Pharma and AI? Let's try augmented intelligence first

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Like smartphones upended everyday tasks from communication to shopping, artificial intelligence promises to change how the pharmaceutical industry discovers drugs, carries out R&D and even commercializes products. Before that happens, though, the industry needs to figure out precisely what AI means and how much investment will be required. Further challenges include trepidation about how best to prove it works and confusion over its power. According to a survey of over 12,000 participants conducted by consultancy PwC in 2016, lack of trust and a need for the human element were the biggest hurdles to using AI in healthcare. "I don't think artificial intelligence is really here; it's more augmented intelligence.


Where are the opportunities for medtech and pharma in 2020?

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It's that time when we start to look ahead to what next year holds for the life science sector...Lu Rahman outlines 2020s big medtech players A decade ago the healthcare advances create by AI would have seemed the stuff of dreams. But back in 2018 Theresa May announced plans to use artificial intelligence and data to transform the way certain diseases like cancer. The technology is moving at a pace – this year we heard that a team led by the University of Surrey had filed the first ever patent for inventions autonomously created by AI without a human inventor. Professor Ryan Abbott explained the implications this had for the life science sector: "These filings are important to any area of research and development as well as any area that relies on patents. Patents are more important in the life sciences than in many other areas, particularly for drug discovery. These tasks can be the foundation for patent filings. "As AI is becoming increasingly sophisticated, it is likely to play an increasing role in R&D including in the life sciences.


Artificial intelligence in drug discovery and diagnosis - Pharmaphorum

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Machine learning is widely predicted to make drug discovery and patient diagnosis quicker, cheaper and more effective in the future, and signs of this can already be seen. Nearly 70 years ago, artificial intelligence researchers at New Hampshire's Dartmouth College discussed building machines that could sense, reason and think like people -- a concept known as'general AI'. But their plans were destined to remain in the land of science fiction for quite some time. However, in the last decade the rapid growth in computer-processing power, the availability of large data sets and the development of advanced algorithms have driven major improvements in machine learning. AI researcher Ben Goertzel brought to light'narrow AI' in 2010.


Why big data is good for your health - SWI swissinfo.ch

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At the University Hospital of Giessen and Marburg 6,000 patients are waiting for a diagnosis of their rare conditions. Most patients have spent years bouncing from one doctor to another, building up huge dossiers of medical notes. Rare diseases typically take at least five years to correctly name, and sometimes up to 30, by which time it can be too late for effective treatment. "This is an inefficient, costly business," Dr Jurgen Schafer, who heads the German university's medical team, said at a media conference at IBM Zurich in October. "The computer is not going to replace the physician.


How Artificial Intelligence Is Accelerating Life Sciences

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The drug development lifecycle is long and fraught with heavy risk -- it takes a staggering 10 – 15 years on average, with ultimately only 12 percent of drugs in clinical trials gaining approval by the U.S. Food and Drug Administration (FDA) [1]. To put this in perspective, 22.7 percent of all global research and development spending in 2017 was in the healthcare industry, second only to 23.1 percent spent in the computing and electronics industry, yet the product lifecycle and cost are much higher [2]. For example, the original iPhone took two and a half years to develop from concept to launch, and an estimated $150 million spent in research and development [3]. In contrast, the average cost of new drug and biologics is $2.87 billion when factoring in the post-approval research and development costs, according to figures released in May 2016 by The Tufts Center for the Study of Drug development (CSDD) [4]. For pharmaceutical companies that have launched more than four drugs, the median cost is closer to a staggering $5.3 billion according to analysis by industry expert Matthew Herper of Forbes [5].