This document summarizes a presentation on digitizing clinical study design using TransCelerate's digital data flow solutions platform. The agenda includes an interactive demonstration of building a new study and tutorials on various study builder functions. It also covers more advanced topics like using Microsoft Word to edit studies and manage library elements. The document discusses the underlying technology powering the platform including Azure services, security, and integrations. It outlines user stories and roles. Finally, it describes potential future visions for the platform including using blockchain for greater visibility, transparency, and accelerated approval workflows in clinical trials.

1. Digitizing Clinical Study Design
April 2020
TransCelerate
Hackathon

2. Ryan Tubbs
Team Leader
LinkedIn
Vasu Ranganathan
Business Processes
LinkedIn
Gerald Kukko
Solution Architecture
LinkedIn
Tianna Umann
Blockchain
LinkedIn
Brent Groom
Interactive Demo
LinkedIn
Brian Nikonow
User Experience (UX)
LinkedIn
Michelle Hendrickson
User Experience (UX)
LinkedIn

3. Agenda

5. Today's Headline - EXTRA! EXTRA! READ ALL ABOUT IT
"TransCelerate Digital Data Flow Solutions Platform enables the building of Global Clinical Study Design in 3 minutes! “
https://youtu.be/Mqf1x6COGbE

6. Interactive Demonstration

8. New Study
Covers P0, 1
https://youtu.be/XbDvLgimJmE
Study Builder Tutorial
P0-P6 of the Study Builder
https://youtu.be/AS2eqIw9BjM
Advanced - Using Microsoft Word, Deepdive
Use Microsoft Word to Edit a Study and Manage
Elements; Covers P3, L1, L2
https://youtu.be/axiciIquSOU
Advanced - Library Management and Library Import
Covers L5
https://youtu.be/4YRTi14_VtQ
Advanced - Digital Library Metadata Management
Covers L1-L4
https://youtu.be/_ZN4l72Q4OU
Advanced - Library Creation and Management
Covers L5
https://youtu.be/xjZTSEaaC8g

9. https://hackathon.intelinotion.com
User Email Password
Nancy Edge nedge@intelinotion.com 2019Rtpl
Jon Planet jplanet@intelinotion.com 2019Rtpl
Cam Mistry cmistry@intelinotion.com 2019Rtpl
Bill Label blabel@intelinotion.com 2019Rtpl
crih@microsoft.com

10. User Guide

11. User Story
1 – Study Build Navigation
2 – Data Access
3 – Export Protocol Content
L1 – Manage Elements
L2 – Manage Element Values
L3 – Manage Element Relationships
L4 – Manage Value Relationships
L5 – Library Import
User Story
P0 – New Study
P1 – General Protocol Info
P2 – Study Objectives
P3 – Study Endpoints
P4 & P5 – Mandatory Elements and
Manage Schedule
P6 – Version Study

20. JSON
DOCX
CSV

27. 1
3
2

28. 1
42
JSON
DOCX

30. Underlying Magic

31. HTTPS
Web Mobile
EDC
CTMS
PPM
Azure Search
Service
Azure Active
Directory
Azure Key
Vault
Azure Blob
Storage Service
Azure Postgres DB
Service
Azure Logic Apps
Integration Service
Core App
Service
Audit
Service
Caching
Service
Notification
Service
Client App
Service
Azure File Service
Office 365
Co-Authoring
& Collab. Service
App DB
Service
Content Proc.
Service
Task Mgmt.
& WF Service
Azure Traffic
Manager
Azure
Kubernetes
Service
Nginx
Ingress
Controller
Azure Load
Balancer
Highly secure secret
& key management
Sigle sign on & role-
based access control
Fully managed
file share
Scalable
Modern Microsoft
Word application
extends Word
authoring UX and
tightly integrates
micro services to
enable

32. Constant advocate for end user.
Acts as voice of user.
Understand existing ecosystems.
Evaluate development abilities.
Satisfy business requirements
Establish key performance indicators
Help define MVP and future road map

33. Empathize
Ideate
Define
• Understand the base requirements
• Identify current pain points
• Establish personas (who is using this product and why?)
• Evaluate similar existing products to set baseline
• Keep users at the heart of all activities
• Define the problem based on research and not assumptions
• Establish road map and user journey map
• Create backlog of requirements based on MVP
• Establish future goals for post MVP
• Construct a saleable navigation solution
• Group content to align with user’s mental model
• Begin to explore visual language
• Build wireframes to review with subject matter experts
Prototype
Validate
• Build out flow document in Sketch to view how all pages interact with one another
• Constructed InVision (high fidelity) prototype to test functionality with users
• Evaluate how designs will align with development efforts and back end services
Repeat
• Conducted various levels of user testing ranging from actual developed coded to prototypes
• Task-driven testing allows users to control the experience to gauge ease of use
• User acceptance testing ensures design has fulfilled provided user stories

34. Wireframes

35. Technical Feasibility
Vs
Customer Value
This activity compares the development effort against the
benefit to the user for all features. It helps the team establish
what an MVP looks like and provides focus on what needs to be
specific tasks.
Technical Feasibility
Customer Value
HighLow
Low
High
User Stories
MVP

36. High Fidelity
Prototype

37. Industry Standards & Best Practices
Expected Behaviors & Recognizable Patterns
Focus on Information Architecture
Reduce User Cognitive Load
Ensured we used functionality that aligns with user’s mental model.
Helps encourage adoption and increases retention.
Allows the user to quickly navigate in a logical flow.
Presenting the user with grouped content and populating drop downs with relevant
content

38. Clear visual indicators alerts
user to what is required.
Form field title’s are
persistent at all times
eliminating confusion.
Selection summaries
provide immediate feedback
showing the user the
selections made.
“Help text” assists user in
knowing what type of action
they need to perform.
(Select from drop down or
populate with free text)
Presenting the user with
efficient enabled vs disabled
state ”call-to-actions” or
buttons informs them when
the section is completed.

39. Provide the user with a
“safety net” for potentially
destructive actions.
Align with the knowledge of
green means “go” and red
means “stop” makes it clear
to the user the impact of
each button.
Easy control for adding and
removing selections
Operating within a modal
suggests to the user that
they have not navigated
deep within any flow
The user has the ability to
expand open text fields to
view additional text as
apposed scrolling within a
small window.

40. Art of the Possible
Looking toward the future…

41. Our Future State Vision
We hope you enjoyed test-driving our prototype! This interactive UI represents our unique vision for creating a standards-based end to
end digital clinical trials workflow that is automated, seamless, and accelerates critical life-saving medicines to market – starting with
Alzheimer's disease.
We believe the clinical trials industry is at a critical juncture. Now, more than ever, emerging technologies have the potential to transform
the way drug trials are run. Just like taking the keys to a Porsche, technology is accelerating faster than ever and disrupting wide swaths of
industry. One compelling new technology that has surfaced in recent years is Blockchain. Blockchain consists of a series of blocks in which
each consists of a cryptographic hash of the previous block, a timestamp, and transaction data. By requiring a match between the user
and the encrypted hash, this “distributed ledger” provides an immutable source of truth that is safe and hackproof. While Blockchain
originated in the financial industry, a growing number of other applications are emerging across industries, such as in real estate,
insurance, and asset management.
Imagine for a moment the possibility of a Blockchain controlled Clinical Trial workflow that provides participants with immediate visibility
into all study metadata, including protocol titles, objectives, amendments, import/export query logs, and more. Take it further and
consider a Blockchain-controlled IRB board consent process:
 Clinical Study protocol is revised, and study site request a change to their consent.
 The change request is logged on the blockchain and triggers a notification to the IRB board
 The IRB board approves the consent change.
 The approval is logged on the blockchain. This triggers an event that notifies all the stakeholders of the change in the consent.
Blockchain holds vast potential to transform clinical trials research. If you enjoyed our prototype, then you’ll love our vision of a digital
ledger-based clinical trial workflow that accelerates the marketing of life-saving medicines.

42. https://www.youtube.com/watch?v=ra19YBdajoc
Art of the Possible
Covers the UX and underlying technology
https://youtu.be/ra19YBdajoc

44. Scenario #1
The immediate solution for
visibility and communication
regarding amendments will
leverage blockchain technology
to enable near real time visibility
into amendments to the protocol.
It will also give the team full
transparency into the clinical
trial lifecycle along with the ability
to accelerate the overall workflow.
Furthermore, regulatory, study
sites, and other ecosystem
stakeholders involved in the
clinical trial will gain access
to the end to end study data
artifacts, approvals, and reports.
The added benefit of the solution
is the team is able to integrate
blockchain as part of their
existing infrastructure instead
of a rip and replace solution.
Report
Patient
Enrollment
Data
Collection
Data
Analysis
Protocol
Design
Validation
SOA EDC
Protocol
SAPCSR
MetaData
Ecosystem Amendment Reporting Visibility and Notification
IRB
Consent
Change
Request
CRO
Protocol
Revision/
Amendment
Stakeholder
Network
Consensus
1
2 3 4
A trusted shared, single source of
data truth enables visibility of all
stakeholders into process enabling
efficiency in the revision, reporting,
and approval of study trial
documents.
Modern technologies such as
blockchain and automated study
event notifications work together
to accelerate the clinical research
trial process.
1. Clinical Study protocol is
revised, and study site request
a change to their consent.
2. The change request is logged
on the blockchain and triggers
a notification to the IRB board
3. The IRB board approves the
consent change.
4. The approval is logged on the
blockchain which triggers an
event that notifies all the
stakeholders of the change
in the consent which enables
them to update their internal
systems documentation

45. Scenario #2
Lydia, a clinical data scientist at Contoso, is leading
the phase III clinical research trial submission for the
new Alzheimer’s drug study. The company recently
deployed a new solution called blockchain to
accelerate the study design and protocol creation and
provide more transparency and data sharing. The
solution also enables her team to produce
deliverables on activities that previously required
input from the study design team. The new workflow
now allows teams across the clinical trial
stakeholder’s ecosystem to work in parallel.
This new system not only allows users to quickly
enter required trial information into the CT.gov
website, it also offers seamless submission of the
CTSD information to the appropriate health authority.
Blockchain opens up the possibility of near real-time
visibility, removes upstream data dependencies, while
enabling parallel authoring to efficiently sync report
and other data component deliverables . Thanks to
blockchain technology, team authors can now share
components and reports in a much more secure
environment.
Ecosystem Parallel Activities
Trial Summary
Report
Report
Patient
Enrollment
Data
Collection
Data
Analysis
Protocol
Design
Validation
CT.gov Updates
SOA EDC
Protocol
SAPCSR

46. Shared
Clinical
Research
Study Data
Private Data Process
Private Data Process
Private Data Process
Private Data Process
Private Data Process
Analysis
Publishing
CRO
Study Site(s)
Pharma
Sponsor
.
.
.
.
.
Health
Authority
Compliance
Audit

47. ´ Off Chain
Shared Data Process
Consent change
request
Protocol
Revision/
Amendment
Stakeholder
Network
Consensus
CRO
2
3
4
Shared Data
Process
CRO
Pharma
Sponsor
Study Site(s)
Data
Analysis
Patient
Enrollment
Data
Collection
Report
meta
data
Protocol
Design
Validation
SOA
CSR
Protocol
SAP
EDC
Health
Authorities
1

48. Shared Data
Process
IRB
Pharma
Sponsor
Study Site(s)
Data
Analysis
Patient
Enrollment
Data
Collection
Report
Protocol
Design
Validation
SOA
CSR
Protocol
SAP
EDC
Health
Authorities
Stakeholders Shared Data Layer ( Blockchain Ledger)
CT.gov
Updates
Trial Summary
Report

49. Data
Analysis
Patient
Enrollment
Data Collection
Report
Generation
meta data
sources
Study Protocol
& Set up
Validation
SAP
Protocol
DM345
Final 1.0
SOA EDC
CSR
Protocol DM345
Inclusion/Exclusion
Change
 The Blockchain Ledger Watcher monitors events occurring on the blockchain.
Events reflect information relevant to individuals and systems.
 Events are captured and sent to the Consumer
 The Consumer delivers information regarding the data received from the
Watcher to Data Storage where the Analytics Engine processes the
information through ML/AI
 The ML/AI output is shared with the Intelligent Agent which communicates
the information to the End Users with ability to populate updates to
upstream/downstream processes.
Blockchain
Watcher
1
2
3
4
6
Shared Data Layer (Blockchain Ledger)
Protocol
TransCelerate Clinical Trial Intelligent Agent for automated Study Design build and support
Intelligent Agent
ML
Reinforcement
Learning
Machine Learning
AI
Transaction
Consumer
The Sponsor Protocol team makes a change
to the study inclusion/exclusion criteria
The transaction (change) is recorded on the
ledger
The Blockchain Watcher service pushes the
transaction message to the Transaction
Consumer
The Transaction Consumer sends the
information to the Machine Learning engine
The Machine Learning model processes the
information the output is sent to the
Intelligent Agent.
The Agent alerts the SOA, EDC and SAP
teams of the change and offers to update
their inclusion/exclusion documentation. The
teams can also ask the Agent to open up a
line of communication with other team
members or ask the Agent to schedule a
meeting if they have any questions
regarding the update.
The Agent consumes any feedback and
records the workflow for resolution of the
update which is used for reinforcement
learning to improve the systems accuracy.
1
2
3
4
5
6
5
7
7

50. Reviewer Network Consensus Blockchain LedgerIRB AppovalIntelligent Agent
Inclusion/Exclusion
Update Validated
Update
New Blockchain Transaction
Notificatoin
Approve Protocol
Update
IRB
Approval
Validated
Approval
1
2
3
4
5
6
7
Stakeholders Shared Data Layer ( Blockchain Ledger)
Shared Data
Process
CRO
Pharma
Sponsor
Study Site(s)
TransCelerate Shared Data Workflow leveraging Blockchain and ML/AI
Health
Authorities

51. IRB Approval Smart Contract
1. Section Owners submit section
review
2.Site Consent Owner Updates any
Change Request if required
(Step 1 & 2 may repeat until reviewer
signs off)
3. IRB board Approves Consent
Section
Enter your Site ID
Site Admin Log in (public/private key)
Choose an Action
Generate Internal IRB Informed Consent Review
Template
Submit Approved IRB Consent
Submit Adverse Event document
Submit Protocol deviation document
Submit IRB Informed Consent Amendment approval
Informed Consent Template Builder
Please choose your components
PART I: Information Sheet
Introduction
Purpose of the research
Type of Research Intervention
Participant selection
Voluntary Participation
Information on the Trial Drug/Device/Therapy
Procedures and Protocol
Unfamiliar Procedures
Description of the Process
Duration
Side Effects
Risks
Benefits
Reimbursements
Alternatives to Participating
Add Another Section
PART II: Certificate of Consent
Participant Statement of Consent
Illiterate Participant Statement of Consent
Statement by the researcher/person taking consent
Add another section
Part I
Section A
Reviewer
Part I
Section B
Reviewer
Part I
Section C
Reviewer
Part II
Section D
Reviewer
Multi Center Clinical Web Portal
IRB Board
Clincal Trial
Shared Ledger
IRB Notification
Clinical Trial
Site Consent
Owner
Content
Section A
Reviewer
1. Section A Consent Review submission
with Change Request
2. Consent owner Notification
Distributed
Ledger Watcher
4. Content Reviewer
Notification
IRB Section A Approval
3. Section A Update
5. Section A approval sign off
TransCelerate Innovation for IRB Consent Approval Portal
powered by Blockchain

52. Persona Narratives

53. Contoso Pharma is a fictitious
biopharmaceutical company we
created to bring our story to life.
We're about to take you on a journey
where you’ll meet Frank, Jane,
Matteo, Ingrid, and Jocelyn – the five
actors responsible for rolling out
InteliBuilder.
Contoso Pharma seeks to introduce
their first Alzheimer drug to the
public in over 17 years. Their
previous drug failed to get
approved after over 10 years in
development and at a cost of over
$2 billion USD.
In order to close the gap in time
and money in bringing its Alzheimer
drug to market, Contoso Pharma
realizes it needs to rethink the
traditional methodologies
surrounding how clinical trial
studies are designed and delivered.
To address this concern Contoso
Pharma has elected to use
InteliBuilder to streamline the
process.

54. Demonstrates the “Master Library of Study
Design Elements”
The Problem
Frank is a clinical content steward who works within the Clinical
Standards Group at Contoso Pharma. Frank’s responsibility is to
interact with various investigators across a number of institutional
boards, including IRB and FDA, to develop the terminology and
standards required for a comprehensive search strategy across
multiple medical sources. He must continually verify the quality
and integrity of data submitted for review, ensure it follows all
industry standards, and be exacting enough to call out data
inconsistencies and gaps in information.
Frank is flustered by the cumbersome and archaic nature of his
job – managing communications and emails across all players,
checking online sources, cross-checking paper-based
documentation. With modern technology, Frank dreams there
must be a better way to “digitize” and automate the content
management process for clinical trials research
The Turning Point
Frank gets a call from Matteo, Clinical Director, at Contoso Pharma
who informs him that they are adopting a new, innovative Study
Builder and Digital Repository that will make the process
seamless. Frank is skeptical, but excited.

55. Demonstrates the “Master Library of Study
Design Elements”
The Solution
Frank starts using the system and quickly finds that Libraries can
be generated for creation and management of specific design
elements in the clinical trial lifecycle.
Metadata tags associated with the Library can be configured at
the time of Library creation as Mandatory or Optional, so that any
objects created or imported into the Library will be required to be
tagged with these metadata values.
Frank sees that various components managed in the Library can
be configured for “Type of Reuse” such as “As Is” or “Verbatim,
“Repurpose” or “Derivative.” This design enables downstream
users to optionally edit them to provide additional control of
standard terms and content based on the Library level controls
placed on the design elements. This will help control consistency
and quality of standardized data and content – while making
Frank’s job much easier.
Frank sets up a number of relevant reusable libraries for the Study
Design elements that are tagged by applicable metadata such as
Therapeutic area, including libraries for:
• Objectives, End Points
• Inclusion, Exclusion Criteria
• Protocol Title

56. Demonstrates the “Master Library of Study
Design Elements
The Resolution
Frank can’t believe how easy and powerful this solution is! He is
particularly excited about the ability to import from external
sources into the digital repository (such as TransCelerate libraries
or CDISC). This will enable sponsors from regulatory agencies to
login to the system and maintain and update the specific libraries
across any number of Therapeutic areas, Indications, and other
study parameters.
Frank feels he is now better equipped to ensure that data will
flow seamlessly from these design elements into the protocol and
other relevant documents, as well as export for downstream
systems such as CTMS.
Frank calls up Matteo and says: “I’m sold!”

57. Demonstrates the “Study Build – Navigation” Feature
The Problem
Jane is the lead clinical scientist for the study. On the previous Alzheimers study, her and her team
experienced months of setbacks and delays. She recalls having to triangulate between various
compliance and regulatory agencies, patient rights, and an avalanche of paperwork.
Completing the design swiftly and with predictability has always eluded her. She knows all to well that
the processes to search, find, and verify sources requires considerable time to copy and paste from
PDFs into the study trial templates. This quality control process is often very cumbersome and time
consuming, not to mention considerably prone to errors.
The Turning Point
To address their key pain points and improve efficiencies, Jane’s manager, Matteo, has been leading
an initiative on how to create a new streamlined process. She learns that the digital Study Builder will
enable her team to build a clinical study with predefined agency/institutional or company defined
templates and libraries based on a single source of truth. For example, the builder inherits correct
metadata values from the Product such as Compound Number, Therapeutic Area, and Indication. It
also is designed to prepopulate relevant data from a large number of institutional databases, saving
the manager considerable amounts of time from cross-checking and copy/pasting sources
Even before launching into this project, Jane has high hopes about the potential time savings this
platform will introduce into her clinical trials workflow. But she also has some degree of apprehension.
She hopes this works!

58. Demonstrates the “Study Build – Navigation”
Feature
The Solution
Jane logs into the Study Builder, follows the directions, and
navigates to the Business Object Navigator.
She selects “New” from the drop-down to start building the study.
The Study Builder is pre-populated with properties from the name
of her experimental product “Wonderdrug!”
Jane proceeds to fill in the specific metadata required:
• Protocol Number
• EudraCT Number
• IND Number
• Study Phase

59. Demonstrates the “Study Build – Navigation”
Feature
The Resolution
Jane creates a new Clinical Trial study called Alzheimer’s Study –
3172020 and saves it in the database.
Jane is impressed with how fast and seamless this went compared
to the old “cut and paste” approach.

60. Demonstrates the “Initiate Study Build & Study
Build Design”
The Problem
Now, let’s get to know Matteo, Director of Clinical Operations at
Contoso. Matteo manages a staff of 20 people who are working
on the Alzheimer drug clinical trial. Matteo is responsible for
ensuring the successful completion of the trial protocols and that
they operate according to the highest ethical and industry
standards. Matteo is deeply concerned by the enormous time and
cost of all the study design activities – generating clinical reports,
connecting the right data to the correct protocols, and managing
all upstream and downstream schedules, etc.
Matteo would like nothing more than to create a Digital Data
Flow – one that generates a “single source of truth” – for the end-
to-end study process.
The Turning point
Matteo’s team has been working with TransCelerate to test out a
new digital Study Builder and Design Repository. He’s eager to
see it in action. His lead clinical scientist Jane has already kicked
off the study named Alzheimer’s Study – 3172020.
•
•
•
•

61. Demonstrates the “Initiate Study Build & Study
Build Design”
The Solution
Matteo logs in to the new platform to retrieve Alzheimer’s Study
– 3172020 and initiate the Study Design process.
Matteo builds the Protocol Title of the study based on hyperlinks
to prepopulated libraries and templates. He then defines the
Study Objective as follows: “To assess the effect of [study
intervention #1] on the ADAS-COG and CIBIC + scores at Week
[X] in participants with Mild to Moderate Alzheimer’s Disease.”
Matteo next enters the Study Masking Information,
Intervention, and Arms. For these categories, he chooses
Double Blind, Xanomeline, and High Dose respectively.
Matteo can select the Objectives and Endpoints for the study
using the standards managed and governed in the Objectives and
Endpoints libraries. Matteo selects the appropriate Objectives,
Objective Level and related Endpoints. For each Endpoint, the
appropriate visit Timeframes, Units and Biomedical Concepts are
selected from controlled standard metadata terms.

62. Demonstrates the “Initiate Study Build & Study
Build Design”
The Resolution
Matteo is impressed! Not only was this easy (and kind of fun) but
he also has options for generating the study design:
• Choose a new Design template as the starting point
• Populated from a previous Study Design
• Start from scratch, if user is defining the design elements for the
first time
Matteo chooses to select a template for the Alzheimer’s therapeutic
area to use for the design, and next edits the Schedule of
Assessments. This outlines the activities, a plan for administration of
study treatment, and a list of assessments and procedures that are
to be performed for the duration of the study.

63. Demonstrates “Document Protocol Generation
for TransCelerate CPT”
The Problem
Meet Ingrid, the Medical Writer at Contoso Pharma. Ingrid
oversees a staff of three other writers who are responsible for
generating the company’s clinical studies and reports, including
QC on all protocols, amendments, and administrative changes. On
top of this, Ingrid must manage all upstream and downstream
schedules for her team and guarantee that all content changes
are imported to the company’s central database.
Ingrid is stressed out because she spends so much time project
managing her team that she hardly can keep up with content
production, report generation, and QC. Most of the time it feels
like she’s squeezing 25 hours into 24. It’d be great if she could
leverage technology to create efficiencies in her content workflow
and reduce authoring time while maintaining consistency and the
same high standards.
The Problem
Ingrid has just learned from Matteo, her director, that the
department a new digital Study Builder and Design Repository.
They meet for a briefing and he shows her the new solution.

64. Demonstrates “Document Protocol Generation
for TransCelerate CPT”
The Solution
Ingrid logs in to the new platform to start building out the auto
insertion protocol for Alzheimer’s Study – 3172020. Her job is to
ensure the study is reusing and auto-inserting the correct library
content, and that the control of this content is based on the right
library component policies. Ingrid must also verify that the design
of each document maps correctly to the overall digital data flow.
Ingrid edits the document protocol generation engine with
templates that will be used to automate the Protocol Title for the
Study Builder. By providing automated links to the Common
Statistical Analysis Plan (SAP) and Common Clinical Study Report
(CSR) templates, Study Managers will now be able to save
considerable amounts of time in formulating titles to their
studies.

65. Demonstrates “Document Protocol Generation
for TransCelerate CPT”
The Resolution
Next, Ingrid builds in auto generation features into the remaining
initial protocol design entities (Study Objectives, Endpoints,
Assessments, Forms). These are based on the selected key
attributes on the protocol record of Therapeutic Area, Indication,
Study Phase, and Study Type.
Ingrid will initially focus on auto generating TransCelerate CPT
documents. However, in the near future she will be asked to
migrate to auto-generating the draft eCRFs and other related
downstream documents from a master set of common data
elements. Additional industry standards on the agenda to be auto
generated include CDISC, Clinical Trials.gov, EudraCT, and more.
Ingrid sees many benefits of the auto-generation feature
especially as it introduces Study Managers to early visualization of
their work and facilitates early detection of errors or
inconsistencies.

66. Demonstrates the “Study Design – Export”
Feature
The Problem
Jocelyn is a biostatistician at Contoso Pharma and part of the
team leading the Alzheimer drug study. She works on Jane’s team
and is responsible for monitoring how the study is conducted and
to ensure full integrity of the results for reporting and external
validation.
Much of Jocelyn’s time is spent writing research proposals and
conveying her findings to pharma professionals and the broader
scientific community. A painstaking component of Jocelyn’s work
involves collecting, organizing, and cross-checking the study data
against numerous medical databases to ensure her results are
as accurate as possible. Much of this is process is very manual
and tedious.
The Turning Point
Jocelyn is called to an important meeting with Jane and Matteo
where she’s introduced to a new Study Builder and Design
Repository. Could it be that her days of wrangling data are over??

67. Demonstrates the “Study Design – Export”
Feature
The Solution
Jocelyn logs into Contoso’s new Study Builder and locates the
saved Study Design components for the Alzheimer trial study
initiated by Jane and built out by Matteo. The study can be
exported in JSON or other formats for downstream uses to
support the end-to-end digital dataflow.
Jocelyn proceeds to publish the Study Design elements output in
JSON format.

68. Demonstrates the “Study Design – Export”
Feature
The Resolution
Jocelyn previews the JSON format export of the Study Design
output. After a careful review, she is ready to import the data into
the EDC and CTMS. Jocelyn is surprised by how easy it is to
manage the Study Builder. She now has the ability to provide
automated workflows to benefit other downstream users. Jocelyn
has waited a long time for this and couldn’t be happier.

69. Appendix