Tag Archives: ADaM

The Only Three (3) [Programming] Languages You Should Learn Right Now (eClinical Speaking)

On a previous article that I wrote in 2012, I mentioned 4 programming languages that you should be learning when it comes to the development of clinical trials. Why is this important, you may ask? Clinical Trials is a method to determine if a new drug or treatment will work on disease or will it be beneficial to patients. Anayansi Gamboa - Clinical Data Management Process If you have never written a line of code in your life, you are in the right place. If you have some programming experience, but interesting in learning clinical programming, this information can be helpful.

But shouldn’t I be Learning ________?

Here are the latest eClinical programming languages you should learn:

1. SAS®: Data analysis and result reporting are two major tasks to SAS® programers. Currently, SAS is offering certifications as a Clinical Trials Programmer. Some of the skills you should learned are:

  • clinical trials process
  • accessing, managing, and transforming clinical trials data
  • statistical procedures and macro programming
  • reporting clinical trials results
  • validating clinical trial data reporting

2. ODM/XML: Operational Data Modeling or ODM uses XML to build the standard data exchange models that are being developed to support the data acquisition, exchange and archiving of operational data.

3. CDISC Language: Yes. This is not just any code. This is the standard language on clinical trials and you should be learning it right now. The future is here now. The EDC code as we know it will eventually go away as more and more vendors try to adapt their systems and technologies to meet rules and regulations. Some of the skills you should learn:

  • Annotation of variables and variable values – SDTM aCRF
  • Define XML – CDISC SDTM datasets
  • ADaM datasets – CDISC ADaM datasets

CDISC has established data standards to speed-up data review and FDA is now suggesting that soon this will become the norm. Pharmaceuticals, bio-technologies companies and many sponsors within clinical research are now better equipped to improve CDISC implementation.

Everyone should learn to code

Therefore, SAS® and XML are now cooperating. XML Engine in SAS® v9.0 is built up so one can import a wide variety of XML documentation. SAS® does what is does best – statistics, and XML does what it does best – creating reportquality tables by taking advantage of the full feature set of the publishing software. This conversation can produce report-quality tables in an automated hands-off/light out process.

Standards are more than just CDISC

If you are looking for your next career in Clinical Data Management, then SAS and CDISC SDTM should land you into the right path of career development and job security.

Conclusion: Learn the basics and advanced SAS clinical programming concepts such as reading and manipulating clinical data. Using the clinical features and basic SAS programming concepts of clinical trials, you will be able to import ADAM, CDISC or other standards for domain structure and contents into the metadata, build clinical domain target table metadata from those standards, create jobs to load clinical domains, validate the structure and content of the clinical domains based on the standards, and to generate CDISC standard define.xml files that describes the domain tables for clinical submissions.

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.

Disclaimer: The legal entity on this blog is registered as Doing Business As (DBA) – Trade Name – Fictitious Name – Assumed Name as “GAMBOA”.

Source:

SAS Institute
CDISC

CDISC/CDASH Standards at your Fingertips

A standard database structure using CDISC (Clinical Data Interchange Standards Consortium) and CDASH (Clinical Data Acquisition Standards Harmonization) standards can facilitate the collection, exchange, reporting, and submission of clinical data to the FDA and EMEA. CDISC and CDASH standards provide reusability and scalability to EDC (electronic data capture) trials.

There are some defiance in implementing CDISC in EDC CDMS:

1. Key personnel in companies must be committed to implementing the CDISC/CDASH standards.

2. There is an initial cost for deployment of new technology: SDTM Data Translation Software, Data Storage and Hosting, Data Distribution and Reporting Software.

3. It can be difficult to understand and interpret complex SDTM Metadata concepts and the different implementation guides.

4. Deciding at what point in a study to apply the standards can be challenging: in the study design process, during data collection within the CDMS [CDASH via EDC tools], in SAS prior to report generation [ADaM], or after study completion prior to submission [SDTM].

5. Data management staff [CDM, clinical programmers], biostatisticians, and clinical monitors may find it difficult to converge on a new standard when designing standard libraries and processes.

6. Implementing new standards involves reorganizing the operations of (an organization) so as to improve efficiency [processes and SOPs].

7. Members of Data Management team must be retrained on the use of new software and CDISC/CDASH standards.

standards8. There are technical obstacles related to implementation in several EDC systems, including 8 character limitations [SAS] on numerous variables, determining when to use supplemental qualifiers versus creating new domains, and creating vertical data structure.

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Anayansi Gamboa, MPM, an EDC Developer Consultant and clinical programmer for the Pharmaceutical and Biotech industry with more than 13 years of experience.

Available for short-term contracts or ad-hoc requests. See my specialties section (Oracle, SQL Server, EDC Inform, EDC Rave, OpenClinica, SAS and other CDM tools)

As the 3 C’s of life states: Choices, Chances and Changes- you must make a choice to take a chance or your life will never change. I continually seek to implement means of improving processes to reduce cycle time and decrease work effort.

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Disclaimer: The legal entity on this blog is registered as Doing Business As (DBA) – Trade Name – Fictitious Name – Assumed Name as “GAMBOA”.

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.