Process Consistency and Variability Reduction 26 March 2007 PDA, Verona, Italy Lynn Torbeck Torbeck and Assoc.

Overview  GMP  Ed Fry  Variability  PAT: A Play in Three Acts  Seven ways to achieve consistency

(a)  “Such control procedures shall be established to monitor the output and to validate the performance of those manufacturing processes that may be responsible for causing variability in the characteristics of in-process material and the drug product.”

(a)  Note that the words validate and variability are in the same sentence.  It seems to me that the authors were telling us to find, control, manage and if possible, reduce variation as part of our validation studies.

Ed Fry  Fry, E., “The FDA Viewpoint”  Drug and Cosmetic Industry, Vol 137, No. 1, July 1985  Ed was Director, Division of Drug Compliance, CDER Office of Compliance, FDA  Speaking for the FDA in the paper:

Ed Fry  “Experiments are conducted (that is validation runs) to assure that factors that would cause variability are under control, and will result in an output that meets the specifications within the limits of the ranges that you had previously established.”

Ed Fry  “The regulations require validation of those processes responsible for causing variabilities in characteristics of in-process materials or finished products.”  “However, the regulation implies that not everything that takes place in a pharmaceutical manufacturing plant causes variability.”

Ed Fry  “Therefore, some thing don’t need to be validated. We never intended to require that everything [that] takes place in an manufacturing operation is subject to a validations study.”  Wow! Did he really say that?

It’s Deja’ vu All Over Again?  Is PAT bring us back full circle to the original intentions of the GMP’s?  Reading the PAT guidance we find many references to statistics and variability.  “What sources of variability are critical?”  “How does the process manage variability?”

PAT Guidance  “Facilitating continuous processing to improve efficiency and manage variability.”  “A process is generally considered well understood when (1) all critical sources of variability are identified and explained; (2) variability is managed by the process; and (3) product quality attributes can be accurately and reliably predicted over the design space...”

Dr. W. Edwards Deming  The famous statistician (1900 – 1993).  Taught Statistical Quality Control to the Japanese after WWII  “If I had to reduce my message for management to just a few words, I’d say it all had to do with reducing variation.”

Variability is the Enemy  How many of our quality problems would go away if there were little or no variability in our processes and our laboratory data?  Variation may be the spice of life in our personal lives but is the source of errors, discrepancies, OOS, lost time, OOT, deviations, adverse effects, patient risk, rejected lots and recalled lots.

Reduce Variability  Each of us, as individuals and as a industry, must work every day to reduce variation and variability in our selves, our methods, material, measurements, machines, processes, products and the environment.

Deming’s Message to Japan  If you reduce variability, you will reduce scrap, rework and rejects. You can then make a better product at less cost. You will capture a larger market share. Your people will be employed and you will prosper. Paraphrase of Deming’s message

Our Old / New Goal  Where is this variability coming from and what have I, we, done to manage it, minimize it, control it and, if possible, to eliminate it?  Clearly the tools we need must include the science of variation: the field of statistics.  We need to use simple statistics, statistical quality control and statistical process control.

Process Capability Studies  Many companies are not using the data they currently collect. They have never looked at their processes and historical data with flowcharts, process maps, time plots or control charts. They often only look a the last year of data for the annual review.  For many, the goal is not to find anything!

Process Capability Studies  They have never identified the potential critical steps and critical factors. They do not do process capability studies, do not know what Cpk is for critical responses and have never compared visually the natural variability of the process to the specification criteria.

PAT: A Play in Three Acts  Act One: Passive, historical, observational and empirical: Analyze historical data that exists. Map and flowchart the process. Identify potentially critical factors and responses. Do a statistical analysis and process capability. Brainstorm ways to reduce variability.

PAT: A Play in Three Acts  Act Two: Active, current, experimental and empirical: DOE to define critical factors and responses. DOE to achieve Process/Product ruggedness. DOE to define the formulas for Design Space. Determine realistic specification criteria. Use new information to reduce variation.

PAT: A Play in Three Acts  Act Three: Interactive, in-line, on-line, at- line and theoretical. Real time high tech rapid measurements, NIR. Large volumes of data. Chemometrics, multivariate statistical analysis. Correlate to end product testing. Real time release.

Misconceptions of variability  We have variability because the equipment needs to be replaced with new technology.  We do too many tests.  Variability exists because somebody didn’t do their job correctly.  Variability is an inherent fact of life and there isn’t any thing we can do about it except to live with it. It’s cost of business.

Variability is the Enemy  “Special Cause” variation is the result of a single source. Use CAPA to solve it.  “Common Cause” variation is the result of multiple small sources all contributing to the sum total.  CAPA will not work for common cause.  We need a culture change to address common cause variation.

Sources of Variation  Common cause variation: People Materials Methods Measurement Machines Environment

Confronting the Enemy 1.Operational Definitions 2.Achieve the Target 3.Flexible Consistency 4.Hold Constant Controllable Factors 5.Mistake Proofing 6.New Technology 7.Continuous and forever improvement

Operational Definitions  A very detailed and exacting description of an activity, procedure, place or thing.  SOP’s are operational definitions.  Reduce variation by having procedures well defined.  If we don’t tell an employee exactly what we want them to do, then anything they do within reason must be acceptable.

Achieve the Target  Stop the cultural practice of just getting within the limits as a goal.  The new attitude must be to strive to hit the target all the time and every time.  30(25, 35) is the way to write criteria.  Everyone must participate.

Flexible Consistency  Often more than one acceptable way to do a task. But rather than let each person do it a different way, we get everyone together and agree as a group to all do it the same way.  If a better way is proposed, then everyone changes to the new way all together  The ultimate team approach.

Hold Constant  Obvious but obviously needed.  If something can be controlled, it should be controlled.  Again a cultural issue, not a regulatory one.  This is not a case of over-control and not an issue of investigations of deviations for critical factors.

Mistake Proofing  Make it impossible to make a mistake.  A mechanical “stop” on a drill press.  Color coded paper work and equipment.  White paint on the torque wrench.  Forms and documents design.  Range checking in computer software.

Back to Basics  Dr. Walter Shewhart  Dr. W. Edwards Deming  Dr. Joseph Juran  Dr’s Box, Hunter and Hunter  Professor Kaoru Ishikawa  Armand V. Feigenbaum

In Summary  Statistical Quality Control started in the 50’s.  You can’t go from the Wright brothers to the space shuttle in one leap, but maybe two.  No instant pudding, must do the basics first.  The reason other industries are doing so well with PAT is that they have spent 50+ years getting the simple stuff done correctly first.

Thank You Questions?