Benefits of a Flexible SCE

How is the clinical reporting landscape changing?

The clinical reporting landscape is evolving rapidly, driven by technological advancements, market expectations, and the increasing adoption of open-source solutions. However, even amid all these changes, certain fundamental aspects remain constant. The regulatory frameworks that govern clinical reporting remain stringent. Agencies like the FDA, EMA, and PMDA continue to mandate strict adherence to Good Clinical Practice (GCP), 21 CFR Part 11 compliance, and rigorous data integrity principles. Sponsors are responsible for ensuring that their statistical computing environments (SCEs) demonstrate reproducibility, transparency, and traceability—regardless of the technologies in use. Validation remains a key requirement for traditional proprietary software like SAS® or newer open-source solutions. 

It is important to note that regulations are also changing. The past few years have seen significant growth in new drug applications in R from across the industry, with many more planned and regulatory authorities being far more open to accepting new file formats. In 2015, the FDA published a software clarifying statement that stated that they do not require the use of specific software for statistical analyses but that the software used must be documented upon submission.

Factors like this fuel the growing adoption of open-source statistical software across the industry. R, in particular, has gained traction due to its flexibility, extensive package ecosystems, and strong community support. This shift towards open-source software is helping organisations reduce costs, increase agility, and attract a broader talent pool.

Cross-pharmaceutical user groups like Pharmaverse also bridge the validation gap by collaborating to produce opinionated R packages under a shared vision of a trusted set of tools for all. Where in the past, this was constrained by regulation and nervousness about adopting community-developed software, pharmaceutical companies and regulators are coming together to meet this challenge head-on. Added to this, Posit (previously R studio) now offers tools to rigidly manage R and Python packages, allowing for consistent reproducibility of results.

The market is also changing, with increased expectations around reducing time to market for drug compounds, fuelled by the innovations demonstrated through COVID alongside the rise of AI and Generative AI as a productivity enabler.

Organisations also want flexibility and efficiency while delivering trusted results that comply with industry regulations. While many organisations have traditionally adopted complex in-house-built statistical computing environments tailored to their organisational needs, concerns around the cost of maintenance, the need for specialised IT resources, and scalability are driving a move away. Specifically, organisations are looking to move towards more scalable platforms that integrate cloud computing, provide best-of-breed closed and open-source statistical analysis tooling, and support modern development best practices. 

Why flexibility matters

So why is flexibility so important? 

• Organisations are increasingly looking for systems that allow them to scale—both in terms of resources used to manage workloads and to support increased usage. Cloud computing also lifts the constraints on traditional on-premise platforms with fixed resources, which have always been notoriously difficult to update and scale.
• If you ask a statistical programmer what tools they need, they will invariably want the best of both worlds. In clinical programming, that means choosing SAS and Open Source software. Both have strengths and with SAS Viya and its solutions, it is possible to have a single integrated set of tools that provide comprehensive data processing, analytical and data visualisation capabilities. 
• As clinical reporting environments become more varied and collaborative, the importance of version control and auditability has never been greater. Traditional workflows often relied on shared network drives and manual change tracking, leading to inefficiencies and compliance risks. Modern statistical computing environments leverage version control systems like Git to ensure robust source control across all applications, facilitate collaboration, and maintain a clear audit trail. 

What does a Flexible SCE look like?

So, what are the characteristics of a modern statistical computing environment, and how can Katalyze Data help? 

Built to fit – We believe in keeping it simple. One platform with an integrated set of analytical tools that fits your quality system, your requirements and usage and your organisation’s IT and data strategy. Your platform should fit your needs – multiple environments, specific versions of SAS and Open Source, source control capabilities, security model and access to all the necessary tools.

Hosted where needed – Not all organisations are ready for the cloud, and that’s fine. Whether the preference is to have an on-premise platform running in your organisation’s data centre or running in the cloud, fully hosted and available for geographically dispersed teams, we will build it and make it secure. If high availability is important, that will be central to your SCE’s architecture. We will also help you to scale your platform as your organisation grows. 

Fully Supported – We offer a range of support services, from fully managed if required for peace of mind and, if you lack the support resources, to light touch third-line support to back up your IT team. We will also ensure your platform is updated with regular operating systems, analytical software and security vulnerability updates.

The right tool in the right hands – A flexible SCE should accommodate multiple programming languages, including SAS, R, and Python, allowing teams to use the best tool for each task. We partner with SAS and Posit to provide enterprise analytical capabilities through a workbench of tools built on a modern technical architecture. Katalyze’s education team are also here to ensure your teams understand how to use the latest tools and programming languages.

Source Controlled! – Our analytical stack incorporates version control to ensure traceability, collaboration, and compliance with regulatory requirements. If you have a specific implementation of Git that you want to use to manage code repositories, no problem!

Trustworthy analytics – How can we depend on analytics if users can download packages at will? The answer is to put strict governance controls in place. Posit’s Open Source package management capabilities ensure your organisation can manage the repositories used by your clinical reporting teams and manage updates with appropriate revalidation.

User Access Control & Security – Statistical reporting environments need to be secure, whether they operate on-premise or in the cloud, and available to staff, be they permanent or contract. Role-based access control (RBAC) and audit logging ensure that your clinical data remains secure and compliant.

Stamp of validation – Your platform will be delivered and validated for use and load tested to ensure it is performant and fit for purpose, with a full validation trail that demonstrates quality throughout the deployment lifecycle and beyond. Katalyze’s stamp of validation ensures compliance with Good Clinical Practice, GAMP and FDA CFR 21 Part 11 regulations, providing peace of mind. Furthermore, Katalyze Managed Services will help you keep your platform compliant throughout its lifetime.

 How we can help

At Katalyze Data, we believe that not all SCEs are equal, and not all are built or should be built the same. Organisations are unique, requirements are not static, and your investment in a clinical reporting platform needs to ensure your business has the flexibility and agility to succeed. 

Please contact the Katalyze team for a free, no-obligation consultation on how we can partner with you to deliver a validated SCE service that is fit for your business.