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Transitioning to Cloud-based Solutions Within the Clinical Research Industry
Article

Transitioning to Cloud-based Solutions Within the Clinical Research Industry

Transitioning to Cloud-based Solutions Within the Clinical Research Industry
Article

Transitioning to Cloud-based Solutions Within the Clinical Research Industry

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Sudeep Pattnaik, ThoughtSphere

Clinical research, trial management, and implementation can be costly, complex and time-intensive. Traditionally, clinical trials data and documentation have been kept as paper records, which compromises security and is inefficient. Digitizing clinical processes mitigates these issues, but many in the clinical research industry are taking it one step further and transitioning to cloud-based solutions for improved medical research and drug development efficiency. Big data analytics and distributed computing are two cloud-based techniques which can centralize computational and research tools. 


Naturally, as with any relatively new technology solution for a regulated environment, hang-ups persist with regards to security and regulatory compliance. Despite the cloud’s potential to maximize data security, the misconceptions around the risks and pitfalls still cloud perceptions of how beneficial this technology could be. It is important to weigh up the benefits of cloud-based computing solutions with the potential downfalls, and address the ways in which platforms can be improved and optimized in the future. With the ability to keep the spiraling costs of clinical trials under control, and provide on-the-fly data analytics, cloud-based solutions are on the rise and are a key discussion point for trials management teams across the industry.

Computing comparisons


Firstly, it is important to discuss the differences between cloud storage and cloud computing. The former is a model network of online data repositories where data is stored and hosted by a third-party server, and the latter incorporates software into the storage system and provides the mechanisms for data management. The National Institute of Standards and Technology (NIST) has identified and described four different types of cloud computing deployment models,1 with varying capabilities depending on the objectives of the user:

Private cloud (single tenant): exclusive use by a single organization, situated on- or off-site, and managed either by the organization, a third party, or both.

Community cloud: exclusive use by a specific community of users from organizations with mutual goals, situated on- or off-site, and managed by one or more of the organizations, a third party, or both.

Public cloud (multi-tenant):
Open use by the general public, situated on the premises of the cloud providers, and is managed by an academic or government organization, or by a business.

Hybrid cloud:
An integration of two or more separate cloud infrastructures (private, community or public) which remain distinct entities. They are bound by standardized technology that enables data and application portability.

When these cloud systems are compared with traditional computing approaches in clinical trial management, it is clear that the capabilities are beyond those of previous approaches. Hybridized cloud infrastructure can also include merging cloud systems with traditional IT, which makes this model popular in large enterprises. Such infrastructures are agile and scalable, therefore, supporting complex business services, particularly clinical trials.


Using the cloud in pharma: Dispelling the myths

There are a number of pre-conceptions about using the cloud in the pharmaceutical industry, such as difficulties maintaining validation, long implementation timelines, and lack of data security, privacy, integrity and segregation. It is often thought that the cloud platforms which are conducive to compliance and validation, take longer to implement. This need not be the case if upfront planning of validation strategies are introduced. Planning ahead is an investment, but one which pays off in the long term.

Regulatory compliance, approval from health services and approval from insurance companies all need to be standardized before cloud computing is widely accepted in the clinical trials sphere. Data security must support compliance with the Food and Drug Administration's (FDA) Title 21 Code of Federal Regulations (CFR), specifically Part 11, the Electronic Records; Electronic Signatures rule that requires computer systems and controls be available for FDA inspection.2 Stakeholders must therefore be rigorous with finding the right cloud technology provider, which is sensitive to the particular elements of life science and clinical trial data security and regulations.

Traditionally, the cloud generates more than its fair share of skepticism when it comes to data security. However, the need for rigorous security measures has not directly come from the introduction of cloud computing: whether organizations use paper-based or technology-based data management, data security has always been a primary concern. Data security, privacy and integrity were reported to be top of the list of concerns regarding the implementation of cloud systems in life sciences in 70% of cases.3 If the appropriate cloud platform is chosen, its capabilities should enhance security and privacy, rather than compromise it.

Benefits of the cloud in clinical trial management

Despite the myths and skepticism surrounding cloud security, validation and compliance, there is little evidence to support denial of its ability to provide unparalleled analytical power of disparate, complex clinical trials data. Advantages of using cloud-based clinical solutions are:4

Improved study control

As a result of enhanced clinical trials information, such as user views and permissions, and trial location requirements, decisions can be made faster by the clinical trial manager. Each trial location can be monitored in real-time, for data entry professionals and requirements. Better control also facilitates cross-site collaboration. 

Real-time reporting

Cloud-enabled reporting provides top-quality data for risk-based monitoring (RBM), by making data available in real-time with no data transfer lag time. Managers are immediately alerted to serious adverse events (SAEs), so rapid decisions can be made.

Device diversity

The ability to access data from any device, for example a mobile, laptop, tablet or workstation, means that the physical location of the study, those involved, and the data, do not have to be considered.

Costs efficiencies

IT costs are reduced with cloud-based data solutions, because there is no longer a need to rent storage space for the servers. By its very nature, the time-savings attributed to cloud computing translate into cost savings. Time is saved by ready-to-use, always update software. It is thought that a large, phase three trial can cost between $30M–$60M for a pharmaceutical company,5 so it is unsurprising that a solution is needed now to minimize the IT costs.


The future of the cloud

There is no doubt that the cloud transition is happening now. The clinical research industry is taking the necessary steps to adopt cloud computing for clinical trials management, but is still some way behind other industries in terms of speed of progression and acceptance. Platforms and cloud-enabled products are available, which draw on the latest technologies in big data technology, to optimize the cost of the clinical development process. Such innovative cloud platforms are able to integrate with existing IT solutions, with a seamless and efficient implementation process.

References


1. Mell, P., & Grance, T. (2011, September). The NIST Definition of Cloud Computing [PDF]. Gaithersburg: National Institute of Standards and Technology, U.S. Department of Commerce. Retrieved from: http://nvlpubs.nist.gov/nistpubs/Legacy/SP/nistspecialpublication800-145.pdf. Last accessed: 18 July 2017. 

2. Electronic Code of Federal Regulations. Title 21, Part 11, Electronic Records: Electronic Signatures. (2011). Retrieved from: https://www.ecfr.gov/cgi-bin/text-idx?SID=3ee286332416f26a91d9e6d786a604ab&mc=true&tpl=%2Fecfrbrowse%2FTitle21%2F21tab_02.tpl%

3. Saleem, Y., Iqbal, M., Amjad, M., Bashir, M. S., Hayat, M. F., Farhan, M., . . . Shah, A. A. (2012). High security and privacy in cloud computing paradigm through single sign on. Life Science Journal, 9(4), 627-636. Retrieved from: http://www.lifesciencesite.com/lsj/life0904/096_10913life0904_627_636 

4. Kutac, N. (2014) Using Cloud-Based Technologies in Clinical Trials. Datatrak whitepaper. Retrieved from: http://www.datatrak.com/home/resources/white-papers/

5. Wall, M. (2017, February 21). How drug development is speeding up in the cloud. Retrieved from: http://www.bbc.co.uk/news/business-39026239



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