OpenClinica 3.1.3 Now Available

We are thrilled to announce the general availability OpenClinica 3.1.3. This latest release of the OpenClinica clinical trial software provides over 100 fixes and enhancements, including:

  • Improved performance and stability, including 80% increase in max user load and 40% faster page turn times
  • Numerous improvements to OpenClinica’s internationalization/localization support
  • Support for CRF version migration of individual event CRFs
  • Enhanced security with strong password configuration options
  • Greater reliability when entering or editing data in repeating groups
  • Ability to run rules at data import and when loading data via web services
  • Fixes to nested simple conditional displays in CRFs

For a more complete overview, you may view the 3.1.3 release notes.

Download OpenClinica 3.1.3 Community Edition

Three Things I Learned About Export Job Performance From My Uncle Paulo

1. “Realize you can try to do it all…but you’ll do it slowly, very slowly.”

It’s understandable that there may be a desire to export every single dimension, for every CRF in your study, for all time. However, if that export takes 15 hours, then a job starting during off-hours may impact users the next business day, or worse, users in an alternate time-zone who may just be starting their work day.

It’s better to first get a sense of how long a small subset (e.g. reducing the temporal scope to a month) of data will take, manually, and take the elapsed time for the export to complete and multiply by the scope quotient (i.e. estimated total scope divided by reduced scope) to figure out a rough estimate of how long your export may take.

2. “Those temporal scope fields are your friend.”

If you don’t choose a temporal scope for your dataset, you will get data for a wider timeframe than you’re likely to be alive. This is may be fine for a dataset with a few dimensions, or if you happen to be looking for specific data you aren’t sure you may capture accurately with too narrow of a time scope.

However, if you KNOW what the scope is, you should specify this. This is more important with very large dataset. Breaking the dataset down into smaller scoped datasets will give you the flexibility of manageable chunks of data to schedule for export.

3. “Let your jobs breathe.”

You wouldn’t schedule two appointments, one after the other, if you didn’t know what time the first appointment would end, would you? The same idea applies to scheduled export jobs. While there’s nothing inherently wrong with scheduling one job after the other, you can only get away with this when you have a clear sense of when the first job may end. If you don’t have any idea when the first job may end, while the first job may complete successfully, the second will not if it is overrun by the first. When in doubt, give your jobs enough time to complete, by spacing them out.

Remember, it’s better to measure twice, and cut once. (My uncle Paulo didn’t actually say this last one.)

– Tope Oluwole

Clinical Trials in the Cloud

I got a phone call the other day from a longtime OpenClinica user about the announcement of our new OpenClinica Optimized™ Hosting. He remarked on how leading companies in the industry (including his) are making big investments in cloud computing products and services, because these technologies provide easy-to-access functionality on an infrastructure that is more redundant, scalable, and cost-effective than you could hope to build or buy on your own.

However, in the clinical research field, putting together such an offering is not for the faint of heart. Though our free OpenClinica Community Edition has been installed and run by users on cloud servers for years, our OpenClinica Enterprise Edition offering (which carries regulatory guarantees) would have to meet rigorous reliability, security, and regulatory compliance requirements. How can this be accomplished if you don’t actually know where your data physically resides at any point in time on the cloud?

Prior to the launch of Optimized Hosting, we offered each hosted customer a dedicated server or two server (application + database) setup. This provided a certain peace of mind from knowing that your clinical data lives on a dedicated piece of hardware, but for many the costs were high and suffered from the inherent limitations of being tied to a physical machine. At the end of last year our data center partner achieved SAS 70 Type II certification for their cloud services, and we decided it was time to begin diligence on a cloud-based offering for OpenClinica.

We have spent the past 9 months listening to our customers’ needs and concerns, a designing and testing a solution. The resulting OpenClinica Optimized™ Hosting is an innovative hybrid architecture that provides the best of both worlds:  the scalability, high availability, and flexibility of the cloud combined with the peace of mind that your data lives in purpose-built dedicated hardware.Clinical Research in the Cloud

In short, OpenClinica Optimized Hosting offers greater fault tolerance, with better scalability and performance, at a lower cost than alternatives. Here’s how it works:

Application

Each OpenClinica application instance is a cloud server cloned from an image that has been qualified according to our exacting installation instructions. We configure the instance according to the customer’s supplied configuration parameters and complete operational qualification (OQ). The instance is typically available and ready for production use within a day or two. Thanks to the cloud, computing resources are instantly scalable on-demand.

Database

Dedicated (non-cloud) high performance database machines are configured in a master/slave relationship to provide instant data replication and fault tolerance. By utilizing multiple slave databases located in different geographic regions, the OpenClinica Optimized Hosting database cluster is designed for zero data loss even in event of nuclear strike. The servers use the fastest hard disk technology available today (Fusion-io®), dramatically improving database performance. For example, in our testing, we commonly see data extracts run up to 10x faster than in the prior environment. Database servers are physically isolated via CISCO ASA firewall to eliminate all nonessential access credentials.

Validation and Compliance

OpenClinica Optimized Hosting provides maximum flexibility and transparency in the area of change control and compliance. It has been constructed around a carefully designed set of controls to ensure all updates are fully tested (and documented) in the environment prior to release, and that customers can have upgrades and maintenance releases applied according to their individual schedules and priorities.

One of the great advantages of OpenClinica is the choice it offers – you can use and extend the open source licensed code, you can choose between OpenClinica Community Edition and OpenClinica Enterprise, you can deploy it locally or choose the hosted option. Or, any combination of the above. The new Optimized Hosting environment enhances that choice by providing a fast, reliable, and cost-effective way to get up and running with OpenClinica.

For more on security in OpenClinica Optimized Hosting, see Clinical Trials in the Cloud – Part II.

– Cal Collins

OpenClinica 3.1 is Finally Here!

After nearly 20 months, OpenClinica 3.1 is finally ready to meet the world as a production ready application.  You may download OpenClinica 3.1 here.  It has been a long and arduous road, but the final incarnation of 3.1 is the most significant leap forward for the OpenClinica clinical trials software.

OpenClinica 3.1 further accelerates clinical productivity and enhances the clinical trial experience in a number of notable ways:

  • Improved data entry save time and increased performance for accessing large amounts of data.  The architecture around the data entry process in OpenClinica was re-factored to allow more concurrent users accessing the system while conducting more intensive simultaneous processes.  With this re-factoring, page turn times have seen a 10x (and sometimes better) speed improvement.  At the same time, large extracts which had to be broken into smaller subsets in the past can now be executed in a single batch.
  • Skip logic to ensure data entry users only see CRF fields and sections relevant to entering their data.  When a user accesses an eCRF to enter data for a patient or subject, they will only see the fields pertinent to be collected at that time.  Logic can be built in to the eCRF to show or hide additional fields based on the values provided in previous questions.
  • Streamlined discrepancy and query management infrastructure that allows issues around questionable data to be resolved more quickly.  A new interface for creating and responding to discrepancies, as well as new filters for query aging, to support faster resolution of data issues.  The number of clicks for filtering/sorting discrepancy notes, viewing the data responsible for the discrepancy note, and returned back to your filtered set of reports has been cut in half.
  • GUI-based creation, testing, and management of complex cross field/cross form multivariate edit checks.  A simple drag and drop interface has been implemented to facilitate the faster creation of complex edit checks.  This new interface interacts with authorized OpenClinica instances to speed up the study design process for OpenClinica Enterprise edition clients.
  • Plug-in architecture for exporting data collected in OpenClinica which supports the transformation of data into any output format.
  • OpenClinica Data Mart to easily report clinical trial results collected through OpenClinica.

These last two items have been covered extensively in previous blog posts.  Please see Plug-in Architecture for OpenClinica Data Extracts and Video Demo of New OpenClinica Data Mart.

We will be hosting an OpenClinica Community Virtual Forum shortly to demonstrate some of these new capabilities.  Also, keep this blog on your RSS feed or bookmarked in your browser, as future posts will dive into more details of the new features and functionality in OpenClinica 3.1.

– Paul Galvin