Within the life sciences, Computer System Validation (CSV) and system-remediation projects bring a full set of challenges: agreement on risk and which areas to focus on, gaining a clear understanding of the technology that underpins compliance needs, defining and correlating industry & company standards to a wide variety of SDLC documents- to name just a few.  As pharma and biotech companies increasingly develop regulated-solutions using agile frameworks, the ability to recognize and consistently apply critical success factors to CSV efforts becomes even more relevant.   

I’ve listed six key components of an optimal CSV framework here; these components can help a validation / qualification program meet compliance requirements AND budget objectives, will make efforts more effective and efficient, help focus resources and time on the correct priorities, and provide a robust CSV and quality framework as an outcome of CSV-program investment.

These components are:

Structure: validation programs with a high degree of structured knowledge and explicit documentation (that provide guidance on standards and “how-to” logistics) will put less reliance on skilled staff to make sporadic discretionary judgements about operational details.  This knowledge base will also get junior team members operating effectively in a shorter time.  Things to consider: is there a defined CSV/SDLC methodology? Is it clear of overlap, ambiguity, or conflicting guidance? Is there cohesiveness between high-level guidance documents and lower-level specifics?  Is there a program infrastructure for robust document storage & revision tracking?  Is there a shared body of meeting outcomes, standards, and compliance decisions that team members can draw from and contribute to?

Culture & Commitment: There should be an emphasis on achieving quality, not just producing artifacts that represent quality.  Management should demonstrate the desire to instill and build CSV capability as an effective process and a measured competency.  It’s also important to recognize that high-caliber people are needed to develop this organizational competence, and their time, focus, and discretion will be needed in large amounts at the outset; even if they play key roles within ongoing operations of the quality organization.

Knowledge: Immature CSV efforts frequently over-rely on ad-hoc decisions from key individuals. Operational direction and understanding within a CSV project commonly looks like:

Implicit-knowledge = ad hoc spotlighting (i.e., senior quality members on the project are needed to answer questions of “what should we do” and “what about…“  as they occur; frequently on a recurring basis)

when actually, CSV projects should evolve so they operate from:

Explicit-knowledge = street-lighting (knowing in advance what potential obstacles and decisions lie ahead, and having complete visibility on what needs to be done to reach the destination)

As much as possible, CSV projects should look to convert implicit internal knowledge by senior staff about validation approach, logistics, and standards to documented explicit knowledge that can be leveraged by all program team members. 

Organization: The ideal CSV project mix has strong players in the following roles:

  • a Quality Representative able to take a holistic view of CSV and advocate for product integrity / safety
  • an IT Representative who can translate highly-complex technology aspects, so quality representatives can make informed decisions
  • a Program / Project Manager capable of triangulating stakeholder viewpoints into shared decisions and who can aggressively articulate what the project needs to succeed
  • a Business Representative who can communicate business context and anticipate areas of regulatory scrutiny.


Process Execution:  If you were to make a list of the top ten possible risks (related to CSV & FDA compliance) that keep you awake at night; is your organization and effort focusing on them by order of priority? Don’t spend 35% of effort on risk #10 at the expense of risks 1-9.  Secondly, the CSV process generates work product- so, the standard benchmarks of process execution are key.  Evaluate for timely decision-making, information and asset re-use, documented standards, and rapid escalations of questions / issues.

Measures of Performance:  with the above components operational, performance measures will help refine the framework you’ve put in place.  Some common enemies of CSV efforts are in-efficient processes or artifacts, delayed decisions, extended or repeated document reviews, and ambiguous methodologies and roles.  Ensure your performance measures capture these and others; heat map dashboards will help convey CSV process performance to stakeholders.


To Conclude:  While the ability of CSV artifacts to withstand regulatory scrutiny is a key concern of stakeholders- it is also critical to understand how organization, program and process dynamics, and human nature can determine success or failure for a CSV effort (and its degree of effectiveness and efficiency). Establishing some key program-structure components will ensure project success, help meet business objectives according to priority, and provide a robust ongoing CSV capability.