Cloud services in a multi-tenant data center generate economies of scale and enable sharing of resources that can reduce costs and improve technology availability while keeping each client’s data separate and secure.

To address rising cost and risk pressures, improve innovation, and focus on core competencies, many science-based organizations across diverse industries including biopharmaceuticals are looking for ways to improve operational agility, lower costs, and collaborate more effectively with industry partners. Over time, these externalized collaboration networks increase in size and complexity. Many combine numerous partners with diverse objectives involving single or multiple research projects that, in some cases, can tie up more than 50 percent of a commissioning organization’s IT budget. Internet-based collaboration solutions such as email, SharePoint, VPN, Citrix and other data exchange mechanisms introduce security challenges, incompatible data formats, and the need to prepare and curate files manually. Such complications can negatively impact data quality, lengthen project timelines, increase failures and reduce productivity.

With these challenges in mind, many life science organizations are turning to cloud-based solutions as a scalable, secure, state-of-the-art informatics environment that also reduces the informatics footprint. The cloud allows organizations to set up a robust collaboration workspace quickly and easily with minimal IT support. The system is available anywhere, anytime—and organizations only pay for what they use. Growing interest in the cloud option is evidenced by a 2016 ServiceNow survey of 1,850 executives and managers in which 52 percent reported having “cloud-first” policies for new technology purchases, an adoption stance that will increase to 77 percent within the next two years.

A 2016 IDG survey of IT and business decision makers found that 68 percent of respondents intend to investigate or deploy cloud analytics solutions over the coming year. Respondents with currently deployed cloud analytics solutions cited the advantages of lower up-front costs (60 percent) over on-premises solutions. They also cited greater agility and faster time to market (61 percent), more rapid and cost-effective scaling for large data sets (60 percent), and improved self-service capabilities for non-technical users (51 percent).

As cloud technology matures and attracts increased attention, organizations are often uncertain about the best way to evaluate, select, and implement a cloud-based research informatics workspace. Organizations investigating cloud feasibility should look for a hosted system that offers strong data safeguards, secure document sharing, and a range of extensible scientific applications.

Secure information management

Successive RightScale State of the Cloud Reports have identified security as the number one challenge of cloud adoption, only dropping to second place in its 2016 report. In 2017, security concerns fell to 25 percent vs. 29 percent in 2016. This shift reflects the incremental effort of cloud providers to adopt recognized security standards and build trust in their user communities. ISO 27001 is one of the most widely recognized and internationally accepted best-practice standards for information security management. Cloud providers should offer ISO accreditation for the systems, technology, processes, and data centers supporting their cloud environments. Systems for safeguarding data need to be certified to an accepted industry standard now and in the future.  

Agile data and document sharing

A successful hosted collaboration system will allow multiple partners to capture and share real-time data and information. Scientists can rapidly access and share research data including experiments, chemical structures, assays and other test results which significantly accelerates informed decisions based on the most complete and current information available. No time is lost on data transformation and interpretation. Data originators ensure that their data resides in the system as intended. The ability to annotate data provides context for other scientists using the information. For research-sponsoring organizations, there is a benefit to keeping data in the cloud, because there can be a clear delineation between the hosted collaboration system and in-house, server-based systems, and data.

Scientific applications supporting defined needs

A cloud-based research informatics system should support a range of scientific workflows, enabling project team members to access the applications and data they need, wherever they are, at any time. Typical applications include:

  • A flexible, multi-disciplinary electronic lab notebook enabling scientists to capture and share experimental methods
  •  A scientific workflow authoring application supporting scientific services, data harmonization/synchronization, standard business rules, and application extensions
  • A mobile application permitting collaborating teams to communicate using mobile devices, easily accessing, searching, and sharing real-time project information
  • Data analysis and visualization applications providing scientific analysis, data pipelining, visualization, and charting capabilities via mobile devices
  • An open portal where scientists can publish and share protocols and reports—enhancing broad dissemination of project information

Implementing a cloud-based research informatics system is a big step. How can organizations effectively measure the success of adopting this technology once it is up and running? They can expect a number of benefits to appear over time including time and cost savings through data exchange and communication automation, reduced TCO resulting from infrastructure in the cloud, shorter project timelines and improved efficiency with cloud agility—all of this making it possible for them to meet changing business needs by spinning collaborations up and down quickly in the cloud. Key Performance Indicators (KPIs) organizations typically use are measures of (1) scientist productivity, (2) IT spending per user/application, (3) time spent implementing new software applications, and (4) average time to start up, run and close down a project. 

By 2020, at least a third of all data will pass through the cloud. More than 43 percent of organizations expect to deliver the majority of their IT capability through public cloud services by 2020, and they will access 78 percent of IT resources through some form of cloud by 2018. The numbers speak for themselves. Now is the time for science-based organizations to begin defining and implementing effective cloud strategies to improve agility, reduce costs, and support end-to-end collaboration dynamics.

Frederic Bost
Senior Director, Cloud R&D, Dassault Systèmes BIOVIA

Frederic Bost is the product director of ScienceCloud at Dassault Systèmes BIOVIA.  He is the creator of HEOS, the first cloud-based drug discovery collaboration platform on the market, which was acquired by BIOVIA in 2012 to become the core of BIOVIA ScienceCloud. Prior to joining BIOVIA, Frederic held several positions in the life sciences industry including global head of Research IT for a large organization.