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European Biopharmaceutical Review

Natural Intelligence Looks at AI

Artificial intelligence (AI) is the fourth industrial revolution. Machinelearning, Big Data, and basic science have reached a tipping point where the question is not if, but when. Media coverage of AI is abuzz with driverless cars, facial recognition, and data analytics. However, public reception is divided. Is it a positive transformation of the human condition or a brave new world? Nations and industries alike have embraced AI, fearing to be left behind in the race for global competitive advantage.

AI is now being adopted by all the major biopharmaceutical companies at every stage of their pipeline workflows. Industrial and academic research centres and a spate of new startups and investors are all sprinting towards this new reality. Still, the hype and skepticism surrounding biotechnology applications of AI echoes earlier paradigm shifts in the drug discovery – high throughput screening, molecular modelling, and rational design. Critics say these never lived up to the promise, yet they continue to play an important role in drug discovery today.

What Is AI?

AI consists of software systems based on the confluence of computing power, large data sets, and models that mimic the understanding of the human brain. They attempt to self-learn from training sets of data and develop the ability to interpret new inputs. They provide reasoned outputs and predictions in new situations. These learning engines are model-free. Cause-and-effect is not as obvious as one might expect in a linear regression or a decision tree. Simultaneously, they achieve a high level of predictive accuracy in datasets that are too large and multidimensional for an individual to handle.

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Emile Bellott is a member of the EBR Industry Advisory Board, a graduate of the Harvard Business School, US, a Chinawatcher, and an industry consultant with experience in the biotech and biopharma industry.
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Emile Bellott
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