eclinicalsol.com

Implementing a Clinical DataRepository and AnalyticsPlatform in 90 Days

DATA IS SIMPLY

EAUTIFULBDATA AGGREGATION EXTRAVAGANZAThis artful imagery is an abstract representation of data comingfrom a myriad of sources to create a single, impactful image.Created by data artist, Tatiana Plakhova

Revolutionizing Clinical Researchfor Efficiency and Insights

Contents

Bringing new treatments to market is costly, risky, and competitive .... 3

Leveraging clinical trial data to decrease risk, time, and cost...... 4

CDRs are critical for life sciences companies...................................... 5

Implementing a CDR within a meaningful timeframe

and a reasonable budget ........................................................................................ 5

Benefits of implementing a next generation CDR ........................................ 7

Best practices for implementing a CDR in 90 days ........................................ 8

Technology partner requirements ...................................................................... 9

Visualizations: Easily view, interact, and understand trial data .............. 10

Implementation expectations ............................................................................ 12

Case study: Correlation between AEs and lab results ................................ 13

Case study: Collecting and aggregating many data sources .................. 14

About us .................................................................................................................... 15

Author: Raj Indupuri, CEO ...................................................................... 15

2

Bringing new treatments to marketis costly, risky, and competitive

There is no doubt that the effort and cost to bring a drug successfully to market is

significant. In addition, once approved, pharmaceutical and biotechnology

companies face intense competitive pressures including crowded marketplaces of

newly approved drugs. In the years from 2005-2011, the median time from first

and second entrant in a newly approved drug class was 2.3 years compared with

4.7 years from 1998-2004. In addition, there is increased use of generic

prescriptions, which account for 80% of all prescriptions written, and an increased

focus on stratified and precision therapies1.

At the same time global research & development (R&D) investment has become

more costly and risky. In 1995, global R&D investment was $33.9 billion and it

dramatically increased to a projected $142.2 billion in 20152. At the same time the

clinical success rates from filing an Investigational New Drug (IND) application to

FDA approval have decreased from 19.1% in the 1990s to 11.3% in the 2010s3. In

short, the costs are increasing while return on investment for the sponsors of the

new therapies is shrinking.

The Tufts Center for the Study of Drug Development (CSDD) found in late-2014

that the cost for developing a prescription medication that gains FDA approval is

$2.6 billion, which represents a 145% increase, when corrected for inflation, over

the estimate CSDD made in 2003. According to Rick Mullin, the author of an article

in Chemical & Engineering News, “the steep rise in costs comes from an intense

effort in recent years to bring efficiency to pharmaceutical R&D. Offsetting any

such savings, according to CSDD, are higher costs due to the increased complexity

of clinical trials, a greater focus on chronic and degenerative diseases, and tests for

insurers seeking comparative effectiveness data”4.

3

1. Getz K., Tufts Center for the Study of Drug Development. Sponsored Research Program. Presented December 2015.2. EvaluatePharma, World Preview 2015, Outlook 2020. Published June 2015. Link:http://info.evaluategroup.com/rs/607-YGS-364/images/wp15.pdf3. Tufts Center for the Study of Drug Development. 2015. Link: http://csdd.tufts.edu/index.php4. Mullin R. Tufts Study Finds Big Rise In Cost of Drug Development. Chemical & Engineering News. PublishedNovember 20, 2014. Link: http://cen.acs.org/articles/92/web/2014/11/Tufts-Study-Finds-Big-Rise.html

Leveraging clinical trial data to decrease risk, time, and costClinical trial data is critical to bring new treatments to market quickly and in a

cost-effective manner. Clinical trial data is the most valuable asset for life sciences

companies. However, companies struggle to leverage their data to make better

decisions and to decrease the time it takes to bring a drug to market. Unlocking the

power and insight in clinical data is one way to raise the return in this difficult climate.

In the pharmaceuticals and the life sciences industry, users need to collect and

aggregate data in a manner that allows users to generate actionable insights. A

well-designed clinical data repository (CDR) helps users make important decisions

easily. The newest CDRs empower life sciences companies to leverage data

efficiently for decisions relating to risk-based monitoring, study design

improvements, improved safety monitoring, CRO oversight, better trial

management, and portfolio management decisions. The capabilities are growing

quickly and robust CDRs are available that allow companies to reap considerable

value from clinical data. Implementing a CDR does not have to be a major IT

initiative. With the right technology partner a CDR can be implemented in

90 days.

CDRs support clinical development

4

• Risk Based Monitoring (RBM)• Protocol deviations trends • Monitor site performance such as screen failure rate, planned vs. actual enrollment, time to resolve queries, etc.

Clinical Operations

Data Management

Pharmacovigilance

Medical Monitors

• Review data (i.e., lab, ECG, vital sign, efficacy) for trends, plausibility, and outliers

• Quickly produce reports to support cleaning• Perfrom reconciliation between different data sources

• Perform technical SAE reconciliation between clinical and safety databases

• Review safety and EDC data together for analysis

Biostatistics • Review data to ensure confirmation to protocol• Efficiently prepare regulatory submissions

• AEs and concomitant medication monitoring• Review early discontinuations for safety signals• Review comments for unreported AEs/SAEs• Review dosage information for protocol compliance

CDRs are critical for life sciences companiesNo longer is the implementation of a clinical data repository something that

requires major resources and infrastructure investment. Next generation clinical

data repositories can aggregate data from many sources including EDC, ePRO,

CTMS or labs, into one place seamlessly. Data is controlled and organized and users

are able to easily integrate data from many sources into one view. Reporting and

analysis are simpler and easier with all data aggregated into one view.

Technological advances such as cloud computing and analytics help meet the

goals of bringing new products to market more quickly and efficiently. A CDR will

drive efficiencies and support clinical trial development activities such as...

Increased transparency and real-time visibility into clinical and

operational data

Enhanced collaboration between investigators, sponsors, and partners

Increased efficiency and speed to conduct trials and prepare

submission-ready data sets

Enhanced capabilities to support effective risk-based monitoring

strategies and safety signal detection

Establish governance models for data and standards to ensure

compliance with regulatory requirements

Decreased frustration and costs in managing and completing trials

Implementing a CDR within ameaningful timeframe and areasonable budget

Life sciences companies share a common desire to harness the power of their

clinical data to enhance decision making and speed up the development process

and time to market introduction. Early CDRs have traditionally taken a long time to

implement and have been costly. Historically they were based on frameworks that

took significant amounts of time to implement. Framework solutions require

experts with intimate knowledge of the system to implement it correctly, and

custom workflows and configurations challenge the boundaries increasing the

risk of failure.

5

Next generation CDRs are fit for purpose solutions that work out of the box

without the need for customization and are built leveraging best practices.

Companies that have pursued this path have found that they were able to save

time and money, and the CDRs were far easier to implement than an overarching

custom solution.

In order to expedite the implementation, it is important to consider the scope of

the data that would be included and prioritize integration accordingly.

Data integration prioritization

The first priority is to focus on the needs of internal customers for study specific

and aggregated clinical trial and operational data. Begin with the highest priority

customers (ie, statisticians, medical monitors, clinical trial managers, and data

managers) to narrow the scope of the data to be initially integrated and ensure the

highest priority needs are met from the beginning.

After the highest priority data, begin to integrate other data sources to support

advanced analytics. Including all of this data provides life sciences companies with

enhanced abilities to leverage clinical data for decision-making, clinical trial cohort

analyses, planning for future clinical trials, and identifying safety signals.

The ability to leverage unstructured data sources for efficient decision making

transforms a CDR into a knowledge management system.

6

• Study specific clinical data

• Study specific operational data

• Aggregated clinical data

• Aggregated operational data

1ST PRIORITY: Clinical andoperational data

• Biomarkers• Microsample analyses• Pharmacovigilance• Genomics• Other sources such as EHR, wearables

2ND PRIORITY: Other data

• MS Word documents• MS PowerPoint presentations

• PDFs

3RD PRIORITY: Unstructured datasources

Benefits of implementing a next generation CDR

Today, 2nd generation CDR solutions are fit for purpose solutions that focus on

self-service and do not entail any customizations.

The technology benefits of newer CDRs, which are more easily and quickly

implemented include:

Fit for purpose platform—provides a configurable platform without the

need of customizations. These platforms are easily scalable and provide the

opportunity to begin with one type of data and to integrate other data

types over time. Remember, your clinical trials are unique, and starting with

an out-of-the-box software solution based on best practices ensures quick

implementation at a decreased cost.

Cloud platform—a Software as a Service (SaaS) delivery model provides

new versions of the software as they are released and users benefit from

the new capabilities immediately. Cloud platforms are quick to set up,

require minimal internal technical resources, and offer a low cost of

ownership as no internal infrastructure is needed.

Out-of-the-box integration—no customization is needed for common

data formats such as SAS, Excel, CSV, XML, etc. Additionally, next

generation CDRs offer self-service capabilities such as import data on

demand, and the ability to configure and manage advanced integrations

easily.

The analytics benefits include...

Guided analytics transform data into visualizations and actionable

information—large volumes of data are transformed for safety review,

monitoring, and clinical operations planning in out-of-the box dashboards

and visualizations without the need for programming.

7

Self-service reports—users can easily run standard reports out-of-the-box

to support data cleaning, reconciliation, and efficacy reporting.

Additionally, reports can be easily created or modified without additional

programming or data modeling.

New CDRs leverage data standards to easily integrate data in compliance with

SDTM and ADaM, and mapping and programming is minimized in this case.

Leveraging CDISC Operational Data Model (ODM) standards support

out-of-the-box interoperability with other clinical systems and minimizes custom

integrations. Users can also search, browse, and utilize metadata within the CDR,

thus reducing the effort for data governance.

Implementing a next generation CDR results in faster implementation and

decreases resource requirements to manage the CDR going forward.

Best practices for implementing a CDR in 90 days

Next generation CDR solutions are quickly implemented in a budget-friendly

manner. To do so focus on key questions that enhance the company’s ability to

share clinical trial data across the organization. Key questions to consider

include…

Business and IT issues—determine how to maximize ROI with existing

systems and technology, and consider how to integrate systems from

multiple vendors and service providers.

Data silos—evaluate how to reduce data silos in order to provide better

access to data that can lead to more insights and better decision-making

and better control of clinical data.

Process issues—identify how to implement repeatable processes to gain

efficiencies across clinical trials, and identify any issues hindering the

productivity of Data Managers and Clinical Research Associates.

8

Start the implementation of a CDR by outlining the critical components of data

strategy, data utilization, and an initiative champion. Defining a data strategy with

common objectives and key results is a critical starting point. Next, life sciences

companies must understand at the outset how data is used in the organization

currently and the goals for leveraging clinical trial data in the future. Last, and

equally important, it is critical to identify a group of influential individuals to unite

the organization around the purpose of the CDR and promote collaboration.

These three areas will set the direction for the CDR implementation process.

Plan for success: Align data strategy, understand data utilization,and select champions

Technology partner requirements

Finding and selecting the “right” technology partner to implement a CDR requires

careful consideration of requirements. Key areas to evaluate include:

For Software as a Service (SaaS) provider, ensure SSAE SOC II certified data

center for the infrastructure and IT components necessary to support the

platform

9

• Define common objectives and key results desired from CDR implementation

• Identify data types and sources to be integrated

• Prioritize data to be integrated into theplatform based on the immediate value to the business. Consider starting with one clinical trial and expanding to integrate more data in a phased approach as earlier integrations are completed successfully

Data strategy

• What problem(s) do you want to solve

• What insights are you looking for

• Who are the information consumers in your organization

• What are the needs these information consumers have in collecting data and gaining insights from it (e.g. real-time safety analysis, risk based monitoring, etc.)

Data utilization

• Identify a team to champion the initiative and unite the various functional groups with a cohesive strategy and to promote collaboration

• The ideal team will include individuals that are influential across the organization, and have a keen understanding of the different roles each function plays and the various systems and processes

• Ensures alignment with organizational objectives

Initiative champion

Platform is compliant with regulatory and industry requirements including

FDA 21 CFR Part 11 and FDA’s Guidance -- Computerized Systems Used in

Clinical Investigations

For SaaS models, ensure the private cloud is hosted at a fully compliant

data center with features such as

● Logical security measures at multiple levels including

firewalls, network access, and application access

● Encrypted communications

● Redundancy and failover measures in place on multiple

layers including electricity providers, internet providers,

firewalls, switches, routers, and physical hosts

● Backups performed on multiple frequencies and are stored

locally for easy access and also stored at a secondary

facility for disaster recovery purposes

Visualizations: Easily view, interact,and understand trial data

Clinical trial data that were once ambiguous listings come to life through analytics

modules. Once data has been integrated and standardized in the CDR platform it is

instantly accessible through advanced analytics and visualizations. These

visualizations enable users to visually interact with their data for views of adverse

events, lab results, patient profiles, and more—all the way from cross trial views

down to the patient level. Drill down capabilities give users complete transparency

and the ability to interact with the data.

Visualizations allow clinical trial sponsors to easily obtain and leverage insights into

clinical and operational data in real-time. Easy and efficient access to adverse event

(AE) data reported as part of a clinical trial helps life sciences companies meet the

imperative to ensure patient safety, support risk-based monitoring initiatives, and

integrate multiple studies into one easy-to-interpret visual.

10

11

Lab Data by Study

Adverse Events by Study

Sample Visualizations

Implementation expectations

Successful implementation of a CDR requires a plan, open communication, and

agreement on the scope of work for the project between the life sciences company

and the technology partner. A critically important tool is a detailed

Implementation Plan that outlines the data to be included in the platform,

summarizes the desired functionality of the platform, and demonstrates the

benefits of the new CDR.

Specifically the Implementation Plan should outline:

Services to be provided

Dependencies and constraints

Data sources to be included

Documents and forms used as a part of the implementation

Project team list including full contact information and their role on

the team

Training to be provided

Quality assurance activities

Detailed project timeline and schedule

Critical components in successfully implementing the CDR platform are team

member training and updating processes and systems to include the CDR

platform. The training phase consists of two phases. The first phase will introduce

team members to the capabilities of the platform and train them on how to use it

effectively. Undoubtedly implementing a CDR platform will change existing

processes and systems for collecting and managing clinical trial data. The second

training phase will train team members on new processes and systems that are

inspired by the CDR platform.

A helpful resource for team members is to select a “Super User(s)” to share

experiences and best practices, as well as reinforce change management principles

on an on-going basis. Additionally, we recommend regular meetings throughout the

implementation process to review progress, discuss challenges, and clarify questions.

12

Case study: Correlation between AEs and lab results

Our client, a west coast biotech company was sponsoring a series of clinical studies, anticipating anupcoming submission. They were using a combination of regional CROs to support their trials andclosely monitor AEs and SAEs in the patient population.

The Chief Medical Officer was frustrated by his inability to access trial data in real-time. The data wouldbe returned to him as datasets from the various CROs and then required the SAS programmers at hiscompany to manipulate the data so that he could view the results. In particular, he wanted to monitorthe lab data and try to understand whether or not there was any correlation between the AEs reportedand the lab results themselves.

Solution Our data management team pulled the data from the ongoing studies into a central database using ourproprietary tool, elluminate®. We also developed a series of views that allowed the company to view thedata in an aggregated and related fashion that was available to the Chief Medical Officer in a few clicksfrom his desktop and required no support from the internal programming team at his company.

While we were preparing this solution, the VP of Clinical Operations asked us to aggregate the dataacross their program as an alternative approach for preparing a Drug Safety Update Report (DSUR).Their hope was to use the elluminate® platform as a means to organize and prepare this timeconsuming and important report submission for the FDA.

ResultsAfter the custom mapping was performed, the Chief Medical Officer was able to view results in nearreal-time and access custom views at the patient level to explore relationships between labs and safetydata, and produce reports in a few clicks.

The DSUR was produced and prepared through the platform and provided to the FDA without themanual intervention and programming time required with previous submissions. The VP of ClinicalOperations estimated that this saved her company weeks of manual programming effort.

13

Case study: Collecting and aggregating many data sources

Our client, a mid-sized global CRO was facing the same challenges many of our sponsors do – the effortto collect and aggregate clinical trial data was highly manual and time consuming. The datamanagement and programming teams were exporting data from multiple systems including EDC,CTMS, lab data, and ePRO into MS Excel and manually reconciling data. At the same time, the teamswere combining the spreadsheets to allow them to aggregate and analyze the results and identifyissues or performance concerns.

SolutionOur professional services team worked with the CRO to build the study feeds into our proprietarysoftware platform, elluminate®. We created standard SOPs and workflows to ensure that once the datafeeds were set up, they could be maintained and extrapolated to other systems as CROs in particularwill work with many platforms. As all of our resources are focused on clinical data management and areknowledgeable about the unique requirements of clinical data management, they were able to offerinsight into best practices and ensure the solution we were developing adhered to requirements andbest practices for drug development.

We worked with the VP of Operations and her teams to create a series of custom views including:• Patient enrollment logs• Lab normal range tracking/maintenance• Eligibility tracking as well as eligible versus non-eligible patients and ability to compare to

protocol deviations• Payment tracking and projections• Patient level data entry status – incomplete, pending, cleaned• Protocol deviation tracking and comparisons

ResultsToday the elluminate® tool allows our client to have more effective interactions with their customers,using the power of visualizations to showcase issues and areas of focus. The head of Clinical Operationssaid it has saved her innumerable hours trying to use spreadsheets and multiple sources of data to drivethe same conversations that are now enabled by a click to produce a report. The IT and programmingstaff have remained focused on other deliverables and the data management and clinical teams havebeen able to access clinical trial information directly, and eliminate an entire step required in theirprevious configuration.

14

See how brilliant data can be.

Visit www.eclinicalsol.com and discover how eClinical Solutions

can help you leverage clinical data to its fullest potential.

Mary CostelloVice President, Global Marketing

Telephone: 866.961.3542E-mail: mcostello@eclinicalsol.com

© 2016 eClinical Solutions. All rights reserved.

About UseClinical Solutions is a software and service provider exclusively dedicated to

supporting clinical research. Our mission is to identify best practices and

technologies to make clinical research data acquisition, standardization,

aggregation, and analytics absolutely simple and easy.

Formed in 2006, the eClinical Solutions team has many years of experience

working in the life sciences industry dedicated to clinical data management and

programming. Through a consultative approach and the mindset that each

individual organization has a unique set of goals and objectives, we partner with

our customers to maximize one of their most valuable assets, their clinical data.

Author: Raj Indupuri, CEORaj Indupuri, CEO, eClinical Solutions, has spent the majority of his career

supporting clinical data management and programming objectives by introducing

and implementing solutions and technologies to further clinical research

development. With a unique blend of hands-on technical and data management

experience, Raj works to advance the eClinical Solutions strategic vision and the

delivery of cloud-based clinical solutions. Raj is responsible for the overall direction

and management of the company and is passionate about bringing innovative

solutions to the industry. For more information on eClinical Solutions, please email

Raj at rindupuri@eclinicalsol.com.