Interactive graphics in Pharma R&D:The right decision

mg r af ti

Francois Mercier, @mgrafitStrata-EU 2013, London, 12-Nov-2013

MultipleSclerosis

1/12

2,500,000 People with MS, in the worldMainly in western countriesMainly women 35-45 y.o.

#15 in R&D spending (~2 $bn/yr)

*http://www.imshealth.com/, http://www.nationalmssociety.org/index.aspx

Price of a marketed MS treatment

30-45 k€/year/patient

Cost &Pr(Failure)

Development of a new drug in MS

300-600 M€

7-12 years

ComplexSystems

2/12

PharmaR&D

Roadmap

3/15

Target identificati

on

Lead discover

y

Lead optimizatio

n

Pre-clinical ADME

Phase I (FiH, safety

profiling)IND

Phase II

PoCEOP2

Phase III (confirmat

ory)

NDAReview MA

RegulatoryEnviro-nment

4/15

IN THE INTEREST OFALL,

STAY INSIDE THE BOX

Data analyses have to be reproducible• Source data are safely stored and data manipulation are traced• Data analyses are available in the form of programs (no GUI)

From PatientTo Data

5/15

Subject (healthy or ill)

Physician

Nurse

Data Warehous

e

Mobile devices (cardiac

function, vital signs)

Labs (biofluids, images, other

samples)

100 subjects ≈ 1-5 GB

From Data ToDecision

6/15

Data manager

Data scientist

Clinical project leader

Therapeutic area head

Clinical development head

Pharmaceutical division head

Raw data

Distillated information

ClinicalDevelop.Strategy

7/15

In clinical projects, a strategy is defined as a compromise between money

and science

€

3√𝑅𝑥

Data manager

Data scientist

Clinical project leader

Therapeutic area head

Clinical development head

Pharmaceutical division head

DecisionMakingProcess

8/15

Communicate

Collect

?

Visualize

Model

Refine

Commu-Nication

Risks

9/15

Loss of informationMute assumptions

CompromisesLack of integration

Misinterpretation

RISKS

How to mitigate these risks?

Raw data

Distillated information

We use models and graphics

Models&

Graphics

10/15

Model Visualize

Two sides of the same coin

− Mathematical language+ Assumptions

+ Universal language− Limited in space and form (2D)

*Data from Nakov et al. Am. J. Hypertension, 2002, 15:583-9.

10 30 100

Darusentan dose (mg)*

DSB

P (m

m H

g)

• Gaussian distrib⁰• Homoscedasticity• Dose is discrete

Real lifeIs

Complex

11/15

How many static graphics to depict this model?

InteractiveGraphics

12/15

Use interactive graphics

InteractiveGraphics

13/15

Use interactive graphics

Conclusion

14/15

• Give control to the end-user• Make scientific discussions an enjoyable experience• Provide context, perspective• Make the assumptions explicit

Interactive graphics in Pharma R&D:The right decision

To take quick and accurate decisions

AcknowLedgments

15/15

Jean Mercier (http://www.khawai.com/)

Olivier Luttringer (Novartis)

Hadley Wickham (http://had.co.nz/)

Mike Bostock (http://bost.ocks.org/mike/)

Thank you

mg r af ti

Francois MERCIERfrancois0mercier@gmail.com

http://www.mgrafit.com