Application of multi-factorial design of experiments to successfully optimize immunoassays for robust measurements of therapeutic proteins

Optimized detection of Salmonella typhimurium using aptamer lateral flow assay

Salmonella typhimurium, a pathogenic bacterium with significant implications in medicine and the food industry, poses a substantial threat by causing foodborne illnesses such as typhoid fever. Accurate diagnosis of S. typhimurium is challenging due to its overlap symptoms with various diseases. This underscores the need for a precise and efficient diagnostic approach. In this study, we developed a biosensor using the Taguchi optimization method based on aptamer lateral flow assay (LFA) for the detection of S. typhimurium. Therefore, signal probe and nanobioprobe were designed using anti-Salmonella aptamer, conjugated with gold nanoparticles (GNPs), and used in LFA. The strategy of this test is based on a competitive format between the bacteria immobilized on the membrane and the bacteria present in the tested sample. Moreovere, the optimization of various factors affecting the aptamer LFA, including the concentration of bacteria (immobilized and into the sample) and the concentration of nanobioprop, were performed using the Taguchi test designing method. The data showed that the optimal conditions for the LFA reaction was 108 CFU/mL of immobilized bacteria and 1.5 μg/μL of nanobioprop concentration. Then, the visual detection limit of S. typhimurium was estimated as 105 CFU/mL. The reaction results were obtained within 20 min, and there were no significant cross-reactions with other food pathogens. In conclusion, the aptamer-LFA diagnostic method, optimized using the Taguchi approach, emerges as a reliable, straightforward, and accurate tool for the detection of S. typhimurium. Overall, this method can be a portable diagnostic kit for the detection and identification of bacteria.

Automated Bioanalytical Workflow for Ligand Binding-Based Pharmacokinetic Assay Development

The growth of therapeutic monoclonal antibodies (mAbs) continues to accelerate due to their success as treatments for many diseases. As new therapeutics are developed, it is increasingly important to have robust bioanalytical methods to measure the pharmacokinetics (PK) of circulating therapeutic mAbs in serum. Ligand-binding assays such as enzyme-linked immunosorbent assays (ELISAs) with anti-idiotypic antibodies (anti-IDs) targeting the variable regions of the therapeutic antibody are sensitive and specific bioanalytical methods to measure levels of therapeutic antibodies in a biological matrix. However, soluble circulating drug mAb targets can interfere with the anti-IDs binding to the therapeutic mAb, thereby resulting in an underestimation of total drug concentration. Therefore, in addition to a high binding affinity for the mAb, the selection of anti-IDs and the assay format that are not impacted by soluble antigens and have low matrix interference is essential for developing a robust PK assay. Standardized automated approaches to screen and select optimal reagents and assay formats are critical to increase efficiency, quality, and PK assay robustness. However, there does not exist an integrated screening and analysis platform to develop robust PK assays across multiple formats. We have developed an automated workflow and scoring platform with multiple bioanalytical assay parameters that allow for ranking of candidate anti-IDs. A primary automated indirect electrochemiluminescence (ECL) was utilized to shortlist the anti-IDs that were selected for labeling and screening in pairs. A secondary screen using an ECL sandwich assay with labeled-anti-ID pairings was used to test multiple PK assay formats to identify the best anti-ID pairing/PK assay format. We developed an automated assay using fixed plate maps combined with a human-guided graphical user interface-based scoring system and compared it to a data-dependent scoring system using Gaussian mixture models for automated scoring and selection. Our approach allowed for screening of anti-IDs and identification of the most robust PK assay format with significantly reduced time and resources compared with traditional approaches. We believe that such standardized, automated, and integrated platforms that accelerate the development of PK assays will become increasingly important for supporting future human clinical trials.

Functional design of experiment for potency assay optimization and in-silico simulation

For biotherapeutic analytics, robust and reliable potency assays are required. Design of experiment (DoE) approaches are used to investigate the impact of multiple assay parameters. Currently, specific assay features (e.g., half effective concentration) are modelled independently from each other. A joint interpretation of several assay features is thus difficult. In our functional DoE approach, we use the functional relationship of the assay features to describe the sigmoidal dose-response curve. With the composed functional form, the direct impact of assay parameters on the dose-response curve shape was modelled. Moreover, a multivariate desirability was defined and used for assay optimization. We believe that functional modelling contributes to understanding the joint influence of assay parameters and helps to design robust biotherapeutic analytics.

Step-by-step full factorial design to optimize a quantitative sandwich ELISA

In this work, a quantitative sandwich ELISA was optimized, through a full factorial design of experiments (DOE) in successive steps of a preliminary protocol obtained by the method of one factor at a time (OFAT). The specificity of the optimized ELISA, the lower limit of quantification, the quantification range and the analytical sensitivity of the antigen quantification curve were evaluated, in comparison with the curve obtained from the preliminary protocol. The full factorial DOE was linked to a simple statistical processing, which facilitates the interpretation of the results in those laboratories where there is no trained statistician. The step-by-step optimization of the ELISA and the successive incorporation into the protocol of the best combination of factors and levels, allowed obtaining a specific immunoassay, with an analytical sensitivity 20 times greater and with a lower limit of antigen quantification that decreased from 156.25 at 9.766 ng/mL. As far as we know, there are no reports of optimization of an ELISA following the step-by-step scheme used in this work. The optimized ELISA will be used for the quantification of the TT-P0 protein, the active principle of a vaccine candidate against sea lice.

Optimising cell-based bioassays via integrated design of experiments (ixDoE) - A practical guide

For process optimisation Design of Experiments (DoE) has long been established as a more powerful strategy than a One Factor at a Time approach. Nevertheless, DoE is not widely used especially in the field of cell-based bioassay development although it is known that complex interactions often exist. We believe that biopharmaceutical manufacturers are reluctant to move beyond standard practices due to the perceived costs, efforts, and complexity. We therefore introduce the integrated DoE (ixDoE) approach to target a smarter use of DoEs in the bioassay setting, specifically in optimising resources and time. Where in a standard practice 3 to 4 separate DoEs would be performed, our ixDoE approach includes the necessary statistical inference from only a single experimental set. Hence, we advocate for an innovative, ixDoE approach accompanied by a suitable statistical analysis strategy and present this as a practical guide for a typical bioassay development from basic research to biopharmaceutical industry.

Using multiple platforms for critical reagents selection process to support pharmacokinetic ligand-binding assay development

We have evaluated the utility of epitope binning on biolayer interferometry (BLI) as a strategy to funnel the selection of candidate pairs suitable for pharmacokinetic assay development. Totally, 8 anti-Idiotypic monoclonal antibodies in 64 possible combinations were tested by BLI, ELISA and Gyrolab^®. Two epitope binning approaches were utilized, in-tandem and classic sandwich. Both formats identified four mutually exclusive bins providing 31 and 25 possible antibody pair combinations, respectively. In contrast, the ELISA and Gyrolab yielded 18 and 9 positive pairs, respectively, with only a partial correlation to the BLI results. Several positive pairs by ELISA and Gyrolab, screened negative by BLI. Just over half of the pairs predicted by BLI were positive on ELISA and less than a quarter were positive on Gyrolab. This evaluation showed, in our case, that BLI was limited in its ability to predict candidate pairs that would be successful in pharmacokinetic method development.

Analytical Tools to Improve Optimization Procedures for Lateral Flow Assays

Immunochromatographic or lateral flow assays (LFAs) are inexpensive, easy to use, point-of-care medical diagnostic tests that are found in arenas ranging from a doctor’s office in Manhattan to a rural medical clinic in low resource settings. The simplicity in the LFA itself belies the complex task of optimization required to make the test sensitive, rapid and easy to use. Currently, the manufacturers develop LFAs by empirical optimization of material components (e.g., analytical membranes, conjugate pads and sample pads), biological reagents (e.g., antibodies, blocking reagents and buffers) and the design of delivery geometry. In this paper, we will review conventional optimization and then focus on the latter and outline analytical tools, such as dynamic light scattering and optical biosensors, as well as methods, such as microfluidic flow design and mechanistic models. We are applying these tools to find non-obvious optima of lateral flow assays for improved sensitivity, specificity and manufacturing robustness.

Recommendations for the development and validation of confirmatory anti-drug antibody assays

Identification and characterization of anti-drug antibodies is a critical component of biopharmaceutical drug development. The tiered approach for immunogenicity testing consists of screening, confirmatory, and characterization assays. Herein, we provide recommendations for confirmatory assays by expanding upon published guidance and present common practices across the industry. The authors recommend scientific approaches for development and validation of confirmatory assays using competition methods in ligand-binding assays, along with statistical formulae for routine use and validation. The paper will assist in understanding the confirmatory assay, and carefully implementing validation criteria a priori, as well as during sample analysis. These approaches represent the authors’ current knowledge and practices, with the aim that more uniform practices will be applied across the industry.

Statistical approaches to developing a multiplex immunoassay for determining human exposure to environmental pathogens

There are numerous pathogens that can be transmitted through water. Identifying and understanding the routes and magnitude of exposure or infection to these microbial contaminants are critical to assessing and mitigating risk. Conventional approaches of studying immunological responses to exposure or infection such as Enzyme-Linked Immunosorbent Assays (ELISAs) and other monoplex antibody-based immunoassays can be very costly, laborious, and consume large quantities of patient sample. A major limitation of these approaches is that they can only be used to measure one analyte at a time. Multiplex immunoassays provide the ability to study multiple pathogens simultaneously in microliter volumes of samples. However, there are several challenges that must be addressed when developing these multiplex immunoassays such as selection of specific antigens and antibodies, cross-reactivity, calibration, protein-reagent interferences, and the need for rigorous optimization of protein concentrations. In this study, a Design of Experiments (DOE) approach was used to optimize reagent concentrations for coupling selected antigens to Luminex™ xMAP microspheres for use in an indirect capture, multiplex immunoassay to detect human exposure or infection from pathogens that are potentially transmitted through water. Results from Helicobacter pylori, Campylobacter jejuni, Escherichia coli O157:H7, and Salmonella typhimurium singleplexes were used to determine the mean concentrations that would be applied to the multiplex assay. Cut-offs to differentiate between exposed and non-exposed individuals were determined using finite mixed modeling (FMM). The statistical approaches developed facilitated the detection of Immunoglobulin G (IgG) antibodies to H. pylori, C. jejuni, Toxoplasma gondii, hepatitis A virus, rotavirus and noroviruses (VA387 and Norwalk strains) in fifty-four diagnostically characterized plasma samples. Of the characterized samples, the detection rate was 87.5% for H. pylori, and 100% for T. gondii assays and 89% for HAV. Further, the optimized multiplex assay revealed exposure/infection to several other environmental pathogens previously uncharacterized in the samples.

Making methods rugged for regulated bioanalysis

Methods started in discovery are optimized as they progress through preclinical and clinical development. Making a robust assay includes testing individual steps for consistency and points of failure. Assays may be transferred, optimized and revalidated several times. A rugged assay will not only meet regulatory requirements, but will execute with a low failure rate and confirm results under repeat analysis. Challenging aspects such as differential recovery, sample stabilization, resolution of isomers or conjugate analysis must be tackled and made routine. The proper selection of the IS can overcome limitations. It is best to know the potential points of failure before a study has started, but lessons learned from each study also provide invaluable insights to improve assay ruggedness.

Application of quality by design and statistical quality control concepts in immunoassays

Quality by design (QbD) expanded in recent years from pharmaceutical processing into analytical chemistry. Beyond online process analytical technology, off-line assays including immunoassays are also starting to benefit from QbD. Although analytical QbD is still a relatively new development, underlying concepts, such as target-oriented development and statistical quality control have been applied to diagnostic assays under the term ‘design control’ for several years. We reviewed how QbD and statistical quality control concepts have been applied both to diagnostic and bioanalytical immunoassays ranging from the use of individual tools to end-to-end QbD-based workflows. We will discuss some of the results of the different approaches to immunoassays, how they fit into the QbD framework and how individual tools may complement a QbD workflow.

A practical approach to automate randomized design of experiments for ligand-binding assays

Background: Design of experiments (DOE) is utilized in optimizing ligand-binding assay by modeling factor effects. To reduce the analyst’s workload and error inherent with DOE, we propose the integration of automated liquid handlers to perform the randomized designs. Results: A randomized design created from statistical software was imported into custom macro converting the design into a liquid-handler worklist to automate reagent delivery. An optimized assay was transferred to a contract research organization resulting in a successful validation. Conclusion: We developed a practical solution for assay optimization by integrating DOE and automation to increase assay robustness and enable successful method transfer. The flexibility of this process allows it to be applied to a variety of assay designs.

Laboratory automation of high-quality and efficient ligand-binding assays for biotherapeutic drug development

Background: Regulated bioanalytical laboratories that run ligand-binding assays in support of biotherapeutics development face ever-increasing demand to support more projects with increased efficiency. Laboratory automation is a tool that has the potential to improve both quality and efficiency in a bioanalytical laboratory. The success of laboratory automation requires thoughtful evaluation of program needs and fit-for-purpose strategies, followed by pragmatic implementation plans and continuous user support. Results: In this article, we present the development of fit-for-purpose automation of total walk-away and flexible modular modes. We shared the sustaining experience of vendor collaboration and team work to educate, promote and track the use of automation. Conclusion: The implementation of laboratory automation improves assay performance, data quality, process efficiency and method transfer to CRO in a regulated bioanalytical laboratory environment.

A generic template for automated bioanalytical ligand-binding assays using modular robotic scripts in support of discovery biotherapeutic programs

Background: Sample dilution and reagent pipetting are time-consuming steps in ligand-binding assays (LBAs). Traditional automation-assisted LBAs use assay-specific scripts that require labor-intensive script writing and user training. Results: Five major script modules were developed on Tecan Freedom EVO liquid handling software to facilitate the automated sample preparation and LBA procedure: sample dilution, sample minimum required dilution, standard/QC minimum required dilution, standard/QC/sample addition, and reagent addition. The modular design of automation scripts allowed the users to assemble an automated assay with minimal script modification. The application of the template was demonstrated in three LBAs to support discovery biotherapeutic programs. Conclusion: The results demonstrated that the modular scripts provided the flexibility in adapting to various LBA formats and the significant time saving in script writing and scientist training. Data generated by the automated process were comparable to those by manual process while the bioanalytical productivity was significantly improved using the modular robotic scripts.

Automate it: ligand-binding assay productivity in a discovery bioanalytical setting

In multiple industries, including the biopharmaceutical industry, automation is synonymous with increased productivity. Environments with high-throughput needs commonly employ automation for efficiency. However, in a discovery bioanalytical ligand-binding assay laboratory setting where the focus is not necessarily on sample analysis throughput, but instead on assay development and characterization, is automation applicable? Can automation enhance productivity when tasks are more customized than routine? In this Perspective we review the different categories of automation with ligand-binding assays with these questions in mind. In considering whether automation technology has progressed far enough to result in a positive return in investment in the discovery setting, the resource investment required to operate in this space was contrasted with the gain in productivity. In our opinion, technology advancements in automated technology platforms, and especially personal automation, have allowed these categories to strike the right balance for investment in the discovery laboratory setting.

Development and optimization of neutralizing antibody assays to monitor clinical immunogenicity

The development of an unwanted immune response to a protein therapeutic is a constant concern and necessitates careful monitoring of this class of drugs during clinical development. Neutralizing antibodies can have a significant impact on bioavailability, efficacy and safety of a protein therapeutic. Consequently, immunogenicity testing is required prior to obtaining regulatory approval and in some cases even after a product is marketed. Given the importance of this testing, it is critical that sensitive and robust assays are developed for detection of clinically relevant neutralizing antibodies. This review will describe considerations and current best practices for developing assays to detect neutralizing antibodies to protein therapeutics.

Utilizing design of experiments to characterize assay robustness

Background: Design of experiments (DOE) is a systematic approach to assess the effects of many factors on a response of an assay. This paper provides a case study whereby DOE was successfully utilized to evaluate robustness parameters for a ligand-binding assay (LBA). Methodology: A 24-run Plackett–Burman design was developed to investigate factors that may have caused a lack of robustness in this particular LBA. We modeled five main effects and their ten two-way interactions, using the standard curve signal as the response. Results: By utilizing DOE, we were able to quickly identify the factors that affected our assay’s performance. The lack of robustness was attributed to the handling of the coat reagent. Factors that had an adverse effect on the coat material were vortexing and freeze–thaw cycles. Conclusion: We recommend that a robustness DOE be conducted prior to the validation of an assay for early identification of critical factors that may impact assay performance.

Validation and life-cycle management of a quantitative ligand-binding assay for the measurement of Nulojix®, a CTLA-4–Fc fusion protein, in renal and liver transplant patients

Background: Nulojix® is a fusion protein composed of the Fc portion of a human IgG1 linked to the extracellular modified domain of CTLA-4. Nulojix differs from another Bristol Myers Squibb product, Orencia® by two amino acids and was approved by the FDA on 15 June 2011 for the prophylaxis of organ rejection in adult patients receiving kidney transplant. Results: A sandwich ELISA utilizing two monoclonal antibodies against CTLA-4 was employed for Nulojix quantification and pharmacokinetic analysis. At least 17 analysts have qualified on the assay and contributed to reportable results over the last 7 years. In-study accuracy and precision demonstrate suitable performance: %bias within -4 to 4%, %CV ≤13% and total error within 6–15%. Incurred sample reanalysis was completed in applicable disease-state populations. The assay was automated and validated in additional clinical matrices (ascites and urine) and Nulojix quantification was validated in the presence of clinically relevant co-administered compounds. In 2011, the biotinylation procedure was modified meriting a regression change (quadratic to 4-parameter logistic) and associated partial validation. Conclusion: This long-term pharmacokinetic program provides a good example of the dynamic clinical environment and adaptation requirements of ligand-binding assays.

A systematic approach to investigate the impact of nonclinical blood processing deviations on large-molecule drug bioanalysis

During nonclinical regulated toxicology studies, blood processing protocol deviations may negatively impact sample integrity and bioanalytical results. Standard practices for resolution of blood processing issues are not well established across the industry. In this article, using an illustrative example, we present a systematic approach to investigate and assess the impact of nonclinical blood processing protocol deviations that involve: assessment of the potential impact of deviations on toxicokinetic evaluation, performance of additional blood processing stability tests to ensure study sample integrity and establishment of study sample results reporting procedures to meet both scientific and regulatory quality requirements. This thorough and systematic approach can serve as a model for other analogous situations.

Method transfer for ligand-binding assays: recommendations for best practice

To support clinical trials, bioanalytical methods are often transferred from one laboratory to another. With the rising number of large-molecule therapeutic proteins submitted for US FDA approval, the demand for large-molecule bioanalytical support and, subsequently, method transfer increases. Ligand-binding assays are the methods most commonly used to quantify endogenous and therapeutic proteins for the assessment of biomarkers and pharmacokinetic parameters. The goal of this review is to provide an overview of ligand-binding assay method transfer, essential parameters for partial method validation and to lay out a strategy to increase the chance of success. The recommendations herein are based on a summary of current publications and the authors' specific experiences, to help increase workload efficiency, maintain positive collaborations with partners and meet program timelines.

Quality assessment of bioanalytical quantification of monoclonal antibody drugs

Monoclonal antibody biotherapeutics are developed to bind to a specific target to affect the target’s biological effect. Reliable measurements of monoclonal antibodies in biological fluids using ligand-binding assays are vital for understanding the pharmacokinetic and pharmacodynamic relationships for efficacy/safety evaluations and dose-regimen selection. The method should be properly characterized and demonstrate adequate assay performance to generate credible data for the right decision making at each specific stage, with considerations on the constraints of timeline, reagent availability and assay caveats. Quality assessment of the assay performance should be based on whether the method is ‘fit-for-use’ to meet the objectives of the study. The basic industrial requirements and recent trends in method and data quality of ligand-binding assays for drug exposure studies at various development stages are discussed.

Unique challenges of providing bioanalytical support for biological therapeutic pharmacokinetic programs

Regulatory recommendations for providing bioanalytical support for biological therapeutics have co-evolved with the increasing success of these unique pharmaceuticals. Immunoassays have been used to quantify biological macromolecules for more than 50 years. These assays rely on the use of antigen-specific antibodies. More recently, LC–MS methods have being adapted to quantitate biologics. LC–MS has attributes that complement the limitations encountered by immunoassays. Whether employing immunoassay or LC–MS methods, compared with traditional chemical-based therapeutics, biological therapeutics present unique analytical challenges to analysts. In this article, we review bioanalytical strategies for supporting biologics and discuss the regulatory and analytical challenges that must be met.

Bioanalytical considerations in the comparability assessment of biotherapeutics

Comparison of biotherapeutic products before and after manufacturing changes is required to show that the products are highly similar. Besides in vitro assessment on the critical quality attributes and potency, biocomparability studies are sometimes required to demonstrate similarities in pharmacokinetic and pharmacodynamic characteristics. The complex and diverse nature of biotherapeutics requires multifaceted considerations in the biocomparability study design, bioanalytical measurements of drug concentrations and/or pharmacodynamic responses, immunogenicity analysis, data interpretation and decision making. A major perspective is to understand the structure and biological functions of the biotherapeutics in relation to the indication. Issues of a common standard and the importance of the use of ligand-binding assays that are sensitive to structural changes are discussed. It would not be possible to use the same process and one-size-fit-all criteria for biocomparability studies of all biologics. Previous examples from industry and our experience of the bioanalytical considerations for fit-for-purpose pharmacokinetic support and immunogenicity assessments are presented.

Guidelines for the development and incorporation of biomarker studies in early clinical trials of novel agents

The National Cancer Institute (NCI) Investigational Drug Steering Committee (IDSC) charged the Biomarker Task Force to develop recommendations to improve the decisions about incorporation of biomarker studies in early investigational drug trials. The Task Force members reviewed biomarker trials, the peer-reviewed literature, NCI and U.S. Food and Drug Administration (FDA) guidance documents, and conducted a survey of investigators to determine practices and challenges to executing biomarker studies in clinical trials of new drugs in early development. This document provides standard definitions and categories of biomarkers, and lists recommendations to sponsors and investigators for biomarker incorporation into such trials. Our recommendations for sponsors focus on the identification and prioritization of biomarkers and assays, the coordination of activities for the development and use of assays, and for operational activities. We also provide recommendations for investigators developing clinical trials with biomarker studies for scientific rationale, assay criteria, trial design, and analysis. The incorporation of biomarker studies into early drug trials is complex. Thus the decision to proceed with studies of biomarkers should be based on balancing the strength of science, assay robustness, feasibility, and resources with the burden of proper sample collection on the patient and potential impact of the results on drug development. The Task Force provides these guidelines in the hopes that improvements in biomarker studies will enhance the efficiency of investigational drug development.

Antibody-based protein multiplex platforms: technical and operational challenges

BACKGROUND

The measurement of multiple protein biomarkers may refine risk stratification in clinical settings. This concept has stimulated development of multiplexed immunoassay platforms that provide multiple, parallel protein measurements on the same specimen.

CONTENT

We provide an overview of antibody-based multiplexed immunoassay platforms and discuss technical and operational challenges. Multiplexed immunoassays use traditional immunoassay principles in which high-affinity capture ligands are immobilized in parallel arrays in either planar format or on microspheres in suspension. Development of multiplexed immunoassays requires rigorous validation of assay configuration and analytical performance to minimize assay imprecision and inaccuracy. Challenges associated with multiplex configuration include selection and immobilization of capture ligands, calibration, interference between antibodies and proteins and assay diluents, and compatibility of assay limits of quantification. We discuss potential solutions to these challenges. Criteria for assessing analytical multiplex assay performance include the range of linearity, analytical specificity, recovery, and comparison to a quality reference method. Quality control materials are not well developed for multiplexed protein immunoassays, and algorithms for interpreting multiplex quality control data are needed.

SUMMARY

Technical and operational challenges have hindered implementation of multiplexed assays in clinical settings. Formal procedures that guide multiplex assay configuration, analytical validation, and quality control are needed before broad application of multiplexed arrays can occur in the in vitro diagnostic market.