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Contact: Eric Rozet, Statistician Eric.Rozet@arlenda.com +32 (0) 473 690 914 www.arlenda.com PowerPoint Presentation
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Contact: Eric Rozet, Statistician Eric.Rozet@arlenda.com +32 (0) 473 690 914 www.arlenda.com
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  1. Contact: Eric Rozet, Statistician Eric.Rozet@arlenda.com +32 (0) 473 690 914 www.arlenda.com

  2. Transfer of analytical methods: the Bayesian way E. Rozet, P. Lebrun, B. Boulanger Eric.Rozet@arlenda.com www.arlenda.com June 12th 2014, Bayes 2014, London

  3. 3 Analytical Methods signal signal concentration concentration y x No direct quantification ! Concentration (X) = ? signal = y Needs calibration…: … to obtain concentration (X):

  4. 4 Analytical Method Life Cycle Development Selection Life Cycle Routine Use Routineuse Routine Use Method Transfer Validation Sendinglab Validation Guarantees ? Receivinglab Reliability ?

  5. 5 Analytical Method Life Cycle What is the final aim of quantitative analytical methods ? Start with the end ! Objective: provide results used to make decisions Release of a batch Stability/Shelf life Patient health PK/PD studies, … What matters are the results produced by the method. Fit for purposemeans: make correct decisions

  6. 6 AnalyticalMethod Life Cycle Need to demonstrate/guarantee that the analytical method will provide, in its future routine use, quality results in order to make correct decisions This is the key aim of Analytical Method Transfer ! How ?

  7. AnalyticalMethod Transfer strategies • <USP 1024>: Transfer of analyticalprocedures • Co-validation • (Re)-validation • Transfer Waiver • Comparativetesting • Comparative testing: • Samplestakenfrom the sameproduced batch are analyzed at the twolaboratories • Usually not a pairedanalysis due to the destructive nature of assays • Assumes sendinglabis the reference 7

  8. Comparative testing: decisionmethodologies • 4 methodologies have been proposed: • Descriptive: point estimates only • Difference: using bilateral Student t-test • Equivalence: using confidence intervals of the parameters • Total Error: usingstatisticaltoleranceintervals (β-expectation toleranceintervals) • None are fully « fit for purpose » demonstrations: • Ensureat the end of AMT to make correct decisions (e.g. batch release)

  9. Comparative testing: new proposition The aim of AMT is to ensurethat the receivinglab and sendinglabwillmakethe samedecisionsusing the analyticalresultswith« high » probability.

  10. Comparative testing: new proposition • Let: • P(CS): Probability to declare batch Compliant by the Sender • P(CR): Probability to declare batch Compliant by the Receiver • P(CS) ⫫ P(CR) • Objective function: Proba to becompliant in the 2 labs Proba to benoncompliant in the 2 labs Proba to make the samedecision in the 2 labs

  11. Comparative testing: commondesign

  12. 12 Comparative testing: commonmodel • By laboratoryi: • One WayRandom ANOVA model • Compute the posteriorprobability to have resultswithinspecifications (λ) • Then:

  13. 13 Case 1: Content HPLC assay • Transfer betweentwo QC labs of an HPLC assay to quantify an active substance in a drugproduct • Data takenfrom: • Dewé et al., Using total error as decision criterion in analytical method transfer, Chemom. Intel. Lab. Syst. 85 (2007) 262–268. • Design: • 1 batch • Sender: 1 run 6 replicates • Receiver: 3 runs, 6 replicates per run • Specificationlimits (λ): ±5% around the target content

  14. 14 Case 1: Content HPLC assay Sendinglaboratory Receivinglaboratory

  15. 15 Case 1: Content HPLC assay

  16. 16 Case 2: Bioassay • Transfer betweentwo QC labs of parallel line assay • Data takenfrom: • 2012 PDA (Parenteral Drug Association) Technical report N°57 Analytical Method Validation and Transfer for Biotechnology products. • Design: • 1 batch • Sender: 4 runs, 2 replicates per run • Receiver: 4 runs, 2 replicates per run • Specificationlimits (λ): ±10% around the target content

  17. 17 Case 2: Bioassay Sendinglaboratory Receivinglaboratory

  18. 18 Case 2: Bioassay

  19. 19 Case 3: Impurity HPLC assay • Transfer between to QC labs of an HPLC assay to quantify an impurity in a drugproduct • Data takenfrom: • Rozet et al, The transfer of a LC-UV method for the determination of fenofibrateand fenofibricacid in Lidoses: Use of total error as decision criterion,J. Pharm. Biomed. Anal. 42 (2006) 64–70 . • Design: • 1 batch • Sender: 1 run 3 replicates • Receiver: 5 runs, 3 replicates per run • Specificationlimits (λ): <0.180 mg of impurity

  20. 20 Case 3: Impurity HPLC assay Sendinglaboratory Receivinglaboratory

  21. 21 Case 3: Impurity HPLC assay

  22. 22 Case 3: Impurity HPLC assayUsinginformative priorfor sendinglab

  23. Conclusions • The proposedmethodologyallows to make a real fit for purposedecision about the acceptability of the AnalyticalMethod Transfer • Probability of successallows to make a riskbaseddecision • Applicable to any type of assaysnot only quantitative ones • Easy extension to more complex designs (severalbatches, …) • Allows to incorporateprior information

  24. Contact: Eric Rozet, Statistician Eric.Rozet@arlenda.com +32 (0) 473 690 914 www.arlenda.com