By Joseph Pategou
Artificial intelligence (AI) is an area of computer science that focuses on the creation of intelligent machines which work and react like humans. The term refers to multiple technologies including machine learning, deep learning, computer vision, strong AI, natural language processing and machine reasoning. Since 1956, progress in this field has been steady but recent advances in technology have created new possibilities. AI has become a much-discussed topic and the availability of big data, cloud computing along with the emergence of machine learning have dramatically increased its impact.
Countries across the world on AI
Several governments have recently raised the topic of AI in public debate and launched major national initiatives. South Korea has announced an AI plan with €800 million over five years, under which a national research centre will be created in the form of a public-private partnership. In 2016, China had created a 3-year program and a fund of €140 million was allocated to the Chinese Academy of Sciences. The U.S government released a diagnostic report on the progress and potential applications of AI in several areas, including a national strategic plan for research and development. In Japan, two new research centres on AI were opened in 2016, with investments worth € 57 million and € 157 million respectively. Canada, France and the European Parliament are investing heavily in this area as well. These technologies are fierce game changers for almost every industry and promise to significantly improve existing business models and create new ones.
AI massively impacts the healthcare industry
When a drug is brought to the market, thousands of molecules are screened in the exploratory phase, out of which only 10 reach clinical development and just one may hit the market. During these phases, companies need to make an extraordinary investment of billions of dollars and of course, success is not guaranteed. AI can help pharmaceutical companies to significantly reduce the time and cut down on the expenses. By using pattern recognition through working on various clinical data sources, AI can help to understand the complex biological processes behind each disease. This makes for a better selection of compounds that are more likely to work for specific patient populations and simultaneously eliminate drugs that can fail.
Artificial Intelligence and Ebola
Atomwise, a startup, has built a system called AtomNet–the first deep learning technology for small molecule discovery, characterized by its unprecedented speed, accuracy, and diversity. Atomwise has been working on developing a drug for diseases like Ebola and Multiple Sclerosis. As far as Ebola was concerned, Atomwise launched a virtual search for safe, existing medicines that could be repurposed to treat the Ebola virus. Evidence showed that two drugs predicted by Atomwise’s artificial intelligence technology may significantly reduce the Ebola infectivity. These drugs were intended for unrelated illnesses and their potential to treat Ebola was previously unknown. This analysis, which typically would have taken months or years, was completed in less than one day.
AI might have a solution to cancer
Berg, a Boston biopharma company, has designed a new approach to drug discovery by using a platform that combines patient biology and artificial intelligence. Based on their platform, this company has been able to develop two drugs to treat cancer—BPM 31510 and BPM 31543. These drugs were built by extracting biological data from healthy and cancerous tissue samples from patients. The data was processed by AI algorithms which analysed it and suggested possible drug treatments. In this case, Berg has used AI to understand how normal cells work, how the transformation of cancer cells occur and which potential treatment is the best. Leading drug companies like GlaxoSmithKline announced a public-private partnership of $43 million with the National Cancer Institute and the US Department of Energy. The aim is to harness high-performance computing and diverse biological data to accelerate the drug discovery process and discover new cancer therapies in under one year.
Some challenges still remain, like data privacy, given recent cyber attacks on health systems around the world. Nevertheless, AI means faster discovery and development of treatments, more precision in treatments and reduction in costs for healthcare systems. Artificial intelligence will definitely redefine how drug discovery is made in the pharmaceutical landscape.
Joseph Pategou is a consultant specialized in the pharmaceutical industry at Wavestone. He holds a Master of Sciences degree in International Strategy and Influence and a Master’s degree in Chemistry and Life Sciences.
Featured Image Source: Visual Hunt
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