Preclinical characterization and clinical translation of pharmacodynamic markers for MK-5890: a human CD27 activating antibody for cancer immunotherapy.

BACKGROUND: Immune checkpoint inhibitors (ICI) have radically changed cancer therapy, but most patients with cancer are unresponsive or relapse after treatment. MK-5890 is a CD27 agonist antibody intended to complement ICI therapy. CD27 is a member of the tumor necrosis factor receptor superfamily that plays a critical role in promoting responses of T cells, B cells and NK cells. METHODS: Anti-CD27 antibodies were generated and selected for agonist activity using NF-кB luciferase reporter assays. Antibodies were humanized and characterized for agonism using in vitro T-cell proliferation assays. The epitope recognized on CD27 by MK-5890 was established by X-ray crystallography. Anti-tumor activity was evaluated in a human CD27 knock-in mouse. Preclinical safety was tested in rhesus monkeys. Pharmacodynamic properties were examined in mouse, rhesus monkeys and a phase 1 dose escalation clinical study in patients with cancer. RESULTS: Humanized anti-CD27 antibody MK-5890 (hIgG1) was shown to bind human CD27 on the cell surface with sub-nanomolar potency and to partially block binding to its ligand, CD70. Crystallization studies revealed that MK-5890 binds to a unique epitope in the cysteine-rich domain 1 (CRD1). MK-5890 activated CD27 expressed on 293T NF-κB luciferase reporter cells and, conditional on CD3 stimulation, in purified CD8+ T cells without the requirement of crosslinking. Functional Fc-receptor interaction was required to activate CD8+ T cells in an ex vivo tumor explant system and to induce antitumor efficacy in syngeneic murine subcutaneous tumor models. MK-5890 had monotherapy efficacy in these models and enhanced efficacy of PD-1 blockade. MK-5890 reduced in an isotype-dependent and dose-dependent manner circulating, but not tumor-infiltrating T-cell numbers in these mouse models. In rhesus monkey and human patients, reduction in circulating T cells was transient and less pronounced than in mouse. MK-5890 induced transient elevation of chemokines MCP-1, MIP-1α, and MIP-1ß in the serum of mice, rhesus monkeys and patients with cancer. MK-5890 was well tolerated in rhesus monkeys and systemic exposure to MK-5890 was associated with CD27 occupancy at all doses. CONCLUSIONS: MK-5890 is a novel CD27 agonistic antibody with the potential to complement the activity of PD-1 checkpoint inhibition in cancer immunotherapy and is currently undergoing clinical evaluation.

Understanding molecular mechanisms of biologics drug delivery and stability from NMR spectroscopy.

Protein therapeutics carry inherent limitations of membrane impermeability and structural instability, despite their predominant role in the modern pharmaceutical market. Effective formulations are needed to overcome physiological and physicochemical barriers, respectively, for improving bioavailability and stability. Knowledge of membrane affinity, cellular internalization, encapsulation, and release of drug-loaded carrier vehicles uncover the structural basis for designing and optimizing biopharmaceuticals with enhanced delivery efficiency and therapeutic efficacy. Understanding stabilizing and destabilizing interactions between protein drugs and formulation excipients provide fundamental mechanisms for ensuring the stability and quality of biological products. This article reviews the molecular studies of biologics using solution and solid-state NMR spectroscopy on structural attributes pivotal to drug delivery and stability. In-depth investigation of the structure-function relationship of drug delivery systems based on cell-penetrating peptides, lipid nanoparticles and polymeric colloidal, and biophysical and biochemical stability of peptide, protein, monoclonal antibody, and vaccine, as the integrative efforts on drug product design, will be elaborated.

Models for Counts and Particle Size Distributions of Subvisible Particle Data.

Traditional statistical analyses of subvisible particle data are usually based on either descriptive statistics, normal-based methods, or standard Poisson models. These methods often do not adequately describe the counts or particle size distribution. They usually ignore relevant information represented in the data, such as count correlation. Therefore, any meaningful analyses of subvisible particle data require a reasonable representation of counts and particle size distribution and the correlation in the data. Such comprehensive approaches are not widely available or used when analyzing subvisible particle data. In this article, we propose the use of generalized linear mixed models to analyze the counts and the particle size distribution of subvisible particle data. These models make optimal use of the information in the data and allow flexible approaches for the analyses of a wide range of data structures. They are readily accessible to practitioners through the use of modern statistical software. These models are demonstrated with two numerical examples using two different data structures.

Coarse-Grained Molecular Dynamics Simulations for Understanding the Impact of Short-Range Anisotropic Attractions on Structure and Viscosity of Concentrated Monoclonal Antibody Solutions.

Understanding protein-protein interactions in concentrated therapeutic monoclonal antibody (mAb) solutions is desirable for improved drug discovery, processing, and administration. Here, we deduce both the net protein charge and the magnitude and geometry of short-ranged, anisotropic attractions of a mAb across multiple concentrations and cosolute conditions by comparing structure factors S(q) obtained from small-angle X-ray scattering experiments with those from molecular dynamics (MD) simulations. The simulations, which utilize coarse-grained 12-bead models exhibiting a uniform van der Waals attraction, uniform electrostatic repulsion, and short-range attractions between specific beads, are versatile enough to fit S(q) of a wide range of protein concentrations and ionic strength with the same charge on each bead and a single anisotropic short-range attraction strength. Cluster size distributions (CSDs) obtained from best fit simulations reveal that the experimental structure is consistent with small reversible oligomers in even low viscosity systems and help quantify the impact of these clusters on viscosity. The ability to systematically use experimental S(q) data together with MD simulations to discriminate between different possible protein-protein interactions, as well as to predict viscosities from protein CSDs, is beneficial for designing mAbs and developing formulation strategies that avoid high viscosities and aggregation at high concentration.

Self-diffusion of a highly concentrated monoclonal antibody by fluorescence correlation spectroscopy: insight into protein-protein interactions and self-association.

The dynamic behavior of monoclonal antibodies (mAbs) at high concentration provides insight into protein microstructure and protein-protein interactions (PPI) that influence solution viscosity and protein stability. At high concentration, interpretation of the collective-diffusion coefficient Dc, as determined by dynamic light scattering (DLS), is highly challenging given the complex hydrodynamics and PPI at close spacings. In contrast, self-diffusion of a tracer particle by Brownian motion is simpler to understand. Herein, we develop fluorescence correlation spectroscopy (FCS) for the measurement of the long-time self-diffusion of mAb2 over a wide range of concentrations and viscosities in multiple co-solute formulations with varying PPI. The normalized self-diffusion coefficient D0/Ds (equal to the microscopic relative viscosity ηeff/η0) was found to be smaller than η/η0. Smaller ratios of the microscopic to macroscopic viscosity (ηeff/η) are attributed to a combination of weaker PPI and less self-association. The interaction parameters extracted from fits of D0/Ds with a length scale dependent viscosity model agree with previous measurements of PPI by SLS and SAXS. Trends in the degree of self-association, estimated from ηeff/η with a microviscosity model, are consistent with oligomer sizes measured by SLS. Finally, measurements of collective diffusion and osmotic compressibility were combined with FCS data to demonstrate that the changes in self-diffusion between formulations are due primarily to changes in the protein-protein friction in these systems, and not to protein-solvent friction. Thus, FCS is a robust and accessible technique for measuring mAb self-diffusion, and, by extension, microviscosity, PPI and self-association that govern mAb solution dynamics.

X-ray Scattering and Coarse-Grained Simulations for Clustering and Interactions of Monoclonal Antibodies at High Concentrations.

Attractive protein?protein interactions (PPI) in concentrated monoclonal antibody (mAb) solutions may lead to reversible oligomers (clusters) that impact colloidal stability and viscosity. Herein, the PPI are tuned for two mAbs via the addition of arginine (Arg), NaCl, or ZnSO4 as characterized by the structure factor ( Seff( q)) with small-angle X-ray scattering (SAXS). The SAXS data are fit with molecular dynamics simulations by placing a physically relevant short-range attractive interaction on selected beads in coarse-grained 12-bead models of the mAb shape. The optimized 12-bead models are then used to differentiate key microstructural properties, including center of mass radial distribution functions ( gCOM( r)), coordination numbers, and cluster size distributions (CSD). The addition of cosolutes results in more attractive Seff( q) relative to the no cosolute control for all systems tested, with the most attractive systems showing an upturn at low q. Only the All1 model with an attractive site in each Fab and Fc region (possessing Fab?Fab, Fab?Fc, and Fc?Fc interactions) can reproduce this upturn, and the corresponding CSDs show the presence of larger clusters compared to the control. In general, for models with similar net attractions, i.e., second osmotic virial coefficients, the size of the clusters increases as the attraction is concentrated on a smaller number of evenly distributed beads. The cluster size distributions from simulations are used to improve the understanding and prediction of experimental viscosities. The ability to discriminate between models with bead interactions at particular Fab and Fc bead sites from SAXS simulations, and to provide real-space properties (CSD and gCOM( r)), will be of interest in engineering protein sequence and formulating protein solutions for weak PPI to minimize aggregation and viscosities.

Protein-Protein Interactions of Highly Concentrated Monoclonal Antibody Solutions via Static Light Scattering and Influence on the Viscosity.

The ability to design and formulate mAbs to minimize attractive interactions at high concentrations is important for protein processing, stability, and administration, particularly in subcutaneous delivery, where high viscosities are often challenging. The strength of protein-protein interactions (PPIs) of an IgG1 and IgG4 monoclonal antibody (mAb) from low to high concentration was determined by static light scattering (SLS) and used to understand viscosity data. The PPI were tuned using NaCl and five organic ionic co-solutes. The PPI strength was quantified by the normalized structure factor S(0)/ S(0)HS and Kirkwood-Buff integral G22/ G22,HS (HS = hard sphere) determined from the SLS data and also by fits with (1) a spherical Yukawa potential and (2) an interacting hard sphere (IHS) model, which describes attraction in terms of hypothetical oligomers. The IHS model was better able to capture the scattering behavior of the more strongly interacting systems (mAb and/or co-solute) than the spherical Yukawa potential. For each descriptor of PPI, linear correlations were obtained between the viscosity at high concentration (200 mg/mL) and the interaction strengths evaluated both at low (20 mg/mL) and high concentrations (200 mg/mL) for a given mAb. However, the only parameter that provided a correlation across both mAbs was the oligomer mass ratio ( moligomer/ mmonomer+dimer) from the IHS model, indicating the importance of self-association (in addition to the direct influence of the attractive PPI) on the viscosity.

Structure, heterogeneity and developability assessment of therapeutic antibodies.

Increasing attention has been paid to developability assessment with the understanding that thorough evaluation of monoclonal antibody lead candidates at an early stage can avoid delays during late-stage development. The concept of developability is based on the knowledge gained from the successful development of approximately 80 marketed antibody and Fc-fusion protein drug products and from the lessons learned from many failed development programs over the last three decades. Here, we reviewed antibody quality attributes that are critical to development and traditional and state-of-the-art analytical methods to monitor those attributes. Based on our collective experiences, a practical workflow is proposed as a best practice for developability assessment including in silico evaluation, extended characterization and forced degradation using appropriate analytical methods that allow characterization with limited material consumption and fast turnaround time.

A comparison of biophysical characterization techniques in predicting monoclonal antibody stability.

With the rapid growth of biopharmaceutical product development, knowledge of therapeutic protein stability has become increasingly important. We evaluated assays that measure solution-mediated interactions and key molecular characteristics of 9 formulated monoclonal antibody (mAb) therapeutics, to predict their stability behavior. Colloidal interactions, self-association propensity and conformational stability were measured using effective surface charge via zeta potential, diffusion interaction parameter (kD) and differential scanning calorimetry (DSC), respectively. The molecular features of all 9 mAbs were compared to their stability at accelerated (25°C and 40°C) and long-term storage conditions (2-8°C) as measured by size exclusion chromatography. At accelerated storage conditions, the majority of the mAbs in this study degraded via fragmentation rather than aggregation. Our results show that colloidal stability, self-association propensity and conformational characteristics (exposed tryptophan) provide reasonable prediction of accelerated stability, with limited predictive value at 2-8°C stability. While no correlations to stability behavior were observed with onset-of-melting temperatures or domain unfolding temperatures, by DSC, melting of the Fab domain with the CH2 domain suggests lower stability at stressed conditions. The relevance of identifying appropriate biophysical assays based on the primary degradation pathways is discussed.

Prediction of viral filtration performance of monoclonal antibodies based on biophysical properties of feed.

Controlling viral contamination is an important issue in the process development of monoclonal antibodies (MAbs) produced from mammalian cell lines. Virus filtration (VF) has been demonstrated to be a robust and effective clearance step which can provide ≥4 logs of reduction via size exclusion. The minimization of VF area by increasing flux and filter loading is critical to achieving cost targets as VFs are single use and often represent up to 10% of total purification costs. The research presented in this publication describes a development strategy focused on biophysical attributes of product streams that are directly applicable to VF process performance. This article summarizes a case study where biophysical tools (high-pressure size exclusion chromatography, dynamic light scattering, and absolute size exclusion chromatography) were applied to a specific MAb program to illustrate how changes in feed composition (pH, sodium chloride concentration, and buffer salt type) can change biophysical properties which correlate with VF performance. The approach was subsequently refined and expanded over the course of development of three MAbs where performance metrics (i.e., loading and flux) were evaluated for two specific virus filters (Viresolve Pro and Planova 20N) during both unspiked control runs and virus clearance experiments. The analyses of feed attributes can be applied to a decision tree to guide the recommendation of a VF filter and operating conditions for use in future MAb program development. The understanding of the biophysical properties of the feed can be correlated to virus filter performance to significantly reduce the mass of product, time, and costs associated with virus filter step development.

Nanoparticulate Impurities in Pharmaceutical-Grade Sugars and their Interference with Light Scattering-Based Analysis of Protein Formulations.

PURPOSE: In the present study we investigated the root-cause of an interference signal (100-200 nm) of sugar-containing solutions in dynamic light scattering (DLS) and nanoparticle tracking analysis (NTA) and its consequences for the analysis of particles in biopharmaceutical drug products. METHODS: Different sugars as well as sucrose of various purity grades, suppliers and lots were analyzed by DLS and NTA before and (only for sucrose) after treatment by ultrafiltration and diafiltration. Furthermore, Fourier transform infrared (FTIR) microscopy, scanning electron microscopy coupled energy-dispersive X-ray spectroscopy (SEM-EDX), and fluorescence spectroscopy were employed. RESULTS: The intensity of the interference signal differed between sugar types, sucrose of various purity grades, suppliers, and batches of the same supplier. The interference signal could be successfully eliminated from a sucrose solution by ultrafiltration (0.02 µm pore size). Nanoparticles, apparently composed of dextrans, ash components and aromatic colorants that were not completely removed during the sugar refinement process, were found responsible for the interference and were successfully purified from sucrose solutions. CONCLUSIONS: The interference signal of sugar-containing solutions in DLS and NTA is due to the presence of nanoparticulate impurities. The nanoparticles present in sucrose were identified as agglomerates of various impurities originating from raw materials.

Improving monoclonal antibody selection and engineering using measurements of colloidal protein interactions.

A limitation of using mAbs as therapeutic molecules is their propensity to associate with themselves and/or with other molecules via nonaffinity (colloidal) interactions. This can lead to a variety of problems ranging from low solubility and high viscosity to off-target binding and fast antibody clearance. Measuring such colloidal interactions is challenging given that they are weak and potentially involve diverse target molecules. Nevertheless, assessing these weak interactions-especially during early antibody discovery and lead candidate optimization-is critical to preventing problems that can arise later in the development process. Here we review advances in developing and implementing sensitive methods for measuring antibody colloidal interactions as well as using these measurements for guiding antibody selection and engineering. These systematic efforts to minimize nonaffinity interactions are expected to yield more effective and stable mAbs for diverse therapeutic applications. © 2014 Wiley Periodicals, Inc. and the American Pharmacists Association J Pharm Sci 103:3356-3363, 2014.

Effect of pegylation on self-association of IFN-α2b.

Pegylation of therapeutic proteins is an established technology used to enhance the bioavailability of an active pharmaceutical ingredient in the body of patients. While the physiochemical properties of pegylated monomeric proteins have been extensively described, there is still limited information on the characterization of pegylated oligomeric proteins. In this study, we report the characterization of a pegylated interferon alpha2b (PEGIFN-α2b) concentration-dependent oligomerization by a series of orthogonal biochemical and biophysical methods. These methods include sedimentation velocity and sedimentation equilibrium analytical ultracentrifugation, matrix-assisted laser desorption ionization, and size exclusion chromatography of bissulfosuccinimidyl suberate cross-linked PEGIFN. We report here that PEGIFN-α2b self-associates in a concentration-dependent manner into mainly monomers, dimers, and trimers. In the presence of the chemical cross-linker, PEGIFN-α2b is primarily monomeric (57%) at concentration lower than 0.3 mg/mL and contains about equal amount of monomers and dimers (47.0% and 37.7%, respectively), about 15% of trimers, and up to 4% of higher molecular weight species at 0.7 mg/mL and above.

Solution pH that minimizes self-association of three monoclonal antibodies is strongly dependent on ionic strength.

Monoclonal antibodies display highly variable solution properties such as solubility and viscosity at elevated concentrations (>50 mg/mL), which complicates antibody formulation and delivery. To understand this complex behavior, it is critical to measure the underlying protein self-interactions that govern the solution properties of antibody suspensions. We have evaluated the pH-dependent self-association behavior of three monoclonal antibodies using self-interaction chromatography for a range of pH values commonly used in antibody formulations (pH 4.4-6). At low ionic strength (<25 mM), we find that each antibody is more associative at near-neutral pH (pH 6) than at low pH (pH 4.4). At high ionic strength (>100 mM), we observe the opposite pH-dependent pattern of antibody self-association. Importantly, this inversion in self-association behavior is not unique to multidomain antibodies, as similar pH-dependent behavior is observed for some small globular proteins (e.g., ribonuclease A and α-chymotrypsinogen). We also find that the opalescence of concentrated antibody solutions (90 mg/mL) is minimized at low ionic strength at pH 4.4 and high ionic strength at pH 6, in agreement with the self-interaction measurements conducted at low antibody concentrations (5 mg/mL). Our results highlight the complexity of antibody self-association and emphasize the need for systematic approaches to optimize the solution properties of concentrated antibody formulations.

Insights into crowding effects on protein stability from a coarse-grained model.

Proteins aggregate and precipitate from high concentration solutions in a wide variety of problems of natural and technological interest. Consequently, there is a broad interest in developing new ways to model the thermodynamic and kinetic aspects of protein stability in these crowded cellular or solution environments. We use a coarse-grained modeling approach to study the effects of different crowding agents on the conformational equilibria of proteins and the thermodynamic phase behavior of their solutions. At low to moderate protein concentrations, we find that crowding species can either stabilize or destabilize the native state, depending on the strength of their attractive interaction with the proteins. At high protein concentrations, crowders tend to stabilize the native state due to excluded volume effects, irrespective of the strength of the crowder-protein attraction. Crowding agents reduce the tendency of protein solutions to undergo a liquid-liquid phase separation driven by strong protein-protein attractions. The aforementioned equilibrium trends represent, to our knowledge, the first simulation predictions for how the properties of crowding species impact the global thermodynamic stability of proteins and their solutions.

Coarse-grained strategy for modeling protein stability in concentrated solutions. III: directional protein interactions.

We extend our coarse-grained modeling strategy described in parts I and II of this investigation to account for nonuniform spatial distributions of hydrophobic residues on the solvent-exposed surfaces of native proteins. Within this framework, we explore how patchy surfaces can influence the solvent-mediated protein-protein interactions, and the unfolding and self-assembly behaviors of proteins in solution. In particular, we compare the equilibrium unfolding and self-assembly trends for three model proteins that share the same overall sequence hydrophobicity, but exhibit folded configurations with different solvent-exposed native-state surface morphologies. Our model provides new insights into how directional interactions can affect native-state protein stability in solution. We find that strongly-directional attractions between native molecules with patchy surfaces can help stabilize the folded conformation through the formation of self-assembled clusters. In contrast, native proteins with more uniform surfaces are destabilized by protein-protein attractions involving the denatured state. Finally, we discuss how the simulation results provide insights into the experimental solution behaviors of several proteins that display directional interactions in their native states.

Analytical model for studying how environmental factors influence protein conformational stability in solution.

We introduce an analytical modeling strategy for probing the conformational stability of globular proteins in aqueous solution. In this approach, the intrinsic (i.e., infinite dilution) thermodynamic stability and coarse structural properties of the proteins, as well as the effective protein-protein interactions, derive from a heteropolymer collapse theory that incorporates predicted temperature- and pressure-dependent hydrophobic interactions. Protein concentration effects are estimated by integrating this information into a molecular thermodynamic model, which is an ad hoc generalization of the exact equilibrium theory of a one-dimensional binary mixture of square-well particles that interconvert through an isomerization (i.e., folding) reaction. The end result is an analytical multiscale modeling approach which, although still schematic, can predict that folded proteins exhibit a closed-loop region of stability in the pressure-temperature plane and that protein concentration has a nonmonotonic effect on protein stability, results consistent with qualitative trends observed in both experiments of protein solutions and simulations of coarse-grained protein models.

Heteropolymer collapse theory for protein folding in the pressure-temperature plane.

We revisit a heteropolymer collapse theory originally introduced to explore how the balance between hydrophobic interactions and configurational entropy determines the thermal stability of globular proteins at ambient pressure. We generalize the theory by introducing a basic statistical mechanical treatment for how pressure impacts the solvent-mediated interactions between hydrophobic amino-acid residues. In particular, we estimate the strength of the hydrophobic interactions using a molecular thermodynamic model for the interfacial free energy between liquid water and a curved hydrophobic solute. The model, which also reproduces many of the distinctive thermodynamic properties of aqueous solutions in bulk and interfacial environments, predicts that the water-solute interfacial free energy is significantly reduced by the application of high hydrostatic pressures. This allows water to penetrate into folded heteropolymers at high pressure and break apart their hydrophobic cores, a scenario suggested earlier by information theory calculations. As a result, folded heteropolymers are predicted to display the kind of closed region of stability in the pressure-temperature plane exhibited by native proteins. We compare predictions of the collapse theory with experimental data for several proteins.

Coarse-grained strategy for modeling protein stability in concentrated solutions. II: phase behavior.

We use highly efficient transition-matrix Monte Carlo simulations to determine equilibrium unfolding curves and fluid phase boundaries for solutions of coarse-grained globular proteins. The model we analyze derives the intrinsic stability of the native state and protein-protein interactions from basic information about protein sequence using heteropolymer collapse theory. It predicts that solutions of low hydrophobicity proteins generally exhibit a single liquid phase near their midpoint temperatures for unfolding, while solutions of proteins with high sequence hydrophobicity display the type of temperature-inverted, liquid-liquid transition associated with aggregation processes of proteins and other amphiphilic molecules. The phase transition occurring in solutions of the most hydrophobic protein we study extends below the unfolding curve, creating an immiscibility gap between a dilute, mostly native phase and a concentrated, mostly denatured phase. The results are qualitatively consistent with the solution behavior of hemoglobin (HbA) and its sickle variant (HbS), and they suggest that a liquid-liquid transition resulting in significant protein denaturation should generally be expected on the phase diagram of high-hydrophobicity protein solutions. The concentration fluctuations associated with this transition could be a driving force for the nonnative aggregation that can occur below the midpoint temperature.