TAIPEI, Taiwan – The topic of where technology will take health care in the near future was approached from numerous perspectives on the first day of BioTaiwan. While long-term questions such as what tasks will remain for humans were harder to answer, there was more certainty about the changes that are on the horizon.

One of the dominant trends at the intersection of technology and health care is the shift toward precision medicine, said the event's first speaker, Reenita Das, senior partner and senior vice president for transformational health at Frost & Sullivan. A futurist, Das described precision medicine as "the right product to the right person at the right time through the right channel."

The move toward precision medicine is being driven by the current unsustainability of health care rather than technological advances themselves, she said.

"The cost of health care is prohibitive, and it is a totally dysfunctional system," Das said, "We need to focus on better outcomes."

One place to start is to move health care providers away from administrative work, which can occupy 80 to 90 percent of their work time. There are also opportunities to move from disjointed care to coordinated care via the internet of things.

That linkage of different sensors and devices will enable a large-scale shift from location-dependent care to location-agnostic care, Das said. Diagnosis, monitoring and treatment will be able to be done in any location, while discrete care interactions will yield to a continuous care model. "Health care will be anyplace, anytime, anywhere," she said.

One of the more useful places for collecting patient data is the hospital bed. In a hospital with 200 beds, there is, on average, one fall a day, according to Jason Wang, co-founder of Medicustek Inc. Those falls may be due to disorientation from drugs or simply poor balance due to old age. Medicustek has developed an in-bed monitoring system to prevent bed falls and pressure sores. Known as the Sensable Care System, it reduces bed falls by 75 percent. "That means we're saving lives," said Wang.

The system's sensor pad for beds, which was developed and tested in Taiwan, is able to monitor heart rate, respiration, position and movements in bed. That allows for monitoring of the aftereffects of medicine on a patient.

Speaking during an afternoon session on integrating technologies for health care applications, Wang said he envisions the system moving out of expensive hospital rooms and into people's homes. Not only do patients save the cost of a hospital bed, he noted, they're more comfortable at their own homes. Systems such as Sensable will allow passive data collection and active patient participation for better insights.

Additional areas in which technology will bring health care home, Wang said, were telemedicine and robot caregiving, although he had more confidence in the former becoming more common in the near term than the latter. Artificial intelligence developments that will enable robots to replace humans in certain aspects of health care are unlikely anytime soon, he said, noting that "machines are very good at 'what' and 'how', but they're not very good at 'why'."

One area where big data technology is making earlier inroads is drug discovery.

"The future of biological research and medical breakthroughs involves integration of AI and machine learning and large-scale high-throughput experimental biology," said Jeffrey Lu, co-founder and CEO of Engine Biosciences Pte. Ltd. Lu's company has built a platform aimed at improving data and increasing the scale of iterative learning while reducing the cost of drug discovery. It focuses on drug discovery for genetically defined cancers, neurodegeneration and skin diseases.

Artificial intelligence can also be used to improve efficiency and outcomes of CNS clinical trials, said Sharon Fernando, senior clinical scientist, clinical surveillance and training, at Syneos Health Inc.'s APAC division.

"Quality patient selection and reliable efficacy endpoints are two of the most critical elements of a successful CNS clinical trial," Fernando said.

The convergence of AI and medicine is still relatively new, and for companies who are entering that field from whatever angle, the approach requires creativity and flexibility. Fernando said that Syneos Health starts with collaboration between experts across different regions – the U.S., Europe, South America and Asia.

"In terms of our clinical surveillance and training, we also have a project management side, which will get the data together and integrate it into our systems that then the programmers are able to turn into interpretable scalable data for scientist and medical directors to then understand," she said.

For Lu, building the right team has meant keeping molecular scientists, data scientists and clinical scientists on a level playing field. "You have to be mindful when interviewing candidates and look for people who are going to be able to work as equals with others," he said, "You need to recruit people without equals."

With all that data involved, much of it sensitive, privacy protection was a recurring theme in the afternoon talks and panel discussion. Consumer pushback against Facebook's monetization of user data and its spread of fake news were cited by Wang as warnings for the health care industry.

"The competitive advantage in AI for health care will be trust – you have to be able to trust the information you're getting," Wang said. "Can you imagine fake news in health care?"