Mathematical modeling to address challenges in pancreatic cancer

Prashant Dogra, Javier R. Ramírez, María J. Peláez, Zhihui Wang, Vittorio Cristini, Gulshan Parasher, Manmeet Rawat

Research output: Contribution to journalReview articlepeer-review

9 Scopus citations


Pancreatic Ductal Adenocarcinoma (PDAC) is regarded as one of the most lethal cancer types for its challenges associated with early diagnosis and resistance to standard chemotherapeutic agents, thereby leading to a poor five-year survival rate. The complexity of the disease calls for a multidiscipli-nary approach to better manage the disease and improve the status quo in PDAC diagnosis, prognosis, and treatment. To this end, the application of quantitative tools can help improve the understanding of disease mechanisms, develop biomarkers for early diagnosis, and design patient-specific treatment strategies to improve therapeutic outcomes. However, such approaches have only been minimally applied towards the investigation of PDAC, and we review the current status of mathematical modeling works in this field.

Original languageEnglish (US)
Pages (from-to)367-376
Number of pages10
JournalCurrent Topics in Medicinal Chemistry
Issue number5
StatePublished - 2020

All Science Journal Classification (ASJC) codes

  • Drug Discovery


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