Predicting novel targets for existing drugs using side effect information

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Lars Juhl Jensen

Systems Biology Workshop, Technical University of Denmark, Lyngy, Denmark, May 14-15, 2009

Predicting novel targets for existing drugs using side effect information Lars Juhl Jensen

the problem

new uses for old drugs

drug–drug network

shared target(s)

chemical similarity

Campillos & Kuhn et al., Science , 2008

Campillos & Kuhn et al., Science , 2008

similar drugs share targets

only trivial predictions

the idea

chemical perturbations

phenotypic readouts

drug treatment

side effects

the implementation

information on side effects

package inserts

Campillos & Kuhn et al., Science , 2008

text mining

side-effect ontology

backtracking

Campillos & Kuhn et al., Science , 2008

side-effect correlations

Campillos & Kuhn et al., Science , 2008

GSC weighting

side-effect frequencies

Campillos & Kuhn et al., Science , 2008

raw similarity score

Campillos & Kuhn et al., Science , 2008

p-values

Campillos & Kuhn et al., Science , 2008

side-effect similarity

chemical similarity

Campillos & Kuhn et al., Science , 2008

reference set

drug–target pairs

Campillos & Kuhn et al., Science , 2008

drug–drug pairs

score bins

benchmark

Campillos & Kuhn et al., Science , 2008

fit calibration function

Campillos & Kuhn et al., Science , 2008

probabilistic scores

the results

drug–drug network

ATC codes

Campillos & Kuhn et al., Science , 2008

categorization

Campillos & Kuhn et al., Science , 2008

Campillos & Kuhn et al., Science , 2008

Campillos & Kuhn et al., Science , 2008

map onto score space

Campillos & Kuhn et al., Science , 2008

the experiments

20 drug–drug relations

in vitro binding assays

Campillos & Kuhn et al., Science , 2008

Campillos & Kuhn et al., Science , 2008

Campillos & Kuhn et al., Science , 2008

K i <10 µM for 11 of 20

cell assays

Campillos & Kuhn et al., Science , 2008

9 of 9 showed activity

the future

target side-effect profiles

drug–target network

integration with STITCH

Acknowledgments ,[object Object],[object Object],[object Object],[object Object]

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Predicting novel targets for existing drugs using side effect information

1. Predicting novel targets for existing drugs using side effect information Lars Juhl Jensen

3. new uses for old drugs

4. drug–drug network

5. shared target(s)

6. chemical similarity

7. Campillos & Kuhn et al., Science , 2008

8. Campillos & Kuhn et al., Science , 2008

9. similar drugs share targets

10. only trivial predictions

12. chemical perturbations

13. phenotypic readouts

14. drug treatment

15. side effects

16. the implementation

17. information on side effects

18. package inserts

19. Campillos & Kuhn et al., Science , 2008

20. text mining

21. side-effect ontology

22. backtracking

23. Campillos & Kuhn et al., Science , 2008

24. side-effect correlations

25. Campillos & Kuhn et al., Science , 2008

26. GSC weighting

27. side-effect frequencies

28. Campillos & Kuhn et al., Science , 2008

29. raw similarity score

30. Campillos & Kuhn et al., Science , 2008

32. Campillos & Kuhn et al., Science , 2008

33. side-effect similarity

34. chemical similarity

35. Campillos & Kuhn et al., Science , 2008

36. reference set

37. drug–target pairs

38. Campillos & Kuhn et al., Science , 2008

39. drug–drug pairs

42. Campillos & Kuhn et al., Science , 2008

43. fit calibration function

44. Campillos & Kuhn et al., Science , 2008

45. probabilistic scores

46. the results

47. drug–drug network

49. Campillos & Kuhn et al., Science , 2008

50. categorization

51. Campillos & Kuhn et al., Science , 2008

52. Campillos & Kuhn et al., Science , 2008

53. Campillos & Kuhn et al., Science , 2008

54. map onto score space

55. Campillos & Kuhn et al., Science , 2008

56. the experiments

57. 20 drug–drug relations

58. in vitro binding assays

59. Campillos & Kuhn et al., Science , 2008

60. Campillos & Kuhn et al., Science , 2008

61. Campillos & Kuhn et al., Science , 2008

62. K i <10 µM for 11 of 20

63. cell assays

64. Campillos & Kuhn et al., Science , 2008

65. 9 of 9 showed activity

67. target side-effect profiles

68. drug–target network

69. integration with STITCH

70.