Life sciences companies have historically lagged in their cloud and emerging technology adoption due to burdensome regulatory requirements and risk-averse cultural beliefs. However, the global pandemic has forced regulated companies to rapidly shift from a Cloud-First strategy to a Cloud-NOW strategy and adopt new operating models to maintain business continuity and enhance their workforce experience to accommodate remote employees globally.
Much of this shift to the cloud has come in the form of business applications that enable capabilities like secure workflows, electronic signatures, audit trails, and access to digital content management to ensure employees can continue to collaborate remotely. Yet real business value comes in the ability to link, share, and analyze data in new ways, both within the organization and increasingly from outside through partners, customers, and suppliers. Cloud platforms are instrumental in breaking down silos of data from business applications and other areas of an organization’s technology stack to integrate workflows, making data scalable, available, and accessible without sacrificing security and compliance to drive innovation across the enterprise.
Further, the cloud can offer life sciences companies access to new tools and technologies in areas outside of the core competencies of traditional life science organizations. These include areas such as artificial intelligence (AI), machine learning/ deep learning (ML/DL), natural language processing (NLP), and robotic process automation (RPA) to more tailored product innovations for the life science sector. These new cloud capabilities are already enabling ground-breaking life sciences companies to confront both process and data challenges that were impossible just a few years ago. Beyond merely enhancing process integration and data analytics challenges, cloud computing can be a key component of any sizeable digital transformation effort in any life sciences organization.
Until now, there has not been an accessible, packaged solution for GxP workloads inclusive of infrastructure management and control, cloud services management, and business applications. Workloads refers to any GxP related business process and regulated data (i.e., security, strict controls, governance, data management, etc.). While some rigid solutions based on traditional computer system validation (CSV) models exist, they do not address the challenge of operating in a very dynamic public cloud environment and are cost prohibitive to maintain.
Today’s regulated business workloads require a new level of flexibility and scale to handle the needs of life sciences business. In this white paper, we will introduce a new solution – USDM Cloud Assurance – for continuous compliance of regulated workloads on the public cloud that is accessible, scalable, and designed to address global infrastructure (IaaS), cloud service platforms (PaaS), and business application software (SaaS).
To continue reading Regulated GxP Workloads in the Public Cloud, download the complete white paper.