The recent Intelligent Health AI conference in Basel, Switzerland brought together 1,500 clinicians; government ministers and regulators from the WHO, FDA and EC; technologists; startups; and C-suite life sciences executives from 68 countries to discuss the future of AI and data—and its potential implications for healthcare. The energy and commitment to change and progress in the room was palpable!
From the very first day of the conference, Patrice Matchaba, Head of Corporate Responsibility at Novartis, called on each member of the audience to “reimagine healthcare” and to bring the power of collaboration to change the outcome for patients worldwide.
Power of data
Bertrand Bodson, the Chief Digital Officer of Novartis, gave some practical examples of how they are using data and AI to accelerate and inform their business. They are screening the 1.5 million compounds in their research archives to accelerate and optimize research as well data mining their two million patient years of development data to bring products to market more effectively. In addition, Novartis is leveraging Shyft’s analytics platform to gain insights from their 100,000 daily interactions with healthcare practitioners.
Steve Guise, Global Head of Roche Pharma Informatics, spoke about AI addressing the challenges of a labor-intensive industry and Roche’s commitment to the three tenets of:
Even the regulators acknowledged the importance of having—and sharing—patient data. In a panel on “How do you regulate a device that uses a self-improving algorithm?,” leaders from the FDA and European Commission discussed the Electronic Health Data System Interchange, a commitment signed by EU member states to provide access to one million genomes in Europe by 2022.
Dozens of startups participated in the event including Benevolent AI, one of the few HealthTech unicorns, and Recursion Pharmaceuticals. The array of startups showed the potential in taking any kind of data to solve a particular problem. Benevolent AI spoke about their formula of “Chemists + Cheminformatics + AI” and how they use deep learning to figure out how a compound behaves. Recursion’s main message focused on their philosophy that “images” have the highest data density per dollar. They discussed how they center their organization on the four use cases of:
Vocalytics argued that voice technology can reach a much larger population of patients than other tech such as phones, watches or IoT devices. These were only a few of the startups present. I encourage you all to get out and meet as many startups as possible to understand what they have to offer your business. This is what the Accenture HealthTech Innovation Challenge does—connects startups with life sciences and healthcare companies to tackle some of the world’s biggest healthcare challenges.
I also had the opportunity to discuss how data availability and analytics—combined with machine learning and AI—can fundamentally change our existing business models. In the continuous learning environment that AI enables, linear business models can evolve to circular models of continuous innovation, trial, test and learn centered on the patient. The real-time data flow from patients helps companies know more precisely what is working and what is not, enabling companies to develop new products and services more quickly and effectively. It lays the groundwork for bringing an improved patient outcome to market—continually. All of this will help patients in the long run and break down some of the traditional industry constraints. Accenture’s Kaveh Safavi, senior managing director—health industry, took up this theme in his discussion of how AI will open the “iron triangle” of access, affordability and effectiveness of healthcare.
The opening day also coincided with Apple’s announcement of their Apple Watch Series 4 with inbuilt electrocardiogram (ECG) and fall detection capability—truly a sign of the times.
The industry has been talking about connected health for a long time. We’re on the cusp of making it happen with data and AI acting as the superhighways that blast through industry silos and inefficiencies. Our recent research on Raising the Life Sciences Commercial IQ with Applied Intelligence looks at how this might work in practice. It features use case examples and key steps to get started with AI in commercial operations, marketing operations, sales operations and patient engagement.
Although there are likely to be some bumps on the way, it is an exciting and liberating moment!