SomaLogic proteomics reveals new biomarkers and provides mechanistic, clinical insights into Acetyl coA Carboxylase (ACC) inhibition in Non-alcoholic Steatohepatitis (NASH).

Non-alcoholic Fatty Liver Disease (NAFLD) and Non-alcoholic Steatohepatitis (NASH) are major metabolic diseases with increasing global prevalence and no approved therapies. There is a mounting need to develop biomarkers of diagnosis, prognosis and treatment response that can effectively replace current requirements for liver biopsies, which are invasive, error-prone and expensive. We performed SomaLogic serum proteome profiling with baseline (n = 231) and on-treatment (n = 72, Weeks 12 and 16, Placebo and 25 mg PF-05221304) samples from a Phase 2a trial (NCT03248882) with Clesacostat (PF-05221304), an acetyl coA carboxylase inhibitor (ACCi) in patients with NAFLD/NASH. SomaSignal NASH probability scores and expression data for 7000+ analytes were analyzed to identify potential biomarkers associated with baseline clinical measures of NAFLD/NASH [Magnetic Resonance Imaging-Proton Density Fat Fraction (MRI-PDFF), alanine aminotransferase (ALT) and aspartate aminotransferase (AST)] as well as biomarkers of treatment response to ACCi. SomaSignal NASH probability scores identified biopsy-proven/clinically defined NIT-based (Presumed) NASH classification of the cohort with > 70% agreement. Clesacostat-induced reduction in steatosis probability scores aligned with observed clinical reduction in hepatic steatosis based on MRI-PDFF. We identify a set of 69 analytes that robustly correlate with clinical measures of hepatic inflammation and steatosis (MRI-PDFF, ALT and AST), 27 of which were significantly reversed with ACC inhibition. Clesacostat treatment dramatically upregulated Wnt5a protein and Apolipoproteins C3 and E, with drug-induced changes significantly correlating to changes on MRI-PDFF. Our data demonstrate the utility of SomaLogic- analyte panel for diagnosis and treatment response in NAFLD/NASH and provide potential new mechanistic insights into liver steatosis reduction, inflammation and serum triglyceride elevation with ACC inhibition. (Clinical Trial Identifier: NCT03248882).

Mass cytometry for the multiplexed quantification and characterization of target expression on circulating cells in whole blood.

Characterization of target abundance on cells has broad translational applications. Among the approaches for assessing membrane target expression is quantification of the number of target-specific antibody (Ab) bound per cell (ABC). ABC determination on relevant cell subsets in complex and limited biological samples necessitates multidimensional immunophenotyping, for which the high-order multiparameter capabilities of mass cytometry provide considerable advantages. In the present study, we describe the implementation of CyTOF® for the concomitant quantification of membrane markers on diverse types of immune cells in human whole blood. Specifically, our protocol relies on establishing Bmax of Ab saturable binding on cells, then converted into ABC according to a metal's transmission efficiency and number of metal atoms per Ab. Using this method, we calculated ABC values for CD4 and CD8 within the expected range for circulating T cells and in concordance with the ABC obtained in the same samples by flow cytometry. Furthermore, we successfully conducted multiplex measurements of the ABC for CD28, CD16, CD32a, and CD64, on >15 immune cell subsets in human whole blood samples. We developed a high-dimensional data analysis workflow enabling semi-automated Bmax calculation in all examined cell subsets to facilitate ABC reporting across populations. In addition, we investigated impacts of the type of metal isotope and acquisition batch effect on the ABC evaluation with CyTOF®. In summary, our findings demonstrate mass cytometry is a valuable tool for concurrent quantitative analysis of multiple targets in specific and rare cell types, thus increasing the numbers of biomeasures obtained from a single sample.

A Novel GUCY2C-CD3 T-Cell Engaging Bispecific Construct (PF-07062119) for the Treatment of Gastrointestinal Cancers.

PURPOSE: Gastrointestinal cancers remain areas of high unmet need despite advances in targeted and immunotherapies. Here, we demonstrate potent, tumor-selective efficacy with PF-07062119, a T-cell engaging CD3 bispecific targeting tumors expressing Guanylyl Cyclase C (GUCY2C), which is expressed widely across colorectal cancer and other gastrointestinal malignancies. In addition, to address immune evasion mechanisms, we explore combinations with immune checkpoint blockade agents and with antiangiogenesis therapy. EXPERIMENTAL DESIGN: PF-07062119 activity was evaluated in vitro in multiple tumor cell lines, and in vivo in established subcutaneous and orthotopic human colorectal cancer xenograft tumors with adoptive transfer of human T cells. Efficacy was also evaluated in mouse syngeneic tumors using human CD3ε transgenic mice. IHC and mass cytometry were performed to demonstrate drug biodistribution, recruitment of activated T cells, and to identify markers of immune evasion. Combination studies were performed with anti-PD-1/PD-L1 and anti-VEGF antibodies. Toxicity and pharmacokinetic studies were done in cynomolgus macaque. RESULTS: We demonstrate that GUCY2C-positive tumors can be targeted with an anti-GUCY2C/anti-CD3ε bispecific, with selective drug biodistribution to tumors. PF-07062119 showed potent T-cell-mediated in vitro activity and in vivo efficacy in multiple colorectal cancer human xenograft tumor models, including KRAS- and BRAF-mutant tumors, as well as in the immunocompetent mouse syngeneic tumor model. PF-07062119 activity was further enhanced when combined with anti-PD-1/PD-L1 treatment or in combination with antiangiogenic therapy. Toxicity studies in cynomolgus indicated a monitorable and manageable toxicity profile. CONCLUSIONS: These data highlight the potential for PF-07062119 to demonstrate efficacy and improve patient outcomes in colorectal cancer and other gastrointestinal malignancies.

A Physiologically-Based Pharmacokinetic Model for the Prediction of Monoclonal Antibody Pharmacokinetics From In Vitro Data.

Monoclonal antibody (mAb) pharmacokinetics (PK) have largely been predicted via allometric scaling with little consideration for cross-species differences in neonatal Fc receptor (FcRn) affinity or clearance/distribution mechanisms. To address this, we developed a mAb physiologically-based PK model that describes the intracellular trafficking and FcRn recycling of mAbs in a human FcRn transgenic homozygous mouse and human. This model uses mAb-specific in vitro data together with species-specific FcRn tissue expression, tissue volume, and blood-flow physiology to predict mAb in vivo linear PK a priori. The model accurately predicts the terminal half-life of 90% of the mAbs investigated within a twofold error. The mechanistic nature of this model allows us to not only predict linear PK from in vitro data but also explore the PK and target binding of mAbs engineered to have pH-dependent binding to its target or FcRn and could aid in the selection of mAbs with optimal PK and pharmacodynamic properties.

Feasibility of Singlet Analysis for Ligand Binding Assays: a Retrospective Examination of Data Generated Using the Gyrolab Platform.

There are many sources of analytical variability in ligand binding assays (LBA). One strategy to reduce variability has been duplicate analyses. With recent advances in LBA technologies, it is conceivable that singlet analysis is possible. We retrospectively evaluated singlet analysis using Gyrolab data. Relative precision of duplicates compared to singlets was evaluated using 60 datasets from toxicokinetic (TK) or pharmacokinetic (PK) studies which contained over 23,000 replicate pairs composed of standards, quality control (QC), and animal samples measured with 23 different bioanalytical assays. The comparison was first done with standard curve and QCs followed by PK parameters (i.e., Cmax and AUC). Statistical analyses were performed on combined duplicate versus singlets using a concordance correlation coefficient (CCC), a measurement used to assess agreement. Variance component analyses were conducted on PK estimates to assess the relative analytical and biological variability. Overall, 97.5% of replicate pairs had a %CV of <11% and 50% of the results had a %CV of ≤1.38%. There was no observable bias in concentration comparing the first replicate with the second (CCC of 0.99746 and accuracy value of 1). The comparison of AUC and Cmax showed no observable difference between singlet and duplicate (CCC for AUC and Cmax >0.99999). Analysis of variance indicated an AUC inter-subject variability 35.3-fold greater than replicate variability and 8.5-fold greater for Cmax. Running replicates from the same sample will not significantly reduce variation or change PK parameters. These analyses indicated the majority of variance was inter-subject and supported the use of a singlet strategy.

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

A 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).

A 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.

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.

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.

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.

Practical quantitative and kinetic applications of bio-layer interferometry for toxicokinetic analysis of a monoclonal antibody therapeutic.

Bio-layer interferometry (BLI) is a label-free technology that can be used for kinetic characterization of proteins. Although other label-free platforms have been used for quantitation purposes (most notably surface plasmon resonance), little work has been done using BLI. Here we present rationale and strategies for the development and analytical qualification of a BLI assay for the quantitation of a humanized antibody therapeutic in cynomolgus monkey plasma. Results of the qualification were compared to those of a validated ELISA used to quantitate the same therapeutic. Selectivity, matrix effect, and precision and accuracy were similar between the two methods. Target interference was more pronounced in the BLI assay compared to the ELISA. The main difference between the two assays was in the dynamic range (0.1-10 µg/mL for ELISA vs. 0.4-50 µg/mL for BLI). The monkey plasma BLI assay was applied to rat plasma for the comparison of study samples generated in the same matrix by ELISA. A direct quantitation comparison of sample results for the two methods shows a high degree of agreement (r(2)=0.979, slope=1.017). However, an evaluation of low concentration samples showed a bias of over-recovery in the BLI compared to the ELISA. In addition to utilizing the quantitative capabilities of the platform, we evaluated the utility of using the kinetic properties of the quantitative assay to detect anti-drug antibodies (ADA) and illustrated the potential for ADA to cause either over recovery (non-neutralizing ADA) or under recovery (neutralizing ADA) of a biotherapeutic using the BLI assay.

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.