Regulated Digital Transformation Wrap Up

Regulated Digital Transformation Wrap Up

Over the last few weeks we have spent a fair bit of time discussing digital transformation in a regulated environment. From the business and technology requirements driving the need to make the transformation, to best practices, to common pitfalls that we’ve seen teams run into, to leveraging a data-driven methodology to enable the transition while effectively managing compliance requirements, we’ve covered it all.

Still, given that all that information was spread over the course of multiple posts over multiple weeks, wouldn’t it be nice to have a summarized version instead? Afterall, perhaps you are too busy to go back read them all in their entirety. Or, let’s be honest, perhaps you just don’t want to be subjected to my often rambling dribble and poor attempts at entertainment for that many pages.

And you know what? I don’t blame you for that, dear reader. And no, you need not worry or apologize. My ego will not irreparably hurt or damaged by the cruel admission that you find my my writing to be full of "rambling dribble" and "poor attempts at entertainment". Your judgements are harsh but I'll continue regardless!

However, I hope you disagree with the reader described above and you actually enjoy these blog posts. If that's the case, and you would like to read the original posts for a more detailed description and explanation of the items I will be so briefly summarizing here, fear not! I will link back to each individual post throughout this summary for those of you who preferred reading the whole book rather than the CliffsNotes in college.

To start, let’s recap the "why" and "where" side of things by outlining some of the drivers behind the ongoing need for many regulated teams to begin their digital transformation journey (original post here).

  • Globalization and the increasingly dispersed and remote nature of the workforce (which the current crisis may only further increase)
  • The accelerated pace of development and delivery of drugs and medical devices putting increased demands on associated computer systems
  • Emerging technologies which are forcing an evolution from traditional methodologies
  • Siloed systems and teams which create a blindspot in the enterprise-wide view of compliance risk
  • Mergers and acquisitions resulting in redundant systems and disparate procedures and process across a “unified” organization
  • Economic pressures and business demands to increase competitiveness by shortening development times and reducing cost
  • Outsourcing and sub-contracting putting a strain on the ability to control and govern people and processes
  • Keeping up with the ever-changing and evolving regulatory environment

As a result of these drivers, traditional validation methodologies rooted in document-based approaches (whether paper or electronic) have become increasingly burdensome, disruptive, and hindering as teams try to adapt and evolve to meet the demands of the changing landscape outlined above. Abandoning the document - in its physical or digital form - becomes almost required to make a true digital transformation, but effective and efficient compliance management and execution must be infused as a seamless part of that......which leads us to the "what" part of the discussion.

This is where data-driven validation comes into the picture, which enables regulated teams to achieve compliance deliverables as a natural byproduct of Agile and DevOps oriented workflows and solutions (original post here). The features and benefits derived from the data-driven methodology highlighted here are a crucial and focal requirement for regulated teams as they move through modernization initiatives.

  • Real-time insight and access to data associated with compliance deliverables, enabling nimble adjustments to avoid large compliance breakdowns
  • Repeatable processes across SDLC tools and teams enabling increased governance and reduced risk of error
  • Leverage automation without disruption
  • Comprehensive reporting and analytics with a full panoramic view of the CSV landscape
  • Capture traceability of validation deliverables across the full software development lifecycle

Okay, so now that we're equipped with the highlights of the “why” and the “where” behind the needs driving digital transformation initiatives, as well as the “what” benefits and functions a data-driven approach to CSV can do to facilitate it relative to traditional validation methodologies, I guess the next question might revolve around the “how”. How does a team get from recognizing these requirements, to then implementing a data-driven approach and successfully undergoing digital transformation in a regulated environment?

Wouldn’t some best practices guidelines and common pitfalls to look out for be helpful? Well, you’re in luck, because we have compiled just such a breakdown for you (part 1 of original post here, and part 2 here)…..

  • Perform detailed system analysis to accurately assess overall “system” risk
  • Create a comprehensive Agile CSV strategy that is:
    • Risk-based
    • Systems-based
    • Data-based
  • Implement strategies for reducing cost and complexities of compliance
    • This sounds obvious, but use transformation initiatives to evaluate and weed out overly burdensome, overly complex, or just plain unnecessary processes
  • Develop a comprehensive project plan that includes
    • Project scope
    • Inventory of all GxP systems
    • Comprehensive testing approach
    • Requirements traceability matrix
    • Well defined team and responsibilities
    • System acceptance and release (including e-signatures)
    • Data archiving
  • Create an effective team consisting of all key stakeholders - transparency and communication early and often will remove roadblocks and disruptions
  • Record the validation process
  • Audit all third-party providers
  • Implement consistent periodic reviews
  • Provide regular, ongoing training

It all sounds pretty simple when I just summarize, doesn't it? The simplicity, efficiency, and effectiveness really arrives on the other side, once the major hurdles of transformation and modernization are crossed and a data-driven validation methodology is applied across a team's SDLC. While everything we've outlined does offer a nice high level (it is just a summary, afterall) view of things to prepare for and expect, this type of initiative does require meticulous preparation, early and often communication, and a diligent, concerted execution. 

Not to toot our own horn too much, but this is something that our clients frequently engage us on from both consultative roles, to complete  delivery, so we would be more than happy to discuss this in more detail with anyone who is considering putting this type of initiative on their project slate.

In the meantime, feel free to download this case study detailing how Tx3 and our VERA DevOps solution helped one of the largest biopharma organizations successfully achieve an Agile transformation across the enterprise.


Also, we recently hosted a webinar on SDLC Modernization along with Allergan and much of the content ties in with this series. You can view it at the link below if you are interested.

View Recording Here

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