{"id":16757,"date":"2025-06-26T11:39:22","date_gmt":"2025-06-26T11:39:22","guid":{"rendered":"https:\/\/www.richterbiologics.eu\/key-aspects-to-control-assays-throughout-the-analytical-life-cycle\/"},"modified":"2025-06-26T11:39:23","modified_gmt":"2025-06-26T11:39:23","slug":"key-aspects-to-control-assays-throughout-the-analytical-life-cycle","status":"publish","type":"post","link":"https:\/\/www.richterbiologics.eu\/de\/key-aspects-to-control-assays-throughout-the-analytical-life-cycle\/","title":{"rendered":"Key aspects to control assays throughout the analytical life cycle"},"content":{"rendered":"\t\t
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For biopharmaceutical products, potency testing is a requirement through all phases of clinical investigation and following market approval. Due to the complexity and inherent variability of this type of analysis, an assay control strategy should be established for each specific product, adapted and improved throughout the analytical life cycle <\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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By Sonja Klingelh\u00f6fer at Richter BioLogics<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t
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In the last decades, one of the key changes in the pharmaceutical industry has been the shift towards biotechnological products, broadening in diversity and complexity. This has led to increasing demands for the analytical characterisation of these products, and the use of state-of-the-art analytical technologies and methods. <\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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Potency assays are one of the most crucial tests in the analysis of biopharmaceutical products, as they reflect the mode of action of the respective product and should be related to clinical efficacy. Alterations in the product might also result in reduced stability, so potency assays must also be stability indicative, and the demands for these types of tests concerning accuracy and precision are changing during the analytical life cycle. The use of reliable suitability criteria is key to verifying that a method is fit for its intended purpose. This is true for any method and is reflected in its use as a critical quality attribute. For some methods, concrete expectations for the choice of suitability criteria are given (eg, USP chromatography chapter <621>).\u00b9 However, due to the diversity of potency assays, the setting of suitability criteria is much more complex and concrete guidance is lacking. <\/p>

This article discusses aspects of an assay control strategy for risk mitigation from a contract development and manufacturing organisation (CDMO) perspective. Based on Richter BioLogic\u2019s (RB\u2019s) experience over the last two decades, some of the challenges in defining and correctly setting potency test suitability criteria are outlined. <\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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Regulatory considerations<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t
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\n\t\t\t\t\t\t\t\t\tSuitability criteria are essential for controlling the performance of any assay system, to distinguish between valid and invalid analyses. They are part of the analytical procedure control strategy described in the life cycle approach defined in ICH Q14 and USP<1220>.2,3<\/sup> The enhanced approach (using science-based quality by design principles) focuses on ongoing validity and risk mitigation, rather than the classical approach (single validation studies). Due to the increasing demands on assay control during the analytical method life cycle, suitability criteria are also evolving and changing to protect from high failure rates. Suitable measures and tests, as well as assay-specific set points or ranges, should be selected based on risk assessment and general knowledge, and understanding from assay development.\u00b2 \n\nSuitability criteria fall broadly into two categories, both of which are required for any assay: system suitability tests (SSTs) check whether the assay itself is performing as expected and ensure that all parameters of a method function as required; sample suitability tests are applied to individual test samples and ensure that these samples are behaving as expected.\u00b2\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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Suitability criteria for potency testing<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t
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\n\t\t\t\t\t\t\t\t\tDue to the complexity and inherent variability of potency assays, many parameters may be relevant as potential suitability controls (see Figure 1<\/strong> for examples of measures and tests). General guidance for potency assays on suitability testing can be found in the bioassay chapters of the USP and Ph Eur chapter 5.3.4-8,9 <\/sup>However, apart from similarity testing (sample suitability), only examples are given, and concrete recommendations are lacking. 5 <\/sup>\nThe two most common categories for SSTs are model adequacy (eg, LoF SSQ, R\u00b2) and precision (eg, relative GCI, MSE residuals). 5,2,10 <\/sup> A third commonly used criterion is the potency of the control sample run.5 Other categories belong to the shape of the dose-response curve (eg, assay range, slope or EC50 value), additional positive or negative controls or the maximum number of outliers allowed to be excluded. 2,5,7 <\/sup> Similar measures are used for sample suitability, but the focus here is on similarity testing (eg, parallelism of dose-response curves of standard and sample). In general, suitability criteria should be directly related to the quality of the potency assay and should be defined on a case-by-case basis for each assay system. It should always be considered that the choice and number of suitability tests will directly affect the assay failure rate. This is also reflected in USP<1032> where it is recommended that \u2018only a few uncorrelated standard response parameters\u2019 should be used.\u2075 \t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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Figure 1: Summary of exemplary measures for suitability testing<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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Aspects of RB\u2019s assay control strategy<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t
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Developing, conducting and controlling (cell-based) potency assays for biotechnological products is always a complex task. But from the CDMO lens, the task is even more complex when given the diversity of products produced at a CDMO (eg, recombinant proteins, bacterial vaccines and plasmid DNA in case of RB). One can imagine that the spectrum of potency assays operated by RB\u2019s bioassay group is quite broad, when considering not only the mode of action, but also the assay readouts, designs and statistical evaluation models. In addition, services are provided at all stages of development up to and including market supply. To address this challenge, the group has developed its own phase-dependent best practices regarding assay control strategy \u2013 including a variety of statistical tests \u2013 with the aim to be efficient but flexible to meet specific customer needs. Whether an assay is newly developed by RB or transferred from a customer, the common goal is to quickly gain control of assay performance, and ton successfully and smoothly progress through assay development and validation. <\/p>

The review of assays is a hierarchical process, starting with identification of potential errors in assay performance, followed by identification and elimination of outliers. The latter is an aspect of evaluation that is very special for potency assays and is recommended by several guidance documents.5,8,9,11<\/sup> After this precheck of the assay data, the SSTs are checked and only if they are met is the evaluation of the sample suitability criteria performed separately for each run (see Figure 2<\/strong>). <\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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Figure 2: RB\u2019s hierarchical decision tree of assay control (based on an assay example consisting of two sample runs). After exclusion of any error or outlying value, the suitability criteria are checked, starting with SSTs and followed by sample suitability criteria. (If an assay fails on a system suitability criterion, then a repeat of the whole assay is required; if a sample fails its suitability criterion, then only that sample run needs to be repeated) <\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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By way of example, this article discusses the suitability of different measures of model adequacy. RB generally prefers the use of easily interpretable relative measures as suitability tests, but not only for goodness-of-fit. Especially in the early stages of a project, the use of such measures is advantageous when historical data is limited. <\/p>

However, not all relative measures can be recommended. For example, the R\u00b2 metric (coefficient of determination), which is widely used in regression models and can be easily calculated by a variety of different software systems, is not an optimal measure for potency assays (either for linear or sigmoid regression models). The main disadvantage of R\u00b2 is that it is not an uncorrelated measure, but a combined measure of precision and goodness-of-fit. Another inappropriate relative measure is the lack-of-fit p-value, as the interpretation of the p-value depends on the variability of the respective run. <\/p>

Where historical data is available, the lack-of-fit sum of squares (LoF SSQ) is an absolute measure, that may be used and is also recommended in USP (however, absolute measures such as LoF SSQ are problematic in the case of transfers or other situations where different equipment may be used). Although RB has established a variety of different measures and tests, the general aim is to limit the final suitability criteria to a set of relevant sensitive and uncorrelated parameters. <\/p>

Another aspect of model adequacy is the confirmation of the response model. During assay development, the need for transformation or weighting of the response data is checked by additional graphical evaluation. In the example shown in Figure 3<\/strong>, the correct transformation is shown to have a relevant impact on the accuracy of the final result (relative potency changes from 0.91 to 0.98 after transformation). The appropriateness of the transformation is confirmed by almost normal distributed residuals and improved values for the SSTs monitoring model adequacy. Again, the R\u00b2 metric is relatively insensitive and shows only marginal change after transformation, unlike other measures (data not shown). <\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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Figure 3: Exemplary dose-response curves of a potency run (comparison of standard and sample in duplicates, upper graphs) and the corresponding residual plots (lower graphs). Left: Response (raw) data; Right: transformed response data <\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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Continuous monitoring of assay parameters is also a key factor in assay control as it facilitates improvements. Monitoring of failure rates after validation can trigger method optimisation as well as improvement and refinement of suitability criteria during the life cycle. A high failure rate not only calls into question the robustness and suitability of an assay (regulatory risk), but also represents a commercial risk, as higher quality events can translate directly into higher costs. <\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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Conclusion<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t
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The field of biopharmaceuticals is rapidly evolving, and with it the need for reliable bioassay methods to control product potency. Risk mitigation strategies are in the focus throughout the analytical method life cycle. Along the way, the phase-dependent selection of appropriate acceptance criteria (suitability tests) to control the assay performance is key, and continuous monitoring can facilitate improvements. With a keen awareness of customer needs and regulatory expectations, over the decades RB has developed its own phase-dependent best practices for assay control strategy, which remain flexible to meet specific customer needs. <\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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References<\/strong>:<\/em><\/p>

  1. Visit: usp.org\/sites\/default\/files\/usp\/document\/harmonization\/genchapter\/<\/em>
    harmonization-november-2021-m99380.pdf<\/em><\/li>
  2. Visit: database.ich.org\/sites\/default\/files\/ICH_Q14_<\/em>
    Guideline_2023_1116_1.pdf<\/em><\/li>
  3. Visit: uspnf.com\/sites\/default\/files\/usp_pdf\/EN\/USPNF\/usp-nfnotices\/<\/em>
    gc-1220-pre-post-20210924.pdf<\/em><\/li>
  4. Visit: doi.usp.org\/USPNF\/USPNF_M5877_10101_01.html<\/em><\/li>
  5. Visit: doi.usp.org\/USPNF\/USPNF_M1354_01_01.html<\/em><\/li>
  6. Visit: doi.usp.org\/USPNF\/USPNF_M912_01_01.html<\/li>
  7. Visit: doi.usp.org\/USPNF\/USPNF_M5677_01_01.html<\/li>
  8. Visit: doi.usp.org\/USPNF\/USPNF_M98860_02_01.html<\/li>
  9. Visit: edqm.eu\/en\/d\/418688<\/li>
  10. Visit: ema.europa.eu\/en\/ich-q2r2-validation-analytical-proceduresscientific-guideline<\/li>
  11. Visit: doi.usp.org\/USPNF\/USPNF_M99740_05_01.html<\/li><\/ol>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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    Sonja Klingelh\u00f6fer<\/strong> is a principal scientist at Richter BioLogics<\/strong> and
    holds a PhD in biology. Before joining the pharmaceutical industry,
    she worked at DESY in Hamburg, Germany. Sonja gained experience
    in drug screening (herbal medicines), before setting up a good
    manufacturing practices laboratory specialising in biological assays,
    which she managed for over 20 years. <\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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    Quelle: European Biopharmaceutical Review | Summer 2025<\/em><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"

    For biopharmaceutical products, potency testing is a requirement through all phases of clinical investigation and following market approval. Due to the complexity and inherent variability of this type of analysis, an assay control strategy should be established for each specific product, adapted and improved throughout the analytical life cycle By Sonja Klingelh\u00f6fer at Richter BioLogics […]<\/p>\n","protected":false},"author":15,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[96],"tags":[],"class_list":["post-16757","post","type-post","status-publish","format-standard","hentry","category-produkte-und-technologien"],"acf":[],"yoast_head":"\nKey aspects to control assays throughout the analytical life cycle | Richter BioLogics<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.richterbiologics.eu\/de\/key-aspects-to-control-assays-throughout-the-analytical-life-cycle\/\" \/>\n<meta property=\"og:locale\" content=\"de_DE\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Key aspects to control assays throughout the analytical life cycle | Richter BioLogics\" \/>\n<meta property=\"og:description\" content=\"For biopharmaceutical products, potency testing is a requirement through all phases of clinical investigation and following market approval. 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