The COVID-19 pandemic has strained the biological matrix supply chain. An upsurge in demand driven by numerous COVID-19 therapeutic and vaccine development programs to combat the pandemic, along with logistical challenges sourcing and transporting matrix, has led to increased lead times for multiple matrices. Biological matrix shortages can potentially cause significant delays in drug development programs across the pharmaceutical and biotechnology industry. Given the current circumstances, discussion is warranted around what will likely be increased use of surrogate matrices in support of pharmacokinetic (PK), immunogenicity, and biomarker assays for regulatory filings. Regulatory authorities permit the use of surrogate matrix in bioanalytical methods in instances where matrix is rare or difficult to obtain, as long as the surrogate is appropriately selected and scientifically justified. Herein, the scientific justification and possible regulatory implications of employing surrogate matrix in PK, immunogenicity, and biomarker assays are discussed. In addition, the unique challenges that cell and gene therapy (C&GT) and other innovative therapeutic modalities place on matrix supply chains are outlined. Matrix suppliers and contract research organizations (CROs) are actively implementing mitigation strategies to alleviate the current strain on the matrix supply chain and better prepare the industry for any future unexpected strains. To maintain ethical standards, these mitigation strategies include projecting matrix needs with suppliers at least 6 months in advance and writing or updating study protocols to allow for additional matrix draws from study subjects and/or re-purposing of subject matrix from one drug development program to another.

Flow cytometer is a powerful cellular analysis tool consists of three main components; fluidics, optics and electronics. Flow cytometry methods have been used in all stages of drug development as like ligand binding assays (LBA). Both LBA and flow cytometry methods require specific interaction between the critical reagents and the analytes. Antibodies and their conjugates, viable dyes and permeabilizing buffer are the main critical reagents in flow cytometry methods. Similarly, antibodies, engineered proteins and their conjugates are the main critical reagents in LBA. The main difference between the two methods is the lack of true reference standards for flow cytometry cellular analysis.

Multiparametric flow cytometry is a powerful cellular analysis tool used in various stages of drug development. In adoptive cell therapies, the flow cytometry methods are used for the evaluation of advanced cellular products during manufacturing and to monitor cellular kinetics after infusion. In this report, we discussed the bioanalytical method development challenges to monitor cellular kinetics in CAR-T cell therapies. These method development challenges include procuring positive control samples for the development of the method, flow cytometry panel design, LLOQ, prestain sample stability, staining reagents and data analysis.

Aim: Globally, neurodegeneration accounts for significant morbidity and mortality among the elderly. Millions of people are afflicted with neurodegenerative diseases, with the most notable cases attributed to Alzheimer's, Huntington's, amyotrophic lateral sclerosis and Parkinson's diseases. Sensitive assays that can detect proteopathic anomalies indicative of early neurodegeneration have remained elusive. Therefore, there is an urgent need for sensitive diagnostic and prognostic biomarker assays that can guide the therapeutic regimen in the clinic. Materials & methods: Single molecule array digital immunoassay platform has sensitivity about 1000-fold higher than traditional ligand binding assays. Consequently, we are now beginning to implement ultrasensitive techniques in bioanalysis. Conclusion: In the current study, we evaluated single molecule array technology and report specifications to quantitate neurofilament light chain, a bona-fide biomarker for neurodegeneration. Preliminary neurofilament light screening results from 100 human geriatric cerebrospinal fluid samples displayed huge biological variation and warrants further investigation.

The 12th GCC Closed Forum was held in Philadelphia, PA, USA, on 9 April 2018. Representatives from international bioanalytical Contract Research Organizations were in attendance in order to discuss scientific and regulatory issues specific to bioanalysis. The issues discussed at the meeting included: critical reagents; oligonucleotides; certificates of analysis; method transfer; high resolution mass spectrometry; flow cytometry; recent regulatory findings and case studies involving stability and nonclinical immunogenicity. Conclusions and consensus from discussions of these topics are included in this article.

We evaluated the sample stability for a cellular kinetics and a pharmacodynamic flow cytometry methods. First, the blood collection tubes were compared for the enumeration of chimeric antigen receptor-T cells in human whole blood. Blood samples with chimeric antigen receptor-T cells were stable up to 3 days at room temperature in both conventional EDTA and Cyto-Chex® blood collection tubes (Streck Laboratories, NE, USA), but with better consistency in Cyto-Chex-BCT than conventional EDTA tubes. Second, sample storage temperatures were compared for the basophil activation test in human whole blood samples. The samples were stable up to 3 days for basophil activation test when stored at refrigerator temperature, but not stable when stored at room temperature. It is crucial during the development of method to evaluate all the variables which might impact sample integrity.

Over the last decade, the use of biomarker data has become integral to drug development. Biomarkers are not only utilized for internal decision-making by sponsors; they are increasingly utilized to make critical decisions for drug safety and efficacy. As the regulatory agencies are routinely making decisions based on biomarker data, there has been significant scrutiny on the validation of biomarker methods. Contract research organizations regularly use commercially available immunoassay kits to validate biomarker methods. However, adaptation of such kits in a regulated environment presents significant challenges and was one of the key topics discussed during the 12th Global Contract Research Organization Council for Bioanalysis (GCC) meeting. This White Paper reports the GCC members’ opinion on the challenges facing the industry and the GCC recommendations on the classification of commercial kits that can be a win-win for commercial kit vendors and end users.

The importance of the length and/or structure of fluorescently labeled PNA (peptide nucleic acid) probes for quantitative determination of oligodeoxynucleotides (ODNs) is demonstrated in human plasma using hybridization-based LC-fluorescence assays. The length of the PNA probes impacts the peak shape and chromatographic separation of the resulting PNA/ODN hybridization complexes and affects assay sensitivity, dynamic range and carryover. For quantitative determination of an 18-mer phosphodiester ODN (DNL1818) in human plasma, an assay utilizing an Atto-dye-labeled 12-mer PNA probe provided a linear quantitation range of 0.1-50 ng/ml with excellent accuracy and precision (within -5.3-7.73%). This method provides a convenient method for sensitive and specific quantification of ODNs in biological matrix with limited sample volume and no special extraction.

Pharmacokinetics (PK) defines the disposition of a drug in the body based primarily on measurements in fluids or tissues by various bioanalytical methods during the drug development.Most bioanalytical methods utilize ligandbinding or LC-MS technology, and the assays are validated and applied following the guidelines from various regulatory agencies in their countries (e.g., US FDA, EMEA or Health Canada) [1].These bioanalytical method guidelines focus on the PK of traditional drug compounds; small molecules and large biomolecules.The CAR-T (chimeric antigen receptor) cell therapies, recently approved by FDA, involve administration of 'living drugs' capable of proliferation after infusion.This behavior is very different from conventional drug compounds, and the term 'cellular kinetics' was coined for in vivo 'PK monitoring' of both the expansion and persistence of the genetically engineered CAR-T cells [2].The bioanalytical methods used to measure the levels of these infused cells also differ from conventional methodologies; molecular (polymerase chain reaction-qPCR and sequencing) and cellular assays (flow cytometry) [3].These two technologies play a significant role in the drug development in the recent years.This article is focused on the challenges in the development of flow cytometry bioanalytical methods to quantitatively measure CAR-T cell levels in adoptive cell therapy.

BioanalysisVol. 10, No. 12 EditorialOpen AccessSinglicate analysis: should this be the default for biomarker measurements using ligand-binding assays?Zhuqiu Ye, Jing Tu, Krishna Midde, Mike Edwards & Patrick BennettZhuqiu Ye*Author for correspondence: Tel.: +1 804 977 8334; E-mail Address: zhuqiu.ye@ppdi.com Biomarker Services, PPD Laboratories, 2244 Dabney Road, Richmond, VA 23230, USA, Jing Tu Biomarker Services, PPD Laboratories, 2244 Dabney Road, Richmond, VA 23230, USA, Krishna Midde Biomarker Services, PPD Laboratories, 2244 Dabney Road, Richmond, VA 23230, USA, Mike Edwards Biomarker Services, PPD Laboratories, 2244 Dabney Road, Richmond, VA 23230, USA & Patrick Bennett Biomarker Services, PPD Laboratories, 2244 Dabney Road, Richmond, VA 23230, USAPublished Online:20 Jun 2018https://doi.org/10.4155/bio-2018-0067AboutSectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack Citations ShareShare onFacebookTwitterLinkedInReddit Keywords: biomarkerfit-for-purposeligand-binding assaynonregulated bioanalysisregulated bioanalysissinglicate analysisEvolution of biomarker ligand-binding assays: past & presentRegulated ligand-binding assays (LBAs) must undergo stringent validation in order to provide sufficient confidence in the data. Enormous amount of time, expense and effort are consumed to develop a new drug and get it released for use. If the drug candidate meets with late stage failure, the losses can be disastrous. Therefore, pharmaceutical companies are constantly seeking ways to improve effectiveness in the drug development process with reduced costs and time. Advances in our understanding of biology and disease mechanisms have led to a rapidly growing interest in using biomarkers to enhance the drug discovery/development process. Traditionally, biomarkers have been widely analyzed in clinical laboratories for disease diagnosis, prognosis and strategizing therapeutic interventions. Biomarkers have also been used in later-stage clinical studies as an effective adjunct to assess drug efficacy and toxicity. In recent years, exploratory biomarkers have been increasingly utilized to help pharmaceutical companies make internal decisions on early stage clinical studies such as proof of concept, go-no-go decision and mechanism of action by offering rapid turnaround and fit-for-purpose method validation strategies in nonregulated environments [1].Biomarker method validation typically evaluates fundamental parameters, including precision, accuracy, selectivity, specificity, parallelism and stability. Parallelism is critical to assess relative accuracy, sensitivity, matrix effect and minimum required dilution [2]. Precision and accuracy are essential to define assay reproducibility. There are many sources of assay variability, either within a run or between different runs. For example, traditional plate-based ELISA involves manual steps that tend to introduce human errors compromising either intra-assay or inter-assay precision and accuracy. For LBA in bioanalysis, it is a long-standing practice to perform duplicate (or even triplicate) analysis of calibration curves, QCs and samples to reduce potential assay variability.However, in the modern LBA world, duplicate analysis may no longer serve its intended purpose. First, it is questionable if duplicate analysis improves assay variability. Conventional 'duplicate analysis' is performed by pipetting a sample into two adjacent wells. Today's handheld pipettes are manufactured to be highly repeatable. Use of automated pipetting can further reduce variability by eliminating repetitive manual operations. Pipetting two aliquots of a sample into adjacent wells is far less likely to cause assay variability when compared with more complex operations such as independent sample preparations in separate runs. This probably explains why intra-assay variation is typically much tighter than inter-assay variation in most LBAs. Second, with the advancement in science and technology, novel highly reproducible platforms have emerged that are extensively employed for bioanalytical labs. Examples of these instrumentation platforms include Meso Scale Diagnostics™ MSD® (MesoScale Discovery) (electro-chemiluminescent immunoassay), Gyros Protein Technologies™ Gyrolab® (disc-based microfluidic system), Singulex™ Erenna® and Quanterix™ Simoa® (paramagnetic bead based systems) and Protein Simple™ ELLA Simple Plex® (cartridge-based microfluid system). LBA methods using such automation, multiplexing and multiarray systems are providing excellent precision and accuracy, high-throughput and ultimate sensitivity with reduced costs. Last, the utilization of high-quality reagents, optimized method designs and automatic liquid handlers has also improved assay performance to a significant extent.Current regulatory guidelines specifying replicate analysis in LBA method validation differ. The US FDA [3] mentions that accuracy and precision can be improved by the use of duplicate analysis but only recommends duplicate analysis for calibrator samples and quality control samples, whereas the European Medicine Agency guideline [4] recommends the analysis of calibrators, quality control and study samples at least in duplicate. Does duplicate analysis necessarily correlate with improved precision and accuracy? Can singlicate analysis deliver the same quality of data as duplicate analysis? The 6th Workshop on Recent Issues in Bioanalysis (WRIB) meeting in 2012 addressed this topic and reached a consensus: "It is generally accepted to run singlicate analysis once the assay has been demonstrated to be robust" [5]. At the Crystal City V meeting in 2013, a similar consensus was reached: "The concept of running singlet analysis for LBAs if the method allows this and the number of replicates can be driven by the data during validation" [6]. The 10th European Bioanalysis Forum (EBF) Workshop in Barcelona, November 2017, opened a panel discussion solely on this topic, and each panelist (Enric Bertran of Roche Innovation Center Basel, Johannes Stanta of Covance, Craig Stovold of AstraZeneca and James Lawrence of Envigo) presented comparison studies of duplicate analysis results with simultaneous singlet evaluation of designated duplicates. Their data demonstrated that the outcome of key parameters both for validation and study samples was within a one-digit difference between duplicate and singlicate analysis. Matthew Barfield (from GSK) mentioned that GSK had filed five successful submissions of compounds, all done in singlicate analysis, without raising any concerns from regulatory authorities (during workshop WS-8: Single vs Duplicates, EBF 10th Open Symposium 15–17 November 2017). A few groups already have taken the initiative to publish their work comparing duplicate and singlicate analysis for regulated PK LBA performance. At the 7th EBF workshop in 2014, the QPS (Quest Pharmeceutical Services, LLC) Netherlands LBA group recalculated the results using singlicate approaches out of duplicate results. Their data showed that there were no significant differences between prestudy validation, in-study validation including incurred sample reanalysis (ISR), and test sample results between duplicates and singlicates [7]. Clark and his colleagues evaluated the relative precision of duplicates compared with singlicates using 60 Gyrolab datasets containing over 23,000 replicate pairs in up to 23 assays. They found no statistically significant bias in intrasubject variability between the replicates, while a significant intersubject variability was observed. They concluded that running replicates from the same sample will not significantly reduce variation or change PK parameters [8]. Hottenstein et al. also compared a GSK ligand-binding method validation performed in singlicate for a biotherapeutic fusion protein with the results from QPS where the validation was completed in duplicate. They concluded that LBAs performed by singlicate analysis can deliver robust data as duplicate analysis, which meets current regulatory and industry guidance [9].Singlicate analysis: regulatory acceptance & scientific implementationAlthough the acceptance of singlicate analysis has been proposed for a while, the regulated bioanalytical community remains apprehensive of accepting singlicate analysis into routine practice. What is preventing them from doing so? The reason is seemingly due to the absence of a clear regulatory guideline for singlicate analysis. Unless sufficient evidence is collected, regulatory authorities may not be convinced that the singlicate analysis approach is sound. The burden-of-proof to generate supporting data for singlicate analysis is with pharmaceutical companies and CROs. To shift the industry paradigm, more solid data demonstrating comparable precision and accuracy results between singlicate and duplicate analysis are needed.In fact, singlicate analysis is not just wishful thinking. Singlicate analysis is standard practice employed in clinical diagnostic labs. Some may argue that this is mainly due to the application of automatic analyzers and the requirements to adhere to CAP/CLIA/CLSI regulations in validating and applying rugged assays to support patient diagnosis and medical treatment decisions. Singlicate analysis has also been the standard in regulated LC–MS labs for decades. Some may argue that this is because LC–MS assays incorporate an internal standard. Jo Goodman (from MedImmune) at the 10th EBF open symposium pointed out that the internal standard used in LC–MS assays is to normalize the data and compensate for potential sample lost during extraction, injection and other pretreatment processes [pers. comm.]. However, newer LC–MS assays being applied to biotherapeutics (e.g., hybrid LBA-LC–MS and SISCAPA techniques) are multistep methods that usually are more complex than LBA assays. Considering these examples, implementation of singlicate analysis in LBA-like LC–MS methods seems reasonable to accept.Singlicate analysis in biomarker LBAs: future perspective & conclusionSo far, data from publications and conferences have indicated that singlicate analysis could be the future direction for regulated LBAs. In our opinion, singlicate analysis in nonregulated biomarker bioanalysis easily could be adopted as standard practice. Conceptually, fit-for-purpose biomarker assay validation is intended to be a flexible, dynamic model for assay characterization. Biomarker assays provide evidentiary data intended to support its context of use, in other words, the stage of development of the drug candidate. We propose adopting a standard of singlicate analysis for fit-for-purpose biomarker LBAs if it can be concluded from validation data that singlicate analysis is robust. Scientific judgment should be made to determine if duplicate or singlicate analysis is more appropriate when an assay is tricky or not robust. If the biomarker data are for critical decision-making and drug submission, adopting a 'regulated PK assay model' of duplicate analysis with tightened QC acceptance criteria is recommended. Previous method validation or sample analysis data conducted with duplicate analysis also can be re-evaluated to assess robustness using singlicate analysis. It is anticipated that no statistically significant difference between singlicate and duplicate analysis would be found. Another alternative, although not common, ISR can be conducted. ISR analysis provides valuable in-study validation data to further support assay reproducibility. One example is the Protein Simple® ELLA system, which yields triplicate results from a single well was used for an exploratory sHer-2 biomarker assay in our lab and 97% of the 300 ISR results compared within 30% to the original result [10].Birnboeck et al. stated, "We are convinced that singlicate analysis can become a next evolutionary step in the conduct of LBAs, especially in combination with automation" [11]. We strongly believe that adopting singlicate bioanalysis in biomarkers will not only reduce the financial burden of drug development, but also pave the way to industry-wide acceptance of singlicate analysis for both regulated and nonregulated LBAs.AcknowledgementsThe authors thank R Jenkins for his critical review of this manuscript.Financial & competing interests disclosureThe 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 testimony, grants or patents received or pending, or royalties.No writing assistance was utilized in the production of this manuscriptOpen accessThis work is licensed under the Attribution-NonCommercial-NoDerivatives 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/4.0/References1 Lee JW, Devanarayan V, Barrett YC et al. Fit-for-purpose method development and validation for successful biomarker measurement. Pharm. Res. 23(2), 312–328 (2006).Crossref, Medline, CAS, Google Scholar2 Jing T, Patrick B. Parallelism experiments to evaluate matrix effects, selectivity and sensitivity in ligandbinding assay method development: pros and cons. Bioanalysis 4(18), 2213–2226 (2017).Google Scholar3 US FDA. Draft Guidance for Industry: Bioanalytical Method Validation. www.fda.gov/downloads/drugs/guidances/ucm368107.pdf.Google Scholar4 European Medicines Agency. Guideline on Bioanalytical Method Validation. EMA/CHMP/EWP/192217/2009, 21 (2011). http://www.ema.europa.eu/docs/en_GB/document_library/Scientific_guideline/2011/08/WC500109686.pdf.Google Scholar5 DeSilva B, Garofolo F, Rocci M et al. 2012 White paper on recent issues in bioanalysis and alignment of multiple guidelines. Bioanalysis 4(18), 2213–2226 (2012).Link, CAS, Google Scholar6 Booth B, Arnold ME, DeSilva B et al. Workshop report: crystal city V – quantitative bioanalytical method validation and implementation: the 2013 revised FDA guidance. AAPS J. 17(2), 277–288 (2015).Crossref, Medline, CAS, Google Scholar7 QPS Holdings, LLC. Conducting ELISAs: are duplicates always necessary or do singlicates suffice? www.qps.com/news-boianalysis7–2014.php.Google Scholar8 Clark TH, Yates PD, Chunyk AG et al. Feasibility of singlet analysis for ligand-binding assays: a retrospective examination of data generated using the gyrolab platform. AAPS J. 18(5), 1300–1308 (2016).Crossref, Medline, CAS, Google Scholar9 Hottenstein CS, Becker C, Asher C et al. Case study analysis of singlicate versus duplicate ligand-binding assay performance of a single bioanalytical method. AAPS Meeting Poster Abstract, NBC 2015 collection. http://abstracts.aaps.org/Verify/NBC15/PosterSubmissions/M1056.pdf.Google Scholar10 Zhuqiu Y, Tu J, James H et al. Simple PlexTM ELLA: a high throughput microfluidic immunoassay platform for the detection of human sHER-2 in human serum. Poster presented at: EBF 10th Open Symposium, 15–17 November 2017.Google Scholar11 Birnboeck HF, Schick E, Justies N. Singlicate analysis in regulated bioanalysis using ligand-binding assays: where are we heading? Bioanalysis 9(17), 1357–1359 (2017).Link, CAS, Google ScholarFiguresReferencesRelatedDetailsCited ByMarathon Running Increases Synthesis and Decreases Catabolism of Joint Cartilage Type II Collagen Accompanied by High-Energy Demands and an Inflamatory Reaction11 October 2021 | Frontiers in Physiology, Vol. 12Feasibility of singlicate-based analysis in bridging ADA assay on Meso-Scale Discovery platform: comparison with duplicate analysisZhihua Jiang, John Kamerud, Zhiping You, Soma Basak, Elena Seletskaia, Gregory S Steeno & Boris Gorovits19 July 2021 | Bioanalysis, Vol. 13, No. 14Improving Science by Overcoming Laboratory Pitfalls With Hormone Measurements31 December 2020 | The Journal of Clinical Endocrinology & Metabolism, Vol. 106, No. 4Improving Chinese hamster ovary host cell protein ELISA using Ella®: an automated microfluidic platformKathleen Van Manen-Brush, Jacob Zeitler, John R White, Paul Younge, Samantha Willis & Marisa Jones3 July 2020 | BioTechniques, Vol. 69, No. 3Neutral DNA–avidin nanoparticles as ultrasensitive reporters in immuno-PCR1 January 2020 | The Analyst, Vol. 145, No. 14Recommendations for singlet-based approach in ligand binding assays: an IQ Consortium perspectiveRenuka Pillutla, Boris Gorovits, Carol Gleason, Jorge Quiroz, David Christopher, Manuela Braun, Catherine Brockus, Douglas Donaldson, Tobias Haslberger, Ling He, Mark Qian, Jens Sydor, Enaksha Wickremsinhe & Lakenya Williams19 June 2020 | Bioanalysis, Vol. 12, No. 12European Bioanalysis Forum recommendation on singlicate analysis for ligand binding assays: time for a new mindsetMatthew Barfield, Joanne Goodman, John Hood & Philip Timmerman24 January 2020 | Bioanalysis, Vol. 12, No. 5Well-developed ligand-binding assays demonstrate robust performance using singlet analysisDouglas Donaldson, Shobha Purushothama, Eric David, Kristopher King, Shuguang Huang, Devangi S Mehta & Lauren F Stevenson12 December 2019 | Bioanalysis, Vol. 11, No. 22Biomarker assay validationSteven P Piccoli & Fabio Garofolo25 June 2018 | Bioanalysis, Vol. 10, No. 12 Vol. 10, No. 12 Follow us on social media for the latest updates Metrics History Received 12 March 2018 Accepted 27 March 2018 Published online 20 June 2018 Published in print June 2018 Information©2018 Zhuqiu Ye & Patrick BennettKeywordsbiomarkerfit-for-purposeligand-binding assaynonregulated bioanalysisregulated bioanalysissinglicate analysisAcknowledgementsThe authors thank R Jenkins for his critical review of this manuscript.Financial & competing interests disclosureThe 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 testimony, grants or patents received or pending, or royalties.No writing assistance was utilized in the production of this manuscriptOpen accessThis work is licensed under the Attribution-NonCommercial-NoDerivatives 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/4.0/PDF download

The 18th Annual Land O'Lakes Bioanalytical Conference, titled 'Cutting-Edge Bioanalytical Technologies and Concepts - Issues, Solutions and Practical Considerations for Applications in Novel and Emerging Modalities', was held 10-13 July 2017 in Madison, WI, USA. This Land O'Lakes Conference is presented each year by the Division of Pharmacy Professional Development within the School of Pharmacy at the University of Wisconsin-Madison (USA). The purpose of this conference is to provide an educational forum to discuss issues and applications associated with the analysis of xenobiotics, metabolites, biologics and biomarkers in biological matrices. The conference is designed to include and encourage an open exchange of scientific and methodological applications for bioanalysis. This report summarized the presentations at the 18th Annual Conference.

Parallelism is an essential experiment characterizing relative accuracy for a ligand-binding assay (LBA). By assessing the effects of dilution on the quantitation of endogenous analyte(s) in matrix, selectivity, matrix effects, minimum required dilution, endogenous levels of healthy and diseased populations and the LLOQ are assessed in a single experiment. This review compares and discusses all available approaches that can be used to assess key assay parameters for pharmacokinetic and biomarker LBAs, as well as the advantages and disadvantages of each approach. This review also summarizes a systematic approach that can apply to guide endogenous LBA method development and optimization with a suggested way to interpret parallelism data.

The 10th Global CRO Council (GCC) Closed Forum was held in Orlando, FL, USA on 18 April 2016. In attendance were decision makers from international CRO member companies offering bioanalytical services. The objective of this meeting was for GCC members to meet and discuss scientific and regulatory issues specific to bioanalysis. The issues discussed at this closed forum included reporting data from failed method validation runs, GCP for clinical sample bioanalysis, extracted sample stability, biomarker assay validation, processed batch acceptance criteria, electronic laboratory notebooks and data integrity, Health Canada's Notice regarding replicates in matrix stability evaluations, critical reagents and regulatory approaches to counteract fraud. In order to obtain the pharma perspectives on some of these topics, the first joint CRO-Pharma Scientific Interchange Meeting was held on 12 November 2016, in Denver, Colorado, USA. The five topics discussed at this Interchange meeting were reporting data from failed method validation runs, GCP for clinical sample bioanalysis, extracted sample stability, processed batch acceptance criteria and electronic laboratory notebooks and data integrity. The conclusions from the discussions of these topics at both meetings are included in this report.

This chapter provides information on the internal and external logistics and practices required to operate a regulated bioanalytical laboratory. Despite commonality afforded by health authority guidances, the organizational structure of laboratories conducting regulated bioanalysis varies across the industry. For example, an internal bioanalytical laboratory operating within a pharmaceutical company is likely to be structured and operate significantly differently from a contract research organization (CRO) laboratory focused on the same discipline. From personal experiences, we can attest to the potential benefits for different operational structures, tools, and practices depending on the size and geographical footprint of a bioanalytical organization. Particularly, as a bioanalytical laboratory grows, the need to adapt to the scale of data handling, information management, and associated communications requires operational structures to evolve accordingly. These and other variables discussed in this chapter demonstrate the operational and logistical differences between different types of bioanalytical laboratories. Despite the structural differences, there are also some common logistical and operational requirements for all regulated bioanalytical laboratories including: (1) Information Technology (IT) systems that provide security, data management, and automation, (2) Standard Operating Procedures (SOPs) and policies that drive both regulated and business activities, (3) metric tracking that assists in both business operations and scientific operations, and (4) document and sample lifecycle management.

The 9th GCCClosed Forum was held just prior to the 2015 Workshop on Recent Issues in Bioanalysis (WRIB) in Miami, FL, USA on 13 April 2015. In attendance were 58 senior-level participants, from eight countries, representing 38 CRO companies offering bioanalytical services. The objective of this meeting was for CRO bioanalytical representatives to meet and discuss scientific and regulatory issues specific to bioanalysis. The issues selected at this year's closed forum include CAPA, biosimilars, preclinical method validation, endogenous biomarkers, whole blood stability, and ELNs. A summary of the industry's best practices and the conclusions from the discussion of these topics is included in this meeting report.

BioanalysisVol. 8, No. 22 CommentaryBiomarkers: more of a challenge for bioanalysis than expectedPatrick BennettPatrick Bennett*Author for correspondence: E-mail Address: patrick.bennett@ppdi.com Biomarker Laboratories, PPD Inc., Richmond, VA 23230, USAPublished Online:5 Oct 2016https://doi.org/10.4155/bio-2016-4991AboutSectionsView ArticleView Full TextPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareShare onFacebookTwitterLinkedInReddit View articleKeywords: bioanalysisbiomarkersregulatory complianceReferences1 Biomarkers Definitions Working Group. Biomarkers and surrogate endpoints: preferred definitions and conceptual framework. Clin. Pharmaco. Ther. 69(3), 89–95 (2001).Crossref, Medline, Google Scholar2 US Department of Health and Human Services, US FDA, Center for Drug Evaluation and Research. Guidance for Industry, Bioanalytical Method Validation – Draft Guidance (2013). www.fda.gov/downloads/drugs/guidancecomplianceregulatoryinformation/guidances/ucm368107.pdf.Google Scholar3 Arnold M, Booth B, King L, Ray C. Workshop report: Crystal City VI – Bioanalytical method validation for biomarkers. AAPS J. doi:10.1208/s12248-016-9946-6 (2016) (Epub ahead of print).Crossref, Medline, Google Scholar4 EMEA. Committee for Medicinal Products for Human Use. Guideline on bioanalytical method validation (2011). www.ema.europa.eu/docs/en_GB/document_library/Scientific_guideline/2011/08/WC500109686.pdf.Google Scholar5 Timmerman P, Herling C, Stoellner D et al. European Bioanalysis Forum recommendation on method establishment and bioanalysis of biomarkers in support of drug development. Bioanalysis 4(15), 1883–1894 (2012).Link, CAS, Google Scholar6 Lowes S, Jucker R, Jemal M et al. Tiered approaches to chromatographic bioanalytical method performance evaluation: recommendation for best practices and harmonization from the global bioanalysis consortium harmonization team. AAPS J. 17(1), 17–23 (2015).Crossref, Medline, CAS, Google Scholar7 Booth B. When do you need a validated assay? Bioanalysis 3(24), 2729–2730 (2011).Link, CAS, Google Scholar8 Sommer U, Morales J, Groenewegen A et al. Implementation of highly sophisticated flow cytometry assays in multicenter clinical studies: considerations and guidance. Bioanalysis 7(10), 1299–1311 (2015).Link, CAS, Google ScholarFiguresReferencesRelatedDetailsCited ByCurrent Regulatory Guidance Pertaining Biomarker Assay Establishment and Industrial Practice of Fit-for-Purpose and Tiered Approach14 July 2017The breadth of biomarkers and their assaysMark E Arnold, Hendrik Neubert, Lauren F Stevenson & Fabio Garofolo14 October 2016 | Bioanalysis, Vol. 8, No. 22 Vol. 8, No. 22 Follow us on social media for the latest updates Metrics Downloaded 188 times History Published online 5 October 2016 Published in print November 2016 Information© Future Science LtdKeywordsbioanalysisbiomarkersregulatory complianceFinancial & competing interests disclosureThe author has 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 testimony, grants or patents received or pending, or royalties.No writing assistance was utilized in the production of this manuscript.PDF download

Recent innovations and improvement in Orbitrap technology have enabled routine Orbitrap MS-based analysis of intact monoclonal antibody and related products. hi this chapter, LC-MS and LC-MS/MS solutions that include sample preparation, Orbitrap instrumentation and data processing are introduced for routine intact antibody mass measurement as well as subunit sequencing and fragment structure analysis. Measurement of antibody molecular mass under both denatured and native conditions are described with recommendations for best practice and key Orbitrap MS parameters. The results demonstrate accurate and reproducible measurement of molecular mass and relative abundance of glycoforms. The intact subunit sequencing and middle-down approaches efficiently dissociate the light chain and the heavy chain, leading to 67% backbone fragmentation for the intact light chain, and 52% and 32% backbone fragmentation for the single chain Fc (scFc) and Fd' fragments (Fab-domains of heavy chain), respectively. The use of complementary dissociation methods, ETD and HCD, not only improves sequence coverage, but also allows the confident identification and localization of sequence modifications including glycosylation. The improved resolution and scan speed in the new generation Orbitrap mass spectrometers enable the practical utility of online LC in conjunction with subunit or middle-down MS/MS in a high-throughput format. The methods presented here can be used routinely in biopharmaceutical applications.

Flow cytometry is increasingly becoming an important technology for biomarkers used in drug discovery and development. Within clinical development flow cytometry is used for the determination of PD biomarkers, disease or efficacy biomarkers or patient stratification biomarkers. Significant differences exist between flow cytometry methodology and other widely used technologies measuring soluble biomarkers including ligand binding and mass spectrometry. These differences include the very heavy reliance on aspects of sample processing techniques as well as sample stabilization to ensure viable samples. These differences also require exploration of new approaches and wider discussion regarding method validation requirements. This paper provides a review of the current challenges, solutions, regulatory environment and recommendations for the application of flow cytometry to measure biomarkers in clinical development.