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Predicting novel targets for existing drugs using side effect information

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    Predicting novel targets for existing drugs using side effect information - Presentation Transcript

    1. Predicting novel targets for existing drugs using side effect information Lars Juhl Jensen
    2. the problem
    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
    11. the idea
    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
    31. p-values
    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
    40. score bins
    41. benchmark
    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
    48. ATC codes
    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
    66. the future
    67. target side-effect profiles
    68. drug–target network
    69. integration with STITCH
    70. Acknowledgments
      • Monica Campillos
      • Michael Kuhn
      • Anne-Claude Gavin
      • Peer Bork

    + Lars Juhl JensenLars Juhl Jensen, 6 months ago

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