SmartLife - Addressing the Needs of People with Diabetes (PwD) Using Machine Learning

Transcription

1 SmartLife - Addressing the Needs of People with Diabetes (PwD) Using Machine Learning Tina Woerner, Roche Alexander Buesser, IBM September, 19th

2 Roche is a Basel based, global pharmaceutical company 2

3 doing pioneering work in personalised healthcare across diagnostics and pharma CHF 10.4 billion R&D investment 30 R&D sites worldwide ** CHF 53.3 billion sales 26 manufacturing sites worldwide #1 R&D investor in healthcare* Among top 10 R&D investors across industries * Strategy & Global Innovation 1000, Winter 2017 **Pharmaceuticals and Diagnostics 3

4 Our Vision By 2025 we will help people with diabetes everywhere in the world think less about their daily diabetes routine so they can get true relief, day an night. 4

5 st Diabetes is the global epidemic of the 21 century IMAGE BY GSFC / CC BY 2.0 5

6 6

7 Prevalence worldwide 1 of 11 adults has diabetes SOURCE: IDF DIABETES ALTAS 8TH ED., INTERNATIONAL DIABETES FEDERATION,

8 Prevalence worldwide World 425 M 2017 SOURCE: IDF DIABETES ALTAS 8TH ED., INTERNATIONAL DIABETES FEDERATION,

9 Prevalence worldwide World World 425 M M 2045 SOURCE: IDF DIABETES ALTAS 8TH ED., INTERNATIONAL DIABETES FEDERATION,

10 Prevalence worldwide 16 % 35% 110% 84% 15 % 62% 156% SOURCE: IDF DIABETES ALTAS 8TH ED., INTERNATIONAL DIABETES FEDERATION,

11 The challenge living with diabetes

12 More than 50 Therapy Decisions per day, every day Take blood glucose test Estimate carbohydrate intake Calories burned Calculate insulin dose Apply short-acting insulin Apply long-acting insulin Document data in diary Add mealtime info to diary Add health events to diary

13 Living with Diabetes 24 hours 13

14 Living with Diabetes 365 days 14

15 For the rest of your life. 15

16 The biggest challenge Stay in range

17 Job to be done: Keep glucose levels in range Hyper Hypo 17

18 Job to be done: Keep glucose level in range Hyper in Range Hypo 18

19 Three main factors are known to influence the glucose level 19

20 but for reliable estimates many hundred signals need to be taken into consideration 20

21 There is no mono-causal relation in a complex dynamic system 21

22 At the center of it, a human being is required to pull the strings 22

23 How can technology help? 23

24 Technology in the shape of mobile devices take on particular spots 24

25 Technology in the shape of mobile devices take on particular spots 25

26 All data from mobile accessories are transferred to a phone but most of the time into different apps 26

27 Product Vision Your glucose level is low and it will cross the hypo treshold within the next 30 minutes. How about a glass of apple juice? 27

28 We focused on three analytics areas Pattern detection Glucose prediction Focuses on describing historical Based on historical meal information, glucose data Information helps physician adjust the therapy Patient receives feedback on frequent occuring patterns Therapy advice activity, insulin amount and many other features glucose values are predicted To make predictions we need a learning Translates the glucose prediction into advice Simulations are made based on the prediction algorithm to evaluate the algorithm that can formulate the effect of different insulin and carb relationship between the variables to amounts for a particular time span mimic the human metabolism Results are translated into advice 28

29 and collaborated across organizations through a centralized analytics pipeline Centralized variable repository used for analytics Variable Similar patient identification Sample Variable filter Personalized predictive modeling Therapy advice 29

30 As patients metabolisms are very different we identified subpopulations in a clinically meaningful way 30

31 For each subpopulation we applied supervised learning methods Iterate over Historical input data and mulitple more samples Historical output data f(x) Example input data Glucose predictor 31

32 Three points to consider when innovating at the interface of healthcare and AI Co-innovation.. bringing Understand your signal s together people with different distributions. Do they make skills. Industry expertise as a sense in a particular context? Look beyond model accuracy! key differentiator. 32

33 Doing now what patients need next 33

34 Tina Wörner International Product Manager Solution Development Roche Diabetes Care GmbH Phone: Alexander Büsser Lead Data Scientist IBM Global Business Services Phone: