コンペティションから見るAI創薬/AI drug discovery in the view of competitions

日本オミックス医学会シンポジウム 発表資料
場所: 東京医科歯科大学
日付: 2019/3/18

2018/3/20 誤記修正
2018/3/21 誤記修正

Transcript

1. a I (
   M A M89 :)
   3 /21 1 / 0/
   )
   ) A c
   

   View Slide

2. s ( 21 1- 40
   z ( u 76 6 7
   ) ) h o 7M
   M AI(
   : 7 r a
   ( k
   c
   7
   i
   

   View Slide

3. 3
   IS o J P
   123 32
   0 J P T
   0 J P T
   0 J P T
   6 n
   0 J P T
   4 DJ PG
   C A 7E5 D4J A
   C C eB E5
   

   View Slide

4. 
   
   
   
   P GI
   gGI
   M ci 06?5: 0 65A 4? 5 B C 84 6 76
   .?4 8 11ae h
   M ci 2 3 gM N
   M ci g T
   M
   

   View Slide

5. 
   
   
   

   View Slide

6. 6
   AI=
   
   +.9<*!%;7BG
   =?4D
   
   +.1:/"(*
   5C0 A,"(&$
   =
   %&' )6F5C=?
   >@8E3
   -23
   

   View Slide

7. 
   
   
   

   View Slide

8. 
   
   
   
   <;
   .%7
   FC*
   '4
   <;p53L. +
   
   '&(AE!1IBM)
   DK5=(FC*'40
   
   BH1G .%7D/:36I
   (-"8$)
   .%7>@1GJD
   ↑ # 2?, )9
   

   View Slide

9. View Slide

10. 1 0 0
    n RAK ) S2 AK K
    n g 1 0 Ra
    Ra 0 5 Q e
    (
    425 %10/7&
    (!
    *
    ,
    10/(!
    $%)+.#
    #
    "
    425
    'Kaggle(063(-
    

    View Slide

11. 1
    n eh a kGn f R / :/
    V Fod eh aFH lm g Sb
    RHMS A
    n V . :/ i eh
    a cS A
    p 2 / /: / ./: :.
    

    View Slide

12. M ,1 42 , 2 , 0 0 9 22 3.
    n
    ?
    n
    :
    
    AC
    

    View Slide

13. View Slide

14. 4 1
    #)$
    '
    
    !%(
    *
    $
    
    (Convolutional Neural Network)
    $
    %"
    &
    &
    
    
    

    View Slide

15. 1
    $)&
    ("
    
    Fingerprint/Descriptor
    %
    
    &
    (Graph Convolutional Neural Network)
    &
    !
    #
    '
    '
    

    View Slide

16. n 1 G 6 C
    n N
    : Altae-Tran et al, ACS Cent. Sci.,2017,3(4), pp 283–293
    
    
    

    View Slide

17. 
    
    
    
    

    View Slide

18. n ( ) P O N B A
    n I 24 0 2 1 1
    Virtual screening…
    
    
    
    
    
    1
    
    2
    
    3
    
    
    

    View Slide

19. n N
    G
    n K
    C
    
    967
    (#
    
    &).0
    *!
    "%*@
    
    =1;=>*
    
    *(400)
    4?:“”*
    */$,
    862?3'
    
    +(-OK
    

    View Slide

20. 7 8 T d fng
    ] N mi a
    M hmi ]
    C [ Ct ep r
    a 21 . ? 0 ?9 5 ( ) ) (
    )( 02
    s y , 9 T
    u CG ] NaY I
    

    View Slide

21. ( 7 2
    Extended Connectivity Fingerprint
    Functional Connectivity Fingerprint
    Topological Torsions
    Atom Pairs Fingerprint
    RDKit Fingerprint
    Avalon fingerprint
    !fingerprint (6)
    70
    Random Forest
    Extremely Randomized Trees
    Gradient Boosted Trees
    Multilayer perceptron
    Support Vector Regression
    !
    $)%(&' (5)
    65 = 30#
    Elastic Net Pfinal
    Level 0
    Level 1
    "
    #
    
    1 2 ) ):
    

    View Slide

22. 
    Fingerprint
    ECFP FCFP TT AP RDK AVLN F-Stacking
    RF 0.848 0.855 0.816 0.686 0.652 0.722 0.892
    ERT 0.869 0.889 0.844 0.798 0.671 0.768 0.907
    GBT 0.852 0.864 0.835 0.808 0.733 0.758 0.891
    MLP 0.802 0.777 0.623 0.814 0.651 0.712 0.895
    SVR 0.856 0.852 0.688 0.763 0.662 0.693 0.877
    L-Stacking 0.890 0.911 0.870 0.881 0.799 0.846 0.930 FL-Stacking
    
    
    Level0
    ROC-AUC
    
    ) 1 ) (0( 72
    n 0 3 0
    0
    

    View Slide

23. 2 ( 7 )1)0 3
    5
    
    
    IMSBIO () () 1
    8 1
    Univ-shizuoka 1
    PFDrug ()Preferred Networks 1
    kiharalab 1 1
    Graph CNN
    

    View Slide

24. View Slide

25. 38 5 120
    n 0 u ”Taklbe : ()
    :. 00 1Tcn
    n s T
    n p w Th cn dg
    I I “ L ing
    n r P v T ng D
    n T t p
    o y 2 8: : .2 1 2 - // /: 0:
    

    View Slide

26. )0 3 6 ( 2 1
    n Lel an f LN b i -
    b i -/) -
    n U N gc
    d -
    s
    n D - b i ( 1) -1- P
    t ( 1) )
    vo el an (
    

    View Slide

27. )0 37 ( 2 1
    n 24 9: 9 0
    4
    n 1 9 9 56 8
    2 3 W 2 9 4
    O O
    O
    !!!
    

    View Slide

28. 
    
    
    

    View Slide

29. 9 21
    n
    e l ( g
    n
    K
    n
    )
    a )
    

    View Slide

30. 20 2 3
    n
    3 t 1
    o r ru 2
    a i 1 o ru ) 2
    l1 ru 1es 2
    1 r f K2
    n
    (( h g g K2
    

    View Slide

31. 1 3
    n
    ( )
    )
    n
    :
    )
    

    View Slide

32. X 8
    T 9
    8.
    A
    T 9
    8.
    A
    T 9
    8.
    A
    0
    
    
    
    3 T .
    9? A 5 2
    

    View Slide

33. (
    • 9)
    : / 51)
    5
    • 1 55
    5
    2 1:023/ 5
    

    View Slide