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Data Sharing Initiative Could Improve Our Understanding and Help To Reduce Antimicrobial Resistance
Article

Data Sharing Initiative Could Improve Our Understanding and Help To Reduce Antimicrobial Resistance

Data Sharing Initiative Could Improve Our Understanding and Help To Reduce Antimicrobial Resistance
Article

Data Sharing Initiative Could Improve Our Understanding and Help To Reduce Antimicrobial Resistance

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Antimicrobial resistance (AMR) is a looming global threat, spurred on by years of widespread use and misuse of antibiotics, which has driven the evolution of hard-to-treat so-called “superbugs”. To develop better ways of using and managing the antimicrobials we have and to direct areas for the development of new therapeutics, scientists and analysts are looking for ways to improve our understanding of this gargantuan problem. But with the problem so widespread, many aspects to consider and many parties involved, effective data sharing is a real challenge.


One organization aiming to help is the Vivli Center for Global Clinical Research Data, an independent, non-profit organization, acting as a neutral intermediary between data contributors, data users and the wider data sharing community. Their global data-sharing and analytics platform can be applied to a plethora of datasets in medicine, research and most recently AMR.


We spoke to Dr. Rebecca Li, executive director of Vivli and faculty member at the Center for Bioethics at the Harvard Medical School, about the threat that AMR poses and how Vivli’s data sharing AMR Register could help scientists and medics tackle the AMR problem.


Karen Steward (KS): For those that may be unaware, what’s the significance of the threat that AMR poses?


Rebecca Li (RL): AMR is an “overlooked pandemicfor which the magnitude is at least as large as major diseases such as human immunodeficiency virus (HIV) and malaria. There were 4.95 million deaths in 2019 associated with AMR, 1.27 million directly attributable to drug resistant pathogens. The World Bank Group has emphasized that, unless we act now, AMR will force 24 million people into extreme poverty by 2030. This is because they will be too unwell to work and may lose their jobs. If it is left unchecked, AMR will cost the global economy $100 trillion by 2050.


KS: Can you tell us about what the AMR Register is, how it works and what it provides?


RL: The AMR Register is a public platform where researchers can search for and request access to antimicrobial susceptibility surveillance program datasets that were generated by the pharmaceutical industry. These datasets are high-quality data that can be used, for example, to detect trends in multi-drug resistance over time. The AMR Register has an intuitive filtered search where researchers can select the datasets of interest for their research, they will then be required to complete a short request form stating the purposes of their analysis, and they will then be able to download the raw isolate-level datasets, generally within one working day, for analysis.


KS: What made Vivli feel there was an unmet need for such a register?


RL: There is no current single unified platform for high-quality industry surveillance data. Vivli was given the opportunity to create the AMR Register with seed funding from Wellcome following the creation of a successful pilot register by Wellcome and the Open Data Institute in 2017.


KS: How will the register help scientists and benefit AMR research and therapeutic management and development?


RL: The industry-conducted AMR surveillance programs that will be included on the AMR Register provide high-quality data as they have been collected using standardized methods. Researchers can therefore use the data with confidence to, for example, detect trends in multi-drug resistance over time, inform antibiotic stewardship, and national and international policy and model future resistance trends.


KS: Are there any safety concerns around the sharing of this type of data and if so, how are they being addressed?


RL: The data that will be shared is anonymized, isolate-level data from samples collected in hospitals or the community, which means that it cannot be traced back to any individual and instead, helps inform public health.


Dr. Rebecca Li was speaking to Dr. Karen Steward, Senior Science Writer for Technology Networks.

  

Meet the Author
Karen Steward PhD
Karen Steward PhD
Senior Science Writer
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