Lifecycle Management of Analytical Procedures; What is it all about? Jane Weitzel Independent Consultant

Transcription

1 Lifecycle Management of Analytical Procedures; What is it all about? Jane Weitzel Independent Consultant

2 2 USP Stimuli Article Lifecycle Management of Analytical Procedures: Method Development, Procedure Performance Qualification, and Procedure Performance Verification

3 3 ICH Q8(R2) Definition Quality by Design (QbD) definition is given in ICH Q8. Useful definition te/ich_products/guidelines/quality/q8_r1/ Step4/Q8_R2_Guideline.pdf

4 4 ICH Q8(R2) Definition Quality by Design (QbD): A systematic approach to development that begins with predefined objectives and emphasizes product and process understanding and process control, based on sound science and quality risk management. ep4/q8_r2_guideline.pdf

5 5 Sound Science Metrological approach to measurements Measurement uncertainty Target measurement uncertainty Completely characterises the variability dscience/laboratorymanual/ucm h tm

6 6 All analytical measurements are wrong; it s just a matter of how large the errors are, and whether they are acceptable. Mike Thompson, Imperial College, London

7 7 FDA new guidance Includes Lifecycle concept Only applies to stage 3 Risk assessment Suitable for their intended purpose Systematic approach for method robustness study The methodology and objective of the analytical procedure should be clearly defined and understood Scientifically-based method development and optimization studies Justified acceptance criteria Statistical analysis of validation data GuidanceComplianceRegulatoryInforma tion/guidances/ucm pdf

8 8 Lifecycle Management Continued Performance Verification

9 9 Scientifically Sound and Appropriate Where do these new concepts fit in? CFR has always required use of sound science Decision rules, measurement uncertainty, risk and probability have been used in many scientific areas for many years. We can leverage this experience to more effectively meet cgmp requirements.

10 10 Lifecycle & Control Thoroughly define the purpose of the data Allows you to control the procedure throughout its life. Quantify good enough, significant You can know what is good enough and how much to control.

11 11 Measurement Uncertainty is Needed Measurement uncertainty (MU) allows the risk and probability to be quantified and applied to the use of the data. If you don t know where you are going, any road will do. MU is a major part of defining where you are going.

12 12 Measurement Uncertainty Measurement Uncertainty is a parameter associated with the result of a measurement that characterizes the dispersion of the values that could reasonably be attributed to the measurand Concentration

13 13 Target Measurement Uncertainty An operating characteristic is not significant if its standard deviation is < 1/3 largest standard deviation. It is not a critical variable It does not need an operational procedure control < 1/3

14 14 References EURACHEM CITAC Guide - Quantifying Uncertainty In Analytical Measurements GUM, Guide to Expression of Uncertainty of Measurement /publications/guides/gu m.html

15 15 Estimate MU & USP <1225> The article describes how to estimate MU using data from a procedure validated to USP <1225> cle/ /s

16 16 Target Measurement Uncertainty (TMU) x /M.L.-Jane-Weitzel-and- Wesley-M.-Johnson-Application-of-ISO/IEC Technical-Requirements-in-Industrial- Laboratories

17 17 Process Validation and Lifecyle FDA s Pharmaceutical cgmps for the 21st Century A Risk- Based Approach ovalprocess/manufacturing/questionsandan swersoncurrentgoodmanufacturingpractice scgmpfordrugs/ucm htm

18 18 QbD Concepts The concepts of lifecycle validation for manufacturing processes can be applied to analytical procedures

19 19 Lifecycle Process Lifecycle: All phases in the life of a product from the initial development through marketing until the product s discontinuation ICH Q8(R1) Pharmaceutical Development Analytical Procedure Lifecycle: All phases in the life of an analytical procedure from the initial development through marketing until the procedure s discontinuation

20 20 Analytical Procedure Lifecycle Apply QbD concepts to analytical procedures Output Design Qualification Performance Verification Reportable Result

21 21 Procedure Lifecycle Has 3 Stages Critical Performance Characteristics (e.g. Accuracy, Precision & Measurement Uncertainty) Risk & Probability Intended Use Analytical Target Profile Target Measurement Uncertainty Decision Rule 1 Design 2 Qualification 3 Performance Verification Reportable Result

22 22 Control Critical Performance Characteristics (e.g. Accuracy, Precision & Measurement Uncertainty) Risk & Probability Intended Use Analytical Target Profile Target Measurement Uncertainty Decision Rule 1 Design 2 Qualification 3 Performance Verification Reportable Result Critical variables and operational procedure controls

23 23 ATP Definition Analytical Target Profile (ATP) The ATP is a prospective summary of the objectives of a test and defines the quality requirements, including the expected level of confidence, for the reportable result that will allow the correct conclusion to be drawn regarding the attribute of the material that is being measured.

24 24 Benefits of Using the ATP Analytical procedure is suitable for its intended use throughout its life The performance requirements of the procedure are clearly stated

25 25 Benefits of Using the ATP Any technique and procedure that meets the ATP is suitable Change is assessed in the ability of the procedure to still meet the ATP

26 26 ATP Example from Stimuli Article Assay: The procedure must be able to quantify [analyte] in [presence of X, Y, Z] over a range of A% to B% of the nominal concentration with an accuracy and uncertainty so that the reportable result falls within ± C% of the true value with at least a 90% probability determined with 95% confidence.

27 27 Analytical Procedure Design Select appropriate technology Develop a procedure Perform studies (experiments) to identify and understand the critical variables Identify the critical variables and design suitable operational procedure controls Analytical Target Profile

28 28 Procedure Qualification Qualify that the procedure will work in routine use Demonstrating through experiments and studies Meets the requirements of the ATP E.g. Precision studies, bias studies, Design of Experiments (DOE)

29 29 Continued Procedure Verification (MV) Continually demonstrate the procedure remains in a state of control during use Both during routine use and After changes

30 30 MV - Changes Will happen What is the impact of the change? Perform risk assessment to determine impact of change Does it still meet the Analytical Target Profile?

31 31 MV New Laboratory Procedure Installation Includes knowledge transfer to new laboratory Procedure performed in new laboratory meets requirements of the ATP

32 32 Probability When assessing criticality use risk and probability. Look at the normal distribution to see basis for risk and probability.

33 33 Normal Distribution Curve

34 34 Decision Rule A documented rule... that describes how measurement uncertainty will be allocated with regard to accepting or rejecting a product according to its specification and the result of a measurement. ASME B (reaffirmed 2006)

35 35 Decision Rules References

36 36 Decision Rule with Transition Zone Sometimes called Internal Release Limit Upper Specification Limit Guard Band Acceptance Zone Transition Zone Rejection Zone

37 37 To decide whether a result indicates compliance or noncompliance with a specification, it is necessary to take into account the measurement uncertainty. Upper Control Limit Decision Rule Result plus uncertainty above limit Result above limit but limit within uncertainty Result below limit but limit within uncertainty Result minus uncertainty below limit

38 38 Decision Rule - Probability The product shall be considered non-compliant if the probability of being above the upper limit exceeds 2.5% or being below the lower limit exceeds 2.5%.

39 39 Distribution Curve for 98.0 to 102.0% % below Lower Limit 2.50% % above upper limit 2.50% Total outside limits 5.0% Nominal Concentration (Central Value) Target Measurement Uncertainty (Standard Deviation) 1.02 Enter the largest standard deviation which results in the acceptable Lower Limit 98.0 "Total outside limits". Upper Limit Lower Limit Upper Limit Target Measurement Uncertainty Concentration %

40 40 USP has discussed this specification in the Medicines Compendium Assessing Validation Parameters for Reference and Acceptable Procedures Guideline for Donors/ Instructions for Staff

41 41 Accuracy -1.0% (Bias) -1.0% Bias has impact on proportion outside the limits. % below Lower Limit 16.34% % above upper limit 0.16% Total outside limits 16.5% Nominal Concentration (Central Value) 99.0 Target Measurement Uncertainty (Standard Deviation) 1.02 Enter the largest standard deviation which results in the acceptable Lower Limit 98.0 "Total outside limits". Upper Limit Lower Limit Upper Limit Concentration %

42 42 Change Standard Deviation to 0.6% % below Lower Limit 4.78% % above upper limit 0.00% Total outside limits 4.8% Nominal Concentration (Central Value) 99.0 Target Measurement Uncertainty (Standard Deviation) 0.60 Enter the largest standard deviation which results in the acceptable Lower Limit 98.0 "Total outside limits". Upper Limit Lower Limit Upper Limit Concentration %

43 43 Correct for Bias Modify the procedure to eliminate the bias If that cannot be done, correct for the bias The uncertainty of the bias correction must be included in the overall uncertainty estimate. This is the combined uncertainty which takes into account all sources of uncertainty

44 44 Procedure Design Robustness Identifies Critical Variables

45 45 DOE Timing in the Lifecycle Can occur during method development Can refer to it in the method qualification Part of knowledge management Or Can occur during method qualification (Formerly method validation)

46 46 DOE Examples Based on DOE described by: Youden and Steiner (pp 33 36,50 55) W.J. Youden & E.H. Steiner (1975) Statistical Manual of the AOAC, AOAC INTERNATIONAL, 481 N. Frederick Ave, Suite 500, Gaithersburg, MD , USA. The fifth printing (1987) contains several explanatory foot notes.

47 47 Run Design Experiment (Run) Factor A B C Various Designs D E F G Result s t u v w x y z

48 48 DOE test evaluation Look for factors that have large enough value to cause concern Statistically significant Comparison with Target Measurement Uncertainty reveals if the factor is practically significant Practically significant

49 49 What to do with Significant Factor? When a factor is found to be significant there are a few options Control the factor Change the factor slightly Worst case, go back to procedure development

50 50

51 51 Factors Selected for HPLC Factor Letter DOE Designation A B C D E F G Factor extraction heating time extraction temperature HCl concentration extraction volume column temperature flow rate test sample weight

52 52 Not Practically Significant? The effect of a factor may be statistically significant, but not practically significant. How do you determine this? By comparing the experimental standard deviation (uncertainty) to the target measurement uncertainty.

53 53 Factor D is Statistically & Practically Significant Factor t experimental t critical = 2.09 A 0.1 B 0.7 C 0.1 Significant? D 13.7 YES E 0.8 F 0.1 G 0.0 Target uncertainty is 1.0 Overall uncertainty is 1.75 YES

54 54 Factor D is Statistically but NOT Practically Significant Factor t experimental Significant? t critical = 2.09 A 6.9 YES B 0.9 C 1.1 D 0.5 E 0.1 F 0.1 G 0.5 Target uncertainty is 1.0 Overall uncertainty is 0.90 NO

55 55 No Factor Significant, Statistically or Practically Factor t experimental t critical = 2.09 A 1.5 B 0.4 C 1.0 D 0.0 E 1.6 F 1.0 G 0.5 Significant? Target uncertainty is 1.0 Overall uncertainty is 0.90 NO

56 56 Example Quantitative Elisa Test Factor Buffer Temperature Incubation Temperature Standard/Sample incubation Time Detection Antibody Incubation Time Number of washes before development Substrate Solution temperature Development Time Significant? Yes Yes No No No No No

57 57 ELISA Operating Factor Buffer Temperature Incubation Temperature Further Design Activities Studied further in separate assays. Important to keep buffer cold. They reviewed all design experiments and decided the room temperature had to be kept cold, below 25 C. Operational Procedure Controls Ensured they had adequate refrigeration. Documented buffer temperature before and after its use. Added instructions to procedure. Monitored room temperature during the assay.

58 58

59 59 Critical Variables Need Operational Procedure Controls The critical variables identified during method design and DOE experiments need to be adequately controlled during routine use Critical Variable Needs Operational Procedure Control

60 60 Operational Procedure Controls Instructions SOP Forms (LIMS) Recording information Facility Control Eg. Laboratory temperature Control Charts Reference Materials & Blanks

61 61 Quality System Controls Document Control Supervision Training Can use data from method validation and DOE to set up training activities Can use control charts to set criteria for analyst proficiency tests

62 62 Training Did the method qualification, eg. DOE, determine the analyst is a critical variable? If yes, then Design and implement a rigorous and thorough training program Develop good analyst proficiency tests Monitor analyst performance If needed, Implement regular retraining or qualification

63 63 HPLC Example DOE identified critical variable DOE identified that the extraction heating time is a critical variable From other experiments they knew extraction was complete at 30 minutes In the DOE, two extraction times were used, 15 minutes and 30 minutes

64 64 Added Operational Procedure Control The extraction time was set to 30 minutes ± 1 minute SOP was written with clear, specific instructions specifying the extraction time. The actual extraction time for each test must be recorded and reviewed.

65 65

66 66 Human Error Presents a technique to deal with human error. Based on approaches used in aviation, engineering, medicine and other fields. cle/ /s y

67 67 Approach Review the procedure to identify potential errors Classify the errors Implement appropriate controls based on the classification In the quality system approach errors are seen as consequences of system factors that are inadequate, eg. Laboratory conditions Thus, the appropriate control focuses on the system Don t just blame the analyst.

68 68

69 69 Control Charts and Statistical Process Control - References FDA Field Science and Laboratories describe control charts in their SOP online at: e/laboratorymanual/ucm htm The American Society for Quality has valuable references on control charts:

70 70 Normal Distribution Curve Basis for Chart

71 71 UCL UWL LWL LCL

72 72

73 73 Out of Specification The data from the procedure design, procedure qualification, and continued procedure verification can be used during the investigation of an OOS.

74 74 Guide A recent guide on how to include uncertainty in that review has been published. IUPAC/CITAC Guide: Investigating out-ofspecification test results of chemical composition based on metrological concepts (IUPAC Technical Report) Pure Appl. Chem., Vol. 84, No. 9, pp , IUPAC, Publication date (Web): 9 July 2012

75 75 The Guide Proposes An investigation of the causes based on metrological concepts is proposed. It includes: Assessment of validation data of the measurement process and Its metrological traceability chains, Evaluation of measurement uncertainty, and Related producer s and consumer s risks. This approach allows distinguishing between OOS test results that indicate an actual change of an analyzed product, and OOS test results that are related to the actual measurement

76 76 2 MU Aspects There are two important measurement uncertainty aspects and questions in the fullscale investigation of OOS test results: Is the measurement uncertainty adequate for the intended use? Are the contributions to the measurement uncertainty of the same order of magnitude? That is, is there a dominating uncertainty component? If the answer is no to either of these, the OOS could be caused by the measurement and not the product.

77 77 Basis of metrological approach could oos be result of uncertainty? % below Lower Limit 20.23% % above upper limit 0.00% Total outside limits 20.2% Nominal Concentration (Central Value) 98.5 Target Measurement Uncertainty (Standard Deviation) 0.60 Enter the largest standard deviation which results in the acceptable Lower Limit 98.0 "Total outside limits". Upper Limit Lower Limit Upper Limit Concentration %

78 78

79 79 Periodic Review Guidance for Industry Quality Systems Approach to Pharmaceutical CGMP Regulations A quality systems approach calls for the manufacturer to develop procedures that monitor, measure, and analyze the operations (including analytical methods and/or statistical techniques). Monitoring of the process is important due to the limitations of testing. Knowledge continues to accumulate from development through the entire commercial life of a product. Significant unanticipated variables should be detected by a wellmanaged quality system and adjustments implemented. Procedures should be revisited as needed to refine operational design based on new knowledge.

80 80 Periodic review, GMP Requirement Analytical procedures should be periodically evaluated to verify that they are still operating in a valid manner. The robustness experiment provides a good basis against which to conduct this review. The control charts continually demonstrate a state of control. This will decrease the amount of activity needed during the periodic review.

81 81 Review Includes OOS Investigations When on Out of Specification result is obtained an OOS investigation is done. These OOS investigations should be included in the periodic review.

82 82 Periodic Review Made Easy In the lifecycle approach the continual verification of the method is made easier. Control charts incorporate that review into the regular use of the method. OOS investigations include determination that the method is fit for use. Supported by KNOWLEDGE MANAGEMENT

83 83 Other initiatives Revision of ICH Q2 Britain has set up a committee similar to the USP expert panel method validation and verification. China initiative to use best science.

84 84 How do you learn more? Attend USP workshop Dec. 8 & USP headquarters, Rockville Learn more Give your input to USP What training is needed? How to implement Additional resources.

85 85 Summary Procedure Design Risk Probability Decision Rule Target Measurement Uncertainty ATP DOE Continual Procedure Verification

86 86 Summary Procedure Design Critical Variables ATP DOE Operational Procedure Controls SOP Facility Control Control Charts Reference Materials Continual Procedure Verification

87 87