Lifecycle Engineering

Current-state compliance relies on 100% document-by-document approval, with little or no provision for modular or family-based acceptance. The desired-state alternative is summarized here courtesy of Genentech’s Ron Branning, a major advocate of standardization as a prerequisite of Self-Evident Engineering (SEE).

 “Developing and applying agreed industry standards for specification and validation would:

1. Yield reliable, self-validating outputs at each stage of the development process
2. Eliminate redundancy in testing and documentation
3. Eliminate ambiguity in specifications
4. Eliminate gaps and overlaps in departmental roles and responsibilities
5. Allow regulatory/quality to audit the standards rather than individual tests
6. Save companies time and resources
7. Adapt readily to innovation.”

I look forward to your feedback re the above, particularly in regard to the opportunities/implications associated with item 5.

I came across a staggering quotation recently when reading NIPTE’S excellent Strategic Roadmap for Research & Education. For more on NIPTE (National Institute for Pharmaceutical Technology and Education) be sure to visit www.purdue.edu/dp/nipte.

Meanwhile, here’s the quote: ‘There is typically little transfer of knowledge and information from development to manufacturing, and no transfer of knowledge and experience back to development. Because of limited systematic institutional memory for knowledge generated over time, relearning occupies over 25% of developmental resources’. Enough said? Once again, your feedback requested. 

Current-state compliance is based on ‘documentation, documentation, documentation’, with fragmentation and discontinuity the order of the day. This need not be so. Following on from my previous messages, systems and components can be itemized and codified with a view to acquiring front-loaded attributes and procedures across their lifecycle, this information being used to auto-generate the documented evidence that we require. The advantages in terms of standardization, transparency and scalability are obvious, along with the derivative benefits of data-exchange to & from other business applications (e.g. maintenance, calibration etc.). This message invites feedback in regard to the implications of a data-driven approach to Self-Evident Engineering (SEE).

The current state is based on fragmented and discontinuous lifecycles and workflows, with all of the attendant pitfalls and inefficiencies which I won’t go into here. By comparison, the desired state calls for lifecycle integration and connectivity; with development, design and manufacturing being treated as inseparable items within the compliance continuum. Time for another acronym by the way: Development, Design & Manufacturing Lifecycle = DDML.

While each DDML phase has its own particularities (e.g. preconditions, handshakes, timing, protocols) and sub-phases (e.g. technology transfer, risk assessment, preliminary & detailed design, delivery, C&Q, maintenance, requalification), I am suggesting that not only can they be, but they must be, defined and managed in unison. This message invites discussion and feedback in regard to the implications of lifecycle integration as a constituent of Self-Evident Engineering (SEE).

2007 is here and Donagh has encouraged me to get with the program and start blogging. My intention is to keep these messages brief but ‘provocative’, with a view to creating a forum for dialog and information exchange between fellow travellers….

What I am suggesting in this first message is that operations, parameters, alarms, materials, personnel, methods etc. can be componentized just as readily as physical components and that the incremental registration of such items calls for a panoramic and DIY-based mindset.

This facilitates the integrated and unified approach we’ve all been seeking, with specific benefits that I will present in subsequent messages. For now, I am inviting feedback re the implications of the interdisciplinary registration and codification of design, installation, operational, performance and other ‘components’ as a launching pad for what I’m going to call Self-Evident Engineering (SEE).

This is the launching post of the Campbell Informatics Blog.

Campbell Informatics, founded in 1990, delivers systems modeling and engineering data management products and services to the regulated life science manufacturing sector. See About Campbell Informatics.

What you can expect to read on the Campbell Informatics are:

• Thought provoking and sometimes controversial arguments in Engineering and Quality Data Management for life science manufacturers
• Discussions on improved and more efficient concept models for the sector
• Real challenges in the industry in mini-case-study format
• Occasional relevant News from the industry

Who will be posting on this blog?

• Cliff Campbell, Founder and President, Campbell Informatics
• Donagh Kiernan, CEO, Campbell Informatics
• and more to come later

Enjoy

Donagh

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