Crowdsourcing and open innovation in drug discovery: recent contributions and future directions
Abstract
The past decade has seen significant growth in the use of ‘crowdsourcing’ and open innovation approaches to engage ‘citizen scientists’ to perform novel scientific research. Here, we quantify and summarize the current state of adoption of open innovation by major pharmaceutical companies. We also highlight recent crowdsourcing and open innovation research contributions to the field of drug discovery, and interesting future directions.
Questions for Twitter
Questions this week are thanks to Frederick Grinnell and Samantha Copeland:
- If AI becomes central to all stages of drug discovery, then what role would crowd-sourcing play? Can you give a specific example?
- Can AI make serendipitous discoveries and, if so, would that change the meaning of serendipity?
- What kind of a crowd do you need for successful crowdsourcing? Does it have to be diverse, skilled, are there features that are necessary or a bonus if you have them?
- You mention that in weakly connected interactions (like when companies challenge users to create algorithms as a game) the intentions do not align. Do you think this mis-alignment creates more opportunities for serendipity, or that ‘partially coupled’ (more aligned) interactions will be better for that?
Citation & Links:
David C. Thompson & Jörg Bentzien. Crowdsourcing and open innovation in drug discovery: recent contributions and future directions. Drug Discovery Today, available online Oct 2., 2020: https://doi.org/10.1016/j.drudis.2020.09.020
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