Artificial intelligence that could reduce the cost and speed-up the discovery of new medicines has been developed as part of a collaboration between researchers at the University of Sheffield and AstraZeneca. The new technology, developed by Professor Haiping Lu and his Ph.D. student Peizhen Bai from Sheffield's Department of Computer Science, with Dr. Filip Miljković and Dr. Bino John from AstraZeneca, is described in a new study published in Nature Machine Intelligence. The study demonstrates that the AI, called DrugBAN, can predict whether a candidate drug will interact with its intended target protein molecules inside the human body. AI that can predict whether drugs will reach their intended targets already exists, but the technology developed by the researchers at Sheffield and AstraZeneca can do this with greater accuracy and also provide useful insights to help scientists understand how drugs engage with their protein partners at a molecular level, according to the paper published on February 2, 2023. AI has the potential to inform whether a drug will successfully engage an intended cancer-related protein, or whether a candidate drug will bind to unintended targets in the body and lead to undesirable side-effects for patients.

AlphaFold, DeepMind's protein structure program, is impressive because it reveals so much fundamental information about living organisms. Proteins are the building blocks of life, after all, and as such they are essential to life and to the development of medicines. Proteins can be drug targets, and they can themselves be drugs. In either case, it is important to know the intricate ways in which they fold into various shapes. Their coils, floppy bits, hidden pockets and sticky patches can control, for example, when a signal is sent between cells or if a process is turned on or off.

Equidock, the machine learning system the researchers developed, can directly predict a protein complex like this in a matter of seconds.

Artificial intelligence and the cell's self-cleansing system are the keys behind the novel medication. The treatment may strengthen other organs as well. One in six Norwegians over 80 is affected by Alzheimer's disease. Numbers are even higher worldwide, and there is still no cure available. Researchers at the faculty have developed an artificial intelligence (AI) method to help them identify potential new medicines for Alzheimer's.

The discovery of new drugs is an undeniably important undertaking and represents a massive global market. Statista indicates that the drug discovery market worldwide finds itself on an exponential trajectory, with the expected market value poised to reach 71 billion U.S. dollars by 2025. As of 2016, the market was valued at just 35.2 billion U.S. dollars. Of course, this comes as no surprise; the U.S. pharmaceutical industry, after all, was coined'Big Pharma' for a reason. By 2021, Big Pharma profits for prescription drugs are expected to reach $610 billion and, in 2015, Americans spent $457 billion on prescription drugs.

Artificial Intelligence can be used to innovate our health system even more. It can be done either in the diagnosis phase, the medicine production, vaccine discovery, prediction of pandemics, and so on. We already discussed some examples in the diagnosis phase, now let's talk about using AI to bring new ways of doing your tasks. Developing a new medicine is difficult. It requires many hours of work and investing tons of money.

Chris Smith and Phil Sansom delve into the world of artificial Intelligence (AI) to find out how this emerging technology is changing the way we practise medicine... Mike - I think this is an area where AI stands a really good chance of making quite dramatic improvements to very large numbers of people's lives. Carolyn - Save lives and reduce medical complications. Beth - That's a concern - when machine-learning algorithms learn the wrong things. Andrew - Frankly revolutionary productivity that we are now starting to see from these AI approaches in drug design. Lee - It will replace all manual labor in all research laboratories. And then suddenly everyone can collaborate. Phil - But what was previously sci-fi is now closer to reality. AI technology exists, and there's a brand new frontier where it's being applied to the world of healthcare. Chris - But this isn't the AI you see in the movies. In the words of Kent University computer scientist Colin Johnson, "this is more software than Schwarzeneggar"... Colin - When scientists say AI, they often mean some piece of code that's running on a computer and it's taking some inputs.

Drug discovery is the process of identifying new medicines for treating or curing human diseases.1 Historically, the discovery of new medicines involved extracting ingredients from natural products and basic research to find potential treatments. Progress was generally slow, frustrating and labour-intensive. The majority of drugs discovered during the 20th century were chemically synthesised small molecules, which still make up 90 per cent of drugs on the market today.2 Their advantages include simple manufacturing and administration routes. They also have low specificity and a stable shelf life, meaning they are safe and effective for large groups of people.

For a new compound to make it from initial discovery through development, testing and clinical trials to finally earn regulatory approval can take a decade or more. Nine out of 10 promising drug candidates fail somewhere along the way. As a result, on average, it costs life sciences companies $2.6 billion to introduce a single new prescription drug. This is much more than just a challenge for life sciences companies. Streamlining drug development is an urgent issue for human health more broadly.

For a new compound to make it from initial discovery through development, testing and clinical trials to finally earn regulatory approval can take a decade or more. Nine out of 10 promising drug candidates fail somewhere along the way. As a result, on average, it costs life sciences companies $2.6 billion to introduce a single new prescription drug. This is much more than just a challenge for life sciences companies. Streamlining drug development is an urgent issue for human health more broadly.