5/2/ :35 PMPreventing OOS Deficiencies2 List of Topics Briefly review: Barr Case FDA OOS Guidance Able Laboratories Story PDA Scientific Advisory Board Committees Troublesome fundamentals Unresolved issues Preventing OOS deficiencies Final recommendations
5/2/ :35 PMPreventing OOS Deficiencies3 Barr Case Audited in 1989, 1991 and Refused to accept a consent decree. FDA was forced to go to court. Civil action taken June Decision in favor of the FDA on February 4, 1993.
5/2/ :35 PMPreventing OOS Deficiencies4 Barr and Statistical Issues Initial investigations Full investigations Testing Retesting Averaging Outliers techniques
5/2/ :35 PMPreventing OOS Deficiencies5
5/2/ :35 PMPreventing OOS Deficiencies6 Barr: Lessons Learned FDA takes OOS issues very seriously. OOS SOP’s, laboratory logs and documented investigations will be part of any Quality System review. Companies are still getting Form 483 observations for not having an adequate SOP or for not following the SOP.
5/2/ :35 PMPreventing OOS Deficiencies7 Barr: OOS Prevention Analysts, supervisors and managers should read and discuss the Barr case and understand the OOS issues in context.
5/2/ :35 PMPreventing OOS Deficiencies8 FDA Guidance “Investigating Out of Specification (OOS) Test Results for Pharmaceutical Production.” Issued as a draft in September Still in draft as of today. FDA has sent it to the attorneys. Final version could be out this year.
5/2/ :35 PMPreventing OOS Deficiencies9 Draft: OOS Prevention All laboratory personnel, analysts, supervisors and managers should read, study and discuss in-depth, sentence by sentence if necessary, the draft OOS guidance. Then do it again when the final guidance is released.
5/2/ :35 PMPreventing OOS Deficiencies10 Able Labs – Cranbury, NJ Massive number of OOS errors Recall of all 46 products 3,184 lots recalled Five ANDA’s withdrawn Hundreds of staff laid off Sold to Sun Pharm in December 2005
5/2/ :35 PMPreventing OOS Deficiencies11 Able Labs: Lessons Learned It is still possible to have wide spread misunderstanding of the Barr case, the OOS guidance and OOS SOPs. Apparently the analysts felt they could not give an “incorrect result.” Management needs to instill and cultivate a “GMP Culture” in the analytical laboratory.
5/2/ :35 PMPreventing OOS Deficiencies12 Able Labs: OOS Prevention Review the Able Labs web site. Discuss the Able Labs story with laboratory analysts, supervisors and managers. Discuss what a “GMP Culture” means in the analytical laboratory and how to develop and reward it.
5/2/ :35 PMPreventing OOS Deficiencies13 PDA OOS Committees Chemical OOS: Lynn Torbeck, Chair Eight members Draft technical report reviewed by the FDA Planning a PDA/FDA conference Microbial Data Deviations: Jeanne Moldenhauer, Chair Draft in revision
5/2/ :35 PMPreventing OOS Deficiencies14 Troublesome Fundamentals: Outliers Reportable Values Averaging Testing into compliance Full consideration
5/2/ :35 PMPreventing OOS Deficiencies15 Outliers - Defined Extreme values vs outliers:
5/2/ :35 PMPreventing OOS Deficiencies16 Outliers – Judge Wolin "The USP expressly allows firms to apply this test (outlier) to biological and antibiotic assays,..., but is silent on its use with chemical tests.” "In the Court's view the silence of the USP with respect to chemical testing and outliers is prohibitory."
5/2/ :35 PMPreventing OOS Deficiencies17 Outliers - Investigation "In chemical procedures, where method accuracy variation is small, an outlier test may be appropriate as part of an OOS investigation, provided the sample and test procedure assumes homogeneity... as in the composite strength assays. Our current thinking is that outlier tests are never appropriate where the purpose of the sample is to measure uniformity" Paul Vogel, September 10, 1993.
5/2/ :35 PMPreventing OOS Deficiencies18 Outliers - Tests Dixon's criteria, the test in USP, is general in nature and not specific to biological issues. It can be used anywhere the statistical assumptions can be met. In general, statisticians agree with the philosophy that outlier tests should be used infrequently and with great caution.
5/2/ :35 PMPreventing OOS Deficiencies19 Outliers - Recommendations Don't use any outlier rejection test for rejection of chemical test results. But it can be used as supporting information in an OOS investigation to consider retesting. Keep all data, especially suspect data, for future review. Unusual data when seen in context and with other historical data often is not unusual at all, but in fact forms a known and well-behaved statistical distribution.
5/2/ :35 PMPreventing OOS Deficiencies20 Reportable Values “Reportable Values for Out of Specification Test Results” Lynn Torbeck Pharmaceutical Technology Vol. 23, No. 2, February 1999 Special Supplement
5/2/ :35 PMPreventing OOS Deficiencies21 FDA R.V. Definition “It should be noted that a test might consist of replicates to arrive at a result. For instance, an HPLC assay result may be determined by averaging the peak responses from a number of consecutive, replicate injections from the same preparation. The assay result would be calculated using the peak response average.”
5/2/ :35 PMPreventing OOS Deficiencies22 FDA R.V. Definition “This determination is considered one test and one result.”
5/2/ :35 PMPreventing OOS Deficiencies23 Implications of FDA Definition A reportable value is the end result of the complete measurement method as documented. It is the value compared to the specifications. It is the value used for official reports. It is usually the value used for statistical analysis.
5/2/ :35 PMPreventing OOS Deficiencies27 Interpretation The individual determinations do not have to meet the specification. Individual determinations are not reported out of the lab. However the variability of the determinations is a system suitability issue. Set a limit on the standard deviation or %RSD.
5/2/ :35 PMPreventing OOS Deficiencies28 R.V.: OOS Prevention Record in writing the operational definition of the Reportable Value for each test method in the method documentation, any protocols and any reports. Add “Only this reportable value can be compared to the specification criteria.”
5/2/ :35 PMPreventing OOS Deficiencies29 Averaging Specifically, the arithmetic mean; the sum of all of the numbers divided by the count of the numbers. More generally, it is a value that represents the central point of a data set. (In this sense, it can include the arithmetic average, the median, the mode, the geometric mean or the harmonic mean.)
5/2/ :35 PMPreventing OOS Deficiencies30 Averaging "... as a general rule, firms should avoid this practice, because averages hide the variability among individual test results.“ "[Averaging] is particularly troubling if testing generates both out ‑ of ‑ specification and passing individual results which when averaged are within specification. "Here, relying on the average figure without examining and explaining the individual out ‑ of ‑ specification results is highly misleading and unacceptable."
5/2/ :35 PMPreventing OOS Deficiencies31 Averaging "Averaging the results of tests intended to measure the uniformity of the test article is not current good manufacturing practice... because it may hide the variability of the sample the test procedure is intended to detect. For this reason, all individual test results must be reported and evaluated on an independent basis" Paul Vogel, September 10, 1993.
5/2/ :35 PMPreventing OOS Deficiencies32 Averaging: OOS Prevention Do not average out of specification reportable values within specification reportable values to get an in specification result. Do not average reportable values for QA to make a decision. QA must see all individual reportable values, OOS and retests.
5/2/ :35 PMPreventing OOS Deficiencies33 Testing Into Compliance Torbeck, L., “Preventing the Practice of Testing into Compliance”, Pharmaceutical Technology, Oct Testing into compliance is the practice of ignoring valid information that should be used to make decisions. Such a practice is at best not scientific and at worst is fraudulent, illegal, and immoral. Such practices if found must be stopped.
5/2/ :35 PMPreventing OOS Deficiencies34 Testing Into Compliance Averaging OOS results with in specification results to get an in specification result. Physically averaging powers, granulations and liquids to get in specifications results. If not part of the validated process. Discarding data or not recording data until is known to be in specification. Missing samples and rejected cans. Overwriting HPLC chromatograms.
5/2/ :35 PMPreventing OOS Deficiencies35 Not Testing Into Compliance Large initial sample sizes are acceptable if all data generated is reported. Large number of retests are acceptable if all data generated is reported. Failing system suitability is not an OOS. Out of limits for an in-process adjustment is not an OOS.
5/2/ :35 PMPreventing OOS Deficiencies36 Compliance: OOS Prevention Train all laboratory personnel, analysts, supervisors and managers to be able to identify specific situations of testing into compliance. Train to be able to defend situations that are not testing into compliance during an audit.
5/2/ :35 PMPreventing OOS Deficiencies37 Full Consideration “For inconclusive investigations …. The OOS result should be retained in the record and given full consideration in the batch or lot disposition decision. This statement has caused some discussion as it is considered to be vague and undefined. It can, I think, be defined in a simple way.
5/2/ :35 PMPreventing OOS Deficiencies38 Full Consideration First, all QA decisions are made with the Reportable Values, both OOS and retests. Second, QA looks at the magnitude of the retest values compared to the specifications.
5/2/ :35 PMPreventing OOS Deficiencies39 Full Consideration If the retest values are close to the target, the lot can be released. If the retest values are close to the limit that the OOS exceeded, technically the lot can be released, but QA should consider further investigation to determine why the retests are not at target.
5/2/ :35 PMPreventing OOS Deficiencies40 Consideration: OOS Prevention QA should detail and document the logic and rational for decisions based on retesting results after a OOS result is found.
5/2/ :35 PMPreventing OOS Deficiencies41 Unresolved Issues Specification Limits for OOS? What size the retest sample? Second analyst? Statistical treatment of data?
5/2/ :35 PMPreventing OOS Deficiencies44 Specification: OOS Prevention Define in writing the levels of specification criteria. Justify in writing which specifications are considered applicable to OOS and why or why not.
5/2/ :35 PMPreventing OOS Deficiencies45 What Size the Retest Sample? “… a matter of scientific judgment,” “… retesting cannot continue ad infinitum.” “Such a conclusion cannot be based on on 3 of 4 or 5 of 6 passing results, but possibly 7 of 8.” “… will vary on a case by case basis … “ “… an inflexible retesting rule … is inappropriate.”
5/2/ :35 PMPreventing OOS Deficiencies46 What Size the Retest Sample? “The number of retests … should be specified in advance …” “The number of tests should not be adjusted ‘on-the-fly’, as results are being generated.” “… a firm’s predetermined testing procedure should contain a point at which testing ends and the product is evaluated.”
5/2/ :35 PMPreventing OOS Deficiencies47 What Size the Retest Sample? This is an unresolved issue and the statisticians are still publishing journal articles and discussing it. Barr case n=7. Could be too much or not enough. Currently n= 3 to n=9. PDA OOS committee will recommend.
5/2/ :35 PMPreventing OOS Deficiencies48 Retest References Hofer, J., Considerations when determining routine sample size for a retest procedure, Pharmaceutical Technology, Nov Anderson, S., An alternative to the ESD approach, Pharmaceutical Technology, May 2004.
5/2/ :35 PMPreventing OOS Deficiencies49 Retest: OOS Prevention Define in writing the sample size for retests or define the procedure to be used to determine the sample size. Provide scientific justification.
5/2/ :35 PMPreventing OOS Deficiencies50 Second Analyst Guidance suggests a second analyst. Issues: Added complication and variation May not have a second analyst May not find the root cause Second analyst may not be as proficient Recommend that the manager decide and justify decision in writing.
5/2/ :35 PMPreventing OOS Deficiencies51 Statistical Treatment of Data “Statistical treatments of data should not be used to invalidate a discrete chemical test result.” “ … a statistical analysis may be valuable as one assessment of the probability of the OOS result … Another way to say outlier rejection.
5/2/ :35 PMPreventing OOS Deficiencies52 Preventing OOS Deficiencies: Setting specification criteria Statistical Thinking Sources of variation Common cause vs. special cause Variation reduction Training Education
5/2/ :35 PMPreventing OOS Deficiencies53 Setting Specification Criteria: Two sides to the OOS issue. Incorrect limits are the major source of OOS. Many specifications were set early in the development process and may not be appropriate for the current process. Many specification were set using wishful thinking or incorrect approach.
5/2/ :35 PMPreventing OOS Deficiencies54 Setting Specification Criteria: Use historical data Use distribution analysis Normal, log-normal, exponential Don’t use X bar 3S Use Statistical Tolerance Intervals X bar K S for the alert limits where K is based on confidence and percent of future values
5/2/ :35 PMPreventing OOS Deficiencies55 Setting Specification Criteria For action limits, permit the average to vary and widen the Tolerance Limits For accept/reject limits, add a further allowance for stability. Consider the clinical results as part of the justification for limits.
5/2/ :35 PMPreventing OOS Deficiencies56 Statistical Thinking 1. All work occurs in a system of interconnected processes. 2. All processes have variability. 3. Process understanding and variability reduction is the key to success. Variation is the enemy.
5/2/ :35 PMPreventing OOS Deficiencies57 Sources of Variation: Common cause variation: People Materials Methods Measurement Machines Environment Special cause variation: One single factor changed
5/2/ :35 PMPreventing OOS Deficiencies58 Common vs. Special Causes A plot of the data with natural limits illustrates common cause variation. A value that is larger than would be expected by chance alone is assumed to be due to a special cause. Use CAPA to find it.
5/2/ :35 PMPreventing OOS Deficiencies59 Variability Reduction: Display boards Operational definitions Work to target, Target ( Low, High ) Flexible consistency Hold constant Mistake proofing High tech equipment
5/2/ :35 PMPreventing OOS Deficiencies60 Training Training is for a specific task or SOP. The goal is consistency. Freelancing causes problems. Little background is provided. An in-depth understanding is not needed to be in compliance if the SOP is followed.
5/2/ :35 PMPreventing OOS Deficiencies61 Education Someone needs to: Learn and understand the basic philosophy and principles. Know the background as it relates to the topic. Understand the material well enough to be able to make difficult decisions with confidence and be able to defend them.
5/2/ :35 PMPreventing OOS Deficiencies62 Need for Understanding Why was Able Labs out of compliance? Defend Reportable Values. Defend specifications applicable to OOS Defend not testing into compliance. Defend retest sample size. Why variability reduction is needed.
5/2/ :35 PMPreventing OOS Deficiencies63 Final Recommendations Read and understand the Barr Case. Read and study in-depth the OOS Guidance. Once is not enough. Audit the company SOP against the Guidance line by line. Have an active program to reduce OOS results. Keep management informed.
5/2/ :35 PMPreventing OOS Deficiencies64 Thank You That ends my presentation. We are now ready for questions and answers.
5/2/ :35 PMPreventing OOS Deficiencies65 References 1. USA vs. Barr Laboratories, Inc. Civil Action No , US District Court for the district of New Jersey, February 4, FDA, CDER, “Guidance for Industry, Investigating Out of Specification (OOS) Test Results for Pharmaceutical Production,” September Torbeck, L., “Reportable Values for Out-of-Specification Test Results,” Pharmaceutical Technology, February Torbeck, L., “Preventing the Practice of Testing into compliance,” Pharmaceutical Technology, October Hahn, G and Meeker, W., Statistical Intervals, John Wiley & Sons, Torbeck, L., “Statistical Thinking,” Pharmaceutical Technology, July 2001.