sanofi press breakfast on behavioral science · sanofi press breakfast on behavioral science - 22...

Sanofi Press Breakfast on Behavioral Science

Friday 22 September 2017

Agenda

2 Sanofi Press Breakfast on Behavioral Science - 22 September 2017 - Paris

• 8.45 - 9.00 Welcome coffee

• 9.00 Kick-off

• 9.00 - 9.10 Introduction by Alexandra Rocca, Global Head of Communications

• 9.10 - 9.20 Reducing the efficacy gap between the clinical and real world settings, the impact of patient behavior in clinical outcomes. Anne Beal, M.D., M.P.H, Global Head of Patient Solutions, Sanofi

WHY UNDERSTANDING BEHAVIORS CAN UNLOCK CARE SUCCESS

• 9.20 - 9.35 How Sanofi is active in the space of Real World Evidence? Bernard Hamelin, M.D., Global Head Medical Evidence Generation, Sanofi

• 9.35 - 9.50 Evidation: a concrete case study to understand the technology behind behavioral science Christine Lemke, Co-founder and President, Evidation Health

• 9.50 - 10.20 Q&A with the floor

• 10.30 Close

Leveraging behavioral science to improve health outcomes

Anne C. Beal, MD, MPH Global Head of Patient Solutions, Patient Solutions Unit

Pharma is facing unprecedented change

4

In the real world, when people have to manage their conditions, they’re not skilled at self-management,

nor are they utilizing their treatments appropriately

Sanofi Press Breakfast on Behavioral Science - 22 September 2017 - Paris

• 50% of health outcomes are determined by behavior,

yet physicians are not well trained for this part of their job1

• 30% of people don’t fill prescriptions for chronic conditions2

• 50% of people with a chronic disease don’t take their

medication as prescribed3

Helps people to achieve improved health outcomes by supporting optimal

utilization of Sanofi products and services and enhancing their activation and

self-management

1Bipartisan Policy Center, 2012; Volpp, Kevin. NEJM Catalyst, 2016 2Tanblyn et al. Annals of Internal Medicine, 2014

3WHO, 2003

5

Leveraging behavioral science to close the gap between real world effectiveness & efficacy…

REAL WORLD

EFFECTIVENESS

CLINICAL TRIAL EFFICACY*

FACTORS CONTRIBUTING TO GAP:

PATIENT self-management, co-morbidities, concomitant medications…

PHYSICIAN patient interaction, care coordination, Rx behavior...

SYSTEM access (formulary, reimbursement, quality of care, affordability…

CONTEXTUAL SES, zip code, race, ethnicity, social support, family, etc.

Medical can bridge

this gap through

evidence-based

interventions by:

Understanding patient

factors behind the gap and

associate them with

outcomes

Designing interventions to

influence key factors that

will lead to improved

outcomes

OU

TC

OM

ES

GA

P

Behavioral Science can address clinical inertia, patient activation and non-adherence which are critical to improving outcomes

*Relative scale of impact for patient factors, HCP, health system, and contextual factors varies case by case. Broader results/ outcomes differences in clinical trial efficacy and real world effectiveness may vary on a case by case basis.


Overwhelmed & disengaged

Becoming aware, but still struggling

Taking action

Hibbard: Patient Activation Measure (PAM)

6

Maintaining

behaviors

LEVEL 1

LEVEL 2

LEVEL 3

LEVEL 4

0-100 point scale

10-20% 10-20% 25-30% 20-25%


Hibbard: Activation and Medication Adherence

7

Source: 2004 National Sample


Advice and Input, Behavioral Science Toolkit

9

Selection of the strategic area of improvement

Recommendations for segmentation

Operational objectives highlighted

Exploration of Tips & Tools, Case studies and References

1 STRATEGIC AREAS OF IMPROVEMENT

(ex: improve adherence. develop patient self management skills etc)

THEN PLEASE SELECT YOUR SPECIFIC STRATEGIC AREA OF IMPROVEMENT, BY CLICKING

ON THE TOPIC

Access To Treatment

Patient Knowledge

Symptoms / Quality Of Life

Health Outcomes

Adherence

Patient Experience With Treatment

Management Of Side Effects

Acceptance Of Therapy

Self Management Skills

Patient Experience With The Service /

Patient Satisfaction

Habit Formation Improve HCP Experience / HCP

Satisfaction

Enhance HCP Management Of

Chronic Illness

Improve Patient’s Relationship With

HCP

Improve HCP Engagement /

Activation

Support HCP Dialogue

With Patients

Leverage Product Characteristics

Differentiate From Competitors

Generate Data On The Impact

Of The Service

Position As A Healthcare Provider

Support Market Access

Support Value

Enhance Efficiency Of Service

Delivery

PATIENTS HCP SANOFI

*Prior to accessing information on your chosen operational objective, you will be presented with key segmentation reminders

Enrollment Content Channels Monitoring

PHYSICIANS / NURSES /

OTHER HCPS

CHANNEL

PERSONALIZATION AND

AUTOMATIONHCP penetration

HCP activation /

engagement

Patient initiation

Patient persistence

Patient engagement

Peer experience content

Differential messaging

PATIENT

Educational content

Motivational content

Peer / Carer content


Typology of channels

Number of interactions /

contact frequency

HCP Monitoring

Patient Monitoring

Outcomes

Value optimization

1

2

3

4

Recommendations for segmentation

Selection of the operational objective

Exploration of Tips & Tools,

Case studies and References

2 PRACTICAL OBJECTIVES

(ex: improve patient enrolment, physician engagement,

develop tool personalization etc)

Enrollment Content Channels Monitoring

PHYSICIANS / NURSES /

OTHER HCPS

CHANNEL

PERSONALIZATION AND

AUTOMATIONHCP penetration

HCP activation /

engagement

Patient initiation

Patient persistence

Patient engagement

Peer experience content


PATIENT

Educational content

Motivational content

Peer / Carer content


Typology of channels

Number of interactions /

contact frequency

HCP Monitoring

Patient Monitoring

Outcomes

Value optimization

1

2

3


Sanofi and Real World Evidence

Bernard Hamelin, MD – Global Head of Medical Evidence Generation

Pharma is facing unprecedented change

11

Vocal patient

populations

Tougher regulatory

controls; societal

expectation

Rising

development

costs

Digital

Health Revolution

Greater

requirements

for post-

marketing

evidence

Payors

pushing for

Real World

Evidence

Shifting

global

demographics

Increased

transparency

expectations

Physicians

seeking

peer-peer

interaction Evidence

generation

needs

to evolve to

better

understand

and improve

patient

outcomes

Increasing

safety

concerns


Evidence requirements are increasing

12

Evid

en

ce

re

qu

ire

d

Sub- mission

Pricing Review

New Competition

Competitor goes generic

New Indication / Formulation

Understand standard of care

Post-marketing commitments (safety etc.) Budget impact

Adherence Unmet need/ disease burden

Patient recruitment

Trial design

Utilization/ prescribing

patterns Long-term safety, clinical outcomes

Head to head safety, comparative effectiveness

Target populations

Differentiation in sub-populations

Effects of switching on outcomes

Usage difference

Differentiate with or vs. protected formulation

Development Launch

Development Growth Phase Mature Phase


Evidence generation methodologies

13

Randomised Clinical Trial

Pragmatic Clinical

Trial

Observational Study


14

Real World Evidence is based on data from multiple sources

RCT

Source : jama, 22 may 2014


What we do: methodologies we use and partners we work with

15

Methodologies Partnerships

Propensity-score matching Meta-analysis

Traditional RWE statistics

OMOP data modelling

Traditional analytics

Machine learning

Predictive modelling Unsupervised clustering

Natural Language Processing (NLP)

Advanced analytics

Rule extraction Model bootstrapping


New data, new platforms, and new analytics make new insights possible

16

NEW SOURCES OF DATA

NEW PLATFORMS AND VISUALIZATION

NEW ANALYTICS


Quantifying impact of behaviors on health outcomes

Evidation Health is a technology and services company that helps individuals and healthcare companies understand the link between everyday behaviors and health outcomes.


Patients and their outcomes have been characterized by using limited data sets based on what was visible to the system.

Visible & Episodic (in clinical settings)

Invisible & Continuous (in real life)

DATA POINTS

TIME


Evidation captures previously invisible everyday behavior data and combines it with traditional clinical data sets to understand behaviors and health outcomes.

clinical trial

data

patient-reported

metrics (symptoms, outcomes,

anytime, anywhere) contextual data

(weather, pollen

count, geolocation,

census data,

occupation, etc.)

behavior data

(activity, sleep, diet, social

media, cognition,

technology interaction,

etc.)

REAL LIFE OF

THE PATIENT

REAL WORLD

PRACTICE

provider system

registries

EHR data

pharmacy and

medical claims

TRIALS


This explosive new data source - behavior data - shows promise to quantify health outcomes more quickly and observe new effects.

Digital Biomarkers

to identify and

quantify:

Social

Location

DEMOGRAPHICS

Lifestyle

PLACES

WEATHER

Voice/Speech Heartrate

Activity

Weight

OTHER..

Sleep

Other… TREATMENT EFFECTIVENESS

EMR CLAIMS

LABS OTHER..

BEHAVIOR

CONTEXT

CLINICAL

Evidation Platform Applications

CONDITION ONSET

INTERVENTION WINDOWS

CONDITION PROGRESSION

Data Analytics for

discovery


It requires a scalable system to connect directly with individuals to gather, contextualize, and combine behavior data with clinical data.

QUANTIFIED IMPACT

CONNECTED POPULATIONS

REAL LIFE DATA

>3 MILLION

patients on the platform,

across multiple therapeutic

areas

>1.5 BILLION

new activity events recorded each

month


…and services combined with a platform to reach individuals for permission-based data sharing

Find people

10x faster

Design research

studies

Execute privacy safe, virtual

study protocols

Interpret and

deliver results

Peer review standard

23 Sanofi Press Breakfast on Behavorial Science - 22 September 2017 - Paris

Results: faster, more proactive care

Digital Biomarker

Discovery

Digital Evidence

Generation

Digital Biomarker

Discovery

Challenge Understand medication

adherence in patients

with diabetes

Assess the effectiveness of

medication adherence

application

Quantify cognitive

decline through voice

and speech signals

Data inputs Weight, activity,

adherence measured

through pharmacy claims

data

Connected monitors,

engagement data, patient

reported outcomes

Voice, speech, clinical

data

Results Discovery of behavior

pattern that led to

adherence drop

Recruited and observed

400+ patients, recruited 10x

faster

Predict cognitive decline

scores solely based on

voice and speech

(research embargoed)

Application Monitor patients and

deliver diabetes

education at right time

Evidence package for use in

market commercialization

Improved screening,

monitor therapeutic

impact (e.g. oncology)

24 Sanofi Press Breakfast on Behavorial Science - 22 September 2017 - Paris

Questions

September 2017

evidation.com

christine@evidation

Thank you

sanofi press breakfast on behavioral science · sanofi press breakfast on behavioral science - 22...

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