Tag Archives: EDC Developer


  • Setting up a project in EDC (Oracle InForm, Medidata Rave, OpenClinica, OCRDC)
  • Creation of electronic case report forms (eCRFs)
  • Validation of programs, edit checks
  • Write validation test scripts
  • Execute validation test scripts
  • Write custom functions
  • Implement study build best practices
  • Knowledge of the process of clinical trials and the CDISC data structure



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Overview of RA eClinica (Technology Pharmaceutical Services)

Overview of RA eClinica (Technology Pharmaceutical Services)

RA eClinica Solutions (Technology Resource Organization), is your best source for customized solutions. We focus exclusively on clinical drug development in the bio-pharmaceutical industry, we addresses a highly specialized need in an extremely large and growing market with an avid demand for qualified personnel. RA eClinica combination of clinical trials development expertise with technology integration and recruiting resource, allows each of our clients to ‘custom design’ their required needs.

RA eClinica collaborate with each client to develop a solution with our experienced ‘SMEs’ of professionals. Each team is trained in a specific functional area to ensure that each of our clients’ need are met. This approach differs from the turnkey approach of Clinical Research Organizations (CRO) employment and the low value-added commodity style of general staffing / recruitment firms.

Our dedication to serving each of our staff as well as our clients, has earned us a reputation as a reliable source of opportunities in the following areas:

Clinical Programming Clinical Research Biostatistics
Clinical Data Management EDC Developers SAS Programmers
IT Professionals Data Managers Project Managers of Data Management

If you are looking for contract staff (short and long term), permanent staff, “contract to perm” employees or project team deployment, let us help you find the right candidate.

Take advantage of everything that RA eClinica Solutions has to offer you. My colleagues and I look forward to the opportunity to work with you in the near future.

Learn the basics on how to implement CDISC data standards concepts on your clinical trials from study design to FDA data analysis submission.

Need SAS programmers, CDISC Subject Matter Experts (SMEs) or a clinical programmer? We can help provide resources in-house / off-shore to facilitate FDA review by supporting CDISC mapping, SDTM validation tool, data conversion and CDASH compliant eCRFs.

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Posted by on November 5, 2015 in eClinical, Information Technology


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Electronic Data Capture (EDC) Future

Electronic Data Capture (EDC) Future

While EDC has been around for many years, we all acknowledge that the percentage of EDC studies has just moved into the majority. Some of the reasons for such a slow uptake include:

1) failure to understand that EDC adoption requires significant change to fundamental business processes hindering pharma from leaving “paper” processes behind;

2) thinking that studies “outsourced” to an EDC vendor means minimal change to a clinical trials organization; and

3) continued evolution of EDC tools and vendors leading to some pharma companies chasing what appears to be the newest and best solution.

One key issue arising from EDC adoption is its disruptive effect on clinical trial site staff. Now, with the majority of clinical trials using web-based EDC tools, clinical site staff are reaching a point where they say no more EDC because the volume of EDC studies severely impacts their ability to maintain source documents and use multiple EDC tools. For example, for one EDC tool, clinical site staff must take training from each sponsor using the tool which produces a huge time burden on those individuals. Broad adoption of EDC (eCRF) standards from efforts like CDISC’s CDASH initiative may alleviate some of that disruption, but clinical site process considerations are largely being ignored. Remember, those folks are critical customers for EDC.

So, there are multiple factors creating problems for EDC adoption and their common threads all point to understanding business processes inside pharma and inside clinical trial sites. Addressing those factors should help EDC move from a simple majority to larger adoption.

The huge number of purely EDC vendors presents problems for the buyer (pharma companies). Many companies are now looking to consolidate numerous vendors to a select few. Therefore, many are looking further into the future than simply choosing an EDC vendor. They may also need an IVRS vendor or perhaps help with the trial design and data monitoring. Many of the EDC vendors cannot provide this one stop shopping. There is a legitimate concern on the part of companies that an EDC vendor may not be around in a couple of years. Many have fallen by the wayside in recent years purely because they could not compete or did not address the needs of the client.

Furthermore, there is a desire for consistency. Difference clinical groups within a company can have different preferred vendors. This can compound the problem of data collection and integration. Lastly, there is the management of the collected data–who owns it, who has access, etc. Internal politics can play a big role here. Many companies (and clinical programs) may simply decide that building is better than buying.

The main problem with EDC in the pharma industry is one of business process change. For many, the technology is very sound, and replaces labor-intensive and cost-intensive historic paper-based approaches. However, the burden of labor shifts from internal data entry staff to site-specific clinical/medical staff. There is an immediate improvement in reducing the number of queries, and that improvement, along with the speed with which data is available, is where many of the benefits reside. THe cost of moving this work to the site is non-trivial.

Research companies can gain more success with EDC systems by altering the business process within their organizations. Because the data is more timely, and more accurate earlier in the process, what else can be done within the business process to leverage the investment in EDC?
EDC is not just about moving data faster, it’s about leveraging the EDC investment of optimize the process whereby new therapies are ultimately approved for use.

RA eClinica is a established consultancy company for all essential aspects of statistics, clinical data management and EDC solutions. Our services are targeted to clients in the pharmaceutical and biotech sector, health insurers and medical devices.

Consultants available for study setup, including CRF design, edit checks and CDISC SDTM clinical data click here.

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Posted by on October 27, 2015 in Clinical Data Management, EDC


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RAeClinica – Clinical Staffing and Resourcing

RAeClinica – Clinical Staffing and Resourcing

RA eClinical Trial Technology, EDC, CTMS, and Technology Integration-Software Development – Web Development and Clinical Research Organization – Contract Research Organization

Source: RAeClinica – Clinical Staffing and Resourcing


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From Non-SAS Programmer to SAS Programmer

SAS Programmers come from many different educational backgrounds. Many has started their careers as a Data Manager in a CRO environment and grew to become a SAS programmer. Others have gone to college and pursued degrees in math, statistics or computer science degree.

Do you have SAS Skills? First, you need to find out more about statistical programming desire skills and start to slowly learn what SAS programmers and statisticians do in the pharmaceutical industry. It is also important to understand the Drug Development and Regulatory process so that you have a better understanding of the industry as a whole as well as the drug approval process.

In addition, I have personally attended several workshop on Statistics for Non-statistician provided by several of my past employers/clients (GSK, Sanofi-Aventis, etc) so I could have a greater understanding of statistics role. I am personally more inclined to the EDC development than becoming a biostatistician but these are just some of the few steps you could take to grow your career as a SAS programmer.

Practice, Practice, Practice!

To begin learning how to actually program in SAS, it would be a good idea to enroll to a SAS course provided by the SAS Institute near you or via eLearning. I have taken the course SAS Programming 1: Essentials, and I would recommended. You could also join SUGI conferences and other user groups near your city/country. Seek every opportunity to help you gain further understanding on how to efficiently program in the pharmaceutical industry. It could well land you a Junior SAS programming position.

Transitioning to a SAS Programming role: Now that you have gotten your first SAS programming job, you will need to continue your professional development and attend additional training, workshops, seminars and study workgroup meetings. The SAS Institute provide a second level, more advance course Programming II: Manipulating Data with the Data Step, SAS Macro Language and SAS macro Programming Advanced topics. There are also SAS certifications courses available to help you prepare to become a SAS certified programmer.

There is a light at the end of the tunnel: Advance!

Your ongoing development will be very exciting and challenging. Continued attending SAS classes as needed and attending industry related conferences such as PharmaSUG to gain additional knowledge and insight on how to perform your job more effectively and efficiently.

As you can see, it is possible to ‘grow’ a SAS programmer from a non-programming background to an experience programmer. All of the classes, training, and projects you will work on are crucial in expanding your SAS knowledge and will allow you to have a very exciting career opportunity ahead of you.

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.


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Good Documentation Practice (GDP) for the EDC / SAS Developer

When writing programming codes for either validating the software or for validation checks, we often have to write comments to explain why we did something.

Since the FDA regulates computerized systems used in clinical trials under the authority of Title 21 the Code of Federal Regulations Part 11 (21 CFR Part 11) – see my other article about 21 CFR Part 11 here, we need to make sure our codes and programs are documented. As you have heard before, if it is not documented, it never happened. Nevertheless, there is no mandatory regulatory agency mandating to have to do this.

GDP is an expected practice”

So how much documentation is needed? We could get into endless discussions of when we should comment, what we should comment, and how much we should comment. I have had plenty of discussions about comments with people with various opinions on the subject.

Here’s a good documentation practice for a SAS code:

For more information please visit the original post at: {EDC} Developer

Need a clinical programmer, Data Programmers (Oracle/SAS/.NET) EDC Specialists (InForm, RDC, Rave)?

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Much effort goes into the specification, development, testing and verification of programmatic edit checks to ensure that the error rate in clinical trial data is sufficiently low as to have no statistically significant effect on the overall trial results. An analysis of several thousand clinical trials, containing over 1.1 billion data values and 1.1 million edit checks, shows that the majority of edit checks (60%) have no impact on data quality; none of these 678,000 edit checks have generated a single data query or discrepancy. What can be learnt from this analysis; can we reduce the overall number of edit checks without compromising data quality; can we identify the ‘high-performing’ edit checks and improve CRF design to avoid data entry errors; are there novel methods that might achieve similar standards of data quality with less effort?


Edit checks are necessary to ensure data quality reaches acceptably high levels.

Since programming edit checks takes time and resources, it’s important to ensure that the effort invested maximizes the benefit and re-usability of each edit check.


See attached document for full article information published by:
Optimizing Data Validation by Andrew Newbigging, Medidata Solutions Worldwide, London, United Kingdom


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Complexity and effectiveness of edit checks


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