Download A Clinical Data Review System to Facilitate Pharmaceutical Research

A CLINICAL DATA REVIEW SYSTEM TO FACILITATE
PHARMACEUTICAL RESEARCH
Martin J. Rosenberg, PhD,
MAJARO INFOSYSTEMS,
INC.
trial information, a Clinical Information System or
CIS. The three functions comprising the current
concept of a Clinical Information System are shown
in Figure 1.
ABSTRACT
In an effort to better manage the enormous volume
of information and to reduce the length of time
required to introduce new drugs in the Untted
States, the U.S. Food and Drug Administration and
the pharmaceutical industry have sought to facilttate
the drug development and NDA review processes
through innovative uses of computer technology.
One such effort is the clinical data review system,
sometimes also known as a medical review system.
Clinical data review systems permtt monttors,
CRA's, managers, and other members of the clinical
staff to monttor the progress and outcome of
ongoing clinical trials. They can also serve as an
important step in the development of a computer
assisted NDA or CANDA.
While such systems have long existed within the
pharmaceutical industry, their use has generally
been limited to the data processing, biostatistics,
and programming staffs. Other users who could
benefit from the information stored in the CIS, such
as medical monttors and CRA's have not had direct
access. Such access would be useful to reduce
paperwork, detect and prevent protocol violations,
and provide valuable information for planning future
studies. We call such a system for use by medical
staff, a Clinical Data Review System.
These concepts are depicted through a
demonstration of the CUNACCESSTM clinical data
review system. Originally developed under Version
5.18 of SAS, CUNACCESS has been substantially
enhanced under Version 6.
CLINICAL DATA REVIEW SYSTEMS
Figure 1: Current CIS
Before a new drug can be introduced into the
marketplace, pharmaceutical firms must undertake
a lengthy research process which can frequently
last five or more years. The company collects
Information about the safety of the drug in both
animals and humans; tts efficacy in the diseases to
be treated; the stabiltty of the drug (how long tt can
the
remain on the she~ wtthout degrading);
pharmacokinetics of the drug, i.e., how tt is
metabolized in humans; and the abiltty of the
company to manufacture the drug in production
quanttties.
In an effort to better manage the volume of
information and to reduce the length of time
required to introduce a drug in the United States,
the Food and Drug Administration, in conjunction
wtth the pharmaceutical industry, has been
experimenting wtth ways of using computer
technology to facilttate the NDA review process.
Such a computer system is called a Computer
Assisted NDA Review system or CANDA. At the
joint PMNFDA conference on CANDAs held in
Washington, DC in June 1990, participants in the
CANDA experiments reported that similar systems
would be of use not only by FDA reviewers, but by
the medical staff of pharmaceutical corporations.
This has provided a further impetus for the
development of Clinical Data Review Systems.
As can be imagined from the magnitude of
information that must be collected, computer
systems have long been a part of the drug
development process. We call a computer system
for the collection, retrieval, and analysis of clinical
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Simu~aneously,
CUNAcCESSTM
With the introduction of these three new classes of
users Onvestigators, in-house medical staff, and
FDA reviewers) Mure clinical information systems
will resemble Figure 2. Not every study will require
all the facil~ies of the future CIS's. In particular,
REDEM is likely to be used in selected studies only.
However, pharmaceutical firms will increasingly
expect to have these capabil~ies at their disposal.
CUNACCESS is a Clinical Data Review System
engineered to take advantage of the emerging
features of SAS. Originally written in Version 5.18
SAS/AF ~are for use on IBM mainframes under
e~her the MVS or VM/CMS operating systems
(Rosenberg 1989a and 1989b), CUNACCESS is being
ported to Version 6 SAS software. These new
releases are called CUNACCESS 2.0 for use w~h SAS
Version 6.04 on PC's and CUNACCESS 3.0 for use on
SAS Version 6.06/6.07 platforms such as IBM
mainframes, DEC VI'J( computers, and PC's running
OS/2. CUNACCESS was specifically designed for use
by medical mon~ors, clinical research associates,
managers and other non-trad~ional users on the
clinical staff, as well as the trad~ional CIS users
(data processing, clinical programming, and
biostatistics). As can be seen from the Main Menu
(Figure 3), CUNACCESS 2.0 has the following
capabil~ies: single or double-key data entry; viewing
and querying of data; graphics; descriptive
statistics; and report generation.
CUNAcCESS
features an extensive context sensitive help system
and an on-line tutorial to aid the new or infrequent
user.
there has been much interest in
computer systems that perm~ the investigator to
enter data and the sponsor to remotely mon~or the
trial. The intent of such systems is to collect more
timely and accurate information. We call such
systems Remote Data Entry and Mon~oring systems
orREDEM.
CUNACCESS
Database
Administrators
are
permitted to structure new datasets,
paint data entry screens, manage study libraries,
and add new users. To protect the integrity of the
data, only users specifically identHied as Database
Administrators have these additional capabilities.
add~ionally
REMOTE DATA ENTRY
AND MONITORING
A key feature of CUNAcCESS is its data dictionary
which is called the Clinical Questions Catalog
(CQC). The Clinical Questions Catalog ensures
uniformity of variables across studies, facil~ating the
pooling of information. It also Simplifies the study
definition process. A list of CUNAcCESS features and
capabil~ies follows.
Use by investigators
1
DATA
MANAGEMENT
I
STATI STI CAL
ANALYSIS
I
AUTOMATED
TABLE AND GRAPH
GENERATION
CLINICAL DATA
REVIEW
CUNAcCESS™ 2.0 Features
Menu-driven
Extensive context sensitive help system
On-line tutorial to aid the new or infrequent
user
Clinical Questions Catalog (data dictionary)
ensures uniformity of variables across
studies, facilitating the pooling of information
Data Administrator's Manual
Use by in-house
medical staff I
I
CANDA
Use by FDA Reviewers
Figure 2: Future CIS
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IN
~NIU-------------------------------
Select Option ===>
eli
n
Ace • • •
('m)
______________--,
II
Enter data
5
Descriptive statistics
2
View data
6
Written reports
3
Rearrange data
7
Leann to use ClinAccess
4
Graphics
8
Exit ClinAccess
level 1 (Main Menu)
Fl
ENTER
HELP
to select
Figure 3: The CUNAccESS 2.0 Main Menu
CUNACCESS™ 2.0 Capabilities
Data Entry
Single or double-key with written
verification report
Interactive range and value checks
Browse data
View and query data in case report form
format
View data in table format
Data Management
Concatenate and merge datasets
Boolean logic queries and subsetting
Select subset of variables from a list
Compute new variables from existing
variables
Retain temporary datasets
Graphics
Printer plots and high resolution color
graphics
Horizontal and vertical bar charts, block
charts, pie charts, scatter diagrams, line
charts (requires SAS/GRAPH)
Descriptive Statistics
Standard statistics for quant~ative data:
mean, standard deviation, variance,
standard error of the mean, minimum,
maximum, sample size, range, sum,
coefficient of variation
Advanced statistics for quant~ative data:
useful for visualizing and summarizing the
shape of the distribution
Cross-tabulations:
frequencies and
percentages for categorical data. Chisquare and Fisher's exact tests.
Report Generation
Customized data listings with optional
column sums
Hierarchical tables of descriptive statistics
Study Defin~ion
Restricted to Database Administrator
Structure new datasets from Clinical
Questions Catalog or from previous
studies
Data entry screens can be customized to
resemble Case Report Forms
Post-processing facility to pelform edit
checks or restructure data
Data dictionary reports
Manage study libraries
An Example
These concepts will be illustrated by an example of
data entry and clinical data review.
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Data Entry Example
standardization, the label, informat, and format may
be customized to the study, while the name, type,
and length of the variable are fixed.
CLiNAccESS 2.0 is designed as an integrated PC
based clinical intormation system, which is
distinguished from other such systems by ~s strong
clinical data review component.
The second method recognizes the fact, that
pharmaceutical firms frequently run similar trials on
a compound. To accommodate this, a table may be
created from a previous study which is similar to the
new study. The two studies need not be identical
as variables may be added and deleted from the
defin~ion.
To maintain consistency, CLiNAccESS
automatically checks to make sure that any variable
which is added is defined in the Clinical Questions
Catalog. The final step in defining a new table is to
specify the primary key. The primary key is the
variable or variables which uniquely identify each
record in the table. This primary key is stored in the
data dictionary and simplifies use of the data review
components of the system by non-traditional users.
The data entry component of CLiNACCESS 2.0
consists of study defin~ion, data entry with on-line
ed~ checking, data verification, and post-entry data
validation.
One or more users are identHied to CLiNAccESS as
Database Administrators (DBA). To protect the
integrity of tile data, only the DBA's have access to
a subsystem of CLiNAcCESS which is used to: create
study libraries, define new studies to the system,
manage existing studies, verify and validate data,
update the Clinical Questions Catalog, and add new
users to the system.
Once the tables are defined, screens can be
customized to resemble case report forms, and
powerful cross field ed~ checks and computations
can be performed during data entry. For example,
to increase accuracy, clinical trial protocols often
require blood pressure to be measured three times
at each reading and the average used as the
response. As shown in Figure 4, the data entry
operator can enter the three sets of blood pressures
and the mean will be accurately computed and
stored in the dataset, available for immediate
analysis.
To define a new study to the system, the DBA first
creates a study library. Then one or more tables are
CLiNAcCESS was
created to hold the data
specifically designed to facil~ate the pharmaceutical
industry's need to create data entry applications
rapidly. To meet this need, tables can be defined in
two ways. First, the table can be created from the
Clinical Questions Catalog by merely selecting the
names of variables to be included from a list. All
defining information such as variable type, length,
label, format, and informat are automatically
included.
To provide ftexibil~ while enforcing
FSEDIT S 2 7 4 . E F F I C A C Y - - - - - - - - - - - - - - - - - - - - - ,
Conmand ===>
Obs
1
Screen 6
STUDY #: 274
STUDY: Curitol in Chronic Disease
CENTER: S.F. GENERAL
PATIENT IDENTIFICATION
INITIALS
10 NUMBER
MJR
274-061
TEMPERATURE and RESPIRATION
TEMPERATURE (Fl:
98.7
RESPIRATION:
14
SITTING BLOOD PRESSURE and PULSE
Reading #1 119 I
Reading #2 120 I
Reading #3 121 I
Pulse:
79
SO
81
AVERAGE READING: 120 I
SO
n
GO TO:
Previous screen
ADVERSE EVENTS DATA:
Figure 4: Cross-field ed~ and computations can be performed during data entry
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Data can optionally be entered a second time
(double-key entry) and a verification report run to
detect key stroke errors.
study (Figure 5). The operation is completely point
and shoot. The user merely pos~ions the cursor on
the study name and presses enter to make the
selection. The user is presented mh a list of data
available to be viewed in the study and similarly
makes a choice. The data is a presented in a format
resembling a Case Report Form so that it will be
familiar to the reviewer (Figure 6). The reviewer can
browse the data and perform queries.
Finally, the DBA can use the complete power of the
SAS system's DATA and PROC steps to create data
validation programs which can be customized for
each study and run from a menu option.
Next the monitor would like a listing of the data, so
that she can discuss the data with the investigator
on the next site visit. She selects the Reports option
on the Main Menu and chooses a Data Usting
CLiNACCESS
Report from the Reports menu.
remembers which study is being reviewed, so that
there is no need to select the same study again.
The user selects which variables will be included in
the report in the order they are to appear from a list
of variables which includes variable descriptions
Once again the variable selection
(Figure 7).
process is point and shoot. The report is displayed
on the screen and can be printed via a menu option
(Figure 8).
Clinical Data Review Example
CLiNAccESS 2.0's strength continues to be the ease
which data can be accessed and manipulated.
To illustrate this, let's take an example of how
CLiNAcCESS, can assist w~h reviewing laboratory
data. The user will view the laboratory data, create
a report displaying the data to take along on a s~e
visit, and then generate another report which
examines the trends in a specific lab test over the
course of the study.
w~h
Throughout this process, data integrity is constantly
maintained. With the exception of the data entry
options, no CLiNAcCESS function changes data in
the underlying database. All data manipulation,
such as selecting subsets of patients, is performed
on copies of the data and stored in the user's
personal library.
Finally there is some concern that similar
compounds have caused an decline in White Blood
Cell counts. The user selects the Descriptive
Statistics report option from the Reports menu.
Then the user selects the variable WBC for analysis,
chooses statistics to compute from a list, and
requests that the statistics be computed for each
treatment group and at each visit. The report is
shown in Figure 9 and indicates that there may
indeed be some cause for concern about
decreased white blood cell counts. The reviewer
can then discuss performing some definitive tests
with a biostatistician.
To begin, the user selects the view data option from
the Main Menu (Figure 3). The user is given a
choice of viewing data in Case Report Form or
Table formats and decides to view the data in CRF
format. The user then selects a study from a list of
studies. For clarity, the list includes the study name
or number and a brief description of the
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lNSTRUCTIONS FOR SELECTING A STUOY
r
Please select a STUDY.
Position the cursor on your choice and press ENTER.
~ELECT
A STUOY
COBIRand ===>
CANCEl
PageUp
PageDown
F1 = KELP
Select one study.
CUROO1
CUR002
CUR003
CUR004
TC1-01
Curitol vs Placebo in hypertension
Curitol vs Placebo in angina
curitol vs Active in angina
Curitol vs Active in MI
TC942 in Rheunato'id Arthritis (open label)
F8
CANCEL
F10
SUBMIT
Figure 5: The user selects a study from a list which includes
the study name or number and a brief description.
FSBRO~SE
Conmand
CUR002.DEM'QG.----------------------,
===>
Obs
1
Screen
STUOY #: CUR002
STUDY:
CUritoL in Chronic Disease
TREATMENT GROUP: Curitol
PATIENT ID #:
INVESTIGATOR:
VISIT:
4
101
J. Schwartz
1
LABORATORY ANALYSES
B. BLOOO CHEMISTRY
Test
1 of
Units
Phosphorus
Alkaline Phosphatase
Bilirubin - Total
SGOT
Uric Acid
LDK
Potassium
ChLoride
Glucose - Fasting
BUN
BUN
F5=PREV LAB
F6=NEXT LAB
5)
Value
mg/dl
..../ml
mg/dl
..../ml
mg/dl
..../dl
4
65
mEqil
mEq/L
mg/dl
mg/dl
mg/dl
F7=HEMATOLOGY
1
39
6
139
4
102
87
15
15
F10=END
Figure 6: User can browse data in a familiar Case Report Form format
964
rOATA LISTING r8ELECT VARIABLE
CORmand ===> Conmand ==>
Select variables to be included in the report.
OK
CANCEL PageUp PageOown CLEAR
,---- DRUG AGE SEX HCT HGB
f--
Cho
X
----=
Spe
=>
=>
=>
~C
RBC PLATELET
NAME
DESCRIPTION
URICAClD
Uric Acid
Hematocrit
Hemoglobin
White Blood Cells
HCT
HGB
wac
=> Rat
=> PLATELET
Fl = HELP
Red Blood Cells
Platelets
N
~
Fl
HelP
Figure 7: User selects variables to be included in the report
Hematology Data
Study CUR002
Patient
10
Visit
Number
Number
Treatment
Sex
2
3
4
5
Curitol
Curitol
Curitol
Curitol
Curitol
Male
Male
Male
Male
101
102
103
1
2
3
4
5
PLacebo
Placebo
Placebo
1
2
3
4
5
Curitol
Curitol
Curitol
Placebo
Placebo
CuritoL
Curitol
Hematocrit
Hemoglobin
",hite
Red
Blood
Cells
BLood
Cells
Platelets
45
54
53
45
53
15.9
15.4
16.0
16.0
15.B
3.1
6.5
6.5
5.5
8.5
4.9
5.6
6.2
5.2
5.3
390
190
130
330
300
Male
Male
Male
46
47
56
45
59
17.7
17.0
17.2
16.8
15.5
9.4
7.5
8.1
8.0
9.0
5.4
4.7
5.4
5.1
5.2
350
250
360
180
260
Male
Male
Male
Male
Hale
52
45
49
56
54
14.7
16.2
15.9
16.5
14.6
8.5
7.3
6.7
3.7
7.4
5.7
5.5
5.3
4.7
5.2
180
360
320
160
300
Male
Male
Male
Source:
ClinAccess(tm)
MJR
February 18. 1991
Figure 8: A Data Listing Report Produced by CLiNAcCESS
965
Trends in White Blood Cell Counts
Study CUR002
NUJi>er
Mean
Maxinun
Mini .......
Yhite Blood Yhite Blood White Blood
Cells
Cells
Cells
White Blood
Cells
Treatment
Visit Nlri>er
Curitol
1
100
7.12
3.30
10.70
2
100
6.88
3.10
11.40
3
100
6.01
3.30
10.30
4
100
5.53
3.50
10.40
5
100
5.50
2.30
9.90
1
100
7.07
2.20
10.90
2
100
6.95
3.20
10.50
3
100
6.89
2.60
11.40
4
100
6.85
3.40
10.00
5
100
6.97
2.30
11.20
Placebo
Source:
ClinAccess(tm)
MJR
February 18. 1991
Figure 9: Report Showing Trends in White Blood Cell Count
SUMMARY
Looking Ahead: CUNAccEssTM 3.0
As the role of the Clinical Information System
expands to encompass non-traditional users such
as investigators, medical monitors, CRA's, and FDA
reviewers, pharmaceutical companies are faced
with an increasingly complex web of technology. In
an effort to simplify the process, we might look for
ways to integrate the various CIS processes. One
way to do this is to explore existing standards in an
effort to expand their use and leverage the investment already made in training personnel and
incorporating the technology.
In 1990, SAS Institute introduced a new generation
of the SAS System, Version 6.06. This release adds
many capabilities, such as indexing and SOL,
usually associated with relational databases.
Additionally, the introduction of muttiple engine
archhecture permits applications written with SAS
software to directly access data stored in such
popular databases as Oracle and IBM's DB2.
Further details of these new capabilities are
described in Rosenberg 1990.
SAS software is the de facto standard in the
pharmaceutical industry for performing statistical
analyses and presenting the resutts in graphical or
tabular forms. Once data is in machine readable
form, most of the subsequent processing is typically
performed in SAS. Consequently, it is reasonable to
examine whether SAS can play an expanded role in
the CIS.
Work is underway to exploit these new capabilities
with a new CLiNAcCESS release currently scheduled
to be available in 1991 on IBM mainframes, DEC
VPIX computers, and OS/2. This new release will
feature an improved user interface which adopts
many of the features such as pull-down menus,
dialog boxes, and scroll bars which have been so
successful in opening up computing to whole new
classes of users.
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ACKNOWLEDGEMENTS
The CUNAccESS™ clinical data review system,
developed entirely w~h SAS software, is designed to
provide mon~ors, CRA's, and other non-trad~ional
users ~h access to the information stored in
clinical databases. CUNACCESS provides: single or
double-key data entry; viewing and querying of
data; graphics; descriptive statistics; and report
CUNACCESS is available on IBM
generation.
mainframes running Version 5.18 of the SAS system
under MVS or VMJCMS and will soon be available
on PC compatibles under SAS Version 6.04. These
releases require the base SAS product, SAS/FSP,
and SAS/GRAPH software. An enhanced release of
CUNACCESS for used wnh Version 6.06/6.07 SAS
software on IBM mainframes, DEC VAA computers,
and PC's running OS/2 is under development.
CUNACCESS is
a trademark of MAJARO
INFoSYSTEMS, INC., Mountain View, CA, USA
All CUNACCESS screens shown are Copyrighted (C)
1988-1991 by MAJARO INFoSYSTEMS, INC. and are
used by permission.
SAS, SAS/AF, SAS/FSP, and SAS/GRAPH are the
registered trademarks of SAS Insmute Inc., Cary,
NC.
Other products are the trademarks or registered
trademarks of their respective owners.
For a number of years now, we've wnnessed the
evolution of SAS software into a product with
greater interactivny data management capabilnies.
Version 6 is a major step in that evolution.
Companies that start now to explon these new
capabilnies through systems such as CUNACCESS,
have the potential of realizing substantial
advantages over their competnors in terms of
reducing the cost and time needed to bring a new
drug to the market.
REFERENCES
MAJARO INFoSVSTEMS, INC. provides statistical
and information management services to the
pharmaceutical, biotechnology, and food products industries, and specializes in extending
computer technology to non-traditional users.
Rosenberg, Martin J.
(1990).
Constructing
Integrated Clinical Information Systems for
Tradnional and Nontraditional Users. Proceedings of
the Fifteenth Annual SAS Users Group International
Conference. SAS Institute Inc., Cary, NC. pp. 10271032.
For further information regarding this paper,
please contact:
Rosenberg, Martin J.
(1989a).
An Integrated
Approach to Computer Systems for NDA
Preparation and Presentation. Proceedings of the
Fourteenth Annual SAS Users Group International
Conference. SAS Institute Inc., Cary, NC. pp. 786792.
Martin J. Rosenberg, Ph.D.
MAJARO INFoSYSTEMS, INC.
99 East Middlefield Road
Suite 31
Mountain View, CA 94043
tel. (415) 961-8432
(415) 961-9260
Rosenberg, Martin J. (1989b). Integrated Clinical
Information Systems for Traditional and NonTraditional Users. Proceedings of the Second Annual
Regional Conference of the NorthEast SAS Users Group.
SAS Institute Inc., Cary, NC. pp. 21-28.
Rosenberg, Martin J. (1988).
Using the SAS
System to Facilitate Clinical Trials Research and
NDA Approval. Proceedings of the Thirteenth Annual
SAS Users Group International Conference.
SAS
Institute Inc., Cary, NC. pp.550-556.
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