Open data, compound repurposing, and rare diseases

Andrew Su, Ph.D.@andrewsuasu@scripps.eduhttp://sulab.org

February 16, 2017

Slides: slideshare.net/andrewsu

Raynaud disease and fish oil2

Raynaud disease

Raynaud disease and fish oil3

Raynaud disease

Fish oil / EPA

Abnormal platelet activity

Abnormal blood

viscosity

High blood viscosity

Elevated RBC rigidity

Vasodilation

Low blood triglycerides

Increased prostacyclins

Raynaud disease and fish oil4

“Undiscovered public knowledge”5

Raynaud disease

Fish oil / EPA

Abnormal platelet activity

Abnormal blood

viscosity

High blood viscosity

Elevated RBC rigidity

Vasodilation

Low blood triglycerides

Increased prostacyclins

A

C

B

B BB

BB

B

“Undiscovered public knowledge”6

Raynaud disease

Fish oil / EPA

Abnormal platelet activity

Abnormal blood

viscosity

High blood viscosity

Elevated RBC rigidity

Vasodilation

Low blood triglycerides

Increased prostacyclins

A

C

B

B BB

BB

B

“Undiscovered public knowledge”7

Building a Network of BioThings (then)8

Eicosapentaenoic acid

Platelet aggregation Fatty Acid

Edge = co-mention

x 1000s article titles

Building a Network of BioThings (now)9

Eicosapentaenoic acid

Platelet aggregation Fatty Acid

x 1000s article titles

x 26 million articles…… and full abstracts

decreases Edge = co-mention

= PubChem:446284 = Timnodonic acid

Information extraction 10

1: Identify all biomedical concepts

2: Identify relationships between concepts

11

PathwaysDiseasesProteinsVariants

GenesDrugs

Goal: Assemble a network of biomedical entities that is comprehensive, current, computable, and traceable.

12

13

PathwaysDiseasesProteinsVariants

GenesDrugs

Goal: Assemble a network of biomedical entities that is comprehensive, current, computable, and traceable.

14

Sou

rce:

http

s://w

ilson

com

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slab

.org

/201

4/03

/06/

calli

ng-a

ll-su

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ters

Question: Can a group of non-scientists collectively perform concept recognition in biomedical texts?

15

16

Experts versus crowd for concept identification

593 PubMed abstracts

6,900 mentions of “disease concepts”

F = 0.87F = 0.78

$$$

17

Experts versus crowd for concept identification

593 PubMed abstracts

6,900 mentions of “disease concepts”

F = 0.87F = 0.87

$$$

• 9 days• 145 workers• Total: $630.96

19

http://mark2cure.org

20

Paid crowdsourcing

• F = 0.84• 28 days• 212 workers• Total cost: $0

$$$

• F = 0.87• 9 days• 145 workers• Total: $630.96

“Help science, please”

Citizen Science

Does Citizen Science scale?21

1,000,000 articles * 10 AE / article 15,828 volunteers

needed10,275 AE * 365 days

212 annotators* 28 days

AE = Annotation events

=

Number of annotation events per year

Number of annotation events per year

per volunteer

Does Citizen Science scale?22

15,828 volunteers

needed

200,000 volunteers

460,000 volunteers

37,000 volunteers

1,000,000+ volunteers

23

Nina Hale https://flic.kr/p/zoVih

Rare disease case study #224

25

26

… but no obvious treatments

Mapping the biomedical network around NGLY1 27

NGLY1

28

http://mark2cure.org

29

A preliminary view of the NGLY1-focused biological network

1,200 contributors3,200 documents 787,400 annotations

30

A preliminary view of the NGLY1-focused biological network

A

C

B

B BB

BB

B

AB

B BB

BB

B

A

B

B BB

BB

B

31

http://slides.com/dhimmel/big-data-seminar

32

http://slides.com/dhimmel/big-data-seminar

33

http://slides.com/dhimmel/big-data-seminar

34

http://slides.com/dhimmel/big-data-seminar

35

http://slides.com/dhimmel/big-data-seminar

36

Biomedical research relies on effective

Pie

tro B

ellin

iht

tps:

//flic

.kr/p

/k5j

mja

KNOWELDGE MANAGEMENT

Ben GoodChunlei Wu Shirley Willis

Sebastien Lelong

Andra Waagmeester

Max Nanis

Cyrus Afrasiabi

Julia Turner

Ginger Tsueng

M2C M2C

Louis Gioia

Toby Li

Karthik G

Kevin Xin

Jake Bruggemann

Mike Mayers

DR

DR

Julee Adesara

Ramya Gamini Greg Stupp Sebastian Burgstaller

Tim Putman Nuria Queralt Rosinach

DRDR

DR

DR M2C

The Crowds Funding