Exploring the re-use of existing data for poverty-related diseases – a scientific or an ethical imperative or both?

Time: To be announced
Where:
To be announced
Session:
Plenary Keynote:
Prof Philippe Guérin

Discussion

Over the last two decades, renewed attention has been given to neglected tropical diseases (NTDs), a subset of poverty-related illness. While irrefutably it was acknowledged that the “classical” market approach could not respond to the challenges of NTDs, a series of initiatives have now been established and are already supporting new research and development for drugs, vaccines and diagnostic tools and this effort should be applauded. Up until now, one thing that all poverty-related infectious diseases shared in common is the overall limited volume of research conducted to understand and test new approaches or guide control programmes. More specifically, the number of clinical trials conducted in the last few decades to support current therapeutic or prophylaxis recommendations are limited in numbers all together: in number of patients recruited, in geographical representation of endemic settings and they often lack representation of the affected population. The root of the problem lies in the limited funding to support larger clinical trials, but also in the challenges in recruiting patients in remote areas and this is sometimes overcomplicated by security concerns and the limited number of research teams working together in each of these diseases. If, by pooling ALL existing individual patient data for each of those diseases generated over the last few decades, we could generate new evidence which could not have been generated by single trials, would it be worth doing? We will discuss the case study of the WorldWide Antimalarial Resistance Network (WWARN), a global data platform for malaria and the subsequent development of the Infectious Diseases Data Observatory (IDDO) as an attempt to establish global data platforms for NTDs and to optimise the re-use of data to maximise the scientific impact of existing knowledge and guide future research.

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