Can the Life Sciences Industry Adopt Cloud Computing?

posted on September 10th 2014 in Solutions with 0 Comments /

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Life sciences companies are adopting cloud computing and software-as-a-service (SaaS) IT models, particularly in the areas of sales and marketing. There is an opportunity to extend the cloud’s impact into areas such as R&D and supply chain. However, there are legitimate concerns about protecting intellectual property and demonstrating compliance with industry regulations.

The primary two concerns our clients express when it comes to leveraging cloud computing for hosting clinical data and related systems are a potential lack of compliance and the potential loss of governance due to using third-party cloud providers.

There are four primary challenges to overcome when using cloud providers for cloud-computing and SaaS IT models including:

1. Physical security of the data center

Cloud hosting providers can often overlook the importance of physical security because they tend to focus most of their efforts on electronic safeguards.  To ensure that a cloud provider has the proper physical safeguards in place, it is necessary to perform adequate due diligence by conducting onsite audits of providers to evaluate their capabilities and compliance with applicable regulations.  Some of the areas to verify during audits include:

  • The building’s physical characteristics (thick walls, locked doors, limited entry points, etc.), think warehouse, not office building
  • The presence of security personnel at the facility, preferably 24/7
  • Continuous monitoring via security cameras
  • Process and measures to ensure that access is granted to authorized personnel only
  • SAS70 or SSAE16 compliance

2. Logical security

Data centers are becoming magnets to hackers all over the world due to the increasing value of information and sensitive data. It is important to ensure that the chosen cloud provider utilizes multiple layers of protection including redundant network firewalls, proactive monitoring, and logging and alerting capabilities. It is also critical to employ strong encryption  algorithms to sensitive data, not only during transit but at rest as well.

3. Share network and computing resources

By definition, cloud providers employ shared pools of resources to be utilized across multiple clients. This increases the risk of security breaches and also raises a concern about performance degradation due to over-provisioning virtual resources.

One way to to address these concerns is to use a dedicated virtual machine per hosted client (subject to project budget of course). While having dedicated server(s) may increase cost, it minimizes the security and performance concerns and offers clients more confidence in adopting software and services hosted in the cloud. Additionally, it allows clients the opportunity to follow their own software upgrade schedule, which ensures that their documentation and training activities can be done on a schedule that makes sense for them.

4. Customizable disaster recovery and business continuity plans

The life sciences industry often requires rigorous backups and solid disaster recovery plans that vary by client depending on their size and the type of data they store and work with. It is important to look for cloud providers that can provide customized backup schedules, storage options, restoration time, and backup rotation and retention that meet different and varying needs and requirements.

The cloud is becoming more sophisticated and offering better overall security and solutions tailored specifically to industry needs. Life sciences companies have the opportunity to accelerate adoption of the cloud across broader parts of their organization to accelerate new-product development, improve patient outcomes, and enable expansion into new markets, all while reducing costs and creating a more agile operating model.

Is your company is adopting cloud-based solutions and systems in R&D functions? If so, please share your experiences and challenges in implementing and using cloud-based systems in clinical trial operations.

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