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MARLAP SCIENCE ADVISORY BOARD CHAPTERS 6 & 7

MARLAP SCIENCE ADVISORY BOARD CHAPTERS 6 & 7. Stan Morton DOE-RESL April 2002. Multi-Agency Radiation Laboratory Protocols Manual. Purpose: Provide guidance and a framework for project planners, managers, and laboratory personnel to ensure that radioanalytical laboratory data will

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MARLAP SCIENCE ADVISORY BOARD CHAPTERS 6 & 7

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  1. MARLAPSCIENCE ADVISORY BOARDCHAPTERS 6 & 7 Stan Morton DOE-RESL April 2002

  2. Multi-Agency Radiation Laboratory Protocols Manual • Purpose: • Provide guidance and a framework for project planners, managers, and laboratory personnel to ensure that radioanalytical laboratory data will • meet a project’s or program’s data requirements and needs.

  3. Chapter 6 - Selection and Application of an Analytical Method • MARLAP recommends the performance-based approach to method selection • Lab selects and proposes a method in response to the APSs and method validation level specified in the SOW • method selection is a complex process that must consider: • APSs - MQOs, method validation status, qualified staff availability, production schedule, radiological and sample TATs, equipment calibration / availability, etc., • Project manager approves use of selected method • evaluates submitted method validation documentation or • evaluates performance of lab re analysis of method validation PT samples

  4. Measurement Quality Objectives • MQOs - analytical portion of the DQOs • statement of performance or requirement for a particular method performance characteristic - can be quantitative or qualitative • method uncertainty, uMR, at a specified concentration (expressed as an estimated standard deviation) • quantification capability (expressed as the minimum quantifiable concentration - MQC) • detection capability (expressed as the minimum detectable concentration - MDC) • applicable analyte concentration range - method’s ability to measure analyte over some specified range

  5. Measurement Quality Objectives • MQOs - analytical portion of the DQOs • statement of performance or requirement for a particular method performance characteristic - can be quantitative or qualitative • method specificity - ability of method to measure the analyte in the presence of interferences • method ruggedness - relative stability of method performance for small variations in method parameter values

  6. Chapter Six: Selection and Application of an Analytical Method 6.1 Introduction 6.2 Method Definition 6.2.1 Performanced-Based Approach and Application 6.3 Life Cycle of Method Application 6.4 Generic Considerations for Method Devel/Selection 6.5 Project Specific Considerations for Method Selection 6.5.1 Matrix and Analyte Identification 6.5.2 Process Knowledge 6.5.3 Radiological Holding and Turn Around Times 6.5.4 Unique Processing Specifications

  7. 6.5.5 Measurement Quality Objectives 6.5.5.1 Method Uncertainty 6.5.5.2 Quantification Capability 6.5.5.3 Detection Capability 6.5.5.4 Applicable Analyte Concentration Range 6.5.5.5 Method Specificity 6.5.5.6 Method Ruggedness 6.5.5.7 Method Bias Considerations

  8. 6.6 Method Validation 6.6.1 Purpose of Method Validation 6.6.2 Laboratory’s Method Validation Protocol 6.6.3 Tiered Approach to Validation 6.6.3.1 Existing Methods 6.6.3.2 Validation for Similar Matrices 6.6.3.3 New Application of a Validated Method 6.6.3.4 Newly Developed or Adapted Methods 6.6.4 Method Validation Documentation

  9. 6.7 Analyst Qualifications and Proficiency6.8 Method Control6.9 Continued Performance Assessment6.10 Documentation Sent to Project Manager Summary of Recommendations6.11 References

  10. MQO - Method Uncertainty Requirement, uMR • The recommended value of uMR is based on the assumption that any known bias in the measurement process has been corrected and any remaining bias is much smaller than the shift, , when a concentration near the gray region is measured. • MAPEP & QAP PE programs should measure laboratory bias as a testing parameter - bias is determined through multiple analyses, not a single measurement • If decisions are to be made about the mean of a sampled population, estimate the uMR of the analytical method at the UBGR (action level) and require that the uMR be  the width of the gray region divided by 10. • If this requirement can not be met, then require at least that the uMR be  the width of the gray region divided by 3.

  11. Example The project planners have identified that the action level for the analyte is 0.10 Bq/g and the lower boundary of the gray region is 0.02 Bq/g. If decisions are to be made about the contaminated areas based on samples, then the uMR at 0.10 Bq/g would be: uMR =  / 10 = (0.10 - 0.02) / 10 = 0.008 Bq/g (8%) If this uMR cannot be achieved, then a method uncertainty as large as  / 3 = 0.027 Bq/g (27%) may be allowed if more samples are taken per contaminated survey area. In terms of method selection, this MQO calls for a method that can ordinarily produce measured results with an expected combined standard uncertainty of 8% at the action level

  12.  is defined as DCGL - LBGR •  is the standard deviation of the measured analyte distribution for the area being remediated • 2 is mathematically defined as (S2 + M2)where S2 is the variance of sampled population (analyte) and M2 is average analytical method (measurement) variance • M is effected by laboratory sample preparation, subsampling, radiochemical and radiometric processes •  /  is defined as the relative shift - number of standard deviations separating the DCGL and the LBGR • Non-parametric tests are used to determine if the null hypothesis (survey unit does not meet the release criterion) can be rejected; Sign and Wilcoxon Rank Sum Tests.

  13. MQO - Method Uncertainty Requirement If decisions are to be made about individual samples in a survey, MARLAP recommends the use of: uMR =  / ( z1- + z1- ) Example: UBGR = 1 Bq/L; LBGR = 0.5 Bq/L;  = 0.05;  = 0.10 uMR = 1.0 - 0.5 / ( 1.645 + 1.282) = 0.17 Bq/L or 17% at the action level. If  = 0.05;  = 0.05, then the following simplification can be used uMR = 0.3 

  14. MQO - Method Uncertainty RequirementFlexibility in Data Review • When Project Planners establish the MQO for method uncertainty for method selection and development, the maximum allowable standard deviation, uMRat the UBGR is specified. • During data evaluation, the measurement uncertainty at any sample analyte concentration  UBGR should not exceed uMR • During data evaluation, the measurement uncertainty at any sample analyte concentration > UBGR should not exceed uMR / UBGR or MR

  15. MQO - Detection Capability • If the lower bound of the gray region is at or near zero and decisions are to be made about individual samples, choose an analytical method whose MDC is no greater than the upper bound of the gray region (action level). • LBGR = 0;  = UBGR • uMR UBGR / ( z1- + z1- ) • uMR * (z1- + z1- )  UBGR • Form of: MDC  UBGR

  16. Method Validation Process • Parameters specified or ascertained from the analytical results generated • Defined Method Validation Level (Table 6.1) • Analytes • Defined matrix for testing, including chemical and physical characteristics that approximate project samples or • Selected project specific or appropriate alternative matrix PT samples, including known chemical or radionuclide interferences at appropriate levels • Defined sample preservation • Stated additional data testing criteria • Establish acceptable chemical / radiotracer yield values

  17. Method Validation Process • Parameters specified or ascertained from the analytical results generated • APSs including MQOs for each analyte / matrix • Chemical or physical characteristics of analyte when appropriate • Action level when applicable • Applicable analyte concentration range including zero analyte (blanks) • Method uncertainty at a specific concentration • MDC or MQC • Bias if applicable • Other qualitative parameters to measure the degree of method ruggedness or specificity

  18. Chapter 7 - Evaluating Analytical Methods and Laboratories • First part of chapter discusses the evaluation of the documentation that the lab sends on the proposed method, method validation and performance in PE programs • Follow up on Chapter 6 on Selection and Application of an Analytical Method • Second part of the chapter discusses the initial and ongoing evaluation of lab services • Follow up on Chapter 5 and Appendix E on Obtaining Laboratory Services

  19. CHAPTER 7EVALUATING ANALYTICAL METHODS AND LABORATORIES • 7.1 Introduction • 7.2 Evaluation of Proposed Analytical Methods • 7.2.1 Documentation of Required Method Performance • 7.2.1.1 Method Validation Documentation • 7.2.1.2 Method Experience, Previous Projects, and Clients • 7.2.1.3 Internal and External Quality Assurance Assessments • 7.2.2 Performance Requirements of the Sow – Analytical Protocol • 7.2.2.1 Matrix and Analyte Identification

  20. CHAPTER 7 CONTINUEDEVALUATING ANALYTICAL METHODS AND LABORATORIES • 7.2.2.2 Process Knowledge • 7.2.2.3 Radiological Holding and Turnaround Times • 7.2.2.4 Unique Processing Specifications • 7.2.2.5 Measurement Quality Objectives • 7.2.2.6 Bias Considerations • 7.3 Initial Evaluation of the Laboratory • … • 7.3.4 Review of Performance Indicators • 7.3.4.1 Review of Internal QC Results • 7.3.4.2 External PE Program Results

  21. MQO - Method Uncertainty RequirementFlexibility in Data Review • When Project Planners establish the MQO for method uncertainty for method selection and development, the maximum allowable standard deviation, uMRat the UBGR is specified. • During data evaluation, the measurement uncertainty at any sample analyte concentration  UBGR should not exceed uMR • During data evaluation, the measurement uncertainty at any sample analyte concentration > UBGR should not exceed uMR / UBGR or MR

  22. Monitoring A Lab’s Quantitative Performance • Premise • Ensuring the Lab meets the method uncertainty requirement • uMR =  / 10 • MR = uMR / UBGR • No method bias is assumed

  23. Use of Internal and External QC Samples • Laboratory Control Samples • % D = 100 * (SSR - SA) / SA • where SSR is measured result and SA is the spike value. Assumes the uncertainty in SA is negligible compared to the uncertainty in SSR. • Warning Limits: ( 2 MR ) * 100 • Control Limits: ( 3 MR ) * 100 • Plot on control chart for trending - no action based on single measurement

  24. Laboratory Control Samples - Example • UBGR= 5 Bq/kg, uMR = 0.35 Bq/kg, MR = 0.07 • LCS is prepared with SA = 10.0 Bq/kg and analytical result of SSR = 11.61  0.75 Bq/kg. • % D = 100 * (SSR - SA) / SA = 100 * (11.61 - 10.0) / 10 = 16.1 • Warning Limits: ( 2 MR ) * 100 or  14 % • Control Limits: ( 3 MR ) * 100 or  21 % • % D is above the warning limit but below the control limit

  25. Use of Internal and External QC Samples • Duplicate Samples - assuming significant activity • Xav = ( X1 + X2 ) / 2 • When Xav < UBGR; test the statistic | X1 - X2 | • Warning Limit: 2.83 * uMR • Control Limit: 4.24 * uMR • Plot on control chart for trending - no action based on single measurement

  26. Use of Internal and External QC Samples • Duplicate Samples - assuming significant activity • Xav = ( X1 + X2 ) / 2 • When Xav > UBGR; • Test the statistic RPD = | X1 - X2 | * 100 / Xav • Warning Limit: 2.83 * MR • Control Limit: 4.24 * MR • Plot on control chart for trending - no action based on single measurement

  27. Use of Internal and External QC Samples Method Blanks - testing criteria are provided. However, the target value for an analytical blank is zero. For the sample specific MDC, the critical level should be used to determine if a blank is statistically positive. Testing Criteria Related to the uMR: Test the statistic: Measured Concentration Value Warning Limits:  2 uMR Control Limits:  3 uMR Plot on control chart for trending - no action based on single measurement

  28. Method Blanks - Example • UBGR= 5 Bq/kg, uMR = 0.35 Bq/kg, MR = 0.07 • Analytical Result: X = 0.20  0.10 Bq/kg • Testing Criteria Related to the uMR: • Warning Limits:  2 uMR or 0.70 Bq/kg • Control Limits:  3 uMR or 1.05 Bq/kg • Analytical result is below the warning limit. Although the test allows for a certain degree of contamination in comparison to the action level, the target value is zero and any blank value > the critical vale would be considered to be positive

  29. Use of Internal and External QC Samples Matrix Spikes - testing criteria are provided. Test the statistic: Z Z = ( SSR - SR - SA ) / {MR ( SSR2 + max(SR, UBGR)2)1/2} where SSR sample result, SA is the spike value, SR is the unspiked value. (Assumes the uncertainty of the spike value is insignificant compared to the uncertainty of the measurements) Warning Limits:  2 Control Limits:  3 Plot on control chart for trending - no action based on single measurement

  30. Matrix Spike Example • UBGR= 5 Bq/kg, uMR = 0.35 Bq/kg, MR = 0.07 • SR = 3.5  0.29 Bq/kg, SA = 10.1  0.31 Bq/kg, • SSR = 11.2  0.55 Bq/kg. Since SR is less than UBGR, max(SR, UBGR) = UBGR = 5 Bq/kg. • Z = ( SSR - SR - SA ) / {MR ( SSR2 + max(SR, UBGR)2)1/2} • Z = ( 11.2 - 3.5 - 10.1 ) / ( 0.07 * ( 11.22 + 52 )1/2 = - 2.80 • Warning Limits:  2 • Control Limits:  3 • Z is less than the lower warning limit (-2) but slightly greater than the lower control limit (-3)

  31. MQO - Method Uncertainty RequirementFlexibility in Data Review • When Project Planners establish the MQO for method uncertainty for method selection and development, the maximum allowable standard deviation, uMRat the UBGR is specified. • During data evaluation, the measurement uncertainty at any sample analyte concentration  UBGR should not exceed uMR • During data evaluation, the measurement uncertainty at any sample analyte concentration > UBGR should not exceed uMR / UBGR or MR

  32. Example - Evaluation of Data Below and Above the UBGR • UBGR= 1 Bq/L, LBGR = 0.5 Bq/L, uMR = 0.17 Bq/L, • MR = 0.17 or 17% • Any result  1 Bq/L should have a measurement ( Combined Standard ) uncertainty no more than 0.17 Bq/L. • Any result > 1 Bq/L should have a relative combined standard uncertainty no greater than 17%.

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