Implementation of flow cytometric biomarker assays in clinical development

Biomarker research has become one of the integral aspects in drug discovery and development. It is broadly utilised to confirm drug mechanism of action (MOA), explore PK/PD correlation, support dose selection and predict response to treatment. Therefore, biomarker data provide valuable information to guide clinical decisions, support drug filings with regulatory agencies and ultimately increase the market value of the drug.

Flow cytometry is a powerful technology for the analysis of multiple biological parameters of individual cells within heterogeneous cell populations. It is widely being used in biomarker research to monitor development and differentiation of cell populations, evaluate target engagement and biomarker expression on/in the cells and assess cell functions and signalling events. However, like most cell-based assays, the implementation of flow cytometric biomarker assays in clinical trials remains a challenge due to the limited stability of clinical specimens, lack of QC materials and the technical variations between analytical laboratories1,2. While the demand for flow cytometric biomarkers increases, assay validation and implementation remains a complex process. With the ultimate goal of timely delivering high quality biomarker data to meet the intended use in cost-effective fashion, the purpose of this review is to provide an overview of current practice in developing, validating and implementing flow cytometric biomarker assays to support drug development.

Assay development, validation and implementation in early clinical development

In early clinical development (phase I/II), a number of potential biomarkers, especially pharmacodynamic (PD) biomarkers, are to be explored. Developing assays with high specificity, sensitivity and robustness is the key at this stage.

While the biomarker hypotheses are usually generated in preclinical studies, clinical biomarker assay development and fit-for-purpose validation occur during the program transition to the clinical stage. In early clinical studies, PK and biomarker results are usually generated from the healthy population. Therefore, samples from healthy donors are often used for assay development and validation. However, in most oncology studies with diseased subjects as the targeted population, the proposed biomarkers may not be expressed at the similar level in patients as that in the healthy donors. In this case, it is necessary to induce biomarker expression mimicking signals expected in the clinical settings3,4. Alternatively, commercially available specimens from diseased subjects may be used for assay development and validation.

The directly florescence-conjugated monoclonal antibodies (mAb) with high affinity to protein of interest are the idea choice. In addition, no drug interference on antibody binding to its target shall be confirmed. This is especially critical in studies of biologics when cell surface protein is the target for drug binding5. When directly conjugated mAb is not commercially available, the use of indirect staining techniques or polyclonal antibodies is an option, but may compromise the ability to quantify the level of protein expression6. To optimise assay sensitivity, brighter fluorochromes, i.e. PE and APC, are often chosen for the detection of proteins with low expression level, while the remaining fluorochromes, i.e. PerCP and FITC, can be used for well-characterised populations such as CD3 and CD47. Once the mAb reagent panel is established, reagent optimisation, including antibody titration to determine the saturating concentration and optimal signal to noise ratio, choice of red blood cell lysing reagents, washes, fixatives and/or permeabilisation reagents, will take place.

When different cell populations are not easily identified by clearly separated cell clusters, proper assay controls are to be considered. Isotype controls or unstained cells used to be widely accepted as gating controls. With the increased use of multiparameter assays, it is now customary to use ‘fluorescence minus one’ (FMO) controls which take into account the effects of spectral overlap from the combination of fluorochromes used in the assay8.

Median Fluorescence Intensity (MFI) can be used to evaluate protein expression level on a per cell basis. Since the signal of fluorescence intensity could change at different photomultiplier tube (PMT) settings on the same cytometer and will vary from instrument to instrument, to standardise the fluorescence signals, the MFI can be converted to Molecules of Equivalent Soluble Fluorochrome (MESF) using reference beads9. Alternatively, one can adjust the instrument settings to provide the same MFI for a reference bead in the target range to provide standardisation10. After a biomarker assay is developed, a validation plan is highly recommended to guide the subsequent tests to quantitatively evaluate the assay performance. In early clinical development, validation for the exploratory biomarkers at minimum includes assessment of sample stability, assay precision, including intraassay precision and inter-assay precision, intra-subject variability4,11.

As the clinical sites of early development are often located in one or a couple countries in the same continent, it takes approximately 24 to 48 hours to deliver the samples to the analytical laboratory. Providing all clinical sites with standardised sample collection, handling and shipping instruction is important to ensure sample integrity. Sample collection tubes with Heparin or EDTA are often used for flow cytometric assays11,12. Upon arrival at the analytical laboratory, the sample integrity, including non-hemolysed and non-clotted conditions, should be evaluated prior to sample process within stability window6.

To ensure consistent assay performance, intra-assay precision (within-run variability assessment) and inter-assay precision (between-run variability assessment) shall be evaluated. Following the fit-for-purpose strategy, precision acceptance criteria should be determined for each assay with consideration of the intended use of the assay. When cell subsets are at least 10 per cent of the parental population, precision with coefficient of variability (CV) less than 20 per cent is generally considered acceptable. However, when measuring rare cell populations or dim fluorescent signals (with low MESF values), a CV up to 30 per cent may also be acceptable. Higher CVs may indicate a need for acquiring more cell events or samples to be analysed in replicates11.

Due to the limited post-collection sample stability, assessing inter-assay precision of whole blood samples is challenging. In some cases, more than one analyst may participate in inter-assay precision experiments. To minimise assay performance variability introduced by different analysts, all analysts should be trained and demonstrate competency with the assay before contributing to assay validation13.

In early clinical studies, exploratory PD biomarkers are often evaluated by testing samples collected at pre- and post-treatment time points. It is essential to test the intra-subject variability using samples from placebo group. Alternatively, samples collected at multiple pre-treatment time points can also be used to evaluate intra-subject variability. Many clinical flow cytometry laboratories are equipped with more than one flow cytometer to handle large numbers of samples from clinical trials. Establishing and implementing an instrument quality plan minimises variability between flow cytometers. Instrument set-up can be standardised to ensure consistency of instrument performance. Additionally, regularly monitoring instrument output helps identify possible instrument malfunctions14,15. Maintaining consistency in key reagents is important to minimise fluctuations in assay results over time. Since whole blood samples for flow cytometric biomarker assays have limited post-collection stability, samples are often processed and analysed upon receiving. Depending on the study design, samples from the same subjects could be collected at different time points with several days to months apart. It is optimal to obtain or sequester sufficient volumes of the same lot of key reagents to perform all analyses in an entire study16. Alternatively, qualifying new lot by performing lot-to-lot comparison prior to switching reagent lots will minimise impact on data quality.

During the course of clinical sample analysis, it is important to use proper quality control (QC) materials to monitor sample processing and analysis. Whenever possible, it is preferred to use QC materials that mimic the clinical sample type and express the biomarkers of interest in the expected target range. Since the signal values of exploratory biomarkers are not easy to anticipate in early clinical trials, continuous evaluation and identification of proper QC materials is a common practice. Once the appropriate QC material is identified, the analytical laboratory shall obtain such QC material in quantity to sustain the length of the study. Preserved whole blood samples are commercially available with a limited phenotype and stability over several weeks and can be used in ambient sample analysis. Alternatively, frozen PBMC or cell lines with expression of biomarker can sometimes be used as ‘home-brewed’ QC materials. The storage condition and stability of such QC materials need to be carefully assessed before being used in clinical studies3,11.

Pre-defined assay acceptance criteria is established by evaluating the 95 per cent confidence interval (mean ± 2 standard deviations) from 10 to 20 analyses using QC materials. During clinical sample analysis, if QC data falls out of acceptance range, it is generally considered that analytical run has failed. Assay troubleshoot is to be carried out immediately to identify and resolve issues in areas including instrument performance, reagent evaluation, sample preparation and data analysis. If necessary, the sample re-analysis is to be performed to prevent loss of data from irreplaceable clinical samples17,18.

Assay validation and implementation in late clinical development

Discussion of the intended use of the biomarker data between the clinical team and the biomarker laboratory is important in all stages of drug development, especially in the later stages (phase III/IV). Because assay validation is an evolving process, the stage-appropriate fitfor- purpose assay validation and laboratory qualification is critical to ensure adequate confidence in the measurements. In studies of registration and product commercialisation, Good Clinical Laboratory Practice (GCLP) and Clinical Laboratory Improvement Amendment (CLIA) guidelines are applied19.

When the flow cytometric biomarker data are to be used for decisions around safety, efficacy, critical PD and differentiation, advanced assay validation is often performed. More rigorous testing of potential interfering components, such as effects of diseased population, disease stages, exposure to different concentrations of drug and concomitant medications, are often evaluated and documented.

With clinical sites located globally, delivery of samples to the analytical laboratory may take much longer. To ensure sample integrity, alternative sample collection methods should be determined to achieve extended sample stability window. While sample collection tubes with Heparin or EDTA may have up to 72-hour post-collection stability, Cyto-Chex blood collection tubes provide extended stability window for some biomarkers12.

With increasing demands of flow cytometric biomarker assays in clinical trials, providers of central laboratory services are expanding flow cytometry capability at networked global laboratories. To effectively manage assay transfer from one laboratory to another, rigorous documentation, controlled SOP with regular review and timely updates and audits are required13. Additionally, strict adherence to performing the assay within guidelines of the SOP is expected. In all cases, to ensure delivery of high quality data, it is important to follow a final written and documented method procedure20.

Upon a validated assay method is trans – ferred, laboratory qualification is performed with pre-defined acceptance criteria. Although in each laboratory, one analyst may primarily be responsible for the assay transfer, more than one analyst is likely to participate in the clinical sample analysis. Therefore, assay training for all analysts followed by a competency assessment is essential to ensure consistent assay performance.

To meet the appropriate level of compliance, standard procedures for data analysis, storage, review, approval and reporting are expected to be established in clinical laboratories. Timely storage of all clinical data files in a validated repository is necessary to protect data integrity and meet regulatory requirements21.

Conclusions

While the use of flow cytometry becomes more prevalent in clinical studies, it is challenging to implement the flow cytometry assays to various stages of drug development, as the stringency of assay validation varies depending on the intended use of data. It is critical to develop an assay implementation plan for assay validation and clinical sample analysis. In the last several years, the American Association of Pharmaceutical Scientists (AAPS) Biotechnology division has established a Flow Cytometry Focus group to take collaborative efforts to provide recommendation on clinical flow cytometry assay implementation and instrument validation. In addition, increased collaboration among pharmaceutical industry, academic and research communities provides great opportunity for the develop ment of best practice guidelines for flow cytometric biomarker assay validation and imple – mentation. It is our hope that the review of validation procedures described here, and the efforts of others in the community, contribute to the establishment of guidelines specific to flow cytometric biomarker assays, to meet compliance requirements for using flow cytometry in drug development.

References

1. Robinson P, Darzynkiewicz Z, Dean PN, et al.: Current Protocols in Cytometry. John Wiley and Sons, New York (2009)
2. Calvelli T, Denny TN, Paxton H, et al.: Guideline for flow cytometric immunophenotyping: A report from the National Institute of Allergy and Infectious Diseases, Division of AIDS. Cytometry. 14, 702-714 (1993)
3. Lee JW, Devanarayan V, Barrett YC et al.: Fit-forpurpose method development and validation for successful biomarker measurement. Pharm. Res. 23(2), 312-328, (2006)
4. Wu DY, Patti-Diaz L, Hill C. The development and validation of flow cytometry methods for pharmacodynamic clinical biomarkers. Bioanalysis. 2, 1617 (2010)
5. Wu D: Standardization of a flow cytometry assay to measure protein expression on monocytes in human whole blood. Presented at: AAPS National Biotechnology Conference, San Diego, CA, USA. 24-27 June 2007
6. Stelzer GT, Marti G, Hurley A, McCoy P, Lovett EJ, Schwartz A. U.S.-Canadian consensus recommendations on the Immunophenotypic analysis of hematologic neoplasia by flow cytometry: Standardization and validation of laboratory procedures. Cytometry. 30, 214-230, (1997)
7. Mahnke Y, Roederer M. Optimizing a multi-color immunophenotyping assay. Clin Lab Med. 27(3), 469 (2007)
8. Roederer M: Spectral compensation for flow cytometry: Visualization artifacts, limitations, and caveats. Cytometry. 45,194-205, (2001)
9. Schwartz A, Gaigalas AK, Wang L, Marti GE, Vogt RF, Fernandez-Repollet E: Formalization of the MESF unit of fluorescence intensity. Cytometry B. 57B, 1-6 (2004).
10. Mittag A, Tarnok A. Basics of standardization and calibration in cytometry – a review. J Biophotonics. (8-9), 470-481 (2009)
11. O’Hara DM, Xu Y, Liang Z, et al: Recommendations for the validation of flow cytometric testing during drug development: II assays. J Immunol Methods. 363, 120 (2011)
12. Davis C, Wu X, Li W, et al. Stability of immuno – phenotypic markers in fixed peripheral blood for extended analysis using flow cytometry. J Immunol Methods. 363, 158 (2011)
13. Ezzelle J, Rodriguez-Chavez IR, Darden JM et al. Guidelines on good clinical laboratory practice: bridging operations between research and clinical research laboratories. J Pharm Biomed Anal. 46(1), 18-29, (2008)
14. Ferbas J, Schroeder MJ. Instrument validation for regulated studies. In: Flow cytometry in drug discovery and development. Litwin V (Ed.) John Wiley and Sons, New York. 267 (2011)
15. Green CL, Brown L, Stewart JJ, et al. Recommendations for the validation of flow cytometric testing during drug development: I instrumentation. J Immunol Methods. 363, 104 (2011)
16. Cunliffe J, Derbyshire N, Keeler S, Coldwell R.: An Approach to the validation of flow cytometry methods. Pharm. Res. 22(12), 2551-2557 (2009).
17. CLIA Standards, 42 CFR Part 493, Subpart K, Standard: Control procedures. 493.1256 (2005)
18. CLIA Standards, 42 CFR Part 493, Subpart K, Standard: Corrective actions. 493.1282 (2005)
19. Hill CG, Wu DY, Ferbas J, et al. Regulatory compliance and method validation. In: Flow cytometry in drug discovery and development. Litwin V (Ed.) John Wiley and Sons, New York. 243 (2011)
20. Maimes MC, Maecker HT, Yan M, et al. Quality assurance of intracellular cytokine staining assays: Analysis of multiple rounds of proficiency testing. J Immunol Methods. 363, 143 (2011)
21. Mountain PJ, Knafel AJ, Butch SH, Dunka L, Markin RS, O’Bryan D. Laboratory instruments and data management systems: Design of software user interfaces and end-user software systems validation operation and monitoring; Approved Guideline Second Edition. Clinical and Laboratory Standards Institute GP19-A2, 23(4), (2003)