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Challenges and Opportunities Around Integration of Clinical Trials Data

30 November, 2017 | Author: Narayana Subramanian: Healthcare Business Analyst,

Rajat Shukla: Sr. Healthcare Consultant, CitiusTech

CitiusTech Thought

Leadership

2

Objective

To understand the processes involved in conducting clinical trials and the stakeholders involved

To identify the typical IT landscape across organizations that conduct / facilitate clinical trials

To identify the potential opportunities for integrating data assets (R&D as well as RWD) and the possible synergies that be offered by the integration

To illustrate the benefits of moving to a platform-based approach for data integration and the limitations of point solutions

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Agenda

Introduction

Clinical Trial Overview

Clinical Trials: Existing IT Landscape and Challenges

Clinical Systems: Challenges with Integrating Data

Clinical Systems: Opportunities for a Platform

Clinical Systems: Author Perspective

References

4

Introduction

Operationally, a Clinical Trial can be defined as a study of human subjects that is designed to answer specific questions related to biomedical or behavioral interventions (drugs, biologics, treatments, devices, or new ways of using known drugs, biologics, treatments, or devices)

Conducting a Clinical Trial is a complex process, consisting of activities such as protocol preparation, site selection, approval of various authorities, meticulous collection and management of data, analysis and reporting of the data collected

Each activity is benefited from the development of point applications which ease the process of data collection, reporting and decision making

The recent advancements in mobile technologies and connectivity has enabled the generation and exchange of a lot more data than previously anticipated. However, the lack of interoperability and proper planning to leverage this data, still acts as a roadblock in allowing organizations truly harness their data assets

This document will help life sciences IT professionals and decision makers understand challenges and opportunities around clinical data integration.

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Clinical Trial: Drug Development Lifecycle

Drug Discovery

10,000Compounds

250 Compounds

Pre-Clinical

IND Submitted

Phase I: 20-100

Phase II: 100-500

Phase III: 1000-5000

NDA Submitted

1 FDAApproved Drug

5 Compounds Clinical Trial

Volunteers

FDA Review

Large-Scale ManufacturingPhase IV

5 Years

1.5 Years

6 Years

2 Years

2 Years

A Typical Drug Development Process

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The role of the sponsor is to finance the study of a new drug or a device and provide management of the trial which includes designing the trial, providing materials, collecting data, monitoring the trial and auditing all procedures and data submitted to support the application for approval from the government

The sponsors can be pharmaceutical or biotechnology companies, Government funded agencies like NIH and NCI, hospitals and universities, NGOs, as well as individual or group of physicians

Clinical Trial Participants (1/2)

Sponsor

Clinical Research Associate (CRA)

Acts as an agent of the drug company and monitors how the trial is being conducted at the study sites

Medical Research Associate (MRA)

Functions like a CRA and is in-house at the sponsor’s facility

Medical Monitor

Physician on-call for protocol questions or safety issues

If a sponsor doesn’t have its own staff to handle the administrative work for the trial, it may hire

• Contract Research Organization (CRO) – Serves as a broker or administrator

• Site Management Organization (SMO) – Provides managerial services for a network of sites

Sponsor’s Team

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Principal Investigator (PI) is the most important site staff and the person responsible for conducting the clinical trial at the study site

Sub-investigators assume the responsibility for patient care assessment

Clinical Research Coordinator (CRC) or Study Coordinator is the person in charge of managing the individual study site

Pharmacist (PHA) dispatches the drugs prescribed by the physician along with the study drug dosage to be given at that particular visit

Lab Coordinator (LC) oversees the lab tests as requested by the PI

Clinical Data Manager (CDM), Clinical Data Programmer (CDP), and the data management staff ensure that data is entered, tracked and validated with widely used industry standard software tools and agreed upon database protocols

Clinical Trial Participants (2/2)

Site Staff

Institutional Review Board (IRB) is a committee designated to review the participation of subjects in research studies

An independent Data Safety Monitoring Board (DSMB) may also be included on important trials. It consists of experts in the field and statisticians who inspect the particular treatment under study. The DSMB can recommend changes during the conduct of the trial or may also stop a trial prematurely due to safety concerns.

The Food and Drug Administration (FDA) provides regulatory oversight for the pharmaceutical industry and assures drug quality and safety

RegulatoryBodies

Subjects are volunteers on whom study is conductedSubject

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Clinical Trials: Existing IT Landscape and Challenges (1/4)

Some of the major activities / functional areas where IT systems are used in Clinical Trials are:

Clinical Data Management: For conducting paper-based and electronic trials. The availability ofElectronic Data Capture systems has greatly facilitated the conduct of globally distributed trials

Trial Management Systems: For planning and tracking trials, deadlines and milestones. This is a project management system which is extremely useful in determining optimum trial sites and investigators

Medical Coding Systems: For coding drug names and medical events / adverse events againstindustry standards (MedDRA and WHODrug for instance)

Drug Safety Systems: For recording and reporting adverse events to regulatory bodies per laiddown regulatory framework. Signal Detection Systems are used for monitoring safety profile ofthe marketed medicinal products

Clinical Data Warehouses: Used to data from all R&D systems and analyzing the same. Thesehave emerged recently and are becoming increasingly relevant today

These systems present a paradoxical situation today : It is extremely complex to integrate them, but it’s equally important to achieve this integration.

Role of IT Systems in Clinical Trials

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Clinical Trials: Existing IT Landscape and Challenges (2/4)

Challenges with Information Integration:

IT systems in Life Sciences have evolved over a period of time to address specific business needs. These weren’t built to be interoperable, therefore integrating information isn’t an easy task.

Silos of Information:

Safety and efficacy of a product are the two fundamental parameters used to evaluate the performance of a medicinal product. However, this information is distributed across multiple R&D and RWE systems.

Standalone Approaches:

When faced with a clinical question, often the approach is to build a new system that addresses immediate requirements. RWE is one such example, where the focus is exclusively on using RWD sources for decision making and not much on integrating / mapping RWD sources with those from R&D to build better decision support systems.

Current Challenges faced

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Clinical Trials: Existing IT Landscape and Challenges (3/4)

Stakeholder Engagement:

Clinical systems (like EDC,

CTMS), integrated with

patient ePROs, devices and

mobile apps can connect

patients and physicians

together

Such systems can enhance

trial participation / safety

surveillance, improve RWD

data collection and can

positively influence patient

compliance

Enhanced Decision Support:

R&D and RWE data, when

comprehensively plotted, can

yield tremendous insights

about comparative

effectiveness, true AE profile,

and can aid in arriving at value-

based / outcomes-based

pricing.

It can also help in faster

initiation and conduct of trials

by helping in site identification,

and improving the RBM

framework

Interoperability and Reporting:

A data platform can

support integration and

standardization of data

from multiple sources

This can shorten the time

needed to prepare

regulatory reports, and

enable seamless

integration with different

partner systems, making

concepts like eSourcing

achievable

Need for Integration of Clinical Data across Sources

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Clinical Trials: Existing IT Landscape and Challenges (4/4)

Integrating safety and efficacy data across diverse sources can significantly enhance commercial and clinical decisions; however several challenges prevent this from happening.

Integration of R&D and RWE Sources: Possible Synergies

Safety & Efficacy Data

R&D as well as RWE sources contain this information about a drug. RWD sources present more complexity in analysis, but offer data a much larger subject population.

Value Based Pricing

RWE can bridge the gap between commercial decision making and R&D. It can generate hard evidence for product differentiation and value/outcome based pricing.

Enhance Future Product Research

RWE generates insights into possible, newer indications for an existing product or patient population where the drug is more effective. This allows organizations to repurpose existing drugs or enable personalized medicine.

Improve Operational Efficiencies

RWE can generate insights into the patient population distribution and help identify potential sites, but when mapped with data present in R&D systems, it can make site identification far more reliable.

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Clinical Systems: Challenges with Integrating Data (1/2)

Evolving IT Landscape

Most of the current systems have evolved as point-in-case solutions for a pressing business need, and have developed in features and complexities over the years. The advent of wearable devices, and a need for Patient Reported Outcomes (ePRO) has added a new range of systems and complexities to existing IT landscape

Little Interoperability Built into Systems

While the systems address the reporting to regulatory in a defined, standardized format (e.g., E2B R2/3 formats for safety reporting), not all support interoperability across solution vendors

Evolution of Regulatory Standards

The regulatory standards too, have evolved progressively. This makes them a moving target to adhere to, something which is not supported by all product versions

Data Model Differences

Due to inherent variability in data models for different applications, building integrations across systems is a complex and time consuming exercise

Mergers and Acquisitions in ISV Space

Several large acquisitions (like that of Relsys and Phase Forward by Oracle Corporation) have led to a sudden obsolescence of some products, forcing users to switch to a new application. This requires complex system migration exercise which often lasts for a few years

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Clinical Systems: Challenges with Integrating Data (2/2)

Custom Integration

Legacy / Partner Systems

Integrated System

Regulatory Standards

Report Per Standards

Regulatory Agencies

Custom Integrations, created to link active and legacy / partner systems; programmed to report against existing regulatory standards.

Integration Challenges:

Most organizations adopt a strategy of integrating critical systems, however such integrations usually break as soon as the product versions are upgraded, when the product vendor is switched, or when the regulatory standards evolve

ISVs, on the other hand, build features for regulatory compliance in new product versions. This presents a compliance challenge

Current IT System

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Clinical Systems: Opportunities for a Platform (1/2)

RWE Platform

Multiple DataModel Support

Data Security

Big Data& NLP

Data Exploration/ Discovery

Faster DataIntegration

Scalable and Future Proof

Machine Learning, AI

Reporting and Data Analytics

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Clinical Systems: Opportunities for a Platform (2/2)

Point solutions for integrating data have a limited utility. They are tied to specific data sources and formats, and need a lot of effort to keep up with evolving regulatory standards

On the other hand, a platform with a well defined data model, backed by a metadata based repository to map different systems, can simplify integration efforts

A platform, while being nimble to onboard new sources, also offers quick solutions to assess the relevance and reliability of the data being collected

These are the same aspects which regulatory authorities like FDA consider before evaluating a hypothesis which is backed by integrating data from diverse sources

By its very nature, a platform can be instrumental in letting organizations anonymize their data and share it amongst themselves by onboarding their systems on the platform

Initiatives like i2B2 and ICHOM rely on the same philosophy of enriching a common data lake, which can be a source for better clinical and operational decision making

Availability of standards like FHIR and SDTM have made it relatively simpler to integrate data from sources across R&D and RWD. A platform with data modeling and transformation capabilities can leverage these standards, and facilitate faster integration

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Clinical Systems: Perspective

A platform can benefit organizations by giving it the flexibility to both on-board new data and to conduct deeper analysis on the aggregated data

An ideal step would be to initiate integration of R&D sources, thereby introducing efficiencies in internal, clinical processes (cross trial analysis, improved RBM framework, faster data transformation)

Organizations with mature systems and processes can explore on-boarding newer data sources (real world / partner) and extending the platform to newer users. This can help them explore areas such as comparative effectiveness and determination of true AE profile of a drug

By breaking the data silos, organizations will be able to optimize their clinical, operational as well as commercial decision making, and be in a better position to collaborate with their partners

R&D and Partner Systems

RWE Data Sources

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References

IDC Health Insights, 2009

DIA Conference, 2015

http://www.marketsandmarkets.com

https://www.openclinica.com

http://www.clinovo.com/

http://www.centerwatch.com

http://www.eclinicalsol.com

http://edcmarket.appspot.com

http://www.ppdi.com

https://thenounproject.com

https://commons.wikimedia.org

https://blog.frogslayer.com/building-software-products-vs-platforms/

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Authors:

Narayana Subramanian

Healthcare Business Analyst

Rajat Shukla

Sr. Healthcare Consultant

thoughtleaders@citiustech.com