The past decade has seen unprecedented adoption of new clinical technology. However, clinical trial sponsors and CROs have not yet been able to fully realize the promised value of their technology investments. The widespread adoption of electronic data collection systems, including EDC, CTMS, Safety and IRT as well as the increasing prevalence of data standards, such as CDISC, have greatly improved the quality and quantity of clinical data. Yet, sponsors and CROs still lack the tools they need to unlock the full value of this data. The primary problems stem from the fact that different data sets remain relatively siloed, making it difficult to discover information that exists across data sets. As a result, data analysis process is filled with delays — from waiting for data upload to waiting for programmers to develop the desired queries and deliver the results.

The next wave of clinical IT innovation will address these problems, initiating a new era of efficiency and interoperability. New IT tools will help stakeholders make decisions more quickly by making the data more accessible and easier to query, which will enable domain experts to ask questions across all relevant data without relying on programmers. These innovations will help identify safety issues and trial bottlenecks earlier, allow for quicker database lock, and ultimately lead to effective drugs getting onto the market sooner, saving lives and helping the sponsor and CROs realize more value from their research pipelines.

The new technologies that will play a key role in this next wave of IT innovation over the coming five years will likely fall into one of three areas:

• Databases, Collections, Storage, and the Cloud,
• Connecting Data, and
• Extracting Information.  

Data Collection, Storage, and the Cloud

Advanced privacy features will be implemented through all layers of clinical technology, helping to protect patient data and ensuring patient privacy is maintained. Next-generation systems will make it possible to attach privacy metadata to the patient data. As patient data is moved from system to system, privacy metadata will be kept intact. All systems will respect this underlying metadata, so if a patient’s data was collected with specific restrictions — such as anonymization within 18 months — these restrictions will be encoded and transmitted with the data. Wherever the data resides 18 months after collection will respect the metadata and anonymize accordingly.

Modern data storage systems will allow large amounts of data to be stored across dozens or hundreds of machines. It is now possible to hold and analyze data on scales that were considered impossible just a decade ago. The next wave of innovation will focus on optimizing for speed, allowing users to run queries across all of the stored data sets in real or near-real time as data is being uploaded to the system. These multi-machine systems will run on commodity off-the-shelf hardware, and are substantially cheaper and easier to maintain than a single, large-capacity machine.

As cell phones and other technology become more and more ubiquitous, they will help facilitate automatic data collection. The ease of creating new devices that work in conjunction with the iPhone, for example, will allow trial designers to collect more data more accurately. In the near future, expect to see several different types of new equipment that will be able to objectively and reliably record a variety of metrics, from blood pressure or heart rate to motor coordination or alertness level, instantly transmitting them through cellular or wireless networks back to the EDC systems in the sponsor’s or CRO’s datacenters. It will also become even easier to collect patient reported outcomes through advances in electronic patient reported outcomes (ePRO) systems.

Cloud computing will reduce the cost of hosting advanced data systems, especially as more cloud vendors develop HIPAA-compliant hosting for storing sensitive patient information. Once there is a competitive market for HIPAA-compliant cloud hosting, the cost will drastically fall, and it will soon become an option to host all data collection systems on a cloud-based system. Cloud computing will provide its users significant advantages by allowing them to dynamically scale their storage and processing power at all stages of a study, which lowers costs and makes it feasible for smaller organizations to utilize processing capabilities that were previously available to only the largest companies with the most hardware investment.

Social networks will become more useful with various aspects of clinical trials, most immediately patient recruitment. We are already seeing social networks and patient communities spring up around various conditions, and such communities can be an efficient means for sponsors and CROs to identify potential study participants and perhaps conduct post-market analysis. However, as with most social media tools, sponsors and CROs will likely need to tread carefully in this area in order to avoid raising privacy concerns with their intended audience.

Connecting Data

The industry will see further integration of Electronic Medical Record (EMR) and Electronic Health Record (EHR) systems into clinical trials. Many regulatory and statistical issues must be addressed in order to make this possible, but the potential benefits can be extremely powerful. For example, it could make available a more thorough record of a patient’s medical history. One major difficulty of this integration will be the ability to reconcile different encoding standards used by various systems, for example HL7 vs. CDISC. A common issue is that the data in hospitals and in clinical research resides in completely different systems. For example, EMR systems are often sold as Software as a Service (SaaS), whereas the clinical systems are often on site and the clinical data collection systems typically reside in a CRO’s datacenter. However, the next five years will bring the adoption of technology that makes it possible to connect these disparate data sources. EMR and EHR integration will also have an impact on patient recruitment, making it easier to find patients who pass the study’s inclusion/exclusion criteria, especially for some of the harder-to-recruit for indications.

Data standardization will help connect data in new and innovative ways, and will continue to become more advanced and prevalent throughout the industry, aided by the maturing of standards like CDISC and HL7. As standards become more sophisticated, modern software tools will become available and will fully utilize these standards. These tools will be able to infer additional information encoded in the standard, and will be able to use that information to improve the usability of the software. Ultimately, this will lead to more powerful tools that will help data managers, clinicians, and executives become more effective in their jobs.

Through enhanced data security, clinical IT will usher in more advanced systems that will ensure data security, integrity, and blinding. There are now technologies that keep track of who looks at what data, which is beneficial in terms of security as it can make it physically impossible for a user to access data that they don’t have permission or credentials to see. Software tools at all levels of the stack will make it impossible to unblind a study by the wrong user. 

Advanced cross-datasource analytics will make it possible to look at all relevant data for one or more studies. These systems allow sponsors and users to work in real time, without having to move the data into a new data warehouse, which can be very costly from a regulatory compliance perspective. Advanced analytics allows sponsors and CROs to see and understand information as soon as it hits the database, regardless of where it resides. In turn, this will prevent bottlenecks, save costs, and help identify dangers earlier in a study. It will also enable sponsors and CROs to find hidden dangers by analyzing data from numerous studies simultaneously.

Extracting Info

Real-time alerting that is reliable and flexible will help all aspects of trial development and execution. Allowing users to set watches on the most relevant data to their task will help them identify problems and more quickly execute actionable items. For example, imagine an adverse event that comes in and needs to be reported. When the adverse event is first entered into the system, an alert will go out to the translation team, which must make sure it’s coded properly and translate the language, if necessary. Once they’ve finished, the result is saved and a new alert goes out to the team that is responsible for filing the alert with the appropriate organizations, for example regulatory bodies or the IRB. This type of alerting is actually becoming more and more important. Since the EDC systems that have been put in place make it possible for sponsors and CROs to monitor data earlier in the study, they need to start getting more sophisticated in how they handle this data. Because they, in theory, have the data in an accessible form, it is their responsibility to make sure that the study is safe and to utilize this data.

Next-generation statistical software will become more prevalent. For the past 30 years, SAS has been extremely dominant in the clinical trials space, despite being difficult to work with and slow to innovate. Over the past several years alternatives have become more popular, such as the open-source language R. Now, we’re starting to see R replacing SAS in many ways, and it looks like this trend will continue. As this happens, we will see broader support for R across all clinical software, especially in analytics software.

Interactive dashboards will help decision makers get access to data earlier, granting a high-level overview in real-time or near-real-time. A dashboard is simply a way to combine multiple visualizations and reports, all in a single view. Dashboards make it possible to understand the most important high-level metrics very easily. Decision makers can then be in a better position identify bottlenecks or problems as early as possible. This becomes particularly helpful if the dashboards pull in data across all relevant datasources, empowering the decision maker to understand all aspects of the trial or business. Next-generation dashboards are perfect for CROs that are looking for the edge when it comes to giving their customers advanced and powerful access to the data. 

The next five years will be an exciting time for the clinical industry and there will surely be many changes. These changes will help usher in the new wave of innovative tools and services that will benefit sponsors and CROs and, ultimately, patients.
 

Rick Morrison is chief executive officer of Comprehend Systems. He can be reached at [email protected].