Deerfield
About Deerfield

Launched in 1994, Deerfield Management Company is an investment firm dedicated to advancing healthcare through information, investment, and philanthropy—all toward the end goal of cures for disease, improved quality of life, and reduced cost of care.

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Investment

Supporting companies across the healthcare ecosystem with flexible funding models…

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Information

Delivering market research to the Deerfield team, its portfolio companies and other partners.

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Philanthropy

A New York City-based not-for-profit devoted to advancing innovative health care initiatives.

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Portfolio Companies

Deerfield generally maintains a combined portfolio of more than 150 private and public investments across the life science, medical device, diagnostic, digital health and health service industries at all stages of evolution from start-up to mature company.

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Research Collaborations

Deerfield partners with leading academic research centers, providing critical funding and expertise to further sustain and accelerate the commercialization of discoveries toward meaningful societal impact by advancing cures for disease.

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Strategic Partners

As a strategic partner, Deerfield offers capital, scientific expertise, business operating support, and unique access to innovation.

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Deerfield Foundation

The Deerfield Foundation is a New York City-based not-for-profit organization whose mission is to improve health, accelerate innovation and promote human equity.

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Cure Campus

Cure is a 12-story innovations campus in New York City that intends to bring together innovators from academia, government, industry, and the not-for-profit sectors to advance human health and accelerate the fight against disease.

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Cure Programming

Cure has a series of expert lectures intended to advance thought in healthcare, management, innovation, policy, and other relevant subjects. This fosters growth and education for those at Cure and its guests.

Events at the Cure

Adverse drug reaction early warning using user search data

Purpose

This research proposes a framework to detect adverse drug reactions using Internet user search data, so that adverse drug reaction events can be identified early. Empirical investigation of Avandia, a type II diabetes treatment, is con-ducted to illustrate how to implement the proposed framework.

Design/methodology/approach

Typical adverse drug reaction identification measures and time series processing techniques are used in the proposed framework. Google Trends Data is employed to represent user searches. The baseline model is a disproportionality anal-ysis using official drug reaction reporting data from the U.S. Food and Drug Administration’s (FDA) Adverse Event Re-porting System (FAERS).

Findings

Results show that Google Trends series of Avandia side effects search reveal a significant early warning signal for the side effect emergence of Avandia. The proposed approach of using user search data to detect adverse drug reactions is proved to have a longer leading time than traditional drug reaction discovery methods. Three more drugs with known adverse reactions are investigated using the selected approach, and two are successfully identified.

Research limitations/implications

Validation of Google Trends data’s representativeness of user search is yet to be explored. In future research, user search in other search engines and in healthcare web forums can be incorporated to obtain a more comprehensive adverse drug reaction early warning mechanism.

Practical implications

Using Internet data in drug safety management with a proper early warning mechanism may serve as an earlier signal than traditional drug adverse reaction. This has great potential in public health emergency management.

Originality/value

Our research work proposes a novel framework of using user search data in adverse drug reaction identification. User search is a voluntary drug adverse reaction exploration behavior. Further, user search data series are more concise and accurate than text mining in forums. The proposed methods as well as the empirical results will shed some light on incor-porating user search data as a new source in pharmacovigilance.