Random forest. Machine learning. Bayesian statistics. These were among the concepts discussed by Amgen SVP Mike Nohaile on a panel devoted to artificial intelligence (AI) and drug development at the 2018 World Medical Innovation Forum, a recent event that Amgen has sponsored for the last four years.
AI in context
Artificial intelligence is generally defined as computer systems able to perform tasks that normally require human intelligence, which could include visual perception, speech recognition or decision-making.
In popular culture, it’s the technology that recognizes your face to unlock your smart phone or what might enable a virtual assistant to recognize the tone of your voice. In the world of healthcare and drug development, however, the potential of this technology remains largely untapped—and what progress has been made remains rather narrow and somewhat esoteric. Amgen’s innovation and digital health team is trying to change that.
It’s still the early days
The integration of AI and biotech is still in its infancy. According to Nohaile, it has not yet reached the stage where most researchers steeped in the world of drug discovery and development have a deep working knowledge of AI and other digital and data analytic tools. For healthcare to fully realize the value of AI and similar technologies, that is precisely what needs to change.
“We are seeing advances like using deep learning to visually scan plates [petri dishes used to grow microorganisms] so that humans don’t have to, and using language processing that involves getting non-trivial keyword insights from scientific literature,” said Nohaile. “But the idea of pressing a button and all the data sets come together and everything just happens? That’s the next generation.”
Amgen’s evolving Digital Health and Innovation capabilities
AI is but one of a series of emerging digital capabilities Amgen is advancing to improve how we do a whole host of activities across the company—from drug discovery and patient identification to optimized interactions with physicians. Other technologies Nohaile and his team are leveraging include digital automation, natural language processing, advanced analytics, and data management.
AI in action at Amgen: Spotting potential osteoporotic bone
Amgen is leveraging machine learning and deep learning, which are two forms of AI, in several segments of our business. One example is a collaborative pilot program to better diagnose osteoporotic fractures. The training of the machine and deep learning algorithms takes place by exposing the algorithms to very large data sets. In this case, the data sets are many thousands of radiological images. It is our hope that this approach will lead to improved diagnosis and ultimately a reduction in secondary fracture risk.
Electricity: A case study in technology adoption
“One of the things I spend most of my time thinking about when it comes to this subject is, ‘how do you get a whole company to really do AI?” he opined. To illustrate his point, he borrowed an analogy from renown computer scientist Andrew Ng about the transformational nature of electricity. “When electric motors came in, it took several decades for people to fully take advantage of them,” he noted. “The first thing they did was put a large electric motor in the middle of the factory, but it took them a long time to realize that they could re-design the entire factory and put electric motors all over the place doing all kinds of things.”
Blending data scientists with scientists
What will it take to bring a data and data analytic revolution to healthcare and drug development? According to Nohaile, “there needs to be money and effort into educating the non-data scientists. They don’t need to know a random forest from a Bayesian network, but it comes back to, ‘how are you going to change the culture so that scientists are working with data scientists?’”
Today, Amgen has dozens of digital health programs and “beyond the molecule” activities at various levels of maturity with plans to further enhance this capability. As we continue to develop this capability, perhaps there will come a day when data-related terminology—and the technology itself—will be commonplace for scientists and others across the industry. “I look forward to a future where Amgen harnesses AI to more fully enable a healthcare transformation for providers, patients, and our society,” said Nohaile.