INVESTIGATE OOT AND OOS IN STABILITY STUDIES

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1 INVESTIGATE OOT AND OOS IN STABILITY STUDIES Kim Huynh-Ba Executive Director Pharmalytik LLC BIOGRAPHY Kim Huynh-Ba has over 25 years of experience in analytical development, project management, strategic drug development and stability sciences. She currently is the Executive Director of Pharmalytik ( where she provides consulting and training services to pharmaceutical companies, including companies operating under FDA s Consent Decree on harmonization and optimization of analytical best practices since In , she took a 2- year leave to join the U.S. Pharmacopeia (USP) as their Director of Pharmacopeial Education Department, where she invigorated their education programs worldwide. Her clients range from large pharmaceutical companies to small contract laboratories in U.S. and also internationally. Kim is an Adjunct Professor at Temple University-School of Pharmacy, Widener University and Illinois Institute of Technology (IIT) teaching Pharmaceutical Analysis, cgmps, ICH guidelines and Quality Audit graduate courses. She is also a short course instructor on cgmp compliance and quality topics for several global organizations such as American Chemical Society (ACS), American Association of Pharmaceutical Scientists (AAPS), Pittsburgh Conference, and many other international training groups. Kim is a member of the USP Council of Experts ( ), where she chairs the Chemical Medicines IV Expert Committee. She is also a member of the Impurities of Drug Products Expert Panel and Food Adulteration Expert Panel. She was the Chair of the USP Good Documentation Practices (GDP) Expert Panel. She is an active member of AAPS and an Alternate Councilor of ACS-Delaware Section. She serves on steering committees of AAPS Stability, CMC, and Pharmaceutical Impurities Focus Groups. She is a member of the Executive Committee of Governing Board of Eastern Analytical Symposium (EAS) and was their 2013 President. She is also a member of PQRI-Stability Shelf Life Committee. Kim has authored numerous technical publications, and book chapters. She is the editor of 2 well-known Stability books: the Handbook of Stability Testing in Pharmaceutical Development: Regulations, Methodologies and Best Practices (2008) and Pharmaceutical Stability Testing to Support Global Markets (2010). She is also working on a manuscript for the Analytical Chemistry: An Introduction to Pharmaceutical GMP Laboratory, that is expected to be available in Kim can be reached at kim.huynhba@pharmalytik.com

2 TOPICS OF DISCUSSION Regulatory Expectations on OOS/OOT Identification of OOT results Identification of OOS results Interactive Exercise WHAT GOES WRONG? OOS continues to be the leading cause of Audit Observations and Warning Letters Citations. Common OOS Observations: Ignoring failing results Reporting only passing results without just averaging failing and passing results no effort to determine root cause of OOS result no corrective or preventive actions no SOP on handling of OOS results testing sample into compliance no proper documentation not expand the OOS to other lots or products

3 DEFINITION OF OUT-OF-SPECIFICATION (OOS) AND OUT-OF-TREND (OOT) OUT OF SPECIFICATION RESULTS With a control process: the method is validated analysts are qualified equipment is calibrated and well-maintained notebooks have full record of testing HOW can you have an OOS? Specs are determined based on clinical data If there is an OOS, what does it say about safety and efficacy? If you don t know the specification, can you get an OOS? But we don t live in an ideal world.

4 HOW TO IDENTIFY OOS RESULTS Compare result with specification Be sure that specification is to required degree of accuracy and round the result to this value. Example: Results is 94.9% Specifications= % of label Specifications= % of label Example: Results is 95% PASS FAIL IDENTIFY OOS RESULTS - IMPURITIES Specifications= % of label Example: Impurities spec NMT 0.10% Example 1: Result is 0.09%, Report as 0.1% or <0.1% Example 2: Result is 0.086% Report as <0.1% PASS FAIL Example 3: Results are 0.07% and 0.12% Option A: = 0.19%, result is 0.095, <0.10% Option B: < = 0.12%, result is 0.06, <0.10% Option C: < = 0.1, result is 0.05, <0.1%

5 HOW TO IDENTIFY OOT RESULTS Out of Trend or unusual results are generally results that: Meet the product specification Are outside the control limits of the process, where control charts are used or Are different to results usually obtained spec: usual results: OOT result: 96.4 How to determine TREND? ASSESSING OOS RESULTS Understand the Drug Product well: product history Process history test history reliability of equipment precision of the test

6 REGULATORY REQUIREMENTS OF ANALYTICAL DATA CGMP REGULATIONS CFR SCOPE (a) The regulations in this part contain the minimum current GMP practice for preparation of drug products for administration to humans or animals. CFR Quality Unit is responsible: Approve or reject all components Review production records (no errors occurred or it ll be fully investigated.) Approve or reject all procedures or specifications These procedures shall be in writing and followed.

7 CGMP REGULATIONS Sec General Requirements Establishment (and change) of specs, standards, sampling plans, test procedures is required Must be followed and documented at time of performance Deviation must be recorded and justified Sec 21 CFR (b)(4) requires the analyst to ensure that all instruments used meet established specifications and were properly calibrated. Validation activities Stability Studies Supplier changes CGMP REGULATIONS Sec Testing and Release for Distribution Conforms to specifications prior to release Free of objectionable microorganisms Sampling and testing plans are described in written procedures Must have acceptance criteria (e) The accuracy, sensitivity, specificity, and reproducibility of test methods shall be established and documented. Such validation and documentation may be accomplished in accordance with Sec (a)(2).

8 CGMP REGULATIONS Sec (f) specifies that products that fail to meet established standards and other relevant quality control criteria will be rejected. Even if a batch is rejected, an investigation is required to determine if the OOS is associated with other products or lots. A written record of the investigation is required. It must include the conclusions and any follow-up. CGMP REGULATIONS Sec General Requirements: Records shall be maintained for all components, drug product containers, closures and labeling.. Such records shall be available for inspection Such records can be used for evaluating at least annually to determine quality standards of drug products

9 CGMP REGULATIONS Sec Production Record Review Record must be reviewed by a Quality Unit. Investigate any unexplained discrepancies Investigate any failure of the batch or its components, even if it is not distributed Investigation shall extend to other batches of DP or other associated DP Written record with conclusion and follow up CGMP REGULATIONS Sec Laboratory Records Complete record of data (charts, graphs, spectra,..) Description of sample (location, quantity, lot, date received, etc) Method used, modification including reason and data to verify Records of reagents and standards Record of all calculations performed including units, conversion factors, and equivalency factors Complete records of periodic calibration of instruments Complete records maintained of all Stability Testing

10 FDA - GUIDE TO INSPECTIONS 4.A. GENERAL: Most manufacturers use systems that provide for the investigation of laboratory test failures. These are generally recorded in some type of log. Ask to see results of analyses of lots of product that have failed to meet specifications and review the analysis of lots that have been retested, rejected, or reworked. Evaluate the decision to release lots of product when the laboratory results indicate that the lot failed to meet specifications and determine who released them. GUIDE TO INSPECTIONS 5.B. LABORATORY INVESTIGATIONS: It is unrealistic to expect that analyst error will always be determined and documented. The inability to identify an error s cause with confidence affects retesting procedures, not the investigation inquiry required for the initial OOS result. FAILURE INVESTIGATIONS At least annually, QA and QC management should review failure reports to detect trends or unacceptable rates of failure related to an assay, process intermediate, or product. The reviews should be conducted in keeping with GMP requirements and must be documented.

11 RETESTING GUIDE TO INSPECTIONS Retesting following an OOS result is ruled appropriate only after the failure investigation is underway and the failure investigation determined in part whether retesting is appropriate. INCONCLUSIVE LOT FAILURE It is appropriate when analyst error is documented or the review of the analyst s work is inconclusive, but is not appropriate for known and undisputed non-process or process related errors. In that case, you need to step up surveillance of future lots. GUIDANCE FOR INDUSTRY INVESTIGATING OOS TEST RESULTS FOR PHARMACEUTICAL PRODUCTION Review of FDA Guidance October 2006

12 DRAFT GUIDANCE FOR INDUSTRY For purposes of this document the term OOS results includes all test results that fall outside the specifications or acceptance criteria established in drug applications, DMFs, official compendia or by the manufacturer. It also applies to all in-process laboratory tests that are outside of established specifications. [FDA guidance For Industry - Draft - Investigating Out-Of-Specification Test Results for Pharmaceutical Production Oct 2006] SCOPE This guidance applies to: chemistry-based laboratory testing of drugs regulated by CDER. traditional drug testing and release methods. active pharmaceutical ingredients, excipients and other components, in-process materials, and finished drug products In-house testing of purchased drug product components CRO performing production or lab testing. Excludes PAT approaches

13 PHASE I: LAB INVESTIGATION PHASE I: LAB INVESTIGATION Identifying and Assessing OOS results Purpose: determine the cause of OOS PHASE II: FULL SCALE OOS INVESTIGATION Investigating OOS test results When the initial assessment can t find the cause and the OOS is confirmed. ASSESSING OOS TEST RESULTS The investigation should be thorough, timely, unbiased, well-documented, and scientifically sound Even if a batch is rejected based on an OOS result, the investigation is necessary to determine if the result is associated with other batches of the same drug product or other products. Batch rejection does not negate the need to perform the investigation. The source of the OOS result should be identified either as an aberration of the measurement process or an aberration of the manufacturing process.

14 ASSESSING OOS TEST RESULTS Contract Lab System suitability Performance Responsibility of Analyst Responsibility of Supervisor Error Assessment Is it an obvious error? Responsibility of Laboratory Management LABORATORY ERROR AND CAPA Laboratory error should be relatively rare. Frequent errors suggest a problem that might be due to inadequate training of analysts, poorly maintained or improperly calibrated equipment, or careless work. Whenever laboratory error is identified, the firm should determine the source of that error and take corrective action to prevent recurrence. To ensure full compliance with the CGMP regulations, the manufacturer also should maintain adequate documentation of the corrective action.

15 PHASE 2 OF THE INVESTIGATION When When the initial assessment does not determine that laboratory error caused the OOS result and testing results appear to be accurate Objective To identify the root cause of the OOS result and take appropriate corrective and preventative action. A full-scale investigation should include review of production and sampling procedures and will often include additional laboratory testing impact of OOS result(s) on already distributed batches. PHASE 2 The investigation should be conducted by the QCU and should involve all other departments manufacturing, process development maintenance engineering

16 PHASE 2 INVESTIGATION 1. Production process review 2. Additional laboratory work Objective: to identify the root cause of OOS result and take appropriate CAPA. Evaluate the impact of OOS result(s) on already distributed batches. OOS FOLLOW UP OOS results may indicate a flaw in product or process design. For example, a lack of robustness in product formulation, inadequate raw material characterization or control, substantial variation introduced by one or more unit operations of the manufacturing process, or a combination of these factors can be the cause of inconsistent product quality. In such cases, it is essential that redesign of the product or process be undertaken to ensure reproducible product quality

17 ADDITIONAL LAB TESTING: RETESTING Must be from the same homogenous material Done by 2nd analyst Predefine testing plan Predefine max # of retests. Take method variability into account when making the plan Take sample variability into account when making the plan No adjust after results obtained. Use scientific principles REPORTING OF RESULTS With clear identified lab error, original test result is invalidated and replaced. Result must be considered if there is no lab or calculation errors One sample, one result Number of replicates must be specified in test methods Confirmed OOS, then batch must be rejected. QCU is responsible to interpret investigation result.

18 AVERAGING If some of the individual results are OOS and some are within specification, and all are within the documented variation of the method, the passing results should not be given more credence than the failing results. To use averaged results for assay reporting, ALL test results should conform to specifications. A high result may lead to concerns about overdosing a patient, while a low result may indicate formulation problems with the potential for a subpotent lot. Averaging results acceptable for: Appropriate for Microbiological assays OUTLIER TEST Statistical procedure for identifying from an array those data that are extremes An outlier may result from Deviation from prescribed test method Variability in the sample The possible use of outlier test should be determined in advance ( SOP, protocol, etc )

19 OUTLIER TESTS Possible use of the outlier test should be determined in advance Should be written in an SOP for data interpretation Should include the specific test to be used Should specify the minimum number of results required to obtain a statistically significant assessment from the test CHEMICAL TESTING Inherently reliable Precision is usually considerably better than for microbiological and biochemical testing Outlier testing is NOT allowed by the FDA guidance, for chemical testing (usually have less replicates) OUTLIER TESTING The use of outlier tests should be written into SOPs for data interpretation and be well documented. The SOPs should include the specific outlier test to be applied with relevant parameters specified in advance. An outlier test will not identify the cause of an extreme observation and, therefore, should not be used to invalidate data. Actually, modern outlier tests are based on the assumption that the population of the samples is contaminated with a value from a second population. Outlier tests have no applicability in cases where the variability in the product is what is being assessed.

20 STRUCTURE OF AN OOS INVESTIGATION Follow the process: Identifying and assessing OOS test results Phase I: Laboratory Investigation Phase II: Full Scale OOS Investigation Conclusion and Documentation CAPA ROOT CAUSE ANALYSIS Materials Methods Environment Normality etc. calculated correctly Dish Washing detergent Changes to method Solvents Reagents Column Any chemist observations Validation report Vials Caps of vials Any changes to anything relevant to testing Changes to gases (GC) Calculations checked Any assumed steps? Glassware Standards-RT-RF Pipettes/manual or automated Training of chemist Temp Humidity of lab control of Instrument type Detector Balance Chemist experience lab Injector ph meter Chemist training Sonicator Vortexer Burette size-able to measure differences? Temperature control of column Glassware washing-personnel changes Equipment People K.HuynhBa & S. Thomas, OOS, Stability Testing to Support Global Markets, Springer, 2010.

21 FLOW OF OOS INVESTIGATION OOS Result OOS investigation Production error Lab error Y Suspect Result Correct if possible Reject batch Invalidate results Perform new test Report new results Assignable cause? N Full Scale investigation Sampling error Resample Revise SOP All result in spec QA Disposition Inconclusive Retest Result OOS Reject batch CONTENTS OF A LIR Clear sample description Who, What, When Equipment checklist System checklist Procedure checklist Standards/samples expiry checklist Is it a Lab error? (Yes/No) Classification of lab error if any Investigation Conclusions (OOS or lab error)

22 STABILITY ISSUES Stability Problems Alternative storage condition Change package more protective Shorter Expiration Date Reformulate product FULL SCALE OOS INVESTIGATION QA responsibility Documented in the batch record Involves all aspects of manufacture, quality control and sampling Understand the reason for investigation Describes corrective actions and endpoint Extend to associate batches or products Notify appropriate staff - manufacturing and/or packaging investigation, QA, lab management, etc.

23 END OF INVESTIGATION Need to determine when to end the investigation and accept the results Compilation of the investigation Corrective Actions Impact on other lots Impact on method/validation/if stability sample If no lab error or statistical error is identified then the original OOS cannot be invalidated and all results must be reported and taken into consideration for batch disposition Batch disposition must be based upon scientific justification and overall data STABILITY OUT OF TREND Types of OOT Data Analytical Alert Process Capability Alert Compliance Alert

24 WHAT IS OUT-OF-TREND (OOT)? An out of trend (OOT) stability result is a result or sequence of results that are within specification limits but are unexpected, given the typical analytical and sampling variation and a measured characteristic s normal change over time 1 Definition: A stability out of trend is when a data point or multiple data points do not fit the typical stability pattern. Ref.: Identification of Out-of-Trend Stability Results, Part II PhRMA CMC Statistics, Stability Expert Teams, Pharmaceutical Technology, October 2005 ANALYTICAL ALERTS Some common approaches for Analytical Alerts Result is outside +/- 5% of initial result Result is outside +/- 3% of previous result Result is outside +/- 5% of the mean of all previous results Absolute % change from label claim Analytical Alerts 1. Observed value (for Stable Properties) 2. Change from previous (for Properties with Change over Time)

25 PROCESS CONTROL ALERT Several data points are required before this type of trend can be detected. Statistically more complex. Can often be found at time of Annual Product Review when stability data is looked at for multiple batches. Good method is slope control chart Calculate slope using all data up to time point of interest. Calculate interval for slope at each time point. Slope for each lot should fall within these limits, if not, the slope is different then historically found. COMPLIANCE ALERT Similarly to process control alert, can often be detected at time of annual product review Calculate shelf life following procedure found in first section. If slopes are different, find shelf life for each batch. Check that all shelf life estimates are greater than or equal to current shelf life.

26 SUMMARY All test results are subject to some element of doubt Use Controls and Validated test methods Use replicates where inherent variation exists Perform trend analyses and report deviations NEVER continue a suspect test SOP conforms with current expectations, clear and complete At some point, testing ends and a product disposition decision must be made Periodically verify method performance Manage investigation as part of lifecycle management or the product THANK YOU! Without data, it would just be another person s opinion. W. Deming Kim Huynh-Ba Kim.huynhba@pharmalytik.com