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 <ul><li>Monica Campillos </li></ul><ul><li>Michael Kuhn </li></ul><ul><li>Anne-Claude Gavin </li></ul><ul>...
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Predicting novel targets for existing drugs using side effect information

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

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Predicting novel targets for existing drugs using side effect information

  1. 1. Predicting novel targets for existing drugs using side effect information Lars Juhl Jensen
  2. 2. the problem
  3. 3. new uses for old drugs
  4. 4. drug–drug network
  5. 5. shared target(s)
  6. 6. chemical similarity
  7. 7. Campillos & Kuhn et al., Science , 2008
  8. 8. Campillos & Kuhn et al., Science , 2008
  9. 9. similar drugs share targets
  10. 10. only trivial predictions
  11. 11. the idea
  12. 12. chemical perturbations
  13. 13. phenotypic readouts
  14. 14. drug treatment
  15. 15. side effects
  16. 16. the implementation
  17. 17. information on side effects
  18. 18. package inserts
  19. 19. Campillos & Kuhn et al., Science , 2008
  20. 20. text mining
  21. 21. side-effect ontology
  22. 22. backtracking
  23. 23. Campillos & Kuhn et al., Science , 2008
  24. 24. side-effect correlations
  25. 25. Campillos & Kuhn et al., Science , 2008
  26. 26. GSC weighting
  27. 27. side-effect frequencies
  28. 28. Campillos & Kuhn et al., Science , 2008
  29. 29. raw similarity score
  30. 30. Campillos & Kuhn et al., Science , 2008
  31. 31. p-values
  32. 32. Campillos & Kuhn et al., Science , 2008
  33. 33. side-effect similarity
  34. 34. chemical similarity
  35. 35. Campillos & Kuhn et al., Science , 2008
  36. 36. reference set
  37. 37. drug–target pairs
  38. 38. Campillos & Kuhn et al., Science , 2008
  39. 39. drug–drug pairs
  40. 40. score bins
  41. 41. benchmark
  42. 42. Campillos & Kuhn et al., Science , 2008
  43. 43. fit calibration function
  44. 44. Campillos & Kuhn et al., Science , 2008
  45. 45. probabilistic scores
  46. 46. the results
  47. 47. drug–drug network
  48. 48. ATC codes
  49. 49. Campillos & Kuhn et al., Science , 2008
  50. 50. categorization
  51. 51. Campillos & Kuhn et al., Science , 2008
  52. 52. Campillos & Kuhn et al., Science , 2008
  53. 53. Campillos & Kuhn et al., Science , 2008
  54. 54. map onto score space
  55. 55. Campillos & Kuhn et al., Science , 2008
  56. 56. the experiments
  57. 57. 20 drug–drug relations
  58. 58. in vitro binding assays
  59. 59. Campillos & Kuhn et al., Science , 2008
  60. 60. Campillos & Kuhn et al., Science , 2008
  61. 61. Campillos & Kuhn et al., Science , 2008
  62. 62. K i <10 µM for 11 of 20
  63. 63. cell assays
  64. 64. Campillos & Kuhn et al., Science , 2008
  65. 65. 9 of 9 showed activity
  66. 66. the future
  67. 67. target side-effect profiles
  68. 68. drug–target network
  69. 69. integration with STITCH
  70. 70. Acknowledgments <ul><li>Monica Campillos </li></ul><ul><li>Michael Kuhn </li></ul><ul><li>Anne-Claude Gavin </li></ul><ul><li>Peer Bork </li></ul>

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