Tag Archives: data management

RAeClinica – Software Development

RAeClinica – Software Development

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

Source: RAeClinica – Software Development


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Case Study 4: A Full Data Management Solution

Case Study 4: A Full Data Management Solution

Working in a Collaborative Environment

The Scenario:

A phase II study was being managed by a CRO that had non-dedicated teams, escalating costs, with project timelines slipping on almost every deliverable.
RA eClinica Solution:

    • RA eClinica assumed responsibility for entire data management activities consisting of Data Management, Study Build / EDC Development, and Statistics and Programming.
    • RA eClinica preferred Data Management systems utilized with Sponsor’s Safety Surveillance system and Clinical Trial Management System, CTMS

Ra eClinica Results:

    • Study ongoing – All deadlines to date have been met or exceeded
    • Cost savings of approximately 35% in comparison to traditional CRO models
    • No turnover since study start

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.

The company is headquarter in Panama City and representation offices with business partners in the United States, India and the European Union. For discussion about our services and how you can benefit from our SMEs and cost-effective implementation CDISC SDTM clinical data click here.


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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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Services: Data Management

Clinical trials play a key role in the pharmaceutical, biotechnology and medical device industry. We have Data Managers, EDC Developers and SAS Programmers available around the clock. Regardless of EDC tool {Medidata Rave, Medrio, Oracle InForm, OpenClinica, Oracle RDC or others}; we strive to provide you the best service by implementing CDISC standards from initial development.

RA eClinica Data Management Solutions

What others Clinical Research Organizations (CROs) consider ‘Unique‘ pages, we consider them ‘Standards‘. Why? We have developed most CDISC standards forms in most {EDC} systems so there is no need to reinvent the wheel.

What you get? Quick turn-around, cost-effective setup. We can setup trials in less time than most CROs as we use libraries from CDISC standards. Our SMEs then can concentrate on ‘Unique’, ‘Study-specific’ or more complex CRFs as per protocol.

For further information, please Contact Us!

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Posted by on June 15, 2015 in Freelancers


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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)?

Contact Us!


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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.


Source: EDCDeveloper

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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