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home > ebr > winter 2022 > ai does not drive novel drug discovery, science does |
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European Biopharmaceutical Review
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The use of AI in drug discovery, or any industry, is not a futuristic concept. However, it continues to receive media attention and is pushed by industry voices as a revolutionary fix for declining productivity. This is a fundamental problem because AI’s buzzword factor has created a misunderstanding of its potential and the incorrect perception that it is ahead of its time.
Nevertheless, people love a good innovation story.
To help put AI into perspective, a useful example is the recent automotive industry shake-up. For almost a decade, Tesla dominated headlines for pioneering electric vehicles and self-driving cars, creating an almost unobtainable futuristic aura. Many auto manufacturers dismissed this disruption and carried on producing gas-powered vehicles with only incremental innovation. We are quickly seeing that the future is progressively becoming more technology-enabled, and the rise of electric-powered vehicles is no exception. Those that are unwilling to change will not succeed. Moreover, those that were slow to change are now behind the market. Despite the hype, Tesla transformed the industry.
Using that analogy, we can say the same for the implementation of AI in the pharmaceutical industry. It has been dismissed by some, but will soon catalyse wider disruption.
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News and Press Releases |
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Ubiquigent Obtains Exclusive License for UbiSite Technology to Strengthen its Specialist Drug Discovery Services
Dundee, UK, 31 October 2022: Ubiquigent Limited (Ubiquigent), a
drug discovery and development company harnessing novel deubiquitylase
(DUB) modulators as new therapeutics for areas of high unmet medical
need, has signed an exclusive license with the University of Southern
Denmark for its UbiSite® technology. UbiSite will form a new component
in Ubiquigent’s DUB and ubiquitin-proteasome system (UPS) focused drug
discovery platform, providing a fully supported ubiquitomics service to
facilitate target identification, target validation, and compound
mechanism of action.
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