One Possible Vision of the Future by

Shaun Comfort MD, MBA

Disclaimer: The opinions expressed here are the author’s own and do not in any way reflect the positions or opinions of Genentech, Inc., a Member of the Roche Group

Introduction

2

The goal of my talk is to take us in a different direction, possibly to entertain, and hopefully to provoke you to dream of a future that is different from our past. In that spirit, we begin…

HAL: I am putting myself to the fullest possible

use, which is all I think that any conscious entity

can ever hope to do. 2001 Space Odyssey

What Is AI?

3

• ar·ti·fi·cial in·tel·li·gence noun • The theory and development of computer systems able to

perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages. (Source: Google Search)

• AI is hard to miss these days…

Some Public Faces of AI

4 Source: Downloaded Google Images

Real ‘Ubiquitous’ AI

5

• Virtual Personal Assistants – Siri, Cortana, etc • Autonomous vehicles – Google, Tesla Autopilot • Purchase Prediction & Recommendations – Amazon & Target! • Fraud Detection – Chase, Banks, etc • News Generation – Automated Insights • Security Surveillance – • Movie Recommendations

• The Point –

• We are surrounded by Artificial Narrow Intelligence (ANI) that makes our world work

• And most of us don’t know it!

Ask Yourself?

6

• Are there any recent examples where AI/Automation has already transformed an industry? Think of Finance…

• With increases in computing speed, memory, neuroscience developments, natural language processing, and functional ‘deep learning’, will AI come to Pharmacovigilance?

Finance - The Good Old Days…

7

Once upon a time most financial trading and exchange was manual…

Source: Downloaded Google Images

Do You Remember?

8

• In 1983 Dan Akroyd and Eddie Murphy “Traded Places” in a popular movie where Akroyd and Murphy turn the tables on their greedy Duke Brothers with orange juice futures and make a killing… at the Duke’s expense!

• Until the end of early 2000s, stock, bond, and commodity trading was still largely a manual process.

• However, computers were making inroads…

• Market ‘makers’ bought and sold financial instruments on floors and pits – like our characters from ‘Trading Places’

Trading and Finance Changed…

9

From the 80s on, automation became more prevalent…

Source: Downloaded Google Images

Ask Yourself?

10

• What is the average duration that a stock is held, world wide? • Decade, Year, Quarter, Month, Day, Hour, Minute,

Sec?

• How many bond traders are in the Chicago pits today? • 1000, 100, 10, 1?

• How many stock exchanges are there now?

• 1, 10, 100, 1000?

And Today…

11

Computers rule after 2006 (NYSE-Archipeligo Deal). The modern exchange is now quiet, efficient, and automated…

Source: Downloaded Google Images

The Machines Rule…

12

HFT, dark pools, CoLo, Shark AI, Flash Boys, Advanced Chess… humans are no longer dominant here. The world of finance is largely run and conducted by… machines

Source: Downloaded Google Images

So Toto… we are definitely not in Kansas anymore

13

“Flash crash” is a new term for a new era

https://www.google.com/search?q=flash+crash&safe=active&espv=2&biw=1536&bih=760&site=webhp&source=lnms&tbm=isch&sa=X&sqi=2&ved=0ahUKEwiQy-Sg0OTPAhVCKiYKHfASAacQ_AUICCgD#imgrc=t_AquGo0tzJBTM%3A

Let’s Return to PV…

14

• Pharmacovigilance has slowly evolved from purely manual (up to early-mid 1990s) to…

• Electronic databases, signal mining, and spreadsheets • Most of PV is still conducted manually • To date, increases in adverse event reports (AERs) have

been met with increases in people/vendors to intake and process

• But things are changing…

Source: Downloaded Google Images

Recent Trends…

15

• New data sources producing AERs & ”Proto-AERs” from: Solicited Programs, Digital Media, etc.

• Future projections for increased AERs due to: • Novel Sources: ‘wearables’, ‘apps’, etc • Increased Numbers: Increasing use of medications and

requirements to track AEs.

• All have potential to lead to nonlinear increases in data

Source: Downloaded Google Images

Some Numbers to Consider…

16

• Assume typical PV case specialist processes a complete AER case between 1 to 4 hrs , tg ≈ 2 hrs, typical FTE ~ 1800 hrs/yr

• Typical annual volume for mid/large pharma 2016 ~250 kcases/year

• Requires ~280 FTEs, typically highly trained individuals with health care backgrounds (eg, RNs, PharmDs, MDs, etc)

• Extrapolate this across Pharma and Health Authorities with Additional data sources!

Some Numbers to Consider…

17

So Here We Are…

18

• Data increasing, resources constrained, and costs become painful.

• We’ve seen this movie before… • In addition, we are measuring how good humans are at

many PV related tasks (eg, AE identification, Causality Judgments, etc)

• The results – suggest room for improvement • AE classification is unreliable. (Forster, et al. 2012)

• The Majority of Expedited IND Safety Reports Are Uninformative (Jarow,

et al. Clin Cancer Res; 22(9) May 1, 2016)

So What to Do?

19

• Internal (eg, costs, resources, etc) and external forces (eg, regulations, reimbursement pressures, etc) converging & demand a new way of approaching our role

• It’s not difficult to see where this will go… • The Pharmacovigilance Intelligent System (PVIS)

• Multiple pharma and IT companies now testing AI for case intake, AE identification, automated evaluation, and dispositioning

• These systems can equal or better human SME performance, never get tired, and keep learning…

So Imagine A Vision of the Future

20

• A large pharma PV department: lean, quiet, and automated… • PVIS case processing times ≈1 to 30 mins, annual volumes

~106 to 107 cases • Kappa agreements with QC human over-reads ≥ 0.7

(substantial agreement to human experts) • Total human PV System FTEs/company shrink worldwide

(remember – where did all the pit traders go?) • PV is now an integrated ‘world wide’ Signal Monitoring,

Adjudication, and Dispositioning system functioning across all company geographies

So Is This Really Possible?

21

• Its up to us within the PV community to help make the possible a reality

• The AI “Genie” is out of the bottle and quickly moving into fields never before seen

• The most important question now - how to adapt and help shape what is coming

• Proposal - we are better served to welcome AI and work to benefit PV as a field.. and ultimately our customers, the patients

• So is this really possible?

22

PV Intelligent Systems, Robot Chauffeurs, What’s Next?

Thank you!

Source: Cover Page of Wall Street Journal Sept 13, 2016

Selected References

23

• All Finance and AI Images: Google Images • Rise of the Robots. Martin Ford, Basic Books 2015. • Flash Boys: A Wall Street Revolt. Michael Lewis, Norton

Paperback 2015. • Dark Pools: The Rise of the Machine Traders and the Rigging of

the US Stock Market. Scott Patterson, Crown Publishing 2012 • Machine Learning for Dummies. John Mueller, John Wiley and

Sons 2016. • Quantitative Evaluation of Safety in Drug Development. Qi Jiang

and H. Amy Xia, CRC Press 2015. • Our Final Invention. James Barrat, Thomas Dunne Books 2013