Or, how to look awfully clever in front of your boss.
“A man who dares to waste one hour of time has not discovered the value of life” said Charles Darwin.
The survival of the fittest applies to the corporate world as much as the natural one and no Engineering Director I know wants to waste time or resources. Calibration of instruments is an area that consumes quite a lot of both.
And yet, relatively few Engineering Directors, even in GMP environments, have brought a truly scientific approach to bear on their calibration program in order to balance risk with cost to create a statistically optimized program.
Are you wasting time & money calibrating everything when in fact, it may not be necessary?
LotusWorks is an outsourced engineering company that has developed an approach to calibration that is more nuanced than the ‘Calibrate everything, and nothing will be missed school. The result is a calibration program that
- Reduces cost
- Increases efficiency
- Reduces risk to product quality
- Increases equipment availability
It may seem counterintuitive to claim to reduce both cost and risk simultaneously, but this has indeed been our experience. Our approach recognizes that only some instruments are equally important, and their likelihood of approaching an out-of-compliance event is low.
How a Calibration Optimization Program works
To optimize a client’s calibration program, we work through a two-phase process that firstly identifies WHAT requires calibration and secondly helps to determine, through statistical analysis, WHEN it needs to be calibrated.
Phase 1: Instrument Classification – identifying what needs calibration
In the first phase, we classify every instrument as either GMP or Non-GMP. Those classified as GMP are further categorized according to their direct/indirect impact on product quality and/or manufacturing environment. A cross-functional, multi-disciplinary Criticality Assessment Team carries out this classification.
Phase 2: Interval Adjustment Process – identifying when it needs to be calibrated
We then use statistical models to identify what is an appropriate calibration interval for every instrument. By taking a statistical approach, it ensures that any calculated intervals will have sound scientific justification based upon previous calibration results and empirical mathematical models. As a result, the calculated interval will encompass the actual environmental conditions, giving you an optimized system, personalized to your specific process requirements.
Adjusting these intervals for calibration based on historical data and statistical algorithms frequently leads to a reduction in the number of calibrations that are required, without increasing risk or endangering compliance.
Quality Risk Assessment factored in
We also identify any possible PNEs (Potential Negative Events that could impact the quality of the final product) associated with extending calibration intervals.
The Impact of a risk-based approach to calibration – a 42% saving in calibrations
LotusWorks has implemented this Calibration Optimization Program with a couple of blue-chip Pharma and Biotech companies and the results are very clear.
Pharma
Before deploying LotusWorks’ Calibration Optimization Program, this client was conducting 10,500 calibrations annually. This number fell by 4,400 once we had completed our analysis and run through the process. That’s a cost saving of 42%.
Biotech
This client specializes in the fermentation, purification and sterile filling of biotech products. It is also involved in the manufacturing of products used in clinical studies worldwide. The plant is approximately 30 years old and has about 2900 calibrations per year.
Implementation of the LotusWorks Calibration Optimization Program led to a reduction in the number of instruments classified as critical from 64% to 46%. The number of annual calibrations was reduced from 2900 to 1400, a 52% reduction.
The results will vary from operation to operation, obviously. Still, these numbers might inform your thinking as to the value such an approach could deliver in your situation.
A risk-based approach can often also reduce risk.
It may be counterintuitive to think that a cost reduction could be accompanied by a decrease in risk to product quality, patient/operator safety and the environment, but it’s true in this case. Our Calibration Optimization program was developed using the ‘International Society for Pharmaceutical Engineers (ISPE) GAMP Good Practice Guide: A Risk-Based Approach to Calibration Management. The GAMP guide was produced with a multifaceted agenda, both to represent the regulatory bodies’ current thinking and also to provide some uniformity across the industry.
Further benefits include a corresponding increase in equipment availability.
As a direct result of a decrease in the number of yearly calibrations, equipment availability will see a corresponding increase. Production time will be optimized as our process is set up to identify problems, determine the root cause and use specifically developed tools and procedures to solve complex problems with simple, highly effective solutions.
How is this different to how my existing calibration program was created?
In very many cases, calibration programs are constructed by experienced engineers auditing the instruments, thinking about their role in the process and GU estimating, based on their experience, how often a particular device should be calibrated. Human nature dictates that they are going to err on the side of caution because they don’t want any blowback coming their way if an issue arises down the line. And let’s face it, that’s not efficient. The Calibration Optimization Program approach is far more scientific and uses historical data analysis and an algorithm to eliminate waste and risk.
My advice? Remember Darwin – value life and don’t waste another hour of it – call LotusWorks now, and ask for more information on our Calibration Optimization Program. Let’s see how we can help your organization become fitter.
For more information on the LotusWorks calibration service offering, visit our sectors page here.