A professor reviewed drugs being tested against COVID-19 that were repurposed from other uses. Researchers generated a knowledge graph embedding from 183k triples connecting proteins, genes, drugs and diseases. Their preliminary link prediction model achieved 50% accuracy at ranking potential interactions, higher than random chance, and integrated machine learning with biological insights on drug development.

1. Ramalli E., Parravicini A., Di Donato G., Salaris M., Santambrogio M.
edoardo.ramalli@mail.polimi.it
Embedding Based Knowledge Graph
Link Prediction for Drug Repurposing
1
July 19, 2020 - vNGC

2. Breaking News
2
“After Saving his own life with a repurposed drug,
a professor reviews every drug being tried against
Covid-19. Here’s what he’s found.”
By Ryan Prior, CNN
June 27, 2020
Edoardo Ramalli -- edoardo.ramalli@mail.polimi.it -- July 19, 2020 - vNGC

3. Knowledge Graph
3
Proteins
Genes
Drugs
Diseases
treat
involved
interacting
parent of
associated
to
encoding
interacting
Edoardo Ramalli -- edoardo.ramalli@mail.polimi.it -- July 19, 2020 - vNGC

4. Knowledge Graph
4
Proteins
Genes
Drugs
Diseases
treat
involved
interacting
parent of
associated
to
encoding
interacting
Triples: 183k, Entities: 63k, Relations: 70
32.0%
22.0%
38.0%
8.0%
Edoardo Ramalli -- edoardo.ramalli@mail.polimi.it -- July 19, 2020 - vNGC

5. Link Prediction
5
Disease
Drug
Protein
High Probability Interaction
Edoardo Ramalli -- edoardo.ramalli@mail.polimi.it -- July 19, 2020 - vNGC

6. Embedding
6
0.3
0.1
...
0.7
0.3
0.1
...
0.7
0.3
0.1
...
0.7
Disease
Drug
Protein
Link Prediction
Edoardo Ramalli -- edoardo.ramalli@mail.polimi.it -- July 19, 2020 - vNGC

7. Preliminary Results
7
Accuracy: we are learning H@10 ~ 0.5 → Random baseline has H@10 = 0
Dataset: Better and more data implies greater results → still plenty of open data to integrate
Time: 12h e2e KG generation and prediction → dimensionality reduction w.r.t. clinical steps
Biological Insight: convergence of ML and better comprehension of pharmaceutical science
Edoardo Ramalli -- edoardo.ramalli@mail.polimi.it -- July 19, 2020 - vNGC

8. Preliminary Results
8
Accuracy: we are learning H@10 ~ 0.5 → Random baseline has H@10 = 0
Dataset: Better and more data implies greater results → still plenty of open data to integrate
Time: 12h e2e KG generation and prediction → dimensionality reduction w.r.t. clinical steps
Biological Insight: convergence of ML and better comprehension of pharmaceutical science
Edoardo Ramalli -- edoardo.ramalli@mail.polimi.it -- July 19, 2020 - vNGC
Embedding Based Knowledge Graph Link Prediction for Drug Repurposing
July 19, 2020 - vNGC
Thank You !
Ramalli E., Parravicini A., Di Donato G., Salaris M., Santambrogio M.
edoardo.ramalli@mail.polimi.it