Computational models have been a major time saver when it comes to predicting which protein molecules could make effective drugs, but many of those methods themselves take a lot of time and computing power. Now researchers at MIT and Tufts have devised an alternative approach based on an algorithm known as a large language model, which can figure out which words (or, in this case, amino acids) are most likely to appear together. The model can match target proteins and potential drug molecules without the computationally intensive step of calculating each protein's 3D structure from its amino acid sequence. The resulting system can screen more than 100 million drug-protein pairs in a single day. The researchers tested their model by screening a library of about 4,700 candidate drug molecules for their ability to bind to a set of 51 enzymes.

Technological advances in recent years have made it easier to capture and store reams of digital patient data. This has resulted in rich troves of genomic data, health records, medical imaging and other patient information that AI platforms can mine to help to develop drugs faster and with greater chance of success in the early stages of creation. Morgan Stanley Research biotechnology analysts Matthew Harrison and Vikram Purohit estimate that "a 20% to 40% reduction in costs for preclinical development across a subset of U.S. biotech companies could generate the cost savings needed to fund the successful development of four to eight novel molecules." This would represent as much as a 15% increase of approved therapies over the total number of novel drug approvals in 2021, demonstrating the potential for biotechs to generate new revenue while helping more patients. The pairing of AI and big data could help patients in other ways.

Artificial intelligence (AI) is no longer advancing in baby steps. In fact, it's starting to leap forward and sprint toward the future. Its recent applications in medicine have been remarkable, especially as a diagnostic tool. For instance, AI can detect melanoma -- a form of skin cancer -- in its early stages, allowing quick response and increased survival rates -- up to 98 per cent! AI is now also able to diagnose diabetic retinopathy (DR) -- a form of blindness caused by diabetes.

The biomedical startup was founded by University of Toronto alumni David Q. Chen, Elvis Wianda, Liran Belenzon, Tom Leung.So far the venture has raised US$8 million, contributed by a group of investors including Montreal's iNovia Capital and Google's Gradient Ventures (which is Alphabet's AI venture capital firm). The new company is called BenchSci and it aims to use artificial intelligence to scan through millions of data points, drawn from published research papers, in order to find new compounds that can help to accelerate the drug discovery process. The focus of the new venture is with finding commercial antibodies. The researchers spent two years building machine learning software that can extract antibody usage data from published figures. This involves decoding millions of papers, with the end result of making the data easily discoverable for scientists.

LONDON (Reuters) - The world's leading drug companies are turning to artificial intelligence to improve the hit-and-miss business of finding new medicines, with GlaxoSmithKline unveiling a new $43 million deal in the field on Sunday. Other pharmaceutical giants including Merck & Co, Johnson & Johnson and Sanofi are also exploring the potential of artificial intelligence (AI) to help streamline the drug discovery process. The aim is to harness modern supercomputers and machine learning systems to predict how molecules will behave and how likely they are to make a useful drug, thereby saving time and money on unnecessary tests. AI systems already play a central role in other high-tech areas such as the development of driverless cars and facial recognition software. "Many large pharma companies are starting to realize the potential of this approach and how it can help improve efficiencies," said Andrew Hopkins, chief executive of privately owned Exscientia, which announced the new tie-up with GSK. Hopkins, who used to work at Pfizer, said Exscientia's AI system could deliver drug candidates in roughly one-quarter of the time and at one-quarter of the cost of traditional approaches.

The world's leading drug companies are turning to artificial intelligence to improve the hit-and-miss business of finding new medicines, with GlaxoSmithKline unveiling a new USD 43 million deal in the field on Sunday. Other pharmaceutical giants including Merck & Co, Johnson & Johnson and Sanofi are also exploring the potential of artificial intelligence (AI) to help streamline the drug discovery process. The aim is to harness modern supercomputers and machine learning systems to predict how molecules will behave and how likely they are to make a useful drug, thereby saving time and money on unnecessary tests. AI systems already play a central role in other high-tech areas such as the development of driverless cars and facial recognition software. "Many large pharma companies are starting to realise the potential of this approach and how it can help improve efficiencies," said Andrew Hopkins, chief executive of privately owned Exscientia, which announced the new tie-up with GSK. Hopkins, who used to work at Pfizer, said Exscientia's AI system could deliver drug candidates in roughly one-quarter of the time and at one-quarter of the cost of traditional approaches.

The world's leading drug companies are turning to artificial intelligence to improve the hit-and-miss business of finding new medicines, with GlaxoSmithKline PLC unveiling a new $43-million (U.S.) deal in the field on Sunday. Other pharmaceutical giants including Merck & Co. Inc.,Johnson & Johnson and Sanofi are also exploring the potential of artificial intelligence to help streamline the drug discovery process. The aim is to harness modern supercomputers and machine learning systems to predict how molecules will behave and how likely they are to make a useful drug, thereby saving time and money on unnecessary tests. AI systems already play a central role in other high-tech areas such as the development of driverless cars and facial-recognition software. "Many large pharma companies are starting to realize the potential of this approach and how it can help improve efficiencies," said Andrew Hopkins, chief executive of privately owned Exscientia, which announced the new tie-up with GSK. Mr. Hopkins, who used to work at Pfizer, said Exscientia's AI system could deliver drug candidates in roughly one-quarter of the time and at one-quarter of the cost of traditional approaches.

This year's historic gush of water through California's rivers brings the dawning of a renaissance for lampreys, a peculiar fish that migrates upstream to spawn but without the fanfare of its salmon and steelhead compatriots. While the critters' nocturnal life and brown, camouflage bodies make them largely invisible to even the most veteran fishermen and paddlers, their sheer abundance has led to more sightings? Watching the lampreys scale the side of Van Arsdale Dam, or opt for an adjacent fish ladder built for spawning salmon, Goodman acknowledged that the fish are a bit off-putting. The Pacific lamprey, native to the state and dating back to before the dinosaurs, doesn't bite humans and provides a slew of environmental benefits. While biologists believe this year's surge of lampreys is tied to high river flows after a near-record wet winter, the fact is they don't know for sure.

LONDON (Reuters) - The world's leading drug companies are turning to artificial intelligence to improve the hit-and-miss business of finding new medicines, with GlaxoSmithKline unveiling a new $43 million deal in the field on Sunday. Hopkins, who used to work at Pfizer, said Exscientia's AI system could deliver drug candidates in roughly one-quarter of the time and at one-quarter of the cost of traditional approaches. "It's still to be proven, but we definitely think we should do the experiment," said John Baldoni, GSK's head of platform technology and science. "We have an obligation to reduce the cost of drugs and reduce the time it takes to get medicines to patients."

Data-sharing business Dropbox Inc is seeking to hire underwriters for an initial public offering that could come later this year, which would make it the biggest U.S. technology company to go public since Snap Inc, people familiar with the matter said on Friday.