Dollars for Profs
Dig Into University Researchers' Outside Income and Conflicts of Interest
Published Dec. 6, 2019
This database was last updated in December 2019 and should only be used as a historical snapshot. There may be new or amended records not reflected here.
Conflict of Interest
Institutions must file significant disclosures to the National Institutes of Health if they determine financial relationships could affect the design, conduct or reporting of the NIH-funded research. The NIH provided us with their entire financial conflict of interest database, with filings from 2012 through 2019.
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Shiladitya Sengupta
Brigham and Women's Hospital, Department: Na
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Mitra Biotech Pvt. Ltd. (formerly know as Mitra Life Sciences)
Equity Interest - Non-publicly traded entity ( e.g., stock, stock option, or other ownership interest)
The grant proposes to engineer, characterize, and validate a cancer ecosystem‐on‐a‐chip platform using breast cancer explants, and develop and train a machine‐learning algorithm to accurately predict a cancer patient’s response to therapy. Mitra Biotech offers
CANscript™ platform, a product that recreates a patient’s tumor microenvironment in vitro, evaluates that patient’s tumor response to tested treatments, and accurately predicts how that cancer patient will respond to treatment. The Institution determined that research is related to the financial interest, and that the financial interest creates a financial conflict of interest under the PHS regulations.
Engineering personalized micro-tumor ecosystems
Narrative Despite the recent development of subtype-specific personalized therapy based on achievements in the fields of molecular and genetic profiling, the cancer treatment still has low efficacy that mostly arise from the limited ability of existing models to recapitulate the tumor heterogeneity and therefore predict the patient tumor responses to therapeutic agents. We propose to develop a novel personalized breast-cancer-ecosystem platform for personalized screening of cancer chemotherapeutics with extremely high accuracy by utilizing patient-derived tumor explant culture, defined tumor grade-matched biomaterial matrices, and autologous patient serum to mimic patient-specific tumor hallmarks. The integration of a machine-learning algorithm will further provide precise and unbiased prediction of the patient responses to chemotherapeutics based on the data gathered from the engineered tumor ecosystem.
Filed on September 26, 2017.
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Notes: When a more specific filing date is not available for an individual financial disclosure or conflict of interest form, we use the year the form was filed. If the year was not disclosed, we report the range of years covered by our public records requests. In a few cases, a start date was provided instead of a filing date. In those cases, we use the start date instead.
Fewer than 10% of records from the University of Florida and fewer than 1% of records from the University of Texas system were removed because they did not contain enough information.
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