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Using the Cloud to Hasten Drug Research and Discovery

Cloud computing is touted for its accessibility and efficiency. Specifically, it's often cited as the ideal platform for collaboration, sharing, and team-based development – but it's not limited to documents, software, and reporting. Instead, it has applications in nearly every discipline – including medicine and drug discovery.

In fact, there has already been many significant breakthroughs in the niche of drug discovery in the 21st century – and much of it is on account of cloud computing. Some of the latest and most notable developments include:

Sanofi, a multinational pharmaceutical company headquartered in France, has recently announced their plans to use Google technology – including their artificial intelligence (AI) and cloud computing tools, in their new Innovation Lab. Apart from speeding up the processes associated with drug discovery, Sanofi hopes to strengthen their day-to-day operations and improve the overall patient experience across the board.

Eli Lilly and Company, a pharmaceutical company based in Indianapolis, Indiana, recently entered into a partnership with the team at Atomwise. Their goal is to pioneer the development of up to 10 new drug targets in a deal that could be valued as high as $560 million. Once again, this initiative will speed up drug discovery as well as target identification. It will also aide scientists in new drug design.

Abraham Heifets, PhD and CEO of Atomwise, clarified their intent in a recent interview by saying: "Lilly has made it clear that they are focused on developing drugs for novel target proteins, which are often challenging and less well studied. Our expertise and tools have been shown to succeed with these kinds of targets, and therefore could be a key to unlocking success for patients."

In other recent news, the team at Recursion Pharmaceuticals has recently secured $121 million in Series C funding to support the ongoing development of their AI-based software. Based out of Salt Lake City, Utah, Recursion, the development team has already earmarked the funds for machine learning, prediction and forecasting, and drug discovery.

Chris Gibson, CEO of Recursion Pharmaceuticals, spoke about this in a recent interview by saying: "With these new resources, we will continue to drive toward a future in which drugs are developed—by people—with a new level of understanding about human biology that was simply not possible before machines."

Even Google is making headlines in the area of medicine. They've already demonstrated machine-learning technology that is capable of beating humans in some of the most popular board games, but their latest machines can predict the shapes of proteins and help diagnose certain diseases. Not only could this speed up the development of new, disease-fighting drugs, but it could potentially be used to identify at-risk patients and aide in prevention before a disease even occurs.

Although Google's DeepMind system isn't experienced in protein folding, it relies on next-gen neural-network algorithms to accomplish work that would normally take the collective efforts of dozens of scientific laboratories. Since the scientists working on this project are "fully focused on their research," they are unavailable for interviews or comments at this time.


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