Tag Archives: annotated study book

Introduction to Clinical Trials

Video introducing cancer clinical trials and their use in clinical practice guidelines

“Copyright Disclaimer Under Section 107 of the Copyright Act 1976, allowance is made for “fair use” for purposes such as criticism, comment, news reporting, teaching, scholarship, and research. Fair use is a use permitted by copyright statute that might otherwise be infringing. Non-profit, educational or personal use tips the balance in favor of fair use.”

Source: Cancer Guidelines – Canada

Standard Naming Conventions for InForm Trials

This document is intended to provide a common set of rules to apply to the naming of clinical trials build using InForm EDC system.

Why use naming conventions?

Naming objects consistently, logically and in a predictable way will distinguish similar records from one another at a glance, and by doing so will facilitate the storage and retrieval of records, which will enable users to browse clinical objects more effectively and efficiently. Naming records according to agreed conventions should also make object naming easier for colleagues because they will not have to ‘re-think’ the process each time.

It has been said that InForm follows the “Hungarian” notation because it is one of Microsoft’s “Best Practices” for .Net standards when defining objects (the code to support those objects use it).

Component Prefix
Form (e.g., frmDemo…) frm
Section sct
Itemset its
Radio Control rdc
Item itm
Pulldown Control pdc
Text box txt
Date and time dtm
Group Control grp
Checkbox chk
Calculated Control cal
Simples smp
Study Element elm
Codelist cl
Study Event evt
Codelist Item citm
Workflow Rule wr
Global Conditions gc
Data Entry Rules (e.g., rulDMConsDTCompare) rul
DataType Prefix
Boolean bln
Byte byt
Character chr
Date dtm
Decimal dec
Double Precision dbl
Integer int
Long Integer lng
Object obj
Short Integer sht
Single Precision sng
String str
User-defined Type udt
Object Prefix
Button btn
CheckBox chk
ComboBox cbo
Control ctr
DataSet ds
DataTable dt
Form frm
GroupBox grp
Label lbl
ListBox lst
PictureBox pic
RadioButton rdb
String str
TextBox txt

Remember keep it consistent. This means that you stick to one particular pattern through out your clinical project. This also includes the words you use for namespaces, classes, methods, interfaces, properties and variables. A prerequisite is that they should be meaningful, significant, descriptive and easily understood with respect to purpose and functionality by anyone who reads the source code.

Happy Programming!

Anayansi Gamboa has an extensive background in clinical data management as well as experience with different EDC systems including Oracle InForm, InForm Architect, Central Designer, CIS, Clintrial, Medidata Rave, Central Coding, OpenClinica Open Source and Oracle Clinical.

The Next Best Thing – Timaeus Trial Builder?

First of all, let me clarify by saying that I am not an expert when it comes to Timaeus. I recently came across this EDC tool while working on a project. We were testing out different EDC applications as part of their new infrastructure solution.

At first, I was hesitant to learn about it. All I knew was that you need it to know ‘Python’. The main programming language for their edit checks/validations and back-end structure but after my first encounter with the tool, I changed my mind. This is one of the easiest tool to use and deploy your clinical study you can find in the market, nowadays.

With that being said, What is Timaeus? This another EDC tool, trial builder application provided by Cmed Technology www.cmedresearch.com which helps build eCRF (data entry screens), edit checks/validations, external loading data and other config files.

In order to grasp this new tool, you will need to familiarize yourself with other technologies such as HTML, XML, Emacs, SVN, Python and the like and understand the TMPL element concept.

TMPL stands for “Timaeus Markup Language”. It has a bit of pieces of codes similar to what you see in HTML or XML files.

Even though the system is lacking of front-end features we are so used to in comparison with similar EDC solutions, nevertheless, this tool gets my thumps up for ease of use, cost-effectiveness, change control capabilities and one of the most robust security systems to capture electronic records as per CFR11 regulations.

A New Way to Collect Data – CDASH

There is a general consensus that the old paper-based data management tools and processes were inefficient and should be optimized. Electronic Data Capture has transformed the process of clinical trials data collection from a paper-based Case Report Form (CRF) process (paper-based) to an electronic-based CRF process (edc process).

In an attempt to optimize the process of collecting and cleaning clinical data, the Clinical Data Interchange Standards Consortium (CDISC), has developed standards that span the research spectrum from preclinical through postmarketing studies, including regulatory submission. These standards primarily focus on definitions of electronic data, the mechanisms for transmitting them, and, to a limited degree, related documents, such as the protocol.

Clinical Data Acquisition Standards Harmonization (CDASH)

The newest CDISC standard, and the one that will have the most visible impact on investigative sites and data managers, is Clinical Data Acquisition Standards Harmonization (CDASH).

As its name suggests, CDASH defines the data in paper and electronic CRFs.

Although it is compatible with CDISC’s standard for regulatory submission (SDTM), CDASH is optimized for data captured from subject visits, so some mapping between the standards is required. In addition to standardizing questions, CDASH also references CDISC’s Controlled Terminology standard, a compilation of code lists that allows answers to be standardized as well.

Example: Demographics (DM)

Description/definition variable name Format
Date of Birth* BRTHDTC dd MMM yyyy
Sex** SEX $2
Race RACE 2
Country COUNTRY $3

*CDASH recommends collecting the complete date of birth, but recognizes that in some cases only BIRTHYR and BIRTHMO are feasible.

* *This document lists four options for the collection of Sex: Male, Female, Unknown and Undifferentiated (M|F|U|UN). CDASH allows for a subset of these codelists to be used, and it is typical to only add the options for Male or Female.

The common variables: STUDYID, SITEID or SITENO, SUBJID, USUBJID, and INVID that are all SDTM variables with the exception of SITEID which can be used to collect a Site ID for a particular study, then mapped to SITEID for SDTM.

Common timing variables are VISIT, VISITNUM, VISDAT and VISTIM where VISDAT and VISTIM are mapped to the SDTM –DTM variable.

Note: Certain variables are populated using the Controlled Terminology approach. The COUNTRY codes are populated using ISO3166 standards codes from country code list. This is typically not collected but populated using controlled terminology.

Each variable is defined as:

  • Highly Recommended: A data collection field that should be on the CRF (e.g., a regulatory requirement).
  • Recommended/Conditional: A data collection field that should be collected on the CRF for specific cases or to address TA requirements (may be recorded elsewhere in the CRF or from other data collection sources).
  • Optional: A data collection field that is available for use if needed

The CDASH and CDICS specifications are available on the CDICS website free of charge. There are several tool available to help you during the mapping process from CDASH to SDTM. For example, you could use Base SAS, SDTM-ETL or CDISC Express to easily map clinical data to SDTM.

In general you need to know CDISC standards and have a good knowledge of data collection, processing and analysis.

With the shift in focus of data entry, getting everyone comfortable with using a particular EDC system is a critical task for study sponsors looking to help improve the inefficiencies of the clinical trial data collection process. Certainly the tools are available that can be used to help clinical trial personnel adapt to new processes and enjoy better productivity.

Anayansi Gamboa has an extensive background in clinical data management as well as experience with different EDC systems including Oracle InForm, InForm Architect, Central Designer, CIS, Clintrial, Medidata Rave, Central Coding, OpenClinica Open Source and Oracle Clinical.

Central Designer aCRF Generation

aCRF casebook ;- PDF file

1. Project Explorer – click on the 2nd level study name

2. File ->; Annotated Study Book Options

3. Uncheck Time and Events table

4. Uncheck Study Object Description Tables
5. Change date variable format to match eCRF ;map, setting is not noted on aCRF output

6. File ->; View Annotated Study Book

7. Pop up screen, click Print in lower right

8. Select Printer – Adobe PDF (single click)
9. Click Preferences

10. Click on Layout tab
11. Change to Landscape

12. Click on Advance tab in lower right

13. Change Scaling as needed, check PDF output as needed

14. Select Print, wait for file name box, aCRF is done.

Time and Events Table – CSV file

1. File ->; Annotated Study Book Options

2. Check Time and Events Table

3. File ->; View Annotated Study Book

4. Click on Save Time & Events as button lower left

5. Give it a file name

Note: ;Steps 1-5 have to be repeated every time as aCRF defaults back to base settings after you close out the study.

Anayansi Gamboa has an extensive background in clinical data management as well as experience with different EDC systems including Oracle InForm, InForm Architect, Central Designer, CIS, Clintrial, Medidata Rave, Central Coding, OpenClinica Open Source and Oracle Clinical.

Clinical Trials Acronyms

ADaM – Analysis Data Model (a CDISC standard) ADR – Adverse drug reation
AE – Adverse Event CRA –Clinical Research Associate
ATC – Anatomic-Therapeutic Chemical Coding dictionary CDASH – Clinical Data Acquisition Standards Harmozation (a CDISC initiative)
CDISC – Clinical Interchange Standards Consortium CDM – Clinical Data Management
CDMS – Clinical Data Management system CF – Consent Form
CSR – Clinical Study Report CRB – Case Record book
CT – Clinical Trial CTA – Clinical Trial Agreement
CD – Common Technical Document CRB – Central Review Board
CRF – Case Report Form CRO – Contract Research Organization
CNS – Central Nervous System GMP – Good Manufacturing Practices
GRP – Good Review Practice GXP – Good Pharmaceutical Practice
eCTD – Electronic Common Technical Document EDC – Electronic Data Capture
EDI – Electronic Data Interchange IB – Investigator’s brochure
IC – Informed Consent IND – Investigational New Drug Application (FDA)
IVRS – Interactive voice response system MedDRA – Medical Dictionary for Regulatory Activities
OC – Oracle Clinical SDV – Source document (data) verification
QA – quality assurance QC – quality control
QL/QOL – Qualify of life R&D – Research and development
SAE – Serious Adverse Event SAS – Statistical Analysis System
WHO – World Health Organization  

Reference: Part of this post was taken from the Applied Clinical Trials website at actmagazine

Anayansi Gamboa has an extensive background in clinical data management as well as experience with different EDC systems including Oracle InForm, InForm Architect, Central Designer, CIS, Clintrial, Medidata Rave, Central Coding, OpenClinica Open Source and Oracle Clinical.

CDER Common Data Standards Issues Document

 Source: FDA (Version 1.1/December 2011)

 The Center for Drug Evaluation and Research (CDER) is strongly encouraging sponsors to submit data in standard form as a key part of its efforts to continue with advancement of review efficiency and quality. CDER has been collaborating with CDISC, a standards development organization (SDO), in the development of standards to represent study data submitted in support of regulatory applications. Study data standards are vendor-neutral, platform-independent, and freely available via the CDISC website (http://www.CDISC.org). CDISC study data standards include SDTM (Study Data Tabulation Model) for representation of clinical trial tabulations, ADaM (Analysis Data Model) for clinical trial analysis files, and SEND (Standard for Exchange of Non-clinical Data) for representation of nonclinical animal toxicology studies tabulations.

CDER has accepted SDTM datasets since 2004; however, due to differences in sponsor implementation of the standard, CDER has observed significant variability in submissions containing “standardized” electronic clinical trial data. CDER has received numerous “SDTM-like” applications over the past several years in which sponsors have not followed the SDTM Implementation Guide. Furthermore, aspects of particular sponsor implementations have actually resulted in increased review difficulty for CDER reviewers. In addition, some sponsors have wrongly believed that the submission of SDTM datasets obviates the need for the submission of analysis datasets, resulting in the delay in review due to the need to request these datasets. The goal of this document is to communicate general CDER preferences and experiences regarding the submission of standardized data in order to aid sponsors in the creation of standardized datasets for both tabulation datasets and analysis datasets. .

This document is not intended to replace the need for sponsors to communicate with review divisions regarding data standards implementation approaches or issues, but instead, it is designed to complement and facilitate the interaction between sponsors and divisions. Because of specialized needs in different divisions, it is likely that divisions may have additional requests or preferences. When uncertainty exists regarding a particular data standards implementation or submission issue, the sponsor should contact the review division to discuss further.

The complete documentation on CDER data standards in .pdf version can be found at the following link: CDER


Anayansi Gamboa has an extensive background in clinical data management as well as experience with different EDC systems including Oracle InForm, InForm Architect, Central Designer, CIS, Clintrial, Medidata Rave, Central Coding, OpenClinica Open Source and Oracle Clinical.

InForm Trial – Complete Trial Removal

Remove a Trial from InForm

1-Open the command promptCommand Prompt

2-if the InForm Service has not started yet, you can start it by entering the following command:

net start pfservice  

NOTE: If you are using InForm Architect, the service may has already be started.

3-Once the server or service is started (completed successfully), you will then remove the trial by entering:

pfadmin remove trial e.g. pfadmin remove trial proto999

NOTE:  InForm can not remove a running trial. 

4-    Enter the following command prior to the remove command above:

pfadmin stop server proto999 /trials

Removal of a trial from the system

It is necessary to remove trials off your system once you have completed the e-crfs to ensure that Architect is working efficiently as you develop more trial e-crfs. 

1- Open the  Data Sources (ODBC)
2- Click on the tab System DSN
3- Highlight the trial that you want to remove.
4- Click the Remove button.

A message will pop up that asks you if you are sure you want to remove the trial’s data source, click Yes button. Click OK button to close ODBC.

Remove a Trial from the Oracle Database

If you are doing trial development work in Architect, you may need to stop the InForm Service before doing these steps. Enter the following command:

net stop pfservice [enter]

sqlplus useruid/pwduid [enter]

SQL*Plus is running now

From here enter the following two commands:

 drop user trialuid cascade;


 To exit SQL*Plus enter:  exit

The trial has been completely removed from the system. Doing this can help keep the system ‘clean’ as well as gets the system ready to fully reinstall this trial again if you needed to fully remove it.

NOTE: If you wish, you may verify that the trial is really gone in Oracle by starting TOAD or PLSQL Developer and check the USER object/table.

Anayansi Gamboa has an extensive background in clinical data management as well as experience with different EDC systems including Oracle InForm, InForm Architect, Central Designer, CIS, Clintrial, Medidata Rave, Central Coding, OpenClinica Open Source and Oracle Clinical.

FDA Compliance: Part 11 Checklist

PART 11 Checklist

Rule Sec. Requirement Satisfied?
11.10(a) Validation of Systems The system is validated (Documentation, Testing and Maintenance) Yes/NO/NA
11.10(k-1) Adequate controls over documentation Controls are present for the distribution, access and use of systems documentation for operation and maintenance Yes/NO/NA
11.10(d) Limiting system access System access is limited to only authorized individuals. Yes/NO/NA
11.10(i) Persons who develop,…have the education, training, and experience There is evidence of qualification (education, training or experience) for persons
who developed the system.
11.10(i) Persons who maintain,…have the education,training, and experience There is evidence of qualifications (education, training or experience) for persons
who maintain the system
11.10(i) Persons who…use…have the education, training,
and experience…
There is evidence of qualifications (education, training or experience) for persons
who use the system.
11.10(i) Written policies…for actions initiated
If electronic signatures are used, a policy is actively implemented, so that individuals
understand the significance of, and are held accountable for, their electronic
11.10(a) Ability to discern invalid or altered records There is a method to detect changes made to records (including direct record changes that
bypass system controls).
11.10(c) Protection of records… There is a method to protect records from accidental
or deliberate damage (including direct record changes that bypass system controls
11.10(b) Generate accurate and complete copies…in both human readable… The system has the ability to produce complete copies of records in printed human
readable format
11.10(b) Generate…in…electronic form… The system has the ability to produce complete copies of records in a common
electronic format (e.g., ASCII, TXT, DOC, XLS, etc.).
11.10(f) Enforce permitted sequencing of steps and events… The system controls the required sequencing of steps and events, as appropriate. Yes/NO/NA
11.10(h) Use of device checks… The system checks that data entries or operating instructions originate only from
authorized locations (e.g., work‐stations),
as appropriate.

Source:FDA CFR Part11

Role of Project Management and the Project Manager in Clinical Data Management


The Project Manager is responsible for the development, oversight of implementation, and communication of clinical research studies.

So what is a Project?

A project is a work effort with a definite beginning and end, an identifiable end result (deliverable), and usually has limits on resources, costs and/or schedule.

What is Project Management?

The application of knowledge, skills, tools, and techniques to project tasks in order to meet project requirements.

In order to be a successful project manager, you need to understand the “Tripple Constraint” and how they affect your project. Let’s look up the WBS-edit checks:

Note: I will refer a project = clinical study

Scope: What is in the contract? How many edit checks, SAS checks and manual checks are required in this study? What is the effort per edit check, SAS check and manual check?

The goal is to convert the idea of data management to that of statistical analysis – an analyzable database.

Time: What are the deliverables and timelines? What resources are needed?

Cost: What are the budget restrictions? Are there any risks associated with any changes?

Project Planning: During the planning of a clinical study, we identify the project scope, develop the project management plan and we identify and schedule the clinical study activities.

Some questions might arise during the project planning phase: how many sites/subjects and pages will be collected?Who will attend team meetings? what study fields will be code (i.e. Adverse Event term)?

Other important activities that the project manager and clinical team members will need to be involved:

Work Break Down (WBS) – it is the list of activities that will be performed during the course of a clinical study.

Resourcing – it is important to assign the right person to a particular task based on skills, education and experience.

ICH Guidelines ‘…all personnel involved in clinical trials must be qualified and properly trained to perform their respective tasks…’

Estimating Cost – look at historical data as well as good estimates from effort per unit and units using your WBS as references.

Scheduling and Budgeting – you will be able to build schedules and budgets that transform project constraints into project success after you successfully construct your Work Breakdown Structures (WBS) and network diagrams and estimate task durations.

Projects managers used techniques for employed to establish project. Project Manager can decide which activity can be delayed without affecting the duration of the projects. They help improving quality and reduce the risks and costs related with the projects.

A recent survey by the Project Management Institute provided 10 challenges affecting project managers. This research intended to identify key factors affecting project team performance:

  1. Changes to Project Scope (Scope Creep)
  2. Resources are Inadequate (Excluding Funding)
  3. Insufficient Time to Complete the Project
  4. Critical Requirements are Unspecified or Missing
  5. Inadequate Project Testing
  6. Critical Project Tasks are Delivered Late
  7. Key Team Members Lack Adequate Authority
  8. The Project Sponsor is Unavailable to Approve Strategic Decisions
  9. Insufficient Project Funding
  10. Key Team Members Lack Critical Skills

Another question to ask is what tools are available to help you get the job done?

  1. Resource allocation (and the software’s ability to easily display staff who were overallocated)
  2. Web-based/SaaS option
  3. Cost/Price of the system (big one!)
  4. Contractual terms we could enter into (i.e. 6 months, 12 months, month to month)
  5. Ability to demo the software and for how long
  6. What sort of customizations could be made to the software after purchase
  7. Types of customers the software has served
  8. Report types
  9. Ability to sync with accounting software and which ones, if so
  10. Timeline generation capabilities and import function with MS Project
  11. Ability to create template projects
  12. Ability to alert on early warning signs (i.e. budget overruns over 10%)

It is suggestted that you review each suggestion on project management tool very, very carefully to determine how it fits your processes.

Your organization’s processes are unique to your organization; no other organization anywhere has quite the same processes. So what may work for one organization may not necessarily work for you. Your organization developed its processes to suit your particular corporate culture, the particular collective character attributes of the employees (their experience, etc.), the type of projects that you execute and the particular types customers/clients that you have (especially the regular ones).

You now have to make sure that the tools you choose work for you and your particular processes. Do not change your processes again to suit whatever workflow (process) is dictated by the fancy tool that the fancy salesman sold to you; you are likely to find that the tool-dictated workflows do not work that well in your organization, with the result that the employees will give up following processes and/or give up using the tool, throwing everything into chaos again.

Be careful if you are looking at tools that offer to do a number of different functions or can be made to do any function you want it to do. They seldom do the job that you bought it for particularly well. For example, I have worked with a tool that was advertised as a combination issue tracking and defect/bug tracking tool. It was used as a defect tracking tool but it was very poor; it was tremendously difficult to make it prepare useful reports. A hand-written tool set up in a spreadsheet (e.g. Microsoft Excel) or database (e.g. Microsoft Access) would have worked better.

That said, there are tools out there that are specific to one particular function but do offer flexible workflows – they may be modified to match whatever processes your organization already follows.

If your organization has just started to organize the PM processes and PMO that would mean processes & other related areas are not explicitly defined. So there may be a huge risk trying to adopt an integrated and centralized project management system. It is more likely to offer you a very comprehensive, complex but expensive solution wherein your problem is still not defined completely. In such a case you are just not ready with the environment and process maturity that an integrated tool requires prior to implementation.

A more efficient approach should be iterative, incremental and adaptive in nature. That means you shall use simple, not so expensive tools with limited scope to begin with; they can be tools with basic functionalities of WBS, scheduling, traceability and custom datasheets. These tools should have capability to exchange data both ways with more commonly uses tools like MS Excel, MS Project, and Word etc. The processes are likely to mature over time and we will then know the real effectiveness of these basic tools in the context of company requirements. That may be the time to analyze and switch to more integrated solutions.

One important key to remember. The role of project management in clinical trials is evolving. There is a debate about who should be the ‘project manager’ for a particular clinical study. CRA or Clinical Data Manager or an independent project manager? Let’s review their roles within data management.

Clinical Research Associate (CRA): main function is to monitor clinical trials. He or she may work directly with the sponsor company of a clinical trial, as an independent freelancer or for a Contract Research Organization (CRO). A clinical research associate ensures compliance with the clinical trial protocol, checks clinical site activities, makes on-site visits, reviews Case Report Forms (CRFs) and communicates with clinical research investigators. A clinical research associate is usually required to possess an academic degree in Life Sciences and needs to have a good knowledge of Good clinical practice and local regulations. In the United States, the rules are codified in Title 21 of the Code of Federal Regulations. In the European Union these guidelines are part of EudraLex. In India he / she requires knowledge about schedule Y amendments in drug and cosmetic act 1945.

Clinical Data Manager (CDM): plays a key role in the setup and conduct of a clinical trial. The data collected during a clinical trial will form the basis of subsequent safety and efficacy analysis which in turn drive decision-making on product development in the pharmaceutical industry. The Clinical Data Manager will be involved in early discussions about data collection options and will then oversee development of data collection tools based on the clinical trial protocol. Once subject enrollment begins the Clinical Data Manager will ensure that data is collected, validated, complete and consistent. The Clinical Data Manager will liaise with other data providers (eg a central laboratory processing blood samples collected) and ensure that such data is transmitted securely and is consistent with other data collected in the clinical trial. At the completion of the clinical trial the Clinical Data Manager will ensure that all data expected to be captured has been accounted for and that all data management activities are complete. At this stage the data will be declared final (terminology varies but common descriptions are Database Lock and Database Freeze) and the Clinical Data Manager will transfer data for statistical analysis.

Clinical Data Management (CDMS) Tools: (we will review each of them on a separate discussion)

  • Standard Operating Procedures (SOPs)
  • The Data Management Plan (DMP)
  • Case Report Form Design (CRF)
  • Database Design and Build (DDB)
  • Validation Rules also known as edit checks
  • User Acceptance Testing (UAT)
  • Data Entry (DE)
  • Data Validation (DV)
  • Data Queries (DQ)
  • Central Laboratory Data (CLD)
  • Other External Data
  • Serious Adverse Event Reconciliation (SAE)
  • Patient Recorded Data (PRO)
  • Database finalization and Extraction
  • Metrics and Tracking – see BioClinica article on Metrics
  • Quality Control (QC)- see discussion on A QC Plan for A Quality Clinical Database

In conclusion, a key component of a successful clinical study is delivering the project rapidly and cost effectively. Project managers must balance resources, budget and schedule constraints, and ever-increasing sponsor expectations.


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Anayansi Gamboa has an extensive background in clinical data management as well as experience with different EDC systems including Oracle InForm, InForm Architect, Central Designer, CIS, Clintrial, Medidata Rave, Central Coding, OpenClinica Open Source and Oracle Clinical.