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Regulated GxP Workloads in the Public Cloud

A USDM white paper on running regulated GxP workloads in the public cloud — why life sciences lagged on cloud adoption, what changed, and how continuous compliance with USDM Cloud Assurance spans IaaS, PaaS, and SaaS.

Regulated GxP Workloads in the Public Cloud
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A USDM white paper on running regulated GxP workloads in the public cloud — why life sciences lagged on cloud adoption, what changed, and how continuous compliance with USDM Cloud Assurance spans IaaS, PaaS, and SaaS.

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What's inside

  • Why life sciences companies historically lagged on cloud and emerging-technology adoption — and how the global pandemic forced a shift from a Cloud-First to a Cloud-NOW strategy.
  • How cloud platforms break down data silos to make regulated data scalable, available, and accessible without sacrificing security and compliance.
  • Why traditional, rigid computer system validation (CSV) models fall short in a dynamic public cloud environment — and are cost prohibitive to maintain.
  • How cloud unlocks AI, machine learning/deep learning (ML/DL), natural language processing (NLP), and robotic process automation (RPA) for regulated organizations.
  • An introduction to USDM Cloud Assurance — continuous compliance for regulated workloads across infrastructure (IaaS), cloud service platforms (PaaS), and business application software (SaaS).

From Cloud-First to Cloud-NOW

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.

Capabilities like electronic signatures and audit trails sit directly under 21 CFR Part 11 electronic records and signatures expectations, and the value of linking and sharing data across the enterprise depends on sustained data integrity as systems and configurations change.

Cloud as a Platform for Innovation

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.

As organizations adopt these capabilities, governing them responsibly becomes part of the compliance picture — an area USDM addresses through AI governance and compliance.

The Gap: No Packaged Solution for GxP Workloads

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.

The USDM point of view In a public cloud, vendors push updates on their own schedules and systems change continuously, so compliance cannot be a one-time validation event — it has to be an ongoing operating discipline. Rigid CSV models that were built for static, on-premises systems break down under that pace and become expensive to maintain. The answer is a continuous-compliance model that spans IaaS, PaaS, and SaaS together, which is exactly what USDM Cloud Assurance is designed to deliver.

A New Solution: USDM Cloud Assurance

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.

FAQ: Regulated GxP Workloads in the Public Cloud

What is a GxP workload in the context of the public cloud?

As defined in this white paper, a workload refers to any GxP-related business process and regulated data — encompassing security, strict controls, governance, and data management. Running these workloads in the public cloud means managing them inclusive of infrastructure management and control, cloud services management, and business applications.

Why have life sciences companies historically been slow to adopt the cloud?

The white paper attributes the lag to burdensome regulatory requirements and risk-averse cultural beliefs. The global pandemic changed that calculus, forcing regulated companies to move rapidly from a Cloud-First strategy to a Cloud-NOW strategy and to adopt new operating models for business continuity and a remote, global workforce.

Why don't traditional CSV models work well for public cloud workloads?

Solutions built on traditional computer system validation (CSV) models are rigid: they do not address the challenge of operating in a very dynamic public cloud environment, and they are cost prohibitive to maintain. Public cloud workloads require a new level of flexibility and scale to keep pace with how often cloud systems change.

What emerging technologies does the cloud make accessible to life sciences?

Beyond core life sciences competencies, the cloud opens access to artificial intelligence (AI), machine learning/deep learning (ML/DL), natural language processing (NLP), and robotic process automation (RPA), along with more tailored product innovations for the sector — helping organizations confront process and data challenges that were impossible just a few years ago.

What does USDM Cloud Assurance cover?

USDM Cloud Assurance is introduced as a solution for continuous compliance of regulated workloads on the public cloud. It is designed to be accessible and scalable, and to span global infrastructure (IaaS), cloud service platforms (PaaS), and business application software (SaaS).

Download the white paper Get the complete white paper on running regulated GxP workloads in the public cloud, including how USDM Cloud Assurance delivers continuous compliance across IaaS, PaaS, and SaaS. To discuss your regulated cloud workloads, contact us.

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