Recommendations on biomarker bioanalytical method validation by GCC

Transcription

1 White Paper Special Focus Issue: Bioanalysis of biomarkers For reprint orders, please contact Recommendations on biomarker bioanalytical method validation by GCC The 5th GCC in Barcelona (Spain) and 6th GCC in San Antonio (TX, USA) events provided a unique opportunity for CRO leaders to openly share opinions and perspectives, and to agree upon recommendations on biomarker bioanalytical method validation. Richard Hougton 1, Dominique Gouty 2, John Allinson 3, Rachel Green 1, Mike Losauro 2, Steve Lowes 4, Richard LeLacheur 5, Fabio Garofolo 6, Philippe Couerbe 7, Stéphane Bronner 8, Petra Struwe 9, Christine Schiebl 9, Timothy Sangster 10, Colin Pattison 10, Rafiq Islam 11, Wei Garofolo* 12, Maria Pawula 13, Mike Buonarati 14, Roger Hayes 15, Mark Cameron 15, Robert Nicholson 16, Jake Harman 16, Jaap Wieling 17, Theo De Boer 18, Scott Reuschel 19, Laura Cojocaru 20, Tammy Harter 21, Michele Malone 22 & William Nowatzke 22 Note: Due to the equality principles of Global CRO Council (GCC), the authors are presented in alphabetical order of company name, with the exception of the first five authors who provided a major contribution to this paper. *Author for correspondence: Global CRO Council (GCC), Toronto, Ontario, Canada Tel.: ; wei@global-cro-council.org; Website: Author affiliations can be found at the end of this article. Background The GCC was formed in an effort to bring together many senior level CRO representatives to openly discuss bioanalysis and the regulatory challenges, many of them exclusive to the outsourcing industry. CROs are unique in that they work with many different pharmaceutical companies and agencies, which results in a unique and comprehensive perspective on scientific approaches in relation to regulatory requirements. Since the formation of this international consortium at the 1st GCC Closed Forum held on 14 September 2010 in Montreal, Canada [1], there have been three meetings in North America [2,3] and two meetings in Europe [4,5]. Furthermore, GCC has published its official recommendations in White Papers [2,5,6], which were well received within the bio analytical arena, including regulatory agencies, and an additional three papers are presently in progress. In an effort to accommodate the schedules of the CRO representatives, GCC meetings will continue to be tied to major conferences where attendance by member companies is anticipated. More information on the GCC unique structure can be found in the publication titled Formation of a GCC [1]. Introduction The 5th GCC Closed Forum was held on 13 November 2011 in Barcelona (Spain) and the 6th GCC Closed Forum was held on 27 April 2012 in San Antonio (TX, USA). A subgroup of CROs highly specialized in biomarker analysis has further expanded, discussed, reached consensus and is now proposing a recommendation on biomarker assay validations. The discussion on this topic began at the 3rd GCC meeting held in Guildford (UK) on 3 and 4 July 2011 where the challenges of biomarker assay validation were identified and the need to generate an official recommendation for the CRO bioanalytical community was confirmed. Biomarker validation A survey was circulated to the GCC members posing questions on the different approaches to qualify or validate biomarker methods. The goal was to be able to form a consensus on qualification or validation of the methods. The results of this survey on biomarkers are presented in Table 1. From the survey, it was found that the most common reference documents used for biomarker qualification and validation are the US FDA guidance [7], the European Medicines /BIO Future Science Ltd Bioanalysis (2012) 4(20), ISSN

2 White Paper Global CRO Council for Bioanalysis (GCC) Table 1. GCC survey on biomarker. Question Europe North America Does your organization apply different definitions to biomarker methods based on study end point and what are they? When would your organization apply a fit-for-purpose qualification to a biomarker method? What parameters would you include in a fit-for-purpose qualification of a biomarker assay? Do you set acceptance criteria before or after the method qualification/ validation for biomarker methods? Yes: 75%; No: 25% Yes: 44%; No: 56% Primary differentiation for bioanalysis: exploratory versus surrogate end point Biomarker definitions: exploratory/research/safety/pd/proof-of-mechanism/primary and secondary end point/stratification/companion diagnostic Regulated method not achievable: 37.5% For everything: 37.5% At sponsor s request: 12.5% Exploratory biomarkers: 12.5% Ligand-binding Calibration: 89% Precision and accuracy : 89% Selectivity/specificity: 78% Parallelism: 67% Storage stability: 67% Sensitivity: 56% Linearity of dilution: 44% Recovery: 33% Others: cross-reactivity, whole plate imprecision, minimum required dilution evaluation Clinical analyzers Calibration: 88% Precision and accuracy: 88% Linearity of dilution: 63% Storage stability: 50% Selectivity/specificity: 38% Parallelism: 38% Recovery: 38% Sensitivity: 25% Kit parameters: 25% Others: reference ranges ( subjects), cross-reactivity Small molecules Calibration: 100% Precision and accuracy: 100% Selectivity/specificity: 90% Matrix effects: 70% Parallelism: 30% Storage stability: 70% Sensitivity: 60% Linearity of dilution: 40% Recovery: 40% Others: reference ranges, carryover Before: 50% After: 12.5% Before and after: 37.5% Regulated method not achievable: 18% For everything: 36.5% At sponsor s request: 9% Exploratory biomarkers: 36.5% Ligand-binding Calibration: 100% Precision and accuracy : 100% Selectivity/specificity: 100% Parallelism: 60% Storage stability: 80% Sensitivity: 60% Linearity of dilution: 60% Recovery: 60% Others: 20%; specificity/cross-reactivity, minimum required dilution evaluation Clinical analyzers No reply from North America Small molecules Calibration: 100% Precision and accuracy: 100% Selectivity/specificity: 100% Matrix effects: 50% Parallelism: 25% Storage stability: 100% Sensitivity: 75% Linearity of dilution: 0% Recovery: 50% Others: reference ranges, carryover Before: 56% After: 11% Modified based on performance: 33% A CRO stated that the acceptance criteria for QCs during sample analysis is statistically linked to the performance of the method at validation using a confidence limit approach Accuracy is not achievable for most biomarkers, only precision check. CLSI: Clinical and Laboratory Standards Institute; EMA: European Medicines Agency; GxP: Good x practice; x can mean clinical, laboratory, manufacturing, pharmaceutical and so forth. Agency guideline [8], Lee et al. [9,10], Chau et al. [11], Cummings et al. [12], Valentin et al. [13] and Clinical and Laboratory Standards Institute (CLSI) guidelines (formerly NCCLS) [101]. As biomarkers are used more and more for determining subjects/patients safety, and biomarker bioanalysis data are currently being submitted to regulatory agencies, it is expected that guidance for biomarker assessments will be included in the upcoming revision of the FDA guidance for method validation expected in From the survey results and subsequent discussions, the majority of organizations apply a fit-for-purpose approach to develop methods 2440 Bioanalysis (2012) 4(20)

3 Recommendations on biomarker bioanalytical method validation White Paper Table 1. GCC survey on biomarker (cont.). Question Europe North America How do you apply acceptance criteria to both qualification/ validation of biomarker methods? What claim of compliance is made for a fit-for-purpose qualification of a biomarker method? What claim of compliance is made for the validation of a biomarker method? What industry reference documents do you refer to for biomarker qualification/validation? For small-molecule biomarker methods, do you use a surrogate matrix, standard addition or some other approach (other)? How often do you apply relative quantitative biomarker methods? Does your organization segregate biomarker work from regulated bioanalysis and, if so, how is this done? Ligand-binding US FDA acceptance criteria: 57% ±20% and total error ±20%: 14% Data reported with QC performance: 14% measure a particular PD change: 14% Clinical analyzers Meets kit performance: 50% ±15%: 17% Data reported with QC performance: 17% measure a particular PD change: 17% Small molecules FDA (±15%): 63% FDA (±20%): 13% Data reported with QC performance: 13% measure a particular PD change: 13% None: 87.5% GxP or none: 12.5% Ligand-binding FDA acceptance criteria: 60% ±20% and total error ±20%: 20% measure a particular PD change: 20% Clinical analyzers Treated as any other large-molecule assay: 100% Small molecules FDA (±15% or as required): 40% FDA (±20%): 20% measure a particular PD change: 40% None: 89% GxP or none: 11% A CRO stated GLP, GCP or no compliance depending on the study but would call it a validation GxP: 25% GLP: 37.5% Non-regulated: 37.5% FDA guidance/ema guideline [7,8] Lee et al. (2006 and 2009) [9,10] Chau et al. (2008) [11] Cummings et al. (2010) [12] Valentin et al. (2011) [13] CLSI guidelines (formerly NCCLS) [101] Surrogate matrix: 40% Standard addition: 30% Surrogate analyte: 20% Rarely: 75% Often: 25% Yes: 25% No: 75% A CRO stated that they have separate departments: department of bioanalysis and department of biopharmaceuticals and biomarkers GxP: 22% GLP: 44% Non-regulated: 34% FDA guidance/ema guideline [7,8] Title 21, Part 58 (FDA GLP) [14] Lee et al. (2006 and 2009) [9,10] Nowatzke and Bowsher (2010) [15] Other White Papers not detailed Surrogate matrix: 50% Standard addition: 25% Surrogate analyte: 25% Rarely: 71% Often: 29% Yes: 22% No: 78% A CRO stated they would consider considering a change if appropriate for client needs Accuracy is not achievable for most biomarkers, only precision check. CLSI: Clinical and Laboratory Standards Institute; EMA: European Medicines Agency; GxP: Good x practice; x can mean clinical, laboratory, manufacturing, pharmaceutical and so forth. by establishing the expectations of the sponsor, defining the scientific goal and the purpose of the assay in terms of target values and acceptance limits, for example, defining the clinical end point, and characterizing the performance of the method during its development or using the precision and accuracy results from validation to set the acceptance criteria for sample analysis using a confidence limit approach. The survey also showed that members use surrogate matrices, surrogate analytes, standard addition and/or other approaches to overcome the inherent problem of endogenous levels for biomarker. The different approaches each have advantages and disadvantages, and selection depends on the intended use and the availability of resources. The consensus reached was that when there is a definitive quantitative clinical end point, the biomarker assay needs to be fully validated and the acceptance criteria should be set based on assay performance and the anticipated use;

4 White Paper Global CRO Council for Bioanalysis (GCC) for example, if determining a change in concentration of tenfold is all that is required, then the FDA guidance [7] or European Medicines Agency guideline [8] acceptance criteria may be unnecessarily stringent for the purpose. When there is a relative clinical end point, the biomarker assay could be validated using the fitfor-purpose approach (some laboratories term this qualification ). Although it was generally acknowledged that the use of reference standards and the calculation of accuracy give the data interpreter and regulators greater confidence in the results of the method, for some reference standards and calculation of accuracy may not be necessary; for example, a screening method. Screening and qualified biomarker are often fit-for-purpose and cost less than validated. If these tiers were used appropriately, then biomarker may be used more widely in the discovery phase. The GCC members claim different regulatory compliance depending upon the degree of qualification/validation, and also due to the regulatory jurisdiction they exist within (e.g., in the UK, GCP would apply regardless of the use of the assay or validation status if human samples are being analyzed). In general, as well as a difference in the extent and level of validation experiments due to regulatory implications, there are also implications with regard to quality assurance involvement in the process and documentation reviews/audits. Currently, most members perform biomarker analysis, including that are not validated, alongside regulated bioanalysis, although some would consider segregating the work if this was required by their sponsors. GCC recommendations The GCC recommends three tiers of biomarker bioanalytical method establishment: Validated; Qualified; Screening. There is still clearly a difference of opinion in what terminology laboratories use to define the tier-level approach to biomarker assay validations. Given the use of the term qualification in the clinical biomarker arena, it would appear to be a good idea to continue to strive for different terminology to avoid ambiguity in laboratory analysis of biomarkers and the tiered approach to validation. One of the major points to take into consideration during method development is to select the appropriate minimum required dilution (MRD). The assay platforms are similar to the ones used for PK/TK ; however, the fundamental approach to determine the MRD is opposite. The biomarker assay needs to be able to detect endogenous level, therefore, the QCs should include a matrix QC (blank) diluted at the MRD as well as spiked QCs (care needs to be taken if using a pooled matrix for QCs due to the potential for analytical issues e.g., aggregation). Overall, one of the typical errors found in the validation of a biomarker is the dilution of serum/plasma to a certain point to try to get a good recovery of the spiked QCs. By doing so, the sample results end up being all below the LOQ during sample analysis. Therefore, the first step should be to always run individuals (normal individuals and disease population) to ensure the correct MRD is chosen. This should be done using parallelism experiments. Table 2 presents the suggested requirements for screening, qualified and validated biomarker for ligand-binding as well as the target acceptance criteria. Clearly, at this point in time, there are no regulatory guidance/guidelines for the validation of biomarker ; only White Papers. However, some of the White Papers have a large representation of different and appropriate scientific authors that have reviewed the experimental requirements and gained a consensus. Some have now been used fairly widely for over 5 years (e.g., Lee et al.) [9]. Therefore, it is recommended that when validating biomarker, the spirit of the exercise should be based on what is expected regulatory wise as laboratories have become accustomed to using regulatory guidance documents in the PK arena over many years. However, due to the different uses of the data (i.e., the clinical implications that are not covered in PK guidance), specific biomarker White Papers, which contain the most appropriate method to validate to ensure they are appropriate for their intended use, are recommended. In addition, it should be considered that the a priori approach is fine for validation, if required, but setting criteria for sample analysis based on the method performance is still the most scientifically sound approach 2442 Bioanalysis (2012) 4(20)

5 Recommendations on biomarker bioanalytical method validation White Paper Table 2. Suggested requirements for screening, qualified and validated biomarker for ligand-binding as well as the target acceptance criteria. Assay performance characteristics Screening Qualified Validated Target acceptance criteria Precision Yes Yes Yes In novel biomarker where there is little or no clinical information on the biomarker of interest, targets for validation performance for the between run (inter-assay) and the within run (intra-assay) CVs should be 25% for the LLOQ QC and 20% for the low, medium, high and ULOQ QCs Accuracy: the agreement between the observed value and the expected or nominal (established) value Yes Yes Yes Range based on ±2 and 3 SD or %RE = mean observed conc. c 100 expected conc. + blank m) When %RE is a multiple of the inter-assay CV of the method; Any QC results >±3 SD is an automatic failure criteria Parallelism Yes Yes Yes Back-calculated dilution adjusted results (% recovery) within ±3 SD (three-times inter-assay %CV) Comments Inter-assay precision is the critical assay performance characteristic to obtain meaningful clinical results; Acceptance criteria for sample analysis can be set on a statistical basis from the data produced at validation, this then confirms the assay is continually and demonstrably under control Accuracy is not always achievable with biomarkers due to the presence of binding proteins or targets; Different acceptance rules can be applied to this information (e.g., ±2 SD = warning, everything has to be within ±3 SD, and the difference between the lowest and highest QC on a batch should not exceed 4 SD) At least three to ten samples from normal or diseased individuals (depending upon biomarker concentration); Since parallelism can demonstrate matrix interference effects, other tests can also be done; Optional: 3 5 individuals with hemolysis and 3 5 individuals with lipidemia for validated assay Specificity No Yes (optional) Yes Total %reactivity = The specificity will be evaluated by HQC PRA spiking the matrix with the average c; 100 ; HQC TA E ) m potential reactive analyte at high, MQC PRA medium and low QC levels; c; 100 ; MQC TA E ) m For a qualified assay, specificity is LQC PRA optional depending on the c; 100 LQC TA E ) m biomarker of interest. For example, NRP1 biomarker will need to be checked on the cross-reactivity of NRP2. Cross-reactivity provided by vendor should be sufficient for qualified %RE: Percentage relative error; HQC: High QC; LQC: Low QC; MQC: Medium QC; PRA: Potential reactive analyte; TA: Target analyte. of controlling the assay in the production phase. It should take into account end point expectations as well as the knowledge of physiological variability. This means that the target acceptance criteria for sample analysis is also set a priori but may be different from that of the validation itself. This is also a sensible approach as clinical and physio logical information are often lacking for novel biomarkers and, therefore, a priori criteria for these are often chosen without any really sound clinical basis. Box 1 shows the suggested minimum requirements for a qualified method with the option of setting acceptance criteria based on the performance of the assay during the qualification process. For ligand-binding and clinical analyzer methods without a reference standard, some sort of positive/negative control is required;

6 White Paper Global CRO Council for Bioanalysis (GCC) Table 2. Suggested requirements for screening, qualified and validated biomarker for ligand-binding as well as the target acceptance criteria. (cont.). Assay performance characteristics Specificity test article Linearity on dilution (using spiked samples) Screening Qualified Validated Target acceptance criteria Yes Yes Yes Test article should be spiked into matrix preferably an unspiked matrix that contains a significant concentration of biomarker or a mid-level QC sample. A range of spikes from 10 to 300% expected C max is advised; Acceptance ±three-times inter-assay %CV Yes only if parallelism cannot be completed Optional Yes only if parallelism cannot be completed R 2 > 0.95; Dilutional linearity is expressed in terms of the agreement (%RE) between the observed results and a nominal target value (nominal value plus endogenous) at three-times inter-assay %CV within the range of quantitation Selectivity No Optional Yes Acceptance criteria based on the range of QCs (3 SD or %RE) Benchtop stability No Optional Yes Acceptance criteria is based on QCs (3 SD at each level of the QC range or %RE) %RE = mean observed conc. c 100 expected conc. + blank m) Comments N/A Endogenous level needs to be taken in consideration in the calculation To be reported; Background need to be subtracted first. If an individual is high compared with the pool serum, then selectivity will not pass Matrice pool should be identical than the one used for determination of the range in precision and accuracy runs Freeze thaw stability No Optional, recommended Yes Acceptance criteria is based on QCs (3 SD at each level of the QC range or %RE) %RE = mean observed conc. c 100 expected conc. + blank m) Matrice pool should be identical than the one used for determination of the range in precision and accuracy runs Long-term stability No Optional, recommended Yes Acceptance criteria is based on QCs (3 SD at each level of the QC range or %RE) %RE = mean observed conc. c 100 expected conc. + blank m) Matrice pool should be identical than the one used for determination of the range in precision and accuracy runs %RE: Percentage relative error; PRA: Potential reactive analyte; QCH: QC high; QCL: QC low; QCM: QC medium; TA: Target analyte. without this, it is difficult to be certain what is being measured. For LC MS/MS methods, the measurement of the mass of the ions provides a degree of selectivity and theoretical transitions can be chosen. The other parameter that should be measured is the precision of measurement to allow statistical evaluation of the significance of any PD change in the biomarker. Future perspective The GCC will continue to provide recommendations on hot topics in bioanalysis of global interest and expand its membership by coordinating its activities with regional and international meetings held by the pharmaceutical industry. Please contact the GCC [102] for the dates and times of future GCC closed forums, and for all membership information. Acknowledgements The GCC would like to thank the following: R Houghton and R Green (Quotient) for leading this initiative, designing the survey, collating the results and making this article a reality; D Gouty (Intertek Alta Immunochemistry), J Allinson (Icon) and M Losauro (Intertek Alta Immunochemistry) for critical review and edition of this 2444 Bioanalysis (2012) 4(20)

7 Recommendations on biomarker bioanalytical method validation White Paper Box 1. Suggested minimum requirements for a qualified method with the option of setting acceptance criteria based on the performance of the assay during the qualification process. Ligand-binding Calibration Precision Selectivity Parallelism Limited storage stability, Specificity (optional) Clinical analyzer methods Calibration Precision and accuracy Linearity of dilution (parallelism ) Selectivity/specificity Limited storage stability LC MS/MS methods Calibration Precision and accuracy Selectivity/specificity Matrix effects/parallelism Limited storage stability Sensitivity Accuracy not applicable. If there is endogenous level present, then percentage relative error (%RE) should include the endogenous (blank) level in the calculation: %RE = observed value c; - 1 ) 100 nominal value + blank QC E m Due to the requirement for samples containing significant concentrations of the biomarker of interest, it may not be possible to conduct these tests until incurred samples are available (with appropriate consent). Long-term stability and freeze thaw stability are critical steps for biomarkers as most of the sample aliquot is used to test multiple biomarkers and very often goes above seven freeze thaw cycles. They are also typically run at the end of the studies, so a 2-year long-term stability is needed. document; R Houghton and J Allinson for facilitating and leading the discussion on biomarkers during the 5th GCC (Barcelona, Spain) and 6th GCC (San Antonio, TX, USA) meetings, respectively; I Dumont and S Martinez (Algorithme Pharma) and T Harter (Unilabs York Bioanalytical Solutions, currently working at Covance Laboratories) for writing the first draft of this White Paper; the GCC member companies who answered the biomarker survey and sent comments and suggestions to complete this White Paper; W Garofolo (GCC) for organizing the logistics of the meetings and coordinating the review of this document. Financial & competing interests disclosure The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert t estimony, grants or patents received or pending, or royalties. No writing assistance was utilized in the production of this manuscript. Author affiliations Except for the first three, company names are in alphabetical order: 1 Quotient Bioresearch, Fordham, UK 2 Intertek Alta Immunochemistry, San Diego, CA, USA 3 Icon Development Solutions, Manchester, UK 4 Advion Bioanalytical Labs, a Quintiles Company, Ithaca, NY, USA 5 Agilux Laboratories, Worcester, MA, USA 6 Algorithme Pharma/Simbec Research, Laval, QC, Canada/ Merthyr Tydfil, UK 7 Atlanbio, St-Nazaire, France 8 Avogadro, Toulouse, France 9 Celerion, Fehraltorf, Switzerland 10 Charles River, Edinburgh, UK 11 EMD Millipore, St Charles, MO, USA (currently working at Celerion, Lincoln, NE, USA) 12 GCC 13 Huntingdon Life Sciences, Huntingdon, UK 14 Intertek Alta LCMS, San Diego, CA, USA 15 MPI Research, Mattawan, MI, USA 16 PPD, Richmond, VA, USA 17 QPS Netherlands BV, Groningen, The Netherlands 18 QPS Netherlands BV, Groningen, The Netherlands (currently working at Eurofins, Groningen, The Netherlands) 19 Tandem Labs, Salt Lake City, UT, USA 20 Tandem Labs, West Trenton, NJ, USA 21 Unilabs York Bioanalytical Solutions, York, UK (currently working at Covance Laboratories, Harrogate, UK) 22 Worldwide Clinical Trials, Austin, TX, USA

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