A CLINICAL DATA REVIEW SYSTEM TO FACILITATE PHARMACEUTICAL RESEARCH

Transcription

1 A CLINICAL DATA REVIEW SYSTEM TO FACILITATE PHARMACEUTICAL RESEARCH Martin J. Rosenberg, PhD, MAJARO INFOSYSTEMS, INC. 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. 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. 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 CUNACCESS TM clinical data review system. Originally developed under Version 5.18 of SAS, CUNACCESS has been substantially enhanced under Version 6. CLINICAL DATA REVIEW SYSTEMS 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 remain on the she~ wtthout degrading); the 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. 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 Figure 1: Current CIS 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. 959

2 Simu~aneously, 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. 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. REMOTE DATA ENTRY AND MONITORING Use by investigators 1 DATA MANAGEMENT I STA TI STI CAL ANALYSIS I AUTOMATED TABLE AND GRAPH GENERATION I CANDA Use by FDA Reviewers Figure 2: Future CIS CLINICAL DATA REVIEW Use by in-house medical staff I CUNAcCESSTM 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 V I'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. CUNACCESS Database Administrators are add~ionally 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. 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. 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 960

3 IN ~NIU , Select Option ===> eli n Ace ('m) II Enter data 2 View data 3 Rearrange data 4 Graphics 5 Descriptive statistics 6 Written reports 7 Leann to use ClinAccess 8 Exit ClinAccess level 1 (Main Menu) Fl HELP ENTER 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. 961

4 Data Entry Example 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 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. To define a new study to the system, the DBA first creates a study library. Then one or more tables are created to hold the data CLiNAcCESS was 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 standardization, the label, informat, and format may be customized to the study, while the name, type, and length of the variable are fixed. 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. 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. FSEDIT S274.EFFICACY , Conmand ===> Obs 1 Screen 6 STUDY #: 274 STUDY: Curitol in Chronic Disease CENTER: S.F. GENERAL PATIENT IDENTIFICATION INITIALS 10 NUMBER MJR TEMPERATURE and RESPIRATION TEMPERATURE (Fl: 98.7 RESPIRATION: 14 SITTING BLOOD PRESSURE and PULSE Reading #1 119 I 79 Reading #2 120 I SO Reading #3 121 I 81 Pulse: n AVERAGE READING: 120 I SO GO TO: Previous screen ADVERSE EVENTS DATA: Figure 4: Cross-field ed~ and computations can be performed during data entry 962

5 Data can optionally be entered a second time (double-key entry) and a verification report run to detect key stroke errors. 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. 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. Clinical Data Review Example CLiNAccESS 2.0's strength continues to be the ease w~h 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. 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. 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 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 Report from the Reports menu. CLiNACCESS 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 (Figure 7). Once again the variable selection process is point and shoot. The report is displayed on the screen and can be printed via a menu option (Figure 8). 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. 963

6 r lnstructions FOR SELECTING A STUOY 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 CUR002.DEM'QG , Conmand ===> Obs 1 Screen 4 STUOY #: CUR002 PATIENT ID #: 101 STUDY: CUritoL in Chronic Disease INVESTIGATOR: J. Schwartz TREATMENT GROUP: Curitol VISIT: 1 LABORATORY ANALYSES B. BLOOO CHEMISTRY 1 of 5) Test Units Value BUN F5=PREV LAB Phosphorus Alkaline Phosphatase Bilirubin - Total SGOT Uric Acid LDK Potassium ChLoride Glucose - Fasting BUN F6=NEXT LAB... /ml... /ml... /dl meqil meq/l F7=HEMATOLOGY F10=END Figure 6: User can browse data in a familiar Case Report Form format 964

7 roata LISTING r8elect VARIABLE CORmand ===> Conmand ==> Select variables to be included in the report. OK CANCEL PageUp PageOown CLEAR Fl = HELP,---- DRUG AGE SEX HCT HGB ~C RBC PLATELET NAME DESCRIPTION URICAClD Uric Acid f-- => HCT Hematocrit Cho => HGB Hemoglobin X => wac White Blood Cells => Rat Red Blood Cells ----= => PLATELET Platelets Spe N ~ Fl HelP Figure 7: User selects variables to be included in the report Hematology Data Study CUR002 Patient ",hite Red 10 Visit Blood BLood Number Number Treatment Sex Hematocrit Hemoglobin Cells Cells Platelets 101 Curitol Male Curitol Male Curitol Male Curitol Male Curitol Male B PLacebo Male Placebo Male Placebo Male Placebo Male Placebo Male Curitol Male Curitol Male Curitol Male CuritoL Male Curitol Hale Source: ClinAccess(tm) MJR February Figure 8: A Data Listing Report Produced by CLiNAcCESS 965

8 Trends in White Blood Cell Counts Study CUR002 Treatment Visit Nlri>er NUJi>er Mean Mini... Maxinun Yhite Blood Yhite Blood White Blood White Blood Cells Cells Cells Cells Curitol Placebo Source: ClinAccess(tm) MJR February Figure 9: Report Showing Trends in White Blood Cell Count Looking Ahead: CUNAccEssTM 3.0 In 1990, SAS Institute introduced a new generation of the SAS System, Version 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 Work is underway to exploit these new capabilities with a new CLiNAcCESS release currently scheduled to be available in 1991 on IBM mainframes, DEC V PIX 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. SUMMARY 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. 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. 966

9 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 generation. CUNACCESS is available on IBM mainframes running Version 5.18 of the SAS system under MVS or VMJCMS and will soon be available on PC compatibles under SAS Version 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. ACKNOWLEDGEMENTS CUNACCESS is a trademark of MAJARO INFoSYSTEMS, INC., Mountain View, CA, USA All CUNACCESS screens shown are Copyrighted (C) 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 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 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 Rosenberg, Martin J. (1989b). Integrated Clinical Information Systems for Traditional and Non Traditional Users. Proceedings of the Second Annual Regional Conference of the NorthEast SAS Users Group. SAS Institute Inc., Cary, NC. pp 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. For further information regarding this paper, please contact: Martin J. Rosenberg, Ph.D. MAJARO INFoSYSTEMS, INC. 99 East Middlefield Road Suite 31 Mountain View, CA tel. (415) (415) 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