AMWA Annual MeetingWashington, DCNovember 2018

David Clemow, PhD, MWCAdvisor Scientific Communications Strategy

Eli Lilly and Company

Medical Communication Data Visualization (MCDV)Bringing Advanced Visualization Techniques to

Scientific Communication

Thursday, November 1, 2018, 9:30-10:30 amRenaissance Washington DC Downtown Hotel Congressional A

©2018

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IssueNeed Improved Ways to Inform and Educate – Address Too Much Info to Process

Source: Wesley Portegies, Medicalwriters.com, Insight-driven Medical Communications, DIA Annual Meeting 2018, Boston, June 24-18

Do customers understand the data behind therapeutics well enough to make informed and educated decisions for patients?

Disclosures need to enable the customer. Advanced data visualizations can help focus content to inform and educate!

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IssueNeed Improved Ways to Inform and Educate – Address The Forgetting Curve

• Ebbinghaus Retention Curveo Decline (transience) of memory retention over timeo Memory retention increases when information reviewed

• Visuals can be printed/stored for easy quick topic review and thus facilitate information retention

IssueNeed Improved Ways to Inform and Educate – Address Adult Learning Needs/Wants

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Advanced data visualizationsuch as interactivity helps data consumption be active education

Traditional data visualization does not meet learning style needs or wants

After 2 weeks, we tend to remember:

10%of what we READ

PASS

IVE

AC

TIVE

20%of what we HEAR

30%of what we SEE

50%of what we SEE & HEAR

70%of what we SAY

90%of what we SAY & DO

Reading

Hearing Words

Seeing Content

Watching and Listening(video, exhibit, demonstration)

Participating(in discussion, giving a presentation)

Simulating real experience(workshop, real-world experience)

Source: Edgar Dale, 1960 {adapted}

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IssueNeed Improved Ways to Inform and Educate – Address Antiquated Data Review

Interactive data visualization enables improved data exploration to gain clinical insight with less work and greater efficiency

Data review from static data outputs on paper or slides is overwhelming, takes enormous work load, and is inefficient

Every analysis needs to be programmed and manually sorted through

Examine data across population and data types with greater seamlessness

Data Analysis & Visualization Software Tool

Patient Subgroup Population

Saf

ety

Dat

aE

ffica

cy D

ata

Tools not integrated into skillsets and processes

IssueNeed Improved Ways to Inform and Educate – Address Recreation of Data Outputs

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Medical Writing

Medical

Med Info

Med Ed

MSLs

RegulatoryFigure, Table, Graphic

Meet Cross-functional Needs

• Vector file type for graphic data outputs

• Communicated data visualization requirements

• Cross-functional needs alignment

Data Output

Functions Using Data Output

Data OutputCreator

ExternalData Output

• Data output recreated to meet formatting needs

• Recreated by multiple functions

• Inefficient

• Customers get different versions

Data Visualization Goal

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Easy to Understand

NotEngaging

Hard toUnderstand

Engaging

NotRecallable

Recallable

RegulatoryPublication

Medical

TablesFigures

Graphics

Data VisualizationInternal and External ToFrom

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Intersect science, creative design, and technology to… Create medical communication data visualizations that… Enhance customer engagement, understanding, and recall of…Scientific data and clinical information.

Data VisualizationWhat & Why

Representation of medical or scientific data using…Static, animated, and interactive visual and digital techniques using…Graphic design principles and techniques.

WHAT

WHY

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Data VisualizationWho

Medical WritingMedical Affairs (Development) Medical InformationMedical EducationMedical Science LiaisonsRegulatory Affairs

Medical CommunicationsUmbrella Partners

Data VisualizationCreation Partners

WHO +StatisticsAnalyticsMedical CapabilitiesInformation TechnologyGraphic Design Group or Vendor

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Data VisualizationPast to Future

ToFrom

1. Raster file type (non-scalable, non-editable)

2. Static figures and tables

3. Posters and presentations lacking data visualization principles

4. Static paper or PowerPoint data review

1. Vector file type (scalable, editable)

2. Animated and/or interactive figures and tables

3. Dynamic congress posters and presentations using graphic design principles and infographics

4. Interactive data analysis and visualization tools used to help data ‘interpretation’ during data review

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Data VisualizationCustomer Needs and Wants Not Being Met

Data VisualizationCustomer Need, Impact, and Value

Data visualization and interactivity are proven to enhance

•Engagement•Understanding•Recall

Data visualization translates to customer impact

•Papers with infographics & illustrations have higher customer impact and sharing scores

•Industry trends•Health literacy literature•Medical communication literature•Medical advisory board data•Medical market research data

Customers want medical communications that are easy to

•Engage•Understand•Remember

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Established Benefits

Attractive – Engaging – Understandable – Believable – Retainable – Impactful

Data VisualizationBenefits

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↑ simplification, clarification, and focused information

↑ customer retention

↑ learning efficiency and effectiveness

↑ engagement

↓ customer interpretation time

↑ fulfillment of customer needs and preferences

↑ customer understanding

Traditional Graphics Low Complexity MCDV Medium Complexity MCDV High Complexity MCDV

•Word table•Bar graph•Line figure•Pie chart

•Figure, slide, poster design•Infographic and symbol creation

•Simple animation graphic•Simple click interactive graphic

•Interactive table/chart•Animated efficacy data figure•Touch interactivity in data application

•Augmented reality info tag linked to a tablet

•3D medical illustration•Video poster•Augmented realityinteractivity

•Interface mobile application content

Data VisualizationDefinition – MCDV by Complexity

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Low or medium complexity can become high complexity quickly…• Data volume• Tactic size or length• Graphic complexity• Digital format• Digital channel

Data VisualizationExample – Low Complexity MCDV – Icons

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Data VisualizationExample – Low Complexity MCDV – Imagery

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Data VisualizationExample – Low Complexity MCDV – Infographic

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Drug X Drug X

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Data VisualizationExample – Low Complexity MCDV – Abstract Figure 3D

Figure 1. Response surface modeling of the contribution of skin and joint improvements to patient HRQoL. (A) Three dimensional scatterplot of skin (y-axis; PASI – percent improvement), joint (x-axis; DAPSA – percent improvement), and HRQoL (z-axis; EQ-5D – change from baseline) improvement at Week 24. A color spectrum is applied to HRQoL improvements (blue [least improvement] to red [greatest improvement]). (B) Response surface of scatterplot estimated by smoothing spline method.

Kavanaugh et al. The Contribution of Skin and Joint Improvements to the Health-Related Quality of Life of Patients with Active Psoriatic Arthritis. Abstract 2539. ACR/ARHP Annual Meeting. Nov 3-8, 2017. San Diego, CA, USA.

Data VisualizationExample – Low Complexity MCDV – Interactive and Animated

19Model Data for Pilot Example

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Data VisualizationExample – Low Complexity MCDV – Abstract Figure Animated

Simpson et al. Rapid and Concurrent Improvements in Signs and Symptoms of Atopic Dermatitis with Baricitinib in a Phase 2 Study. Abstract FC03.02. EADV Congress. Sept 12-16, 2018. Paris, France.

Data VisualizationExample – Medium Complexity MCDV – Manuscript Figure Animated

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Data VisualizationExample – Medium Complexity MCDV – Manuscript Figure Animated

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Data VisualizationExample – Low Complexity MCDV – Interactive Data Analysis Visualization

Use interactive data visualization tools to create data visuals to provide better insight into data

Interactive Data Analysis and Visualization Tool

Model Data for Pilot Example

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Data VisualizationExample – Medium Complexity MCDV – Manuscript Video

Saakshi et al. Early Onset of Clinical Improvement with Ixekizumab in a Randomized Open-Label Study of Patients with Moderate-to-Severe Plaque Psoriasis. J Clin Aesthet Dermatol. 2018;11(5):33-37.

Data VisualizationExample – Medium Complexity MCDV – Augmentation and CGI Graphics

3D CGI Graphics

Augmented RealityTablet Data Visualization Supplementation

with Click Interactivity

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CGI = Computer Generated Imagery

Data VisualizationExample – Medium Complexity MCDV – Digital Format

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Customer Friendly

Work across digital channels

Work across customer types

Perkovic et al. Carmelina® trial baseline characteristics: a cardiovascular and renal outcome trial with linagliptin in patients with type 2 diabetes at high vascular risk. Poster 779. EASD Annual Meeting. Sept 12-16, 2018. Paris, France.

Data VisualizationExample – Medium Complexity MCDV – Interactive Bubble Graph

27Model Data for Pilot Example

Data VisualizationExample – Medium Complexity MCDV – Interactive Data Visualization Application

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Data VisualizationExample – Medium Complexity MCDV – Interactive Journal Table

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Data VisualizationExample – Medium Complexity MCDV – Video Abstract

Video Abstract – Typical• Brief summary of manuscript ~2-7 minutes in length• Video format, audio narration, graphic visualization• Manuscript supplement; not just reading the abstract• Author narrates from a script• Visuals – congress poster or presentation slides• Visuals – supplemental advanced MCDVs• Video – compatible with hosting on YouTube• Format – .mov, .mpg, .mp4, .avi, .flv, .wmv, WebM• File size – per journal guidelines or <1 GB

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Data VisualizationExample – High Complexity MCDV – Video Abstract

Ji et al. Comparison of efficacy and safety of two starting insulin regimens in non-Asian, Asian Indian, and East Asian patients with type 2 diabetes: a post hoc analysis of the PARADIGM study. Diabetes Metab Syndr Obes. 2016;9(9):243-249.

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Data VisualizationExample – High Complexity MCDV – Supplementation through Augmentation

Augmented reality to supplement a manuscript or poster with an iPad application to show 3D graphics and data visualizations

Data VisualizationExample – High Complexity MCDV – Digital Format

Motion Graphics, Visual Effects

Augmented Reality Virtual RealityStop-motion Video, 3D CGI, Animation

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Takes Digital Programming

Data VisualizationExample – High Complexity MCDV – Poster or Manuscript Supplement

Mechanism of Action Video

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Potential Example:Olaratumab (IMC-3G3)PDGFRα antibody

Data VisualizationExample – High Complexity MCDV – Digital Format Poster of Future

Digital Interactive Disclosures

35https://www.youtube.com/watch?v=fbxCGCGYrg4

Data VisualizationCurrent State – Data Analysis + Data Visualization

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Manual review of many documents

Tedious “plucking” of results to…

• Interpret data

• Create tables for publication disclosures

Error-prone churn to produce additional analyses

• Recreate figures to meet venue needs

Generation of statistical analysis results in disconnected, static documents

Data VisualizationFuture State – Data Analysis + Data Visualization

Data Analytics

Digital Visualization

Explore / interpret data meaning

Convey the known relevance

JavaScript/D3Power BISAS VAShiny

SpotfireTableau

Vector-based TFLsDisclosure-ready

Tables & FiguresNon-disclosure-ready

Raster files

SAS Analysis Environment

Data Analysis

Data Visualization

Templates

Writer RecreateDisclosure-ready

Vector files

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Data Analysis &Visualization Software Tools

Data Analysis &Visualization Software Tools

Data ReviewStatic Data Outputs

DataReview

Data VisualizationFuture State – Data Analysis + Data Visualization

A = automation potentialTFL = table, figure, listing GUI = Graphic User InterfaceHIVE = Highly Interactive Visualization EnvironmentHand-generated = not created from analysis environmentDisclosure = regulator & publication medical communications

A AA

A

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Advanced MCDV

SAS ADaMDatabase

Analysis ResultsDataset

Interactive DataAnalysis and

Visualization Tool(eg, Spotfire [GUI])(Meta-data Tagged)

Template

HIVE SessionData Review Meeting

Hand-generated Vector-based

Disclosure-readyTFL / Graphic

Graphing Tool(GraphPad Prism)

(Scalable, Editable)

(Study, Safety, Subgroup, Data-mine, Disclosure Data Review Meeting)

(Created)

(Edited)

Vector-basedDisclosure-ready

TFL / Graphic

(Animated, Interactive)

Data VisualizationFar-future State – Data Analysis + Data Visualization

Disclosure-readyData Visualizations

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Highly Interactive Visualization Environment

Customers:Regulatory AgencyPublication VenueMedical Customer

Data VisualizationAutomation

Use of a Interactive Data Analysis and Visualization Tool with a Graphic User Interface and associated Templates to replace creation of new,

labor-intensive programming scripts for every individual output.

Automation

There is still work involved:

Configuration = Input Choices for the GUI

Programming = Templates, GUI Modules

Workload Shift

Data Exploration, Interpretation, VisualizationLabor-intensive Analyst Programming

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Data VisualizationVector Plots as Output File Type

Example File TypesVector File

Allows scalability (resizing) without

resolution loss

Editable elements

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Data VisualizationVector Plots – Example

Standard SAS Output (Raster File Type)• RTF file• Not editable – picture• Low resolution

Vector-based Output from R• PDF (or EMS) file• Scalable (resizable) figure• Easily editable (eg, in Adobe Illustrator

can adjust font, colors, axis titles)• Always high resolution

Drug X; median, NRDrug Y; median, 15.35 months

Model Data for Pilot Example

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Data VisualizationVector Plots – Example

Created by Stat Analyst

Modified by Medical Writer

Goal: Statistics create so no modification needed(but option when needed)

Medical writer to deliver visualization requirements so modification downstream is NOT necessary

Favors Drug X Favors Drug Y

Favors Drug X Favors Drug YModel Data for Pilot Example

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Data VisualizationAdvanced MCDV – Creation Skills Needed

Digital data visualization techniques: • Graphic design and data visualization principles• Icons and infographics• Video and audio• User interactive installations• Computer-generated imagery (CGI)• Animation• Augmented reality• Virtual reality• Gamification• Integration into web and mobile applications

Creation skills needed include:• Graphic design• Medical illustration and creative design• Videography• User experience and interface design• 2D and 3D CGI programming• Motion, video, model, and animation programming• Graphic and digital programming• Graphic and digital programming• Instructional design• Application, platform, and multimedia designing,

programming, developing, and engineering

Medical writer: • Know what good looks like• Provide visualization requirements• Use data visualization principles• Ensure meet customer needs

Medical writer:• Programming not a skillset • Hand off to graphic design group or outsource

to vendor• Oversee and link analysis with communication

Data VisualizationConclusion

From To

Engaging

Understandable

Retainable

Customer’s Preferences Met

Not Engaging

Difficult to Understand

Difficult to Retain

Customer’sPreferences Not Met

Medical and Scientific Data Disclosures

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Implement Advanced MCDVs

Data VisualizationQuestions

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