Machine Learning Helps Researchers in Hot Pursuit of New Drugs

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Researchers have designed a machine learning algorithm for drug discovery which has been shown to be twice as efficient as the industry standard, which could accelerate the process of developing new treatments for disease. The researchers, led by the University of Cambridge, used their algorithm to identify four new molecules that activate a protein which is thought to be relevant for symptoms of Alzheimer's disease and schizophrenia. The results are reported in the journal PNAS. A key problem in drug discovery is predicting whether a molecule will activate a particular physiological process. It's possible to build a statistical model by searching for chemical patterns shared among molecules known to activate that process, but the data to build these models is limited because experiments are costly and it is unclear which chemical patterns are statistically significant.


New machine learning algorithm can help search new drugs

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LONDON, Feb 12: Researchers say they have developed a machine learning algorithm for drug discovery which is twice as efficient as the industry standard, and could accelerate the process of developing new treatments for diseases such as Alzheimer's. The team led by researchers at the University of Cambridge in the UK used the algorithm to identify four new molecules that activate a protein thought to be relevant for symptoms of Alzheimer's disease and schizophrenia. A key problem in drug discovery is predicting whether a molecule will activate a particular physiological process, according to the study published in the journal PNAS. It is possible to build a statistical model by searching for chemical patterns shared among molecules known to activate that process, but the data to build these models is limited because experiments are costly and it is unclear which chemical patterns are statistically significant. Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed "Machine learning has made significant progress in areas such as computer vision where data is abundant," said Alpha Lee from Cambridge's Cavendish Laboratory.


Machine Learning Algorithm Helps In The Search For New Drugs

#artificialintelligence

Researchers have designed a machine learning algorithm for drug discovery which has been shown to be twice as efficient as the industry standard, which could accelerate the process of developing new treatments for disease. The researchers, led by the University of Cambridge, used their algorithm to identify four new molecules that activate a protein which is thought to be relevant for symptoms of Alzheimer's disease and schizophrenia. The results are reported in the journal PNAS.


The AI robot chemist trying to find the origins of life on Earth

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"If I ask an organic chemist to make me a random new molecule, they can't do it," says Lee Cronin, a professor of chemistry at the University of Glasgow. "It's not because they are stupid. They will ask me what type of molecule and what specification. It could take them one week or ten years. Cronin realised that even though that's a difficult ask for a human being, it probably wasn't such a difficult project for a machine learning robot to undertake.


Machine learning picks up chemistry from molecules

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'It's an art and a science,' explains Joshua Staker, a senior scientist at the US software company Schrodinger. He's referring to deep learning – a branch of computer science that looks set to transform how chemists screen molecules and explore chemical behaviour. Over the past few decades, deep learning has entered the public consciousness through projects such as AlphaGo. A landmark in computing, Google's algorithm is able to autonomously learn and play the board game Go – 1050 times more complex than chess – a challenge once thought to be beyond computers. AlphaGo first defeated a human opponent in 2015, and beat the world number 1 in 2017.