Collaboration, externalisation, data sharing and integration

1. AI & Strategy development in
Life Science & Health:
Collaboration, externalisation,
data sharing and integration
Nick Lynch
1

2. Show me the Data! And the models
2
Oct 1 2020: https://www.stateof.ai/
Xkcd.com

3. Agenda
• Alignment of AI and Data
• Supporting Scientist & Clinician: Augmented
Intelligence
• Where to make AI investments to have biggest impact
• Best Practices in Data Science and AI
• AI Validation
• Collaborations and Pre-competitive

4. AI Strategies & Challenges –plus Talent
4
https://hbr.org/2019/07/building-the-ai-powered-
organization
https://business.linkedin.
com/content/dam/me/bu
siness/en-us/talent-
solutions/emerging-jobs-
report/Emerging_Jobs_
Report_U.S._FINAL.pdf
https://www.accenture.co
m/us-en/blogs/life-
sciences/scaling-ai-in-
biopharma-for-
transformation-and-
growth
https://www.mcki
nsey.com/busine
ss-
functions/mckins
ey-analytics/our-
insights/how-to-
build-ai-with-and-
for-everyone-in-
your-organization
75% 37%
Job Adverts

5. AI & Data – Before and After Covid-19
5 https://www.gsk.ai/blog/gsk-
ai-on-london-tech-week/
Goal: Machine
Readable Meta data
feeding AI Capabilities

6. Generating Data with Reuse in mind: FAIR –
Building Enduring Capability
6

7. How Pharma View AI: Competitive Edge,
Ventures, Collaborations
7The upside of being a digital pharma player (2020), Drug
Discovery Today, DOI: 10.1016/j.drudis.2020.06.002
Can
collaborations
solve some of the
key challenges?
• Regulators
• Patient Focus

8. AI Platforms in Discovery are evolving
8
BRADSHAW: a system
for automated
molecular design
Journal of Computer-Aided Molecular
Design volume 34, pages747–
765(2020)
Méndez-Lucio, O., Baillif, B., Clevert, D. et
al. De novo generation of hit-like molecules
from gene expression signatures using
artificial intelligence. Nat Commun 11, 10
(2020). https://doi.org/10.1038/s41467-019-
13807-w

9. Emerging NLP Advances impacting Life Science?
GPT-3 & AI language Models (OpenAI etc.)
9
https://arxiv.org/abs/2005.14165
Few Shot
Learners
How best to use
RWD/observational data
for increasing data pool.

10. 10Bender & Cortes http://www.drugdiscovery.net/2020/09/09/will-robotics-ai-and-cloud-computing-in-chemical-synthesis-
save-drug-discovery-a-closer-look/
AI ROI & Impact Biggest in the Clinical Phase of
Drug R&D highest impact can be
gained from
• better decisions
(fewer failures) in
clinical reduced time
taken in clinical
• reduced cost in the
lead optimization &
clinical

11. AI Validation & Validating Claims – CONSORT-AI
Reporting & Claims in Deep Learning Studies
11
https://www.bmj.com/content/368/bmj.m689
Conclusion: Future studies should diminish risk of bias,
enhance real world clinical relevance, improve reporting
and transparency, and appropriately temper conclusions.
https://www.nature.com/ar
ticles/s41591-020-1034-x

12. AI Model Validation – a key new role
12
https://blogs.gartner.com/svetlana-sicular/ai-validator-
a-rising-role-for-managing-ai-risk-in-the-enterprise/

13. 13
https://journals.plos.org/ploscompbiol/articl
e?id=10.1371/journal.pcbi.1008126

14. Emergence of Best Practices
• Domain knowledge
• “Fit for purpose”
• Data lifecycle methodology (FAIR)
Quality Data
• Reproducibility is key
• Model lifecycle methodology
• “Fit for purpose”
Quality
Models
• Fail early and cheap
• Human in the loop
• Skills and expectations management
Quality
Organization
References: https://osf.io/eqm9j/ and https://arxiv.org/ftp/arxiv/papers/2006/2006.16189.pdf

15. Collaborative Effort Examples
15
https://www.melloddy.eu/y1
announcement
Federated Learning Project
https://www.theaaih.org/

16. How Challenges help solve problems
16
https://www.synapse.org/#!Synapse:syn20545111/wiki/594083
https://www.kaggle.com/c/lish-moa

17. Datathons
17
• The challenge: Use computation to repurpose already
existing drugs for treatment of rare and neglected diseases
• 2019: Chronic pancreatitis in children is an extremely
painful condition, without a permanent cure
• Results:
- 4 candidate compounds identified
- Clinical trial was proposed, but now delayed
• Bio-IT 2020 Award Winner
• https://www.pistoiaalliance.org/news/pistoia-alliance-elsevier-
datathon/
• 2020: Diffuse Intrinsic Pontine Glioma (DIPG): rare (1000
cases/year worldwide) yet heterogeneous cancer of brain
stem; mean survival time < 1 year
• Objectives:
- Identify molecular subgroups of DIPG
- Identify suitable therapeutic targets in these subgroups (by
analysis of driver mutations or gene expression profiles)
- Assess already known drugs against these targets
• https://www.pistoiaalliance.org/news/ai_coe_datathon2020/

18. Summary & Questions
• Quality & Accessible (FAIR) Data
remains critical
• Focus on Augmented AI for
Scientist/clinician & high impact areas
• AI Validation is critical
• AI Ethics need solving
• Need to collaborate to solve AI
Challenges
• Pistoia Alliance
• AAIH
• FAIRplus
• etc
Thank you & questions
Nick.lynch@curlewresearch.com