Lindsay King

Bioanalytical Approaches to Quantify “Total” and “Free” Therapeutic Antibodies and Their Targets: Technical Challenges and PK/PD Applications Over the Course of Drug Development

The predominant driver of bioanalysis in supporting drug development is the intended use of the data. Ligand-binding assays (LBA) are widely used for the analysis of protein biotherapeutics and target ligands (L) to support pharmacokinetics/pharmacodynamics (PK/PD) and safety assessments. For monoclonal antibody drugs (mAb), in particular, which non-covalently bind to L, multiple forms of mAb and L can exist in vivo, including free mAb, free L, and mono- and/or bivalent complexes of mAb and L. Given the complexity of the dynamic binding equilibrium occurring in the body after dosing and multiple sources of perturbation of the equilibrium during bioanalysis, it is clear that ex vivo quantification of the forms of interest (free, bound, or total mAb and L) may differ from the actual ones in vivo. LBA reagents and assay formats can be designed in principle to measure the total or free forms of mAb and L. However, confirmation of the forms being measured under the specified conditions can be technically challenging. The assay forms and issues must be clearly communicated and understood appropriately by all stakeholders as the program proceeds through the development process. This paper focuses on monoclonal antibody biotherapeutics and their circulatory L that are either secreted as soluble forms or shed from membrane receptors. It presents an investigation into the theoretical and practical considerations for total/free analyte assessment to increase awareness in the scientific community and offer bioanalytical approaches to provide appropriate PK/PD information required at specific phases of drug development.

Theoretical Considerations and Practical Approaches to Address the Effect of Anti-drug Antibody (ADA) on Quantification of Biotherapeutics in Circulation

Continuous improvement in bioanalytical method development is desired in order to ensure the quality of the data and to better support pharmacokinetic (PK) and safety studies of biotherapeutics. One area that has been getting increasing attention recently is in the assessment of “free” and “total” analyte and the impact of the assay format on those assessments. To compliment these considerations, the authors provide a critical review of available literature and prospectively explore methods to mitigate the potential impact of anti-drug antibody on PK assay measurement. This challenge is of particular interest and importance since biotherapeutic drugs often elicit an immune response, and thus may have a direct impact on quantification of the drug for its PK and safety evaluations.

A Priori Prediction of Tumor Payload Concentrations: Preclinical Case Study with an Auristatin-Based Anti-5T4 Antibody-Drug Conjugate

The objectives of this investigation were as follows: (a) to validate a mechanism-based pharmacokinetic (PK) model of ADC for its ability to a priori predict tumor concentrations of ADC and released payload, using anti-5T4 ADC A1mcMMAF, and (b) to analyze the PK model to find out main pathways and parameters model outputs are most sensitive to. Experiential data containing biomeasures, and plasma and tumor concentrations of ADC and payload, following A1mcMMAF administration in two different xenografts, were used to build and validate the model. The model performed reasonably well in terms of a priori predicting tumor exposure of total antibody, ADC, and released payload, and the exposure of released payload in plasma. Model predictions were within two fold of the observed exposures. Pathway analysis and local sensitivity analysis were conducted to investigate main pathways and set of parameters the model outputs are most sensitive to. It was discovered that payload dissociation from ADC and tumor size were important determinants of plasma and tumor payload exposure. It was also found that the sensitivity of the model output to certain parameters is dose-dependent, suggesting caution before generalizing the results from the sensitivity analysis. Model analysis also revealed the importance of understanding and quantifying the processes responsible for ADC and payload disposition within tumor cell, as tumor concentrations were sensitive to these parameters. Proposed ADC PK model provides a useful tool for a priori predicting tumor payload concentrations of novel ADCs preclinically, and possibly translating them to the clinic.

Recommendations for adaptation and validation of commercial kits for biomarker quantification in drug development

Increasingly, commercial immunoassay kits are used to support drug discovery and development. Longitudinally consistent kit performance is crucial, but the degree to which kits and reagents are characterized by manufacturers is not standardized, nor are the approaches by users to adapt them and evaluate their performance through validation prior to use. These factors can negatively impact data quality. This paper offers a systematic approach to assessment, method adaptation and validation of commercial immunoassay kits for quantification of biomarkers in drug development, expanding upon previous publications and guidance. These recommendations aim to standardize and harmonize user practices, contributing to reliable biomarker data from commercial immunoassays, thus, enabling properly informed decisions during drug development.

Ligand binding assay critical reagents and their stability: recommendations and best practices from the Global Bioanalysis Consortium Harmonization Team.

The L4 Global Harmonization Team on reagents and their stability focused on the management of critical reagents for pharmacokinetic, immunogenicity, and biomarker ligand binding assays. Regulatory guidance recognizes that reagents are important for ligand binding assays but do not address numerous aspects of critical reagent life cycle management. Reagents can be obtained from external vendors or developed internally, but regardless of their source, there are numerous considerations for their reliable long-term use. The authors have identified current best practices and provided recommendations for critical reagent lot changes, stability management, and documentation.

Workshop Report: Crystal City VI—Bioanalytical Method Validation for Biomarkers

With the growing focus on translational research and the use of biomarkers to drive drug development and approvals, biomarkers have become a significant area of research within the pharmaceutical industry. However, until the US Food and Drug Administration’s (FDA) 2013 draft guidance on bioanalytical method validation included consideration of biomarker assays using LC-MS and LBA, those assays were created, validated, and used without standards of performance. This lack of expectations resulted in the FDA receiving data from assays of varying quality in support of efficacy and safety claims. The AAPS Crystal City VI (CC VI) Workshop in 2015 was held as the first forum for industry-FDA discussion around the general issues of biomarker measurements (e.g., endogenous levels) and specific technology strengths and weaknesses. The 2-day workshop served to develop a common understanding among the industrial scientific community of the issues around biomarkers, informed the FDA of the current state of the science, and will serve as a basis for further dialogue as experience with biomarkers expands with both groups.

A PTK7-targeted antibody-drug conjugate reduces tumor-initiating cells and induces sustained tumor regressions

PTK7 is a tumor-initiating cell antigen, which can be targeted with an antibody-drug conjugate to confer sustained tumor regressions. Initiating an antitumor attack Cancer is notorious for relapsing after treatment, making it difficult to eradicate from a patient’s body. Such relapses are driven by tumor-initiating cells, a type of stem cells that give rise to tumors. Damelin et al. determined that a protein called PTK7 is frequently present on tumor-initiating cells and developed an antibody-drug conjugate for targeting it. The authors demonstrated the effectiveness of this therapy in mouse models of several tumor types and confirmed that it reduces tumor-initiating cells and outperforms standard chemotherapy. The antibody-drug conjugate also had some unexpected benefits, reducing tumor angiogenesis and promoting antitumor immunity, all of which may contribute to its effectiveness. Disease relapse after treatment is common in triple-negative breast cancer (TNBC), ovarian cancer (OVCA), and non–small cell lung cancer (NSCLC). Therapies that target tumor-initiating cells (TICs) should improve patient survival by eliminating the cells that can drive tumor recurrence and metastasis. We demonstrate that protein tyrosine kinase 7 (PTK7), a highly conserved but catalytically inactive receptor tyrosine kinase in the Wnt signaling pathway, is enriched on TICs in low-passage TNBC, OVCA, and NSCLC patient–derived xenografts (PDXs). To deliver a potent anticancer drug to PTK7-expressing TICs, we generated a targeted antibody-drug conjugate (ADC) composed of a humanized anti-PTK7 monoclonal antibody, a cleavable valine-citrulline–based linker, and Aur0101, an auristatin microtubule inhibitor. The PTK7-targeted ADC induced sustained tumor regressions and outperformed standard-of-care chemotherapy. Moreover, the ADC specifically reduced the frequency of TICs, as determined by serial transplantation experiments. In addition to reducing the TIC frequency, the PTK7-targeted ADC may have additional antitumor mechanisms of action, including the inhibition of angiogenesis and the stimulation of immune cells. Together, these preclinical data demonstrate the potential for the PTK7-targeted ADC to improve the long-term survival of cancer patients.

Preclinical to Clinical Translation of Antibody-Drug Conjugates Using PK/PD Modeling: a Retrospective Analysis of Inotuzumab Ozogamicin

ABSTRACTA mechanism-based pharmacokinetic/pharmacodynamic (PK/PD) model was used for preclinical to clinical translation of inotuzumab ozogamicin, a CD22-targeting antibody-drug conjugate (ADC) for B cell malignancies including non-Hodgkin’s lymphoma (NHL) and acute lymphocytic leukemia (ALL). Preclinical data was integrated in a PK/PD model which included (1) a plasma PK model characterizing disposition and clearance of inotuzumab ozogamicin and its released payload N-Ac-γ-calicheamicin DMH, (2) a tumor disposition model describing ADC diffusion into the tumor extracellular environment, (3) a cellular model describing inotuzumab ozogamicin binding to CD22, internalization, intracellular N-Ac-γ-calicheamicin DMH release, binding to DNA, or efflux from the tumor cell, and (4) tumor growth and inhibition in mouse xenograft models. The preclinical model was translated to the clinic by incorporating human PK for inotuzumab ozogamicin and clinically relevant tumor volumes, tumor growth rates, and values for CD22 expression in the relevant patient populations. The resulting stochastic models predicted progression-free survival (PFS) rates for inotuzumab ozogamicin in patients comparable to the observed clinical results. The model suggested that a fractionated dosing regimen is superior to a conventional dosing regimen for ALL but not for NHL. Simulations indicated that tumor growth is a highly sensitive parameter and predictive of successful outcome. Inotuzumab ozogamicin PK and N-Ac-γ-calicheamicin DMH efflux are also sensitive parameters and would be considered more useful predictors of outcome than CD22 receptor expression. In summary, a multiscale, mechanism-based model has been developed for inotuzumab ozogamicin, which can integrate preclinical biomeasures and PK/PD data to predict clinical response.

Evolution of Antibody-Drug Conjugate Tumor Disposition Model to Predict Preclinical Tumor Pharmacokinetics of Trastuzumab-Emtansine (T-DM1)

ABSTRACTA mathematical model capable of accurately characterizing intracellular disposition of ADCs is essential for a priori predicting unconjugated drug concentrations inside the tumor. Towards this goal, the objectives of this manuscript were to: (1) evolve previously published cellular disposition model of ADC with more intracellular details to characterize the disposition of T-DM1 in different HER2 expressing cell lines, (2) integrate the improved cellular model with the ADC tumor disposition model to a priori predict DM1 concentrations in a preclinical tumor model, and (3) identify prominent pathways and sensitive parameters associated with intracellular activation of ADCs. The cellular disposition model was augmented by incorporating intracellular ADC degradation and passive diffusion of unconjugated drug across tumor cells. Different biomeasures and chemomeasures for T-DM1, quantified in the companion manuscript, were incorporated into the modified model of ADC to characterize in vitro pharmacokinetics of T-DM1 in three HER2+ cell lines. When the cellular model was integrated with the tumor disposition model, the model was able to a priori predict tumor DM1 concentrations in xenograft mice. Pathway analysis suggested different contribution of antigen-mediated and passive diffusion pathways for intracellular unconjugated drug exposure between in vitro and in vivo systems. Global and local sensitivity analyses revealed that non-specific deconjugation and passive diffusion of the drug across tumor cell membrane are key parameters for drug exposure inside a cell. Finally, a systems pharmacokinetic model for intracellular processing of ADCs has been proposed to highlight our current understanding about the determinants of ADC activation inside a cell.

Antibody–drug conjugates nonclinical support: from early to late nonclinical bioanalysis using ligand-binding assays

The objective of antibody-drug conjugate (ADC) bioanalysis at different stages of drug development may vary and so are the associated bioanalytical challenges. While at early drug discovery stage involving candidate selection, optimization and preliminary nonclinical assessments, the goal of ADC bioanalysis is to provide PK, toxicity and efficacy data that assists in the design and selection of potential drug candidates, the late nonclinical and clinical drug development stage typically involves regulated ADC bioanalysis that delivers TK data to define and understand pharmacological and toxicological properties of the lead ADC candidate. Bioanalytical strategies and considerations involved in developing successful ligand binding assays for ADC characterization from early discovery to late nonclinical stages of drug development are presented here.