Post on 20-May-2020
transcript
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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