Aug. 21, 2017 "How AI is shifting the pharma landscape": Today I found this article by Ben Hirschler in the Globe and Mail:
Machine learning is poised to break the world of drug research and development wide open for disorders such as ALS
Artificial-intelligence robots are turbo-charging the race to find new drugs for the crippling nerve disorder ALS, or motor neurone disease.
The condition, also known as Lou Gehrig’s disease, attacks and kills nerve cells controlling muscles, leading to weakness, paralysis and, ultimately, respiratory failure.
There are only two drugs approved by the U.S. Food and Drug Administration to slow the progression of ALS (amyotrophic lateral sclerosis), one available since 1995 and the other approved just this year. Globally, about 140,000 new cases are diagnosed every year and there is no cure for the disease, famously suffered by cosmologist Stephen Hawking.
“Many doctors call it the worst disease in medicine and the unmet need is huge,” said Richard Mead of the Sheffield Institute of Translational Neuroscience, who has found artificial intelligence (AI) is already speeding up his work.
Such robots – complex software run through powerful computers – work as tireless and unbiased super researchers. They analyze huge chemical, biological and medical databases, alongside reams of scientific papers far quicker than humanly possible, throwing up new biological targets and potential drugs.
One candidate proposed by AI machines recently produced promising results in preventing the death of motor neurone cells and delaying disease onset in preclinical tests in Sheffield.
Mead, who aims to present the work at a medical meeting in December, is now assessing plans for clinical trials.
He and his team in northern England are not the only ones waking up to the ability of AI to elucidate the complexities of ALS.
In Arizona, the Barrow Neurological Institute last December found five new genes linked to ALS by using IBM’s Watson supercomputer. Without the machine, researchers estimate the discovery would have taken years rather than only a few months.
Mead believes ALS research is ripe for AI and machine learning because of the rapid expansion in genetic information about the condition and the fact there are good test-tube and animal models to evaluate drug candidates.
That is good news for ALS patients seeking better treatment options. Famous sufferers include Lou Gehrig, the 1923-39 New York Yankees baseball player; actor and playwright Sam Shepard, who died last month; and Hawking, a rare example of someone living for decades with the condition.
If the research goes on to deliver new medicines, it would mark a notable victory for AI in drug discovery, bolstering the prospects of a growing batch of startup companies focused on the technology.
Those firms are based on the premise that, while AI robots won’t replace scientists and clinicians, they should save time and money by finding drug leads several times faster than conventional processes.
British “unicorn” Mead from Sheffield is working with BenevolentAI, one of a handful of British “unicorns” – private companies with a market value above $1-billion (U.S.), in this case $1.7-billion – that is rapidly expanding operations at its offices in central London.
British “unicorn” Mead from Sheffield is working with BenevolentAI, one of a handful of British “unicorns” – private companies with a market value above $1-billion (U.S.), in this case $1.7-billion – that is rapidly expanding operations at its offices in central London.
Others in the field include Scotland’s Exscientia and U.S.-based firms Berg, Numerate, twoXAR, Atomwise and InSilico Medicine – the last of which recently launched a drug-discovery platform geared specifically to ALS.
“What we are trying to do is find relationships that will give us new targets in disease,” said Jackie Hunter, a former drug hunter at GlaxoSmithKline (GSK) who now heads Benevolent’s pharma business.
“We can do things so much more dynamically and be really responsive to what essentially the information is telling us.”
Unlike humans, who may have pet theories, AI scans through data and generates hypotheses in an unbiased way.
Conventional drug discovery remains a hit-and-miss affair and Hunter believes the 50-per-cent failure rates seen for experimental compounds in mid- and latestage clinical trials attributed to a lack of efficacy is unsustainable, forcing a shift to AI.
A key test will come with a Phase IIb study by Benevolent to assess a previously unsuccessful compound from Johnson & Johnson in a new disease area – this time for treating Parkinson’s disease patients with excessive daytime sleepiness.
Big pharmaceutical companies such as GSK, Sanofi and Merck are now exploring the potential of AI through deals with startups.
They are treading cautiously, however, given the failure of “high throughput screening” in the early 2000s to improve efficiency by using robots to test millions of compounds. Yet AI’s ability to learn on the job means things may be different this time.
For Benevolent’s Hunter, today’s attempts to find new drugs for ALS and other difficult diseases marks an important test bed for the future of AI, which is already being deployed in other high-tech areas such as autonomous cars.
“The aim is to show that we can deliver in a very difficult and complex area. I believe if you can do it in drug discovery and development, you can show the power of AI anywhere.”
Apr. 20, 2018 "Machines can put human back in human resources": Today I found this article by Chris Taylor in the Globe and Mail:
Chief human resources officer, Best Buy Canada.
What’s the best way to make your employee experience more human? Bring in the machines.
Technology is making the modern-day workplace virtually unrecognizable. As the digital transformation continues to disrupt all aspects of business and workplace culture, smart companies are looking into innovative ways that artificial intelligence (AI), machine learning and other leading-edge technologies can improve and enhance the employee experience.
We’re now at a point where we can actually improve human capital management by taking large parts of it out of the hands of humans.
As counter-intuitive as it sounds, freeing HR professionals and managers from the more bureaucratic aspects of their responsibilities – including regulatory and other compliance issues – gives them time to be more personal in their work and to do a better job of relating to employees in human terms. It allows employees to use uniquely human capabilities such as critical thinking, creativity and empathy, rather than drowning in processes easily accomplished by technology.
This applies to both intake screening of potential new hires as well as relationships with existing team members. Imagine a future where AI-based solutions let job-seekers interact with voice-activated chatbots to get information about open positions or other potential opportunities. The technology may soon be able to give hiring managers recommendations on best-fit candidates for promotion or hire, or predictions about which candidate will accept an offer.
The modern connected workplace collects staggering amounts of data about habits, preferences and processes – far more than HR personnel can easily process. But give it to an AI application to sift through and suddenly your HR managers have way more flexibility to interact personally with members of the broader team.
At Best Buy Canada, we don’t just sell cool tech, we’re taking some pretty bold steps to embrace the potential of new technology within our business as well. We’re investing in cloud-based solutions that harness the power of AI, voice technology and machine learning to help us better manage every moment of an employee’s journey. We want to offer a self-serve experience, providing information such as schedules, benefits and compensation details in real time.
As technology reshapes our approaches and processes, we’re embracing the applications for AI and machine learning in human capital management, and I view it as a mandatory investment in the future.
As with any evolution, we need to ask important questions and listen to employee feedback before implementing changes. For instance, how do we continue to evolve the employee experience so the best and the brightest not only choose to come and work with us, but also stay and grow? This is of particular importance with respect to retention in the retail and technology sectors.
Today, employees stay with companies not based on compensation or other traditional rewards, but for opportunity, interesting work and the ability to play an active role in managing and deciding how their work gets done. Your work has to be valued, satisfying and, perhaps most importantly, fun.
This is at the heart of Best Buy’s agile methodology. With more than half of the people at our Burnaby, B.C.-based head office working in e-commerce and IT, we’ve completely re-imagined how we approach and execute projects to adopt new ways of doing business. Work is self-driven in an environment of accountability, with team coaches there to help staff members along the way.
We also know the happiness of our employees is linked closely to our community involvement, comprehensive benefit packages, wellness programs and forward-thinking, inclusive culture. By augmenting these very human considerations with technology, such as with a newly implemented health and wellness online platform to help employees track, share and meet their goals, we’re able to offer a well-rounded experience for employees today, as well as for the workforce of the future.
Adopting leading-edge innovations for modern workplaces isn’t without challenges, but the dividends can be astronomical. If you’re not actively engaged in finding ways to harness the power of technology, you risk being left behind not just by your competitors, but by your brightest talent as well.
