Computational Modeling & Data Analytics
In silico-based modeling and analysis allows for robust and reproducible quantitative assessment of tumor progression and treatment response. These methodologies integrate (and often simplify) the complex molecular and cellular interactions between cancer cells, host cells, and mechanical properties and forces in the heterogeneous tumor microenvironment. The insights from these high-throughput, low-cost approaches can be applied beyond cancer to other diseases that feature abnormal biological, chemical, electrical, and physical microenvironments (e.g., autoimmune disorders, infectious diseases, fibrotic conditions, and brain injuries). Applications include:
- Mathematical modeling of tumor growth, biotransport, and mechanics
- Biomarker-based predictive models of individual treatment response/resistance
- AI-assisted quantitative image analysis and digital pathology
- Computer-aided molecular design for drug discovery and design
- Bioinformatics and machine learning for “multi-omics” big-data integration
Publications
Datta M.#, Kennedy M., Siri S., Via L.E., Baish J.W., Xu L., Dartois V., Barry C.E., and Jain R.K.# (2024) “Mathematical model of oxygen, nutrient, and drug transport in tuberculosis granulomas,” PLoS Computational Biology, E-pub ahead of print: https://doi.org/10.1371/journal.pcbi.1011847. (# = corresponding authors.)
Zarodniuk M., Steele A., Lu X., Li J., and Datta M.# “CNS tumor stroma transcriptomics identify perivascular fibroblasts as predictors of immunotherapy resistance in glioblastoma patients,” npj Genomic Medicine, E-pub ahead of print: https://www.nature.com/articles/s41525-023-00381-w. (# = corresponding author.)
Datta M.#, Chatterjee S., Perez E.M., Gritsch S., Roberge S., Duquette M., Chen I.X., Naxerova K., Kumar A.S., Ghosh M., Emblem K.E., Ng M.R., Ho. W.W., Kumar P., Krishnan S., Dong X., Speranza M.C., Neagu M.R., Reardon D.A., Sharpe A.H., Freeman G.J., Suva M.L.#, Xu L.#, Jain R.K.# (2023) “Losartan controls immune checkpoint blocker-induced edema and improves survival in glioblastoma,” E-pub ahead of print: https://www.pnas.org/eprint/MP69MI2GBHTY9VJKDSBQ/full. (# = corresponding author(s).)
Nia H.T.*, Datta M.*, Seano G.*, Ho W.W., Roberge S., Huang P., Munn L.L. and Jain R.K. (2020) “In vivo compression and imaging in mouse brain to measure the effects of solid stress,” Nature Protocols, 15: 2021-2340. (* = equal contributions.) Featured in Nature Community.
Zhao Y. Cao J., Melamed A., Worley M., Gockley A., Jones D., Nia H.T., Zhang Y., Stylianopoulos T., Kumar A.S., Mpekris F., Datta M., Sun Y., Wu L., Gao X., Yeku O., del Carmen M., Spriggs D.R., Jain R.K., and Xu L. (2019) “Losartan treatment enhances chemotherapy efficacy and reduces ascites in ovarian cancer models by normalizing the tumor stroma,” Proceedings of the National Academy of Science, 116: 2210-2219. Featured in New England Journal of Medicine Journal Watch, Medical News Bulletin, Ovarian Cancer News Today, and Medical Xpress.
Arvanitis C.*, Askoxylakis V.*, Guo Y., Datta M., Kloepper J., Ferraro G.B., Bernabeu M.O., Fukumura D., McDannold N., and Jain R.K. (2018) “Mechanisms of enhanced drug delivery in brain metastases with focused ultrasound-induced blood-tumor barrier disruption,” Proceedings of the National Academy of Sciences, 115: E8717-E8726. (* = equal contributions.) Featured in Technology.org, EurekAlert and Medical Xpress.
Nia H.T.*, Datta M.*, Seano G., Munn L.L., and Jain R.K. (2018) “Quantifying solid stress and elastic energy from excised or in situ tumors,” Nature Protocols 13: 1091-1105. (* = equal contributions.)
Nia H.T., Seano G., Liu H., Datta M., Jones D., Rahbari N., Incio J., Chauhan V.P., Jung K., Martin J.D., Askoxylakis V., Padera T.P., Fukumura D., Boucher Y., Hornicek F.J., Grodzinsky A.J., Baish J.W., Munn L.L., and Jain R.K. (2016) “Solid stress and elastic energy as measures of tumor mechanopathology,”Nature Biomedical Engineering 1: 1-11. Featured in Nature News and Views, Nature Reviews Clinical Oncology, Harvard Medical School News & Research, Medical Xpress, and EurekAlert.
Datta M., Via L.E., Chen W., Baish J.W., Xu L., Barry C.E., and Jain R.K. (2016) “Mathematical Model of Oxygen Transport in Tuberculosis Granulomas,” Annals of Biomedical Engineering 44: 863-872.
Datta M., Jackson M.D., and Datta R. (2011) “Of Mice and Men: Their Diet, Metabolism, and Weight Change,” Chemical Engineering Science 66: 4510-4520.