Pharmacovigilance & Social Media A new approach to …docs2.health.vic.gov.au/docs/doc... · A new...

A new approach to Safety Signal Detection: Potential & Issues Karen Whitelock, Drug Safety Responsible, Novartis Pharma Australia

Dr David Lewis, Global Head of Pharmacovigilance

Melbourne, May 2015

Pharmacovigilance & Social Media

Disclaimer

2

The information within this presentation is based on the presenters expertise and experience and represents the views of the presenter for the purpose of this presentation.

| Streamlining Multi-Centre Research May 2015 Workshop | Karen Whitelock & Dave Lewis|6 May 2015 | PV & Social

Media| Business Use Only

Overview: Pharmacovigilance of social media

3

Social media landscape and pharmaceutical medicines

Regulations & guidelines for PV of digital media

AE reporting via Social Media

Overview of Novartis PV of digital media

WEB-RADR IMI project

• Assessment of pharmacovigilance using social media

• Mobile reporting of suspected adverse reactions

• Digital Drug Safety Surveillance

• Data Protection for Health Apps - Data Privacy



Trends in Consumer Technology Computer & smartphone evolution

The digital media landscape... Internet-based applications that allow for the creation and exchange of user-generated content

From: Chopra R - Pharmacovigilance & Digital Media (http://de.slideshare.net/rkc78834/pharmacovigilance-digital-media)

4 | Streamlining Multi-Centre Research May 2015 Workshop | Karen Whitelock & Dave Lewis|6 May 2015 | PV & Social


Multiple threads of digital media

Electronic Health

(eHealth)

Using information and

communication

technologies for the

provision of health related

services (diagnosis,

monitoring treatment)

Telemedicine

Delivery of health

care at a distance

using information

and communication

technologies consumer

healthcare.

Mobile Health

(mHealth)

Using mobile

communication

systems for the

provision of health

related services

Digital Health

The intersection of the

digital revolution with

consumer healthcare,

includes genomics (use of

gene chips to store a

patient’s genetic

identifiers and responses)



5

@Facebook 1.25b users

@Twitter 302m users

@YouTube >1b users

@Pinterest 70m users

Engaging with patients via digital media

Social media Use to provide

information & engage

with stakeholders. Also

valuable within the

organisation to

encourage collaboration

Apps An increasingly wide

array in the market

ranging from information

only through to

sophisticated sensors

and medical devices

Gamification Applying game design

techniques and

mechanics to “real life”

applications in order to

make them more

engaging

Wearables and

smart sensors So far, largely only

wristbands and sensors

but the potential is for

much more



6

Pharmaceutical industry use of digital media MAHs main use of digital media is for marketing and sales

Sponsors are primarily using social media for commercial purposes to distribute information about:

• Medicines (to healthcare professionals and non-HCPs)

• Diseases, and the treatment of disease

• Company matters including announcements

• To listen to patient and professional conversations about marketed medicines, and not to support clinical research

A minority of companies use social and digital media for:

• Patient engagement

• Patient recruitment and retention within clinical trials


Media| Business Use Only | Streamlining

Multi-Centre

Research May

TGA:Monitoring the internet or digital media

1.2.2

Sponsors should regularly screen internet or digital media under their management or responsibility, for potential reports of suspected ARs.

• includes digital media that is owned, paid for and/or controlled by the sponsor.

• frequency of screening allows for valid ARs to be reported within reporting timeframe

based on the date the information was posted on the internet site/digital medium. • Sponsors may utilising their websites to facilitate collection of suspected ARs.

If a sponsor becomes aware of a suspected AR described in non-company sponsored digital medium, • the report should be assessed to determine whether it qualifies for reporting.

Cases from the internet or digital media, the identifiability of the reporter refers to the existence of a real person, that is, it is possible to verify the contact details of the reporter • e.g., an email address under a valid format has been provided

8

| Streamlining

Multi-Centre

Research May

2015 Workshop |

Karen Whitelock &

Dave Lewis|6 May

2015 | PV &

Social Media|

Business Use

Only



VI.B.1.1.4. Information on suspected adverse reactions from the internet or digital media

MAHs should regularly screen internet or digital media

under their management or responsibility, for potential reports of suspected ADRs. In this aspect, digital media is considered to be company sponsored if it is owned, paid for and/or controlled by the MAH.

• The frequency of the screening should allow for potential valid ICSRs to be reported to the competent authorities within the appropriate reporting timeframe

• Marketing authorisation holders may also consider utilising their websites to facilitate the collection of suspected ADRs

EEA Good Pharmacovigilance Practice (GVP) VI PV guidance on digital media (July 2012) focuses on ICSRs



Digital media and safety issues (GVP Module VI)

VI.B.1.1.4. Information on ADRs from digital media (ctd.)

If a MAH becomes aware of a report of suspected adverse

reaction described in any non-company sponsored digital

medium, the report should be assessed to determine

whether it qualifies for reporting.

VI.C.2.2.6 Emerging safety issues

Good practice for the MAH to monitor special internet sites or

digital media (e.g. patients’ support or special diseases groups)

• Check if they describe significant safety issues which may

necessitate reporting in accordance with VI.C.2.2.6.

• Frequency of the monitoring depends on the risks associated to

the medicinal product



Multi-Centre

Research May

2015 Workshop |

Karen Whitelock &

Dave Lewis|6 May

2015 | PV &

Social Media|

Business Use

Only

MAH governance of the use of digital media Most MAHs have developed controls governing use of digital media

Nearly all MAHs have developed guidelines to address use of social media

General guidelines include:

• Rules for discussing company business on personal sites, how to set up a page or site, and privacy issues;

• Guidelines concerning authorized and unauthorized uses by personnel of social media;

• Social Media Advisory Board-specified practices;

• Guidelines for posting video online;

• Directives that stipulate one-way communication between personnel and patients involved in clinical studies;

• Restrictions, e.g., for company business only.



Multi-Centre

Research May

2015 Workshop |

Karen Whitelock &

Dave Lewis|6 May

2015 | PV &

Social Media|

Business Use

Only

AE reporting via social media

Source: White paper on Adverse Event Reporting by VisibleR , Oct. 2011, http://www.visibletechnologies.com/resources/white-papers/adverse-events/

All brand mentions

257,177 posts; 224 brands

100%

Filtered for relevance

24%

With AE terms

5%

Adverse Event reports

0.4% of all brand mentions

3.3% contain AE-specific data

Contain AE

keywords

12,530 posts

3.3% mentions

are case reports

1 in 7 = name

& contact info

| Streamlining

Multi-Centre

Research May

2015 Workshop |

Karen Whitelock &

Dave Lewis|6 May

2015 | PV &

Social Media|

Business Use

Only

Overview of Novartis PV of digital media Highlighting challenges of monitoring the different channels



13

Novartis Pharma

Social Media Programmes Novartis Pharma Social Media

Listening Programmes

Novartis associate/vendor

screening non-NVS controlled

platforms

Single Reports

• AEs with 4 minimum criteria

Aggregate Reports


Single Case Safety Reports

• Within 24 hours

• Send to DSE in the country where AE occurred

(if UNK send to country where AE was

received or reviewed (Local Programs) or

Switzerland/US (Global Programs)

Aggregate Reports

• Monthly reports / End of programme

• Send to country of the Programme Owner

Novartis associate/vendor

screening

NVS controlled platforms

Single Reports



(Novartis product & ADR)

Single Case Safety Reports

• Within 24 hours

• Send to DSE in the country where

the AE took place (if UNK send to

country where AE was received or

reviewed (Local Programs) or

Switzerland/US (Global

Programs)

IMI WEB-RADR research on social media WEB-RAdR consortium will explore PV of social media

Hypothesis Data capture, collation, timely data mining and appropriate analysis can provide actionable intelligence in relation to protection of public health. Research can provide value to stakeholders including patients, healthcare professionals, regulators and to the pharmaceutical industry. Emerging communication technology is changing the way people

interact with their healthcare providers and products • Large body of health care data is being generated in social media • Mobile technology creates an environment where people are constantly

connected to the Internet

The value of such data is not fully established Mining and analysis of social media is an emerging science Regulatory guidance is behind the emergence of new technology



| Streamlining

Multi-Centre

| Streamlining Multi-Centre Research May 2015 Workshop | Karen Whitelock & Dave Lewis|6 May 2015 | PV & Social Media|

Business Use Only

A brief history of Web-RADR over time... Web-RADR is an IMI project involving academia, HAs and industry

New technologies in mobile devices & new apps are leading to an evolutionary change in the extent, geographies and modes of use of the internet

Information gathering and sharing of experiences, opinions and suggestions is becoming routine

Web-RADR is a ground-breaking EU Innovative Medicines Initiative ( ) -funded initiative to recommend policies, frameworks, tools & methods

The project will explore the value of the new developments to assess the insights versus traditional PV

WEB-RAdR IMI project Comprises experts from regulatory agencies, academia, WHO & industry

WEB-RADR consortium brings together expertise from world-leading organisations in their fields

Project structured to enable EFPIA partners to participate in all areas

WEB-RADR has the potential to shape the regulatory framework of the future, thereby augmenting traditional pharmacovigilance

WEB-RADR offers the maximum possible benefits from a regulatory, societal & scientific perspective



WEB-RADR Consortium structure

EFPIA

Applicant Consortium

Regulators

& Patients

Novartis (Lead)

J&J (Deputy)

Sanofi-Aventis

Amgen

AstraZeneca

UCB

Bayer

+ GSK

MHRA (PM)

EMA

Halmed

Lareb

Eurordis

Universities of London, Liverpool & Gröningen

WHO (UMC), Epidemico and SRDC 17

| Streamlining Multi-Centre Research

May 2015 Workshop | Karen

Whitelock & Dave Lewis|6 May 2015 |

PV & Social Media| Business Use Ony

| Dr DJ Lewis | Web-RADR | 14 April 2015 | Business Use Only

Overview of Web-RADR work packages Effective project management to link the work streams together

Mobile & social

media usage

patterns 2b Regulatory framework WP 1

Scientific impact

& new insights 4

Social media

platform 2a

Mobile ADR

reporting app

& safety

comms 3a

http://blog.wpoven.com/2014/10/10/top-project-management-plugins-for-wordpress-2/

http://professionalsocialpromotion.com/top-social-media-platforms/

http://poweredbyssi.com/blog/

http://theinspiredlifeinfo.com/about/

http://www.sparksource.me/the-power-of-social-media-for-small-business/

http://www.diahome.org/en/Meetings-and-Training/About-our-offerings/Instructor-Led Courses/EudraVigilance-Training.aspx

http://www.diahome.org/en/Meetings-and-Training/About-our-offerings/Instructor-Led Courses/EudraVigilance-Training.aspx

https://eudravigilance.ema.europa.eu/human/index.asp

19

Spontaneous

Reporting

Electronic

Paper based

• ICSR quantity & appropriateness

• Quality (VigiGrade)

• Demography

• Duplication (VigiMatch)

• Signal generation

• Qualitative Analysis

• Integration

Comparisons

WEB-RAdR Scientific Impact Traditional pharmacovigilance vs. New

Adverse Drug

Reaction

Positive benefit risk assessment

for each patient

Traditional model

HCP-centric

• Signal generation

• Trustworthiness

• Integration

App-

based

Social

Media

WEB-RADR model

Patient-centric

Identify risks &

tolerability issues

WEB-RAdR Pharmacovigilance of social media Targeting advances beyond state of the art pharmacovigilance

Novel signal detection techniques

Indicators of completeness + quality

Advanced geographic recognition

Filtering capability using EMA IME

Filtering for health system interaction

International collaboration portal for all users

Data export compatibility

Multi-source spontaneous report comparisons

Indicators of completeness + quality (vigiGrade)




Business Use Only

Data quality indicators: healthcare vs patients

Assessment of Novartis data from SRs, literature and POPs

Initial and follow up all time Literature

Spontane

ous

Marketing

Programs

n % n % n %

Formulation 181 13.3

TTO 132 9.7

Demographics 1169 86.2

Indication 936 69.0

Dosage 891 65.7

Action Taken 557 41.1

Duration 19 1.4

Medical History 867 63.9

Lab Data 710 52.4

Dechallenge 225 16.6

Rechallenge 19 1.4

Total no of cases 1356

Average score 4.86946903

4960 65.7

2838 37.6

7058 93.5

4606 61.0

5529 73.2

3389 44.9

2571 34.0

3587 47.5

1135 15.0

1059 14.0

69 0.9

7551

4.740077

1345 73.7

694 38.0

1802 98.8

1371 75.2

1591 87.2

863 47.3

873 47.9

835 45.8

194 10.6

155 8.5

11 0.6

1824

5.6579509

Social media: caveats for patient safety



22

New developments will lead to new challenges for pharmacovigilance

MAHs must obey the law

MAHs must operate ethically

We must not cross the boundaries of the doctor-patient relationship, or be misled by false data or spurious signals

But we should be encouraged by the opportunities that digital media offer...

Future of social media: From telling to engaging

23

New apps and mobile technologies will continue to evolve

Best practices include:

•Establish relationships through two-way dialogue and human connections that encourage participation

•Demonstrate patient and customer responsiveness through timely, transparent responses and request feedback

•Share content that makes the public want to interact with the company and specific brands

•Use of innovative strategies to leverage information and drive online influence




Business Use Only

Digital Drug Safety Surveillance: Twitter Monitoring pharmaceutical products in Twitter (Freifeld et al 2014)

Existing post-marketing adverse event surveillance systems suffer from under-reporting and data processing lags

Social media services such as Twitter are seeing increasing adoption, and patients are using them to describe adverse experiences with medical products

An analysis of 4,401 of these ‘posts with resemblance to adverse events’ (‘Proto-AEs’) from Twitter found concordance with consumer-reported FDA Adverse Event Reporting System reports at the System Organ Class level

Further research is required to investigate this finding

Identifying instances of Proto-AEs in the UK Pilot study results exploring PV of social media

Data collection scheme for Twitter & FAERS



26

Study to compare AE reporting via Twitter and patient reports to FDA

Correlation by SOC proto-AEs in Twitter/FAERS



27

Rank order (log-log scale): Proto-AEs = posts with resemblance to AEs

Social Media ADR Comparison to Pivotal Trial Patient reporting can be of good quality and differs from HCP sources

Antibody abnormal*Herpes zoster (skin)*

Swelling*Migraine*

Paraesthesia*Weight decreased*Skin discomfort*

Headache*Condition aggravated*

AST increasedDyspepsiaVomiting

Lymphopenia

Albumin in urineErythema

RashNausea

DiarrheaPruritisFlushing

Abdominal pain

Social Media (n=42)

051015

Pivotal Trial (Tx arm N=769)

0 10 20 30 40

dimethyl fumarate

Dec 1, 2013 through Jan 14, 2014, Twitter & Facebook

drug:event pairs coded using MedDRA v16

≥2% higher than placebo

Trial Data: Tecfidera US PI


Business Use Only

Social media reports vs FAERS Hypothesis generating for risk minimisation


Business Use Only

Note: Until methods for signal detection in social media and scientific analysis has been fully developed, refined

and finalized, it is proposed that all data extracted from MedWatcher Social and initial findings will be treated as

potential hypotheses for research purposes only.

Pilot Social Data Analysis for Drug List

Data used for

refining algorithms

(WP2A) and

development of

signal detection

methods (WP2B)

Data exported

by MAHs for

evaluation and

analysis

Data used for

scientific impact

evaluation (WP4)

Proposed Process Flow

Validate

Findings from

research > • new insights

on drug

safety

profiles

• Drug Use

• Prescription

patterns

• Patient

compliance

• PV best

practices

Report to

Health

Authorities

,

Publication

s (All)

Signal

Analysis

and Risk

Managem

ent

(MAHs)

Share New

insights

with

Patient

Groups via

Mobile

(WP3A)

(HAs)


Business Use Only

Key points: pharmacovigilance of social media

• Secondary data use – contact with reporter not foreseen

• Masking of pilot drugs for unbiased study

• Anonymous background data for comparative analysis

• Action after validation of process and signal algorithms

• Data sharing between Work Packages during pilot

• Use of findings to guide policy decisions

• Publication of results after completion of research

Proposal is aligned with secondary use of data per GVP VI

Relevance of Data Protection for Health-Apps

“The close interaction with the operating system allows apps to access significantly more data than a traditional internet browser.”

“Apps are able to collect large quantities of data from the device (location data, data stored on the device by the user and data from the different sensors) and process these in order to provide new and innovative services to the end user.”

Personal data

• “Any information relating to an identified or identifiable natural person (data subject)

Health data (sensitive, personal)

• Any personal data closely linked to the health status of a person, such as genetic data or data on a person’s consumption of medicines

Personal Data in Apps

• Automatically generated by the device, (e.g. geolocation data, network settings, IP address)

• Generated by the user through apps (photos, notes, contact lists)

• Generated by the apps (e.g. browsing history)

32

Data privacy - Who am I?

Age: 50-year-old

Gender: Male

Suspected ADR: Respiratory arrest

Suspect drugs: Diprivan, pethidine, alprazolam & sertraline

PMH: Low BMI, vitiligo, lupus

Outcome: Fatal

http://en.wikipedia.org/wiki/Death_of_Michael_Jackson

Occupation: Rockstar

Narrative: Patient was being treated by his personal physician at his mansion. Administration of propofol led to respiratory arrest and paramedics were called to assist. The resulting court case saw the attending doctor found guilty of involuntary manslaughter.







//upload.wikimedia.org/wikipedia/commons/a/a9/Michael_Jackson_Star_on_Hollywood_Blvd_(cropped).jpg

Who am I? Personal medical data

Age: 41 years

Gender: Male

Suspected ADR: Possible drug interaction with alcohol

Suspect drugs: Fluoxetine, tiapride, and albendazole

PMH: Alcoholism?

Outcome: Fatal

Occupation: Deputy Head of Security, Ritz Hotel, Paris

Narrative: Patient was driving a Mercedes at high speed in the Pont d’Alma tunnel in Paris. He lost control of the car and crashed, killing himself and two passengers.




Business Use Only

Summary and vision of the future... Early challenges are being overcome, now we need to generate more

substantive data! Patients are increasingly aware of safety information

Rapid growth of apps & digital media sites as MAHs exploit opportunities

Potential for 2-way interactions is hard to ignore, so mobile reporting & listening capabilities will increase

MAHs must offer real benefits or advantages to patients, and manage the risk of receiving AE reports

Important that pharmacovigilance is carefully managed

Web-RADR provides the opportunity to shape the future, and to work with stakeholders to improve public health

1995

2014

Social media management strategy

36

2016



Questions?



37

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