ARTIFICIAL INTELLIGENCE IN HEALTHCARE Dr Yuanrui Margaret Shi

ARTIFICIAL INTELLIGENCE IN HEALTHCARE Dr Yuanrui Margaret Shi 7 July 2017

2 Contents • Healthcare • Technology innovation in healthcare • Healthcare Artificial Intelligence market • Artificial Intelligence and machine learning • Examples • Challenges • Quintile. IMS

3 Healthcare • Patient care is a complex, sensitive and high risk activity and process • Complex • Patients see doctors with symptoms • Doctors spot the patterns and identify the variations from the norm • Doctors manage the diseases with different treatment options • Sensitive and high risk • Huge variation in disease presentation, and treatment options • Dealing with human beings

4 Technology innovation in healthcare • Successful health care delivery requires effective medical technology • Combination of technology and health = boon! • Break barriers in the future and change the healthcare scenario, creating lasting impact • Robotics • Nanotechnology • Artificial Intelligence

5 Healthcare Artificial Intelligence market • Lucrative market – expected to reach $7. 98 billion in 2022

6 AI and machine learning. How does AI work in healthcare? • Artificial Intelligence is the field of study where we teach computers how to learn • Machine learning is a type of AI that allows computers to make predictions without being explicitly • Provides formal conceptual framework for input processing and decision making in diagnosis and management • Objective decision making with less variance • High speed and efficiency • All result in real benefits to patients

7 What are the examples of AI in healthcare? • Almost every aspect of healthcare could, theoretically, benefit from an AI approach • Microsoft • Predictive analytics in vision care • Google • Clinical decision support in breast cancer diagnosis • IBM Watson • Precision medicine in population health management

8 Challenges • True AI has yet to come • Clinical decision support tools • Companion diagnostics

9 Quintile. IMS • Leading worldwide integrated information and technology enabled healthcare service provider • >50, 000 employees operating >100 countries with leading scientific, analytical and commercial experts • Formed through the merger of Quintile and IMS in October 2016 • Possess global health data assets with Real World Evidence (RWE) insights generated by advanced analytics leveraged by its technology infrastructure

10 Quintile. IMS • Clients include top 100 global pharmaceutical and biotechnology companies • Market opportunity for R&D services and commercial solutions • Growth strategy by continuing to innovate

11 Quintile. IMS • $7. 8 billion revenue with 7. 8% growth • $24 billion enterprise value • $18 billion market capitalisation • 11% shareholder return • Revenue by segment – $3. 5 B in commercial solution, $3. 5 B in R&D solutions, $0. 8 B in integrated engagement services • Revenue by region – $3. 5 B in Americas, $2. 8 B in EMEA, $1. 5 B in Asia Pacific

12 Conclusion ‘Cognitive computing could usher in a golden age – if we shape it wisely. ’ ‘There’s a land rush around AI right now… the competitive advantage is going to come from being cognitive. ’ • IBM President and CEO Ginni Rometty

13 Thank you