On a recent Friday in Boston, Randell Sanders gave a nurse two samples of his blood, plus a sample of urine and saliva. Clinicians would test some of the samples to see how he is responding to treatment for pancreatic cancer. But samples also were sent to a lab where computers using artificial intelligence are changing the way pharmaceutical companies develop drugs. The idea is that machines, which are adept at pattern recognition, can sift through vast amounts of new and existing genetic, metabolic and clinical information to unravel the complex biological networks that underpin diseases. That, in turn, can help identify medications likely to work in specific patient populations, while simultaneously steering companies away from drugs that are likely to fail.

Alphabet Inc. (GOOG) subsidiary Google's artificial intelligence company DeepMind Health has signed an agreement with a hospital that is part of the U.K.'s National Health Service (NHS) network to deploy Streams, an app that monitors critical indicators of a patient's health and alerts doctors. This is the second such deal signed by DeepMind this year. Earlier, the company signed a similar agreement for patient data with three hospitals that operate under the NHS umbrella. As part of the agreements, DeepMind receives access to important patient data and medical histories. News reports have alleged that DeepMind obtained the data without explicit consent from the affected patients.

From computer vision systems for autonomous driving to FDA-approved medical imaging, artificial intelligence (AI) is driving public sector innovation. Governments, defense agencies, and other public sector organizations are adding AI into their platform, solutions, and products to perform tasks that usually require human-level intelligence, such as visual perception, speech recognition, decision making, or translation. In order to change the way services are delivered to the blind or to inspire the next generation of space explorers, organizations need to overcome hurdles related to the scale of data, scale of compute, and variety of devices and platforms that intelligent systems need to ultimately run on. Nonprofits: The Royal National Institute of Blind People is able to change the way services are being delivered to the blind by using AWS. "We are currently using Amazon's Speech-to-Text technology to create and distribute accessible information in the form of synthesized audio content for our many B2B and B2C customers, including utility companies, financial institutions, and media companies, as well as other customer-facing material such as magazines and publications. With the announcement of Amazon Polly, we're excited about the ability to provide an even better experience to these customers by delivering incredibly lifelike voices that will captivate and engage our audience," said John Worsfold, Solutions Implementation Manager, Royal National Institute of Blind People.

Great White North is on the top of that list. Because of its powerful academic research labs, Toronto has supplied a lot of talent in the field but has been experiencing a brain drain. As an effort to retain talent and make Toronto a global supplier of AI capability, the University of Toronto gathered a team of globally renowned researchers and founded the Vector Institute. The independent, non-profit AI research institution has created a lot of buzz and attracted a great deal of funding to its ongoing projects. With a combination of research and commercial goals, according to The Toronto Star, It will be backed by more than $150 million in public and corporate funding.

The key takeaway from Tuesday's RobotLabNYC forum, on "Exploring The Autonomous Future," was humans are the key to robot adoption. Howard Morgan of First Round Capital expressed to the audience of more than 100 innovators working within the automation ecosystem, the necessity of embracing "entrepreneurial marketing" to reach customers. Tom Ryden echoed Morgan's sentiment in his presentation about Mass Robotics, conveying his startups' frustrations with the pace of adoption. Dr. Eric Daimler, formerly of the Obama Administration, concluded the evening succinctly by exclaiming, "we only adopt what we trust." Trust is key for crossing the chasm.

When Bakul Patel started as a policy advisor in the US Food and Drug Administration in 2008, he could pretty much pinpoint when a product was going to land in front of the reviewers in his division. Back when medical devices were heavy on the hardware--your pacemakers and your IUDs--it would take manufacturers years to get them ready for regulatory approval. FDA reviewers could keep up pretty well. But as computer code took on more complex tasks, like spotting specious moles and quantifying blood flow, their duties began to accelerate. Software developers needed months, not years, to make it to the market.

Mobile health apps and wearable devices that use artificial intelligence to help diagnose or even treat medical conditions pose a new regulatory challenge for the U.S. Food and Drug Administration. The government agency has responded by starting to assemble a team of computer scientists and engineers to help oversee and anticipate future developments in AI-driven medical software. This comes at a time when medical devices have evolved from fairly self-contained gadgets into implants and wearables that communicate wirelessly with medical software on separate computers or in the cloud. The definition of medical device has also stretched as smartphone apps and online services--often backed by machine-learning algorithms--promise to deliver medical diagnoses that once would have required a visit to a doctor's office and specialized lab equipment. That is why the FDA aims to create a new digital health unit around people having both the technical expertise and industry experience to understand how machine learning AI and related subjects such as big data, cybersecurity, and cloud computing will all affect health care for Americans.

The Sheffield Institute for Translational Neuroscience (SITraN) and AI start-up BenevolentAI have announced a potentially major breakthrough in the treatment of motor neuron disease, thanks to artificial intelligence. The groundbreaking development for the disease, also known as amyotrophic lateral sclerosis (ALS), came about as scientists from SITraN assessed the efficacy of a drug candidate proposed by BenevolentAI's AI technology. The scientists, led by Dr. Richard Mead and Dr. Laura Ferraiuolo, found there are significant and reproducible indications that the drug prevents the death of motor neurones in patient cell models, and delayed the onset of the disease in the gold standard model of ALS. SITraN is now moving to the next phase of its research, advancing the existing study and assessing the suitability and potential for clinical development. It expects to publish an abstract at the Motor Neurone Disease Association 28th International Symposium in Boston in December.

In mythology unicorns are skittish things, and in business they appear little easier to pin down. EP Vantage has compiled a list of private start-up companies in the healthcare arena that are widely considered to be worth more than $1bn; notably it features very few makers of human therapeutics. Instead these unicorns are involved in cutting-edge computational research such as artificial intelligence, sequencing or virtual reality, or are in risky, unproven areas. It is plausible that one of the reasons they have not been bought is because no acquirer knows where to put them (see table below). Those that are in the business of developing human therapeutics are working in the as-yet unproven field of mRNA - Moderna Therapeutics and Curevac.

As digital health innovation has outpaced the FDA's regulatory structure, the agency's top official wants to overhaul the approval process for new technology. That overhaul comes by way of a new Medical Device User Fee Agreement (MDUFA) that is making its way through Congress despite some recent pushback from Department of Health and Human Services Secretary Tom Price. A portion of the four-year agreement includes the creation of a central digital health unit within the FDA's Center for Devices and Radiological Health. RELATED: Tom Price revisits Trump's proposal to double FDA user fees Although that agreement wouldn't take effect until October, Bakul Patel, associate director for digital health, told Wired that he's already begun hiring key positions for the new department that will eventually include 13 engineers. Once he has a team in place, Patel wants to restructure the FDA's approach to digital health entirely, making it easier for new solutions and technology to get to market faster.