UD01:

Improving medical research and related healthcare through

standardization

Jennie Mc Guirk October 2013

University Day

$800-900 MILLION

Drug Development Life Cycle

8-12 YEARS

1 IN 5 REACH MARKET

Inception

Market

Drug Development and Clinical Trials

Preclinical - Does the drug have merit? Phase I ‒ Is the drug safe for humans? Phase II ‒ does the drug have a therapeutic effect? Phase III ‒ is the effect valuable? Phase IV ‒ post marketing follow-up, any long term effects?

Clinical Trials Process Flow

Protocol Approval

Investigator Selection

Patient Recruitment & Participation Data Collected

& Reviewed

Presentation & Publication of results

Data filed & Registration Obtained / Rejected

Statistical analysis

$800-900 MILLION

Why do we need to standardize?

8-12 YEARS

1 IN 5 REACH MARKET

TIME

COST

How are we standardizing??

CDISC Est 1997

To improve and standardize the way clinical data is acquired and exchanged

“The CDISC mission is to develop and support global, platform-independent

data standards that enable information system interoperability to improve medical research and related areas of healthcare.”

CDISC Goals and Strategies

Goals Strategies

CDISC Models and Initiatives

Provide End to End standardisation

The Protocol

•  Protocol -> Key document; Plan or blueprint of the trial; Describes trial objectives, methods, analysis, organization

•  PRG : Standardize the structure & content of the protocol •  Reduced protocol development and review time •  Increased end-user awareness / understanding •  Can consume the information electronically & leverage the

information downstream

The Database

•  Database -> subject (case) database, referred to as the Electronic Case Report Form (eCRF)

•  CDASH – standardizes data collection •  Reduced database development and review time •  Increased efficiencies for data cleaning •  Increased end-user familiarity / reduce system training time •  Data extracted from the database is a consistent structure

The Analysis

•  Analysis -> Data Extracted from the Database (SAS datasets) •  SDTM – data model used to represent the data collected (also

referred to as the Case Report Tabulation (CRT)) •  ADAM – data model used to represent the analysis data •  Increased efficiencies for data analysis •  Increased end-user familiarity / reduces review time •  Enable standard programming

The Interchange

•  Interchange -> Provision of data to the regulatory body (e.g. FDA) for review/approval

•  CRT-DDS - standard way of packaging the data; standard way of defining the data (SDTM + ADAM)

•  One mechanism of data exchange •  Increased end-user familiarity •  Increased efficiencies for data and analysis review

CDISC Models and Initiatives

eCRF page example

PROT STUDY STUDNUM STUDYID

CDISC SDTM

Study Data Tabulation Model

SDTM Implementation

Guide

SDTM Framework

1. Where should the data go?

2. What type of information should

it contain?

3. What is the minimum information needed?

SDTM Framework: General Observation Class

Interventions

Treatments that are administered to the

subject

Conmeds (CM)

Exposure (EX)

Events Planned protocol

milestones, occurrences,

conditions, or incidents

Adverse Events (AE)

Disposition Events (DS)

Findings

Observations resulting from planned evaluations

Vital Signs (VS)

Physical Exam (PE)

1. Where should the data go?

SDTM Fundamentals: Other Data Classes

Special Purpose

Demographics (DM)

Comments (CO)

Subject Visits Subject Elements

(SV and SE)

Relationship

Related Records (RELREC)

Supplemental Qualifiers (SUPP--)

Trial Design

Trial Summary (TS)

Trial Inclusion (TI)

Trial Visits (TV)

SDTM Framework: Variable Roles

Identifier

Variables used to

identify the record

Study Identifier (STUDYID)

Subject Identifier (USUBJID)

Sequence Identifier (--SEQ)

Topic

Specifies the focus of the observation

Lab Test Name (LBTEST)

Adverse Event Term (AETERM)

Reported Drug Name (CMTRT)

Timing

Timing of the observation

Lab Assessment Date (LBDTC)

Adverse Event Start Date

(AESTDTC)

Exposure End date (EXENDTC)

Qualifier

Values that describe the

results or traits of the observation

Lab Test Result (LBORRES)

Adverse Event Severity (AESEV)

Conmed Dose (CMDOSE)

2. What type of information should

it contain?

SDTM Framework: Core Variables

Required

Basic to the identification of a data record

Must always be present

Cannot be null

Expected

Establish the observation

context

Must always be present

Can be null

Permissible

Present if collected or

derived

Must be present if collected

Can be null or excluded

3. What is the minimum information needed?

SDTM Framework:

Data Class General Observation

Special Purpose

Relationship

Trail Design

Variable Role Identifier

Topic

Timing

Qualifier

Core Variables

Required

Expected

Permissible

For a more detailed introduction to SDTM visit the PhUSE website…

http://www.phusewiki.org/docs/2012/PAPERS/IS/IS04.pdf

and/or attend my presentation today at 4 p.m !!

SDTM Implementation Creating a Mapping

1. Determine the Data

Class

2. Identify Required Variables

3. Identify Expected Variables

4. Identify applicable

Permissible Variables

5. Identify Relationship

Variables

SDTM Implementation Example

1. Determine Data Class

Findings

2. Identify Required Variables

STUDYID

DOMAIN = ‘LB USUBJID

LBSEQ = Derived

LBTESTCD

LBTEST

3. Identify Expected Variables

LBCAT

LBORRES LBORRESU

VISITNUM

LBDTC

Derived

4. Identify Permissible Variables

LBSPID

LBNAM

5. Identify Relationship Variables

LBADD in SUPPLB

LBCLSIG = N in SUPPLB LBCLSIG = Y in SUPPLB

CDISC – Summary

•  improve data exchange •  improve study efficiency

•  improve data quality

•  reduce burden of regulatory submissions

•  improve speed of approval

•  reduce cost of data transfer

•  reduce ost of the drug development life cycle

•  lack of understanding of the standards

•  cost of implementing

•  existing standard do not cover all types of data

•  lack of FDA or other regulatory authority regulation

•  standards change/evolve over time

•  concern about the longevity of the CDISC standards

Benefits Challenges

Some References and Terminology Index

http://www.cdisc.org/ http://www.phuse.eu/

http://www.cdisc.org/stuff/contentmgr/files/0/fdf8540f5324c81f48d3630923b95fd6/misc/

cdisc_journal_friggle_etal_p2.pdf

Questions