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Aim: Characterization of antidrug antibody (ADA)-like reactivity has emerged as critical element of bioanalytical design and assessment of compound immunogenicity risk. Materials & methods: Multiplex immunoassay was applied to detect and characterize ADA like reactivity using Photonic Ring Immunoassay platform (Genalyte). Specific binding to human IgE or human recombinant IL21-receptor-Fc fusion using exogenous reagents as surrogates for drug-specific reactivity was investigated. Results: Multiplexed assay format allowed identification of spiked antihuman IgE reactivity as murine IgG1 and endogenous antihuman recombinant IL21-receptor-Fc reactivity in rheumatoid arthritis sera as antihuman Fc-specific binding. Conclusion: The ability of a multiplex immunoassay platform to identify isotype and domain specificity of antidrug immunoglobulins was shown to be effective and should be considered when screening and characterizing pre- and post-dose ADA reactivity.

Compared with conventional (monospecific) therapeutics, bispecific protein therapeutics present unique challenges for pharmacokinetic (PK) characterization – namely, the characterization of multiple functional domains as well as the consideration of biotransformation or interference by the formation of antitherapeutic antibodies against each functional domain. PK characterization is essential to the success of the overall drug development plan and for molecules with multiple binding domains; multiple bioanalytical methods may be needed to answer critical questions for each phase of drug development. The number of bispecific protein therapeutics entering drug development continues to increase, and therefore, a bioanalytical strategy for the PK characterization of bispecific molecules and study of their in vivo structure–function relationship is needed. This review presents case studies and a regulatory perspective.

The neonatal Fc receptor (FcRn) is a homeostatic receptor responsible for prolonging immunoglobulin G (IgG) half-life by protecting it from lysosomal degradation and recycling it to systemic circulation. Tissue-specific FcRn expression is a critical parameter in physiologically-based pharmacokinetic (PBPK) modeling for translational pharmacokinetics of Fc-containing biotherapeutics. Using online peptide immuno-affinity chromatography coupled with high resolution mass spectrometry, we established a quantitative FcRn tissue protein expression profile in human FcRn (hFcRn) transgenic mice, Tg32 homozygous and hemizygous strains. The concentration of hFcRn across 14 tissues ranged from 3.5 to 111.2 pmole per gram of tissue. Our hFcRn quantification data from Tg32 mice will enable a more refined PBPK model to improve the accuracy of human PK predictions for Fc-containing biotherapeutics.

The 2014 8th Workshop on Recent Issues in Bioanalysis (8th WRIB), a 5-day full immersion in the evolving field of bioanalysis, took place in Universal City, California, USA. Close to 500 professionals from pharmaceutical and biopharmaceutical companies, contract research organizations and regulatory agencies worldwide convened to share, review, discuss and agree on approaches to address current issues of interest in bioanalysis. The topics covered included both small and large molecules, and involved LCMS, hybrid LBA/LCMS, LBA approaches and immunogenicity. From the prolific discussions held during the workshop, specific recommendations are presented in this 2014 White Paper. As with the previous years’ editions, this paper acts as a practical tool to help the bioanalytical community continue advances in scientific excellence, improved quality and better regulatory compliance. Due to its length, the 2014 edition of this comprehensive White Paper has been divided into three parts for editorial reasons. This publication (Part 3) covers the recommendations for Large molecules bioanalysis using LBA and Immunogenicity. Part 1 (Small molecules bioanalysis using LCMS) and Part 2 (Hybrid LBA/LCMS, Electronic Laboratory Notebook and Regulatory Agencies' Input) were published in the Bioanalysis issues 6(22) and 6(23), respectively.

The purpose of this study was to validate the approach of serial sampling from one mouse through ligand binding assay (LBA) quantification of dosed biotherapeutic in diluted whole blood to derive a pharmacokinetic (PK) profile.This investigation compared PK parameters obtained using serial and composite sampling methods following administration of human IgG monoclonal antibody. The serial sampling technique was established by collecting 10 μL of blood via tail vein at each time point following drug administration. Blood was immediately diluted into buffer followed by analyte quantitation using Gyrolab to derive plasma concentrations. Additional studies were conducted to understand matrix and sampling site effects on drug concentrations.The drug concentration profiles, irrespective of biological matrix, and PK parameters using both sampling methods were not significantly different. There were no sampling site effects on drug concentration measurements except that concentrations were slightly lower in sodium citrated plasma than other matrices.We recommend the application of mouse serial sampling, particularly with limiting drug supply or specialized animal models. Overall the efficiencies gained by serial sampling were 40-80% savings in study cost, animal usage, study length and drug conservation while inter-subject variability across PK parameters was less than 30%.

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.

Response surface methods (RSM) combined with a steepest ascent approach is a powerful technique to optimize assay performance. In this case, a ligand-binding assay (LBA) to quantitate a peptide biotherapeutic was optimized for improved sensitivity using this technique. Conditions were elucidated to enable pg/mL quantitation of the peptide in human plasma using steepest ascent to efficiently optimize assay factors. Instead of relying solely on assay development experience and intuition to improve assay sensitivity, this systematic approach takes advantage of a predictive mathematical model generated through response surface methods that defines a specific path towards greater predicted assay sensitivity. The actual response observed along the steepest ascent path was in good agreement with the model for several steps, until reagent concentrations moved beyond the physical limits of the system, and model breakdown occurred. RSM combined with steepest ascent method proved a useful tool for sensitivity optimization in three ways: (1) The required LBA sensitivity performance (approximately 200 pg/mL), measured as a signal-to-noise ratio (SNR) at the targeted lower limit of quantitation (LLOQ), was efficiently achieved in only two optimization experiments; (2) Steepest ascent confirmed that the desired sensitivity was found within the initial RSM design space, and no further gain in sensitivity was found venturing beyond this design space along the steepest ascent path; (3) The desired assay sensitivity was maintained over a reasonable range of reagent concentrations along the steepest ascent path, indicating assay robustness for this parameter.

With the ever increasing speed with which data are generated and the continual implementation of new instrumentation, maximizing the efficiency of data management for ligand-binding assays (LBAs) remains an increasing challenge. At the American Association of Pharmaceutical Scientists Workshop on the 21st Century Bioanalytical Laboratory: Maximizing Quality and Efficiency through Innovation, the attendees recognized the need to address the issue of data management. The eSolutions team, made up of end users and vendors, was formed with this challenge in mind, under the 21st Century Laboratory initiative. The eSolutions team has identified the need for a fully automated data interchange process as the first step to optimizing data management. This will require at least two major advances. First, for instruments capable of capturing raw data and metadata, a common open-source data standard is critical. Software independent of instruments will need to be compatible with the common data standard. Secondly, vendors must ensure that instruments and data analysis systems that process LBA data are enabled for direct bidirectional, file-less transfer of data between laboratory information management systems (LIMS), and instrument systems. In many laboratories conducting assays, LBA data systems and laboratory instruments are often islands of information, separated by an ocean of non-communication. Multiple applications within the laboratories generate reams of data that are stored in separate, non-connected silos of files. Data translation is required to share the data stored within these files with a LIMS or other analytical software. At best, this can be resolved using information technology (IT) resources. However, in the worst case scenario, this translation is performed manually leading to tedious error-prone tasks that require additional quality control (QC) oversight. In order to meet US FDA 21 CFR Part 11 (Electronic Records Electronic Signatures, ERES) regulations, data transfer through a file-based process requires assurance that the data imported into the LIMS are the same data exported from the data acquisition instrument. Therefore, one way to increase laboratory productivity would be through the use of a file-less automated process for data interchange tasks. Automation offers the performance of tasks in a secure, repeatable, and consistent manner without human intervention. Additional benefits of implementing an automated data interchange include: Facilitation of results and metadata transfer from source laboratory instruments (e.g., plate reader) to a data processing system (e.g., a LIMS) The ability to automate laboratory business processes where the format-consistent data can be programmed to be parsed and read by computer software Consistency of data formats between versions of the same software Data comparability between software applications even from different vendors avoiding the business risk of having to maintain legacy systems in order to retain the ability to read stored proprietary raw data in the future While many LBA laboratories clearly see a need for an automated data interchange process, these laboratories must raise awareness of this requirement by supporting the eSolutions team in establishing this process as well as supporting those vendors who choose to participate in the effort. It is absolutely necessary to have active vendor participation to be successful. There is a compelling reason for instrument and software vendors to participate in the creation of an automated data interchange process and to support its adoption. Innovative vendors of LIMS and analytical software will benefit from not having to keep up with the ever changing landscape of data formats. The automated data interchange process also allow new instrument vendors to more easily comply with data management requirements of LBA laboratories, thereby increasing the likelihood that innovative technologies will be adopted. On the other hand, LBA laboratories should be willing to accept an increase in cost for applications to account for costs incurred during adoption of the process and to patronize vendors that adopt the automated data interchange process. In this article, we provide perspectives on the benefit to the LBA community (vendors and users) and what is required to establish an automated data interchange process for LBA data.

The peptide-antibody (Ab) genetic fusion is a promising technology for targeting multiple antigens in a single Ab-like molecule. We have recently described generation and in vitro characterization of several such genetic fusions, using an interleukin (IL)-17A binding peptide and an anti-IL-22 Ab as a model system. In this study we assessed pharmacokinetic profiles of these model genetic fusions in mice. Specifically an IL-17A binding peptide was fused to either the heavy chain or both the heavy and the light chains of an anti-IL22 human IgG1 (referred to Compounds 1 or 2, respectively). Swiss Webster mice were given a single 10 mg/kg IV dose of Compound 1 or Compound 2 and serum concentrations were measured by a fused molecule immunoassay, in which IL-17A was used as a capture and anti-human IgG was used as a detector. In addition, serum samples were assayed using a total human IgG immunoassay. PK parameters were calculated by non-compartmental modeling. The two genetic fusions had similar PK profiles, with total body clearance of ~0.9-1.0 mL/h/kg, volume of distribution at steady-state of ~63-65 mL/kg, and elimination half-life of ~40 h. Our study provides the first characterization of the PK properties of peptide-Ab genetic fusions and suggests that although these genetic fusions appear to be eliminated faster than a typical Ab, the PK profile may be suitable for preclinical and clinical testing.

Contemporary drug discovery leverages quantitative modeling and simulation with increasing emphasis, both to gain deeper knowledge of drug targets and mechanisms as well as improve predictions between preclinical models and clinical applications, such as first-in-human dose projections. Proliferation of novel biotherapeutic modalities increases the need for applied PK/PD modeling as a quantitative tool to advance new therapies. Of particular relevance is the understanding of exposure, target binding and associated pharmacology at the target site of interest. Bioanalytical methods are key to informing PK/PD models and require assessment of both PK and PD end points. Where targets are sequestered in tissues (noncirculating), the ability to quantitatively measure drug or biomarker in tissue compartments becomes particularly important. This perspective provides an overview of contemporary applications of quantitative bioanalysis in tissue compartments as applied to PK and PD assessments associated with novel biotherapeutics. Case studies and key references are provided.