1. Faster Cures For All
Geoffrey H. Siwo
Co-Founder Fit2Cure
Lurie Medical Research Center
Northwestern University, Chicago, IL

2. A century of exponential
progress in Health

3. In 100 years, Life expectancy
increased 100%

4. 93% reduction in child mortality

5. Time from bench to bedside
much shorter

6. ~200 years since discovery of scurvy-lemon juice association to implementation

7. Faster time to clinic, last 100
years

8. But….

9. 7 million children die before
age of 5

11. Bench to bedside still takes
too long

12. 17 years
$1 Billion
90% Failure

13. >10,000 Monogenic diseases

14. We don’t even have data for
most of these diseases

15. Cystic Fibrosis

16. >95% of diseases have no
cures

17. Most medicines don’t work in
most people
Allen Roses, GSK VP Genetics

18. Why?

19. Human Genetic Diversity is
Massive

22. Current system can’t cope

23. We must empower millions to
be part of discovery

24. Can we really?
What if we do?
Are we ready for it?
Is our policy ready for it?

25. Can we?

26. ~3 billion people online by
end of this year

29. What if each computer/
mobile was a lab?

30. Yes, it’s possible…

31. … in Africa
2003: Undergraduate in Africa doing computational modeling of HIV on a pay-to-go computer
2003 to 2005: organized
Bioinformatics training for fellow
students
2010: Students in 2003 group organize
First Virtual Bioinformatics Conference in
Africa

32. …in USA
• 15 year old Jack Andraka develops pancreatic cancer test: 100 times
more sensitive and 28 times cheaper

33. Even more complex
experiments will be possible

34. Virtual Physiological Human

35. Virtual Heart- Cardiod project
• Near-cellular resolution Real-time simulation
of the electrophysiology of the human heart

36. Virtual Brain

37. These complex experiments will
come to your computer

39. Everywhere

40. 628,000 members
2.5 million devices
796,000 years of computing

41. Something from the Nobel
prize in Chemistry 2013

43. >Half a billion people play
computer/ video games for at
least 1 hour a day

44. Why not solve science
problems in games?

46. Fit2Cure
A lab and a scientist on every
computer

47. Computers are incredibly fast, accurate
and stupid. Human beings are incredibly
slow, inaccurate and brilliant. Together
they are powerful beyond imagination

48. With Co-Founders Ian Sander and Victoria Lam

49. Drug discovery pipeline
Identify disease
Isolate protein involved in disease (2-5yrs)
Foldit
Find a drug effective against disease protein (2-5yrs)
Fit2Cure
Preclinical Testing (1-3yrs)
Formulation & Scale-up
FILE IND:
Human clinical trials (2-10yrs)
FILE NDA: FDA
approval (2-3yrs)

50. Game interface

51. Competition! +
Social Impact
Compete with friends!
In the future:
For our top scoring players, we
will be donating (real) money
to an approved research
center or rare & neglected
disease institute of your
choosing, and in your name.

52. Emergent patterns in
play trace
• Expectation-maximization
(EM) based mining of
player data
-user interface design
- novel scientific insights

53. Players can do real
science!
Time (Mins)
HIV-1 Protease

54. Drug
discovery
algorithms
I.P. of
integrating
human
cognition
Drug
Binding
simulation
models
Web-based
gaming
sessions
Analytics
New Insights
New Drugs

55. Design your medicine
in future

56. Connecting Fit2Cure to Your
Genetics: Fit2CureMyDisease
• Fit2Cure links personal genome data from the company
23andMe
• Fit2Cure can alert you when you are playing with a protein in
which you have mutations or allergic drug reactions

57. Print your own medicine

59. Or send to robot scientists
online to make it and mail it to
you

60. Remote controlled chemistry lab

61. Hypothesis generating and
testing robot scientists

62. Adam- The Robot Scientist
• Adam designed hypotheses, experiments and tested them to
discover function of novel yeast genes

63. Who owns the discoveries?

64. Who decides which disease
should be studied first?

65. Should players be compensated?

66. What if players design dangerous
chemical from game?

67. Discoveries are going to
happen faster than policy

68. What are the challenges?

69. • Fast discovery will outpace our ability to
build policy
• Policy must anticipate, there will be no
time
• Central regulation will be extremely
difficult since tools will be available to
many

70. What are the opportunities?

71. • Allow millions to engage in
experimentation in what affects them
• Democratized and rapid discovery
• Realistic simulations of your own health
(Personalized medicine)
• Preparing the world for an unknown
pandemic

72. Acknowledgements
Charles Edison Fund
DynamoidApps
Fit2Cure Players