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Bioanalytical Method Validation Review: Common Problems. Olutosin Remi Idowu, Ph.D. Division of Human Food Safety Office of New Animal Drug Evaluation FDA Center for Veterinary Medicine ( olutosin.idowu@fda.hhs.gov ). Hierarchy of Analytical Methodology. Technique
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Bioanalytical Method Validation Review: Common Problems Olutosin Remi Idowu, Ph.D. Division of Human Food Safety Office of New Animal Drug Evaluation FDA Center for Veterinary Medicine (olutosin.idowu@fda.hhs.gov)
Hierarchy of Analytical Methodology Technique Scientific principle useful for providing information on analyte concentration Example: HPLC Method Distinct adaptation of a technique for a given analytical purpose Example: HPLC analysis of a drug in cat serum.
Hierarchy of Analytical Methodology • Procedure • Written directions necessary to perform a method • Example: Direction on extraction of sample • Protocol (Method SOP) • Set of definitive directions that must be followed without exception, if the analytical results are to be accepted for a given purpose. • Based of method validation • Has GLP implications although method validation is not required to be GLP-compliant
Method Validation Purposes of Method Validation • Establish the performance characteristics of the method • Demonstrate that an analytical method is acceptable for its intended purpose • Establish a method protocol or SOP
Method Validation Purposes of Method Validation • Ensure appropriate method application • Provide objective basis for evaluating the data obtained when using the method • An often ignored aspect of method validation during later method application
Validation Parameters Recommended in FDA Guidance No. 145 Data Quality-Related Parameters • Preparation and storage stability of standard solutions • Method limit of detection (LOD), lower limit of quantitation (LLOQ) and upper limit of quantitation (ULOQ) • Calibration curve linearity • Method specificity/selectivity
Validation Parameters Recommended in FDA Guidance No. 145 Data Quality-Related Parameters • Intra- and inter-assay precision and accuracy • Method recovery • Ability to dilute samples originally above the method upper limit of quantitation (ULOQ) - Parallelism • System suitability
Validation Parameters Recommended in FDA Guidance No. 145 Sample/Analyte Integrity-Related Parameters 9. Freeze-thaw stability of the analyte in the matrix (plasma or serum) 10. Short-term room temperature stability of the analyte in the matrix
Validation Parameters Recommended in FDA Guidance No. 145 Sample/Analyte Integrity-Related Parameters 11. Long-term storage stability of the analyte in the matrix 12. Post-preparative storage stability of the analyte in extracts – short- and long- term
MethodValidation and Evaluation of Incurred Sample Data Data Quality-Related Parameters • LOD is required to evaluate reliability of chosen LLOQ • LOD, LLOQ, ULOQ required to evaluate the validity/reliability of results from analysis of incurred samples Sample/Analyte Integrity-Related Parameters • Stability data required to provide assurance on the integrity of standard solutions and incurred samples during method application
CommonlyEncountered Problems During Bioanalytical Validation/Data Reviews General Problems • Failure to validate method before application to analysis of incurred samples • GLP implication: Code of Federal Regulations 21 CFR 58.33 require study to follow an approved protocol – including method SOP
CommonlyEncountered Problems During Bioanalytical Validation/Data Reviews General Problems • Failure to demonstrate one or more of the validation parameters • Failure to submit all raw and calculated validation data and chromatograms to CVM
CommonlyEncountered Problems During Bioanalytical Validation/Data Reviews • Specific problems • 1. Preparation and storage stability of standard solutions • Failure to document the calculation of the quantity of compound (salt) required to prepare a stock solution having a given concentration of the active ingredient • Incorrect calculation of the quantity of compound (salt) required to prepare stock solution having a given concentration of the active ingredient
CommonlyEncountered Problems During Bioanalytical Validation/Data Reviews Specific problems 1. Preparation and storage stability of standard solutions (cont.) • Wrong molecular mass of salt or active ingredient • Failure to correct for purity when necessary • Incorrect dilution or concentration scheme usually due to failure to account for the total volume of solution obtained following stock solution dilution
CommonlyEncountered Problems During Bioanalytical Validation/Data Reviews 2. Calibration curve • Incorrect regression parameters • Application of weighted regression without statistical justification • Extrapolating below or above the validated dynamic range of the calibration curve during application of the method to incurred samples
CommonlyEncountered Problems During Bioanalytical Validation/Data Reviews 3. Stability of Analyte in Incurred Sample • Failure to demonstrate the stability of incurred samples from the time of sample collection to the time of last analysis of the samples
CommonlyEncountered Problems During Bioanalytical Validation/Data Reviews 4. Raw and Calculated Data • No Table of raw data used to calculate the validation parameters • No Validation chromatograms or illegible chromatograms • Good Laboratory Practice (GLP) regulations 21 CFR 58.130 require the collection of legible data
CommonlyEncountered Problems During Bioanalytical Validation/Data Reviews 5. LC-MS • Failure to account for the fragment ion being measured • Incorrect ion fragmentation
CommonlyEncountered Problems During Bioanalytical Validation/Data Reviews Method Application Problems 1. Data acceptance criteria • Not included in the SOP • Criteria more forgiving than Guidance No. 145 recommendations
CommonlyEncountered Problems During Bioanalytical Validation/Data Reviews Method application problems 2. Re-assay of incurred samples • Decision to re-assay samples not determined by the pre-set QC-based data acceptance criteria • Use of results that were initially rejected
CommonlyEncountered Problems During Bioanalytical Validation/Data Reviews Method application problems 3. Calculation of concentration of incurred samples • Extrapolating below or above the validated dynamic range of calibration curve
CommonlyEncountered Problems During Bioanalytical Validation/Data Reviews Method application problems 4. Chromatograms • Poor chromatography of incurred samples as compared to method validation samples • No system suitability data that are needed to access chromatographic peak purity
CommonlyEncountered Problems During Bioanalytical Validation/Data Reviews Method application problems 5. Analyst Recertification • Failure to demonstrate analyst recertification with method if extended period has passed between method development and use for bioequivalence study
CommonlyEncountered Problems During Bioanalytical Validation/Data Reviews Avoid Bioanalytical Method Review Problems • Submit validation protocol and proposed method SOP to CVM for review and comment • Validate the parameters recommended by FDA GFI No. 145
CommonlyEncountered Problems During Bioanalytical Validation/Data Reviews Avoid Bioanalytical Method Review Problems • Submit validation data (raw and calculated, and all chromatograms) to CVM for review before application of the method to analysis of incurred samples • Be aware that analytical method SOP will be incorporated into the protocol for a GLP bioequivalence study.
CommonlyEncountered Problems During Bioanalytical Validation/Data Reviews Avoid Bioanalytical Method Review SOP Problems • Ensure that method SOP follows a scientifically acceptable format that includes all required sections • Each section of the method SOP should contain the information relevant to that section, without reference to other SOPs that are not subject to FDA/CVM review for the BEQ study
CommonlyEncountered Problems During Bioanalytical Validation/Data Reviews Avoid Bioanalytical Method Review SOP Problems • Avoid setting Data Acceptance and Sample Re-analysis Criteria that may introduce bias • Use only quantitative Data Acceptance Criteria • Report data as numbers, not statements such as “<LLOQ”