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13 October 2020

How Artificial Intelligence plays a key role in pharmaceutical R&D

Developing drugs with AI
The second article in our series about connecting smart ideas explores Artificial Intelligence. How is this innovative technology transforming the world – and the pharma industry in particular? Find out here.

“Success in creating AI would be the biggest event in human history.”

Stephen Hawking

English theoretical physicist, cosmologist, and author

Artificial Intelligence, usually known simply as AI, involves computer systems that are able to perform tasks that usually require a human brain – like translating languages, making decisions or recognising speech patterns. While it’s still expected to take hundreds of years before humankind creates a real AI that functions like a brain, this futuristic technology is already being used across a wide range of industries. Machine learning, for example, is used to find solutions to problems by analysing huge amounts of data (known as “Big Data”) and identifying patterns. In fact, companies in the pharmaceutical industry leverage machine learning when developing new drugs because it can be programmed to identify a suitable drug dose based on specific criteria, and can replace human-based studies with computer-based simulations or even predict the likely success rate of a new drug.

A company based in the UK, for example, has created algorithms that search through research papers, clinical trial results and other sources of biomedical information to look for relationships between genes, drugs and diseases. This machine learning technology is able to systematically analyse and understand connections between data, and then uses AI to extrapolate the connections (more information here). On top of this, deep learning is emerging as an aspect of machine learning that goes one step further. It uses a multi-layered analysis to simulate the way a human mind processes data. In contrast to machine learning, deep learning algorithms determine for themselves whether their prognosis is right or wrong (see more detail here).

Machine learning and deep learning are already an indispensable part of the scientific process, as this article explains. And this trend is widely predicted to gather pace as the technology improves, with exciting potential for the pharmaceutical industry. Many pioneering companies and start-ups are already working on AI-driven solutions to optimise the drug discovery process. Grünenthal, for example, is cooperating with a specialised vendor to create algorithms that can generate and optimise molecules based on data from the company’s research projects. This is particularly exciting because drug development is such an elaborate process. Machine learning and deep learning have the potential to increase the success of research and development in the pharmaceutical industry – and contribute to the development of new medicines that improve quality of life for patients worldwide.

In today’s fast-paced world, it’s more important than ever to share information between companies, academic institutions and other organisations. By exploring new forms of collaboration, players from across industries and around the globe can generate innovative solutions that make the world a better place. This series of articles aims to highlight how connecting smart ideas can stimulate creativity, achieve ambitious goals – and transform our lives forever.
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