The OpenClinica Platform – Developer Round Table Discussions

OpenClinica is a clinical trial software platform that aims to provide data capture, data management, and operations management functionality to support human subjects-based research. It can be used for traditional clinical trials as well as a wide variety of other types of human subjects-based research.

Our vision for the product is to provide data capture, data management, and operations management functionality out-of-the-box, in an easily configurable, usable, and highly reliable manner. The underlying platform should be interoperable, modular, extensible, and familiar – so users can solve specific problems, in a generalizable way.

This past spring, the development team here at OpenClinica, LLC held a series of round table discussions about how this vision is reflected in the product. Our goals were to learn critical standards and information models needed for our technology to truly reflect this vision, to develop a consistent, shared vocabulary for the problem domain and the OpenClinica technology, and identify the most urgent opportunities to put these lessons into practice in the product and the community. In particular, we spent a lot of the time in these discussions about how OpenClinica’s use of the CDISC Operational Data Model helps enable this vision.

The discussions were invigorating and thought-provoking. We’ve recorded them to share with the greater community of OpenClinica developers, integrators, and others who want to better understand how the technology works, the design philosophy behind it, and where we’re going in the future. The videos are embedded below.

But before getting to the videos, here’s a bit more background on how we think about OpenClinica as a product and a platform.

First, OpenClinica functionality should be ready out-of-the-box, easily configurable and highly usable. Some of the most important features include:

  • Data definition and instrument/form design with no or minimal programming
  • Sophisticated data structures such as repeating items and item groups
  • Support for a wide variety of response types and data types (single select, multiple choice, free text, image)
  • Data management and review capabilities (including discrepancy management and clinical monitoring) with flexible workflows
  • ALCOA-compliant controls and audit history over all data and metadata, including electronic signature capabilities
  • Patient visit calendar design with management of multiple patient encounters and multi-form support
  • Reporting and data extract to a wide variety of formats (tab, SPSS, CDISC ODM)
  • Ability to combine electronic patient reported outcome (ePRO) data with clinically reported data using common form definitions (write once, run anywhere)
  • Deployment via multiple media, mobile or standard web browser

Many of these things have already been implemented, and more are under development.

The core concept around which OpenClinica is organized is the electronic case report form (CRF). In OpenClinica, a CRF is a resource that is essentially a bunch of metadata modeled in CDISC ODM with OpenClinica extensions. It doesn’t (necessarily) have to correspond to a physical or virtual form; it may represent a lab data set or something similar. An OpenClinica Event CRF is that same bunch of metadata populated with actual data about a particular study participant. Thus, it combines the metadata with the corresponding item (field) data, with references to the study subject, event definition, CRF version, and event ordinal that it pertains to. In this conceptual view of the world, CRFs (as well as CRF items, studies, study events, etc.) are resources with core, intrinsic properties and then some other metadata that has to do with how they are presented in a particular representation. Built around these core resources are all the workflow, reporting, API, security, and other mechanisms that allow OpenClinica to actually save you time and increase accuracy in your research.

Second, OpenClinica should be interoperable. The ultimate measure of interoperability is having shared, machine readable study protocol definitions, and robust, real-time, ALCOA-compliant exchange of clinical data and metadata that aligns with user’s business processes. It should be easy to plug in and pull out or mix-and-match different features, such as forms, rules, study definitions, report/export formats, and modules, to transport them across OpenClinica instances or interact with other applications. Establishing well defined methods and approaches for integration into existing health data environments is a key goal of interoperability.

Third, OpenClinica should be modular and extensible. OpenClinica already provides some of the most common data capture and data management components and aims to have a very broad selection of input types, rules, reports, data extracts, and workflows. However OpenClinica developers should also have the freedom to come up with their own twist on a workflow, module, or data review workflow and have it work easily and relatively seamlessly with the rest of OpenClinica. User identification, authentication, and authorization should be highly configurable and support commonly used general purpose technologies for user credentialing and single-sign-on (such as LDAP & OAuth).

The CRF-centric model allows us a great deal of flexibility and extensibility. We can support multiple modalities, with different representation metadata for rendering the same form, or perhaps the shared representation metadata but applied in a different way (i.e. web browser vs. mobile vs. import job). We can address any part of the CRF in an atomic, computable manner. This approach has been successfully applied in the Rule Designer, which takes the ODM study metadata and allows browsing of the study CRFs and items, with the ability to drag and drop those resources to form rule expressions. Features such as rules and report/export formats are represented as XML documents. These documents define how the features behave in standardized ways so that one rule can, say, be easily replaced with another rule without having to modify all the code that makes use of the rule.

Finally, OpenClinica aims to be familiar in the sense of allowing data managers, developers, statisticians to work in a design/configuration/programming environment that they already know. Programmers don’t all have the same experience, and it would be somewhat limiting to force OpenClinica developers to all use the same language (Java) that OpenClinica was written in. We are constantly looking at ways to make it possible (not to mention reliable and easy!) for users and developers to interact with and extend OpenClinica in a programmatic way. This can mean anything from data loading to more meaningful integrations of applications common to the clinical research environment. As proponents of open, standards-based interoperability, our starting point is always to develop interfaces for these interactions based on the most successful, open, and proven methods in the history of technology – namely the protocols that power the World Wide Web (such as HTTP, SSL, XML, OAuth 2.0). They are relatively simple, extensively documented, widely understood, and well-supported out of the box in a large number of programming and IT environments. On top of this foundation, we rely heavily on the wonderful work of CDISC and the CDISC ODM to model and represent the clinical research protocol and clinical data.

Session 1:  from 30-March-2012 (start at the 5 min 20 sec mark)

Session 2:  from 06-April-2012 (start at the 1 min 25 sec mark)

Session 2a:  from 20-April-2012

Session 3:  from 27-April-2012

Session 4:  from 11-May-2012

The Evolution of Electronic Data Capture

OpenClinica was recently featured in an article in Genetic Engineering and Biotechnology News titled “Commandeering Data with EDC Systems,” written by Dr. James Netterwald. The article briefly recounts the early days of clinical trial Electronic Data Capture (EDC). But how far have we come? Dr. Netterwald’s title (perhaps unintentionally) conjures up images of struggle and strife, which may be perhaps more a more apropos description of the journey of Electronic Data Capture than it may first appear.

As an industry, it’s taken us a good 20 years to get to where we are, and to be plain, it’s been a slow start. (In my own defense, I, and my company Akaza Research, have only been a party to the industry for the last 5 of those 20 years.) Climbing the evolutionary ladder from shipping laptops to sites to keying data into electronic case report forms is certainly progress by any measure. However, while the days of mailing tapes and disks are over, the days of real electronic data capture are yet to come. Today, most experts agree that somewhere between only one-half and two-thirds of all new clinical trials use EDC software, an of this only a very small fraction are “e-source,” defined as collecting data in electronic form at its source as opposed to keying it in from some other source. In some ways it is ironic that cutting-edge biopharmaceutical technologies are developed themselves with technologies that are, relatively speaking, much further down the technology food chain.

Notwithstanding, there are some enterprising few who have pushed the pace towards true EDC. Spaulding Clinical, a large phase 1 unit in West Bend, Wisconsin has developed a system that automatically captures ECG data from their facility’s patients and directly populates the clinical trial database with these data. A patient wears the ECG device and the data are transmitted wirelessly to the EDC system. However, this slick and highly productive solution was not developed by either the ECG vendor or the EDC vendor. It was developed by hand by one of Spaulding’s own software developers.

Why isn’t this type of solution more commonplace in clinical trials? What prevents the industry from making the most of today’s information technology? With the strong incentives currently in place to make research more efficient, our field could certainly benefit from some more forward thinking.

– Ben Baumann

OpenClinica Community Surpasses 10,000 Members …and oh yeah, what is this open source thing?

Heartfelt thanks to everyone who has supported the OpenClinica project over its relatively brief history. Our community now stands at over 10,000 registered members, representing a 3-fold increase in size over the past two years alone. With members in over 70 countries across six continents, open source is now a central part of the clinical trials software landscape. This is a major accomplishment that we should all be proud of.

While 10,000 may sound like a lot of people, there are still many within the clinical trials industry who do not understand the key concepts of open source. Other software categories have a high prevalence of open source offerings. For instance, when you look at database products (like MySQL, Postgres) and operating systems (like Linux, Android, BSD) there are numerous open source options. Open source is even widely prevalent in the EMR/EHR space, with OpenVista, and over 20 others to choose from.

As OpenClinica ushers the benefits of open source into the clinical trials space, it is instructive to periodically revisit the fundamentals of what exactly open source is.

What is open source?

Open source is a type of free software license–free as in “freedom,” not “beer.”[1] It is not “freeware” and it is not “shareware.” More specifically, open source provides users with[2]:

  • The freedom to run a program, for any purpose
  • The freedom to study how a program works and adapt it to a person’s needs. (Access to the source code is a precondition for this.)
  • The freedom to redistribute copies so that you can help your neighbor.
  • The freedom to improve a program and release improvements to the public, so the whole community benefits. (Access to source code is a precondition for this.)

There are numerous open source software licenses based on the above tenants and roughly 60 open source licenses have been approved by the non-profit Open Source Initiative. The OpenClinica Community Edition is distributed under the LGPL open source license.

Open source as a development model

The software development models around open source projects are typically characterized by transparency and collaboration within the community. Opening the product up to the community, allowing anyone to see the good with the bad, helps to quickly uncover problems and identify areas for improvement. Most open source projects will publicly maintain a project roadmap and defect tracking system. Release cycles of active open source projects tend to be early and often.

The result of such openness and transparency is software that is often more reliable and better performing than proprietary, closed alternatives.

What is professional open source?

A symbiotic relationship exists in a health professional open source model between the Community, Company, and Customer.

Some people may think of open source projects as purely volunteer efforts. That is definitely not the case! While governance models vary from project to project, commercial enterprises have helped make open source consumable by ordinary people and businesses. For example, through its OpenClinica Enterprise Edition, Akaza Research provides support and regulatory assurances that help to minimize business risk and ensure success for organizations wishing to use OpenClinica in mission critical settings. Organizations can turn to Akaza to rapidly develop in-house expertise, obtain hosting and expert professional services, and ensure their OpenClinica systems and users are productive and satisfied.

A pervasive trend in software

Open source is everywhere[3]. From the Firefox web browser to the most popular websites, everyone who uses the World Wide Web uses open source. As web-based technology, OpenClinica and the OpenClinica community are direct beneficiaries of numerous other open source projects. Those within the clinical trials space who recognize the significance of open source will be a step ahead of their colleagues.

– Ben Baumann, Co-Founder, Akaza Research, LLC

Want to be an OpenClinica Community Member? Members get free access to OpenClinica software downloads, Issue Tracker, email forums, and the OpenClinica Case Report Form (CRF) Library. Register at http://www.openclinica.org/register.php.

Footnotes:
[1] See Open Source Software Definition, http://www.opensource.org/docs/osd
[2]From the Free Software Foundation: http://www.fsf.org/licensing/essays/free-sw.html
[3]The SourceForge repository of open source codebases counts over 230,000 OSS projects.

OpenClinica Community and Enterprise Editions

Dear OpenClinica Community,

We are only hours away now from the general release of OpenClinica 3.0. There is a ton of excitement here at Akaza as we get ready to see many months of hard work come to fruition.

In advance of this milestone I’d like to describe a few changes we’re making to how OpenClinica is organized and how the name and logo can be used.

A brief background: As a founding member of the OpenClinica® open source community, I constantly strive to ensure that our technology has a reputation for meeting the highest standards of quality. The growth of OpenClinica® over the past few years is a testament to some success in that area. In my role as CEO at Akaza Research, a business that has invested millions of dollars into development of this open source technology, I recognize that the same reputation of quality is critical to our ongoing success. Part of how we maintain this reputation is to provide quality control over solutions that bear the OpenClinica® name. To enable this, Akaza Research owns the registered trademarks for OpenClinica® and Akaza and reserves the rights to their use.

With the release of 3.0, we are publishing a trademark policy on our website (also summarized below) that defines how the OpenClinica® and Akaza Research® trademarks may be used by members of the OpenClinica community. Our goal is to protect the quality of the OpenClinica® and Akaza brands without inhibiting the freedom that comes with the open source software model. These trademark terms complement the flexibility of open source licensing, by clarifying and creating confidence in the quality and reliability of solutions that bear the OpenClinica® name.

The most visible way the policy will be manifested is by separating the Community and Enterprise editions of the software. The default software download from OpenClinica.org is the Community Edition, pre-configured in a way that complies with the requirements of the trademark policy. The policy itself covers allowed uses of the trademarks for commercial and non-commercial purposes, both for modified (derivative) works and for unmodified versions of the software.

Akaza’s OpenClinica Enterprise customers and partners will be granted separate licenses that include additional permissions on how they may use the trademark in their marketing, operations, and services activities. Their installations will be distinguished as “OpenClinica Enterprise Edition” via the label in the footer of their OpenClinica pages.

I want to stress that 100% of the core OpenClinica source code remains free and under an open source software license. It is our promise that this will always be the case. Over time Akaza will offer additional proprietary services and technology offerings as part of the OpenClinica Enterprise Edition to complement this core, but it is our goal to ensure that the Community Edition always stands on its own as a fully-functioning, 100% open source EDC/CDMS platform.

I hope you share my view that this new policy will provide the clarity and confidence that allow OpenClinica to continue to thrive, without imposing undue restrictions on members of the community.

With that (too lengthy) introduction, here is a summary of the policy. Click here for the detailed, legal version:

CategoryDescriptionTerms and Conditions
OpenClinica Community EditionYou download and install the software on your own, and are not commercially supported by Akaza.You may not use the OpenClinica brand for marketing or sales purposes, and must include the community edition disclaimer.
OpenClinica Enterprise EditionYou are an OpenClinica Enterprise System Level Support subscribers. Other Akaza customers/partners and OpenClinica code contributors may meet the requirements of this category. Contact sales for more detail.Includes limited use of the OpenClinica brand for marketing and sales purposes, ongoing support, and display of “OpenClinica Enterprise Edition” in footer.
OpenClinica Community Edition – Derivative WorkYou download and install the software on your own, make modifications to the code, and are not commercially supported by Akaza. You want to keep the OpenClinica name/logo in the modified version.You may not use the OpenClinica brand for marketing or sales purposes, and must include the community edition disclaimer.. You must also clearly state the software has been modified and the modifications are not supported by Akaza.
Other Derivative WorksYou choose to strip out the references to the OpenClinica and Akaza names and logos from your modified version of the software. The trademark policy does not apply.The OpenClinica source code is licensed under the GNU Lesser General Public License (LGPL). You still must follow the terms of the LGPL, including copyright attribution and requirements for redistribution of source code. Of course, if you choose to follow this course, we hope you’ll also let us know about your software modifications and will contribute these back to the core repositories, both for the benefit of the community and to help ensuring future compatibility of your flavor of the software.

If you are a community user of a prior version of OpenClinica and do not intend to upgrade to the latest release, please contact us if you have questions about how the new policy may affect you.

Best Regards,

Cal Collins

CEO, Akaza Research

Selling open source without mentioning open source

I am a regular reader of  “The Open Road” blog by Matt Assay on news.com. In one of his latest posts, “Getting open-source criticism wrong”, he does a great job of making the case that commercial open source software is about ease of adoption, flexibility, and choice.

It struck a chord because my sales team and I spend a great amount of time and effort explaining to prospective customers that we offer the same level of quality, stability, performance, service, and support as a proprietary vendor. In many cases we must meet a higher threshold than those vendors, because we do not have the lock-in of a commercial software license to compel customers to come back to us for repeat business. Our track record of successful long-term customer relationship is evidence we meet this threshold.

In certain sales situations, for the sake of simplicity and clarity, we have to focus only on these apples-to-apples characteristics, and do not have the opportunity to educate on the economic and technical advantages of OSS as much as we would like. It’s great to know that our open source clinical data management software technology and service offerings can stand successfully on these merits. However, as many readers of this blog already know, open source offers an additional set of critical benefits: “the ability to adopt software rapidly and at low cost, the flexibility to develop and extend their systems as they choose, and the ability to reduce risk by obtaining paid commercial-grade [or better] support”. As more decision makers are coming to understand, it is following this path, rather than the adoption of pricey, monolithic proprietary software, that leads to better outcomes and greater ROI.

Facilitated Data Entry of Lab Results Using OpenClinica’s New Web Services Feature

As mentioned previously, we at Geneuity Clinical Research Services are big fans of OpenClinica and are even more so now with the upcoming release of version 3.0 with its new web services capability.  This article describes how we exploit this new feature to help automate entry of lab results, a particularly important topic given that we do lots of batch testing of specimens and oftentimes test the same specimen for many different analytes.

Prior to 3.0, you had three options when it came to CRF data entry.  The first was to log into OpenClinica’s web interface and manually enter your data.  This was no problem so long as you didn’t have lots and lots of data.  But we did.

Alternatively, you could upload a flat file of your data as long as it was formatted in XML and associated with the appropriate subject id’s and visit descriptions.  Assembling this file wasn’t trivial though and manually looking up each specimen’s subject and event nearly defeated the purpose of the procedure, which was to save time and effort.

Finally, you could do what we did: write custom code to automate the job.  Lab data is amenable to this sort of approach because it is always tagged with something called an accession number that uniquely identifies it.  When designing CRF’s, we always make sure to include a field for the event’s accession number, and when a specimen first arrives through our door the first thing we do is to log into OpenClinica and enter the specimen’s accession number in the appropriate event’s CRF.  Because the number is unique to the study, this entry effectively tags the event and provides a ‘hook’ inside the database so that the event_crf_id of any data item subsequently  annotated with the accession number can be easily looked up using a database query like so: ‘SELECT event_crf_id FROM item_data WHERE value = ‘<accession_number>’.  This, in turn, gives you the requisite information to insert the lab data thusly: ‘INSERT INTO item_data VALUES (‘event_crf_id’, ‘value’ …’ provided you also know the item_id.

To implement this strategy, we wrote custom servlets that operated within the context of our OpenClinica installations.  More recently, we configured MirthConnect channels to do the same.   They worked well and data entry was greatly expedited, but the coding was complex and had to be refactored over and over again for each study and for every CRF change.  While helpful, this strategy wasn’t sustainable in the long run.

Luckily, the latest version of OpenClinica provides a way out.  It incorporates the Spring WS Framework which allows programmers to write something called a ‘web service.’  A web service digests and acts upon XML data sent to it on an on-demand basis over a network.  The source need not be a human being uploading data on a web form, but, more usefully, it can be, say, a clinical testing platform automatically spitting out HL7 messages.  This, of course, is ideal in our case.  So we wrote a web service called ‘EventDataInsert’ that parses XML containing lab data values annotated with accession numbers and item names, looks up the corresponding event_crf_id’s and item_id’s, and inserts the data into item_data accordingly.  The service is generic enough so that it doesn’t have to be refactored for each and every study, but it does make some critical assumptions.  Namely, it assumes that both accession numbers and item names are unique.  So care has to be taken to ensure both these preconditions are met.

The power of EventDataInsert doesn’t just lie in the fact that it handles inserts on an unattended basis, but also in that, like most web services, it requires only simple XML as input.  The latter makes the source of the data irrelevant as long as it can be correctly mapped and transformed into XML.  We often use MirthConnect to do this, using it’s easy-to-use graphical interface to configure channels between incoming raw data and OpenClinica’s web-service interfaces.

The figure below shows a typical deployment of OpenClinica at Geneuity.  MirthConnect is used not only to get data into OpenClinica but also to generate canned PDF reports of the results.  This scenario works for us and gets easier and easier to maintain as OpenClinica evolves new electronic data capture features and makes old ones ever more robust.

Diagram of OpenClinica at Genuity Clinical Research Services
Diagram of OpenClinica at Genuity Clinical Research Services

An Opportunity for Transformational Change in Clinical Trials

Life sciences research is recognized as one of the most technologically advanced, groundbreaking endeavors of modern times. Nevertheless until very recently the preferred technology for executing the most critical, costly stage of the R&D process – clinical trials – has been paper forms. Only in 2008 did adoption of electronic alternatives to paper forms take place in more than half of new trials. This recent uptick in adoption rates is encouraging, but further transformational change in the industry is necessary to fully realize the promise of Electronic Data Capture (EDC) and associated “eClinical” technologies. Two developments that could provide the framework for such change are adoption of open data standards and the use of Open Source Software.

Data standards provide uniform ways to represent information or processes within a specific frame of reference and according to a detailed specification. A standard is “open” when it is not encumbered by patent, cost, or usage restrictions. Open Source Software (OSS) is defined loosely as software that allows programmers to openly read, redistribute, and modify the source code of that software. The combination of OSS and open standards is a proven way to deliver improved flexibility, quality, and efficiency.

A community-driven open source offering that harnesses open standards can produce robust, innovative technology solutions for use in regulated clinical trial environments. Most Open Source Software is built using a collaborative development model. The OSS development and licensing model encourages experimentation, reduces ‘reinvention of the wheel’, and allows otherwise unaffiliated parties to build on the work of others. The result is that OSS can become a key driver of increased IT efficiency and a way to wring out unnecessary costs. In many cases, users can have the best of all worlds: the ability to adopt software rapidly and at low cost, the flexibility to develop and extend their systems as they choose, and the ability to reduce risk by obtaining paid commercial-grade support.

As clinical research struggles to become more automated and efficient, we need to rely on interoperable systems to meet challenges of flexibility, quality, and speed. The OSS development model also naturally leads to the adoption of well-documented, open standards. Because OSS product designers and developers tend to reuse successful components and models where available, OSS technologies are often leading implementers of standards. For example, the National Cancer Institute’s Cancer Bioinformatics Grid (caBIG) initiative is “designed to further medicine’s potential through an open source network” based on open data standards and infrastructure that support sharing of heterogeneous data. This remarkable effort aims to connect large networks of researchers in ways that enables efficient re-use of data, eliminates duplicate systems, and enables new types of translational research.

In industry-sponsored clinical trials, standards such as the CDISC Operational Data Model (ODM), Clinical Data Acquisition Standards Harmonization (CDASH), and Study Data Tabulation Model (SDTM) have gained adoption in both proprietary and OSS software platforms. In some cases, standards are mandated for regulatory submission and reporting (SDTM, clinicaltrials.gov) and obviously must be adopted. Other cases, such as use of ODM, CDASH, and general web standards such as web services and XForms tend to be adopted to the degree they have a compelling business case.

The business case for standards centers on increasing accuracy and repeatability, enabling reuse of data, and enhancing efficiency by use of a common toolset. A well-designed standard does not inhibit flexibility, but presupposes idiosyncrasies and allows extension to support ‘corner cases’. Leading industry voices share compelling arguments how to use standards such as ODM, CDASH, XForms, and Web Services to achieve these goals. Though the details are complicated, the approach offers orchestration of disparate applications and organization of metadata across multiple systems. There is change control support and a single ‘source of truth’ for each data point or study configuration parameter, so when study designs change (as they inevitably do) or a previously committed data point is rolled back, it is automatically shared and manual updates to systems are not necessary. Because the ODM, CDASH, and SDTM are used as a common “language”, the systems know the meaning and structure of data and can process transactions accordingly. Here’s a tangible example:

Lets imagine an IVR system wanted to check with an EDC system if a subject was current in a study (current meaning not dropped out, early terminated or a screen failure).  A Web Service could be offered by the EDC system to respond with a ‘True’ or ‘False’ to a call ‘IS_SUBJECT_CURRENT’ ?  Of course hand-shaking would need to occur before it hand [sic] for security and so on, but following this, the IVR system would simply need to make the call, provide a unique Subject identifier, and the EDC system web service would respond with either ‘True’ or ‘False.  With Web Services, this can potentially occur in less than a second.

Electronic Data Capture – Technology Blog, September 28, 2008

While this integration requirement could be satisfied by development of point-to-point, proprietary interfaces, this approach is brittle, costly, and does not scale well to support a third or fourth-party system participating in the transaction. It is critical that standards be open so that parties can adopt and implement them independently, and later interface their systems together when the business case calls for it. A leading industry blogger makes the case for the openness of standards within the ODM’s ‘Vendor Extension’ architecture: ”The ODM is an open standard, the spec is available for free and anyone can implement it. This encourages innovation and lowers the barriers to entry and therefore costs. Vendor Extensions are not open, the vendor is under no obligation to share them with the market and the effect is that meta-tools and inter-operability are held back.”

Having the software that implements these standards released as open source code only strengthens its benefits. Proprietary software can implement open standards, however given the proprietary vendor’s business interest to lock-in license revenue, might the vendor be tempted into tweaking or ‘extending’ the standard in a way that is encumbered to lock users into their platform? This strategy of “embrace, extend, extinguish” was made famous in the Microsoft anti-trust case of the 1990s, where it came to light that the company attempted to apply these principles to key Internet networking protocols, HTML and web browser standards, and the Java programming language. They hoped to marginalize competing platforms that did not support their “extended” versions of the standards. Thankfully, they had limited success in this effort, and the Internet has flourished into the open, constantly innovating, non-proprietary network that we know today. The eClinical technology field is at a similar crossroads. By embracing open standards, and working concertedly to provide business value in re-usable OSS technology, we can achieve a transformation in the productivity of our clinical technology investments.

How Open Source EDC Can Make Clinical Trials More Productive

Barbara Zwick, from the European clinical trial Evidence and Performance Blog recently published an interview with Ben Baumann, Director of Business Development at Akaza Research. The interview discusses how open source EDC (Electronic Data Capture) clinical trials software can help enhance product time to market and overall productivity of clinical trials. Here are some excerpts from the interview:

[BZ] Today’s big Pharma R&Ds are increasing their demand for efficiency and effectiveness. How are you facing this accelerating demand for speed to market?

[BB] There are a number of ways that OpenClinica can accelerate time-to-market. First, open source software can be much easier and quicker to evaluate and get up and running than proprietary software. People can readily install it and experiment with it. Potential adopters can readily inspect everything down to the source code and directly interact with other members of the OpenClinica community to get rapid, unbiased, real-world feedback.

In addition to a full set of EDC and CDM features one might expect in such a system, OpenClinica has  built-in features that give users the ability to set-up their own studies. Therefore, an organization can get a complete picture of how well the system will work for them before committing to use it.

In short, an organization can make a rapid and highly informed decision whether or not to use OpenClinica without having to go through lengthy vendor-biased demonstrations and negotiations, and rely on a vendor in order to get their studies configured appropriately.

[BZ] How can technologies serve to clinical trial performance, to minimize costs and time to market, and to allow rapid decision making? Are innovative EDC technologies, like your platform, more performant and focused on this specific need, rather than ‘old-fashioned’ EDC Solutions?

[BB] Aside from features of the product and benefits of the open source model described above, Akaza Research’s business model for support is designed to maximize productivity of clinical trials. Our support is comprehensive and highly flexible, so customers are able to obtain support packages tailored to their needs. In addition, our customers find our support to be of extremely high quality-after all support is our primary source of revenue.

Most of our support isn’t priced “per study” so clients are able to amortize their investment over numerous studies and don’t have to go through a lengthy contracting process for each new clinical trial they want to use OpenClinica for. This can really help to minimize costs and accelerate the set-up time for new studies.

[BZ] What are the pro and cons of an open source technologies versus a classical technology in the SaaS model?

[BB] First, OpenClinica is available under both a SaaS model and local deployment. Open source has a number of benefits over “classical” proprietary EDC systems. Here are a few examples:

–  Reduce vendor lock-in. Numerous proprietary EDC companies have failed and gone out of business. Open source products exist and evolve independently of any particular vendor, so if one vendor ceases to exist, there are others readily available to take their place.

–  Improved security. Open source software is frequently more secure and bug free than proprietary software. The open source code is continuously (and often intensely) scrutinized by large community developers and security experts. As a result bugs and security issues are found and fixed usually before they become real problems.

–  Readily customizable. Open source systems can be readily customized and extended–you don’t need to rely on a vendor who may or may not make the software modifications you need. If the system doesn’t work the way to want it to, you can change it.

–  Enhanced validation. Validation can be much more thorough with open source software. Buying proprietary software is like buying a car with the  hood welded shut-you don’t know what’s really know going on behind the scenes. Open source provides the highest level of transparency making it possible to truly validate a system from end-to-end.

Using OpenClinica for ICF-Based Data Acquisition

The use of electronic data capture (EDC) systems in health care, and especially in clinical trials, has been the object of significant research given the potential advantages like improved data quality, reduced cost, and increased trial repeatability. Despite significant interest and promised benefits, real adoption has been somewhat limited to date with most successful implementations performed in the field of pharmaceutical clinical trials. This can be attributed in part to the lack of underlying consistent and reusable internal data models and the high cost and complexity in customizing most EDC systems.

A potential alternative to traditional EDC software is the use of Open Source Software (OSS), broadly defined as software that is distributed as a freely available and freely modifiable system. This freedom gives the user the opportunity to perform structural modifications and adaptations to better integrate the software with pre-existing IT infrastructures, or to adapt it to local needs and requirements. There are many examples of large scale open source software (OSS) systems in health care, including the VISTA electronic health record system, used in the US Department of Defense and in several hundred installations across the world, the Care2X system, Indivo health, and the OpenClinica EDC system. The use of open source software facilitates the harmonization of a coherent and comprehensive data model that can be reused across different systems. In our work, ICF (the WHO classification for functioning and disability) has been selected as the underlying representational model, and implemented in the OpenClinica EDC software. The experimentation involved more than 10 Italian regions, with multiple hospitals and care centers. The EDC system was designed to test the effectiveness of ICF as a basis for data collection on disability and functioning in a wide spectrum of pathologies.

The complete WHO-ICF classification was imported from the CLAmL XML representation into the LexGrid editor, a tool created by Mayo Clinic for the purpose of editing and maintaining ontologies and classifications. Starting from this intermediate representation, the classification was first translated into the Italian language and then exported back into the CLAmL representation; this form was also used as the basis for the creation of the internal EDC data model, later imported into the OpenClinica platform. From this visual representation, a group of experts designed the set of forms that comprise the web application; later, the database structure and the final application templates were fixed and published on a public web site. The joint use of ICF as a representational model for an Electronic Data Capture system, coupled with the choice of open source software, yielded a significant reduction in the cost and implementation time of a multiregional EDC system. The ease of use of the web interface also facilitated interactions with medical experts to quickly implement alternative data representations and to create a stable and fast platform that is currently being used in an actual trial. OpenClinica demonstrates that open source is stable and ready to be used even in the strictest clinical trials, and that by using open source it is possible to create clinical research applications in a faster and more cost effective way.

– Carlo Daffara, Connecta

OpenClinica 2.5 is Here!

It is with great excitement that I can finally say the production release of OpenClinica 2.5 is here! It took a lot of hard work and dedication not just from our developers, but our testers and community contributors as well.

Please go here to download the latest and greatest offering of the preeminent open source application for electronic data capture and clinical data management. You will need to have an account on www.openclinica.org to download it.  If you don’t have one you can register for one.

In the download package you will find installation scripts for both the Oracle and PostgreSQL databases on both the Linux and Windows operating systems. In addition, for folks currently using version 2.2.1 or 2.2.2, there are scripts to upgrade your instance to OpenClinica 2.5.

Everyone will be able to experience the robust new features of the application including Bulk Data Import, Improved Query Management and Resolution, Cross Form/Cross Field Edit Checks, and Editing/Copying Datasets. Also, we have removed the need for a nightly data warehouse script to run and now you can extract data in real time.

Please join Akaza Research on October 7th for a free webinar introducing OpenClinica 2.5. You can sign-up here:

Webinar @ 19:00 – 20:30 (GMT -5:00)
Webinar @ 9:30 – 11:00 (GMT – 5:00)

Of course we’d highly recommend attending a training course so you too can become an expert user of OpenClinica. Our first open enrollment training on OpenClinica 2.5 is being offered October 15-17.

Thanks again to everyone for making this release a success!

– Paul Galvin