological populations and communities , Mathematical Modeling of Natural Phenomena, 9(3): 68-95.
44. Kareva I. and P. Hahnfeldt. (2013) The emerging “hallmarks” of metabolic reprogramming and immune evasion: distinct or linked? Cancer Research. 73(9):2737-42.
45. Kareva I. (2013) Biological stoichiometry in tumor microenvironments. PLoS One. 8(1):e51844.
46. Kareva, I., Berezovkaya, F., & Karev, G. (2013). Mixed strategies and natural selection in resource allocation. Math Biosci Eng, 10(5-6), 1561-1586.
47. Kareva I., Morin B. and G. Karev (2013) Preventing the tragedy of the commons through punishment of over-consumers and encouragement of under-consumers. Bulletin of Mathematical Biology 75(4):565-88.
48. Kareva I., Berezovskaya F. and C. Castillo-Chavez (2012) Transitional regimes as early warning signals in resource-dependent competition models. Mathematical Biosciences 240(2):114-23.
49. Kareva I. (2011) Prisoner’s dilemma in cancer metabolism. PloS ONE, 6(12), e28576.
50. Kareva I. (2011) What can ecology teach us about cancer? Translational Oncology, 4(5), 266-270.
51. Redon, C., Dickey, J., Nakamura, A., Kareva, I., Naf, D., Nowsheen, S., Kryston, T., Bonner, W., Georgakilas, A., Sedelnikova, O. (2010) Tumors induce complex DNA damage in distant proliferative tissues in vivo. PNAS, 107(42): 17992-17997.
52. Kareva I., Berezovskaya F. and C. Castillo-Chavez (2009) Myeloid cells in tumour–immune interactions. Journal of Biological Dynamics, 4(4):315-327.

Books

Kareva, I and G. Karev (2019). Modeling Evolution of Heterogeneous Populations, Academic Press, ISBN: 976-0-12-814368-1.

Kareva, I. (2018). Understanding Cancer from a Systems Biology Point of View: From Observation to Theory and Back. Elsevier Science, ISBN: 9780128136744.

Kareva, I (2015). Niche construction, sustainability, and evolutionary ecology of cancer. Scholars’ Press, ISBN: 978-3-639-86077-1.