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Forder JK, Palakollu V, Adhikari S, Blanco MA, Derebe MG, Ferguson HM, Luthra SA, Munsell EV, Roberts CJ. Electrostatically Mediated Attractive Self-Interactions and Reversible Self-Association of Fc-Fusion Proteins. Mol Pharm 2024; 21:1321-1333. [PMID: 38334418 DOI: 10.1021/acs.molpharmaceut.3c01009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/10/2024]
Abstract
Attractive self-interactions and reversible self-association are implicated in many problematic solution behaviors for therapeutic proteins, such as irreversible aggregation, elevated viscosity, phase separation, and opalescence. Protein self-interactions and reversible oligomerization of two Fc-fusion proteins (monovalent and bivalent) and the corresponding fusion partner protein were characterized experimentally with static and dynamic light scattering as a function of pH (5 and 6.5) and ionic strength (10 mM to at least 300 mM). The fusion partner protein and monovalent Fc-fusion each displayed net attractive electrostatic self-interactions at pH 6.5 and net repulsive electrostatic self-interactions at pH 5. Solutions of the bivalent Fc-fusion contained higher molecular weight species that prevented quantification of typical interaction parameters (B22 and kD). All three of the proteins displayed reversible self-association at pH 6.5, where oligomers dissociated with increased ionic strength. Coarse-grained molecular simulations were used to model the self-interactions measured experimentally, assess net self-interactions for the bivalent Fc-fusion, and probe the specific electrostatic interactions between charged amino acids that were involved in attractive electrostatic self-interactions. Mayer-weighted pairwise electrostatic energies from the simulations suggested that attractive electrostatic self-interactions at pH 6.5 for the two Fc-fusion proteins were due to cross-domain interactions between the fusion partner domain(s) and the Fc domain.
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Affiliation(s)
- James K Forder
- Department of Chemical and Biomolecular Engineering, University of Delaware, Newark, Delaware 19713, United States
| | - Veerabhadraiah Palakollu
- Department of Chemical and Biomolecular Engineering, University of Delaware, Newark, Delaware 19713, United States
| | - Sudeep Adhikari
- Analytical R&D, Digital & NMR Sciences, Merck & Co., Inc., Rahway, New Jersey 07065, United States
| | - Marco A Blanco
- Discovery Pharmaceutical Sciences, Merck & Co., Inc., West Point, Pennsylvania 19486, United States
| | - Mehabaw Getahun Derebe
- Discovery Biologics, Protein Sciences, Merck & Co., Inc., South San Francisco, California 94080, United States
| | - Heidi M Ferguson
- Discovery Pharmaceutical Sciences, Merck & Co., Inc., West Point, Pennsylvania 19486, United States
| | - Suman A Luthra
- Discovery Pharmaceutical Sciences, Merck & Co., Inc., Boston, Massachusetts 02115, United States
| | - Erik V Munsell
- Discovery Pharmaceutical Sciences, Merck & Co., Inc., Boston, Massachusetts 02115, United States
| | - Christopher J Roberts
- Department of Chemical and Biomolecular Engineering, University of Delaware, Newark, Delaware 19713, United States
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Bhandari K, Wei Y, Amer BR, Pelegri-O’Day EM, Huh J, Schmit JD. Prediction of Antibody Viscosity from Dilute Solution Measurements. Antibodies (Basel) 2023; 12:78. [PMID: 38131800 PMCID: PMC10740665 DOI: 10.3390/antib12040078] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2023] [Revised: 11/20/2023] [Accepted: 11/28/2023] [Indexed: 12/23/2023] Open
Abstract
The high antibody doses required to achieve a therapeutic effect often necessitate high-concentration products that can lead to challenging viscosity issues in production and delivery. Predicting antibody viscosity in early development can play a pivotal role in reducing late-stage development costs. In recent years, numerous efforts have been made to predict antibody viscosity through dilute solution measurements. A key finding is that the entanglement of long, flexible complexes contributes to the sharp rise in antibody viscosity at the required dosing. This entanglement model establishes a connection between the two-body binding affinity and the many-body viscosity. Exploiting this insight, this study connects dilute solution measurements of self-association to high-concentration viscosity profiles to quantify the relationship between these regimes. The resulting model has exhibited success in predicting viscosity at high concentrations (around 150 mg/mL) from dilute solution measurements, with only a few outliers remaining. Our physics-based approach provides an understanding of fundamental physics, interpretable connections to experimental data, the potential to extrapolate beyond training conditions, and the capacity to effectively explain the physical mechanics behind these outliers. Conducting hypothesis-driven experiments that specifically target the viscosity and relaxation mechanisms of outlier molecules may allow us to unravel the intricacies of their behavior and, in turn, enhance the performance of our model.
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Affiliation(s)
- Kamal Bhandari
- Department of Physics, Kansas State University, Manhattan, KS 66506, USA;
| | - Yangjie Wei
- Amgen Inc., Thousand Oaks, CA 91320, USA; (Y.W.); (B.R.A.); (E.M.P.-O.); (J.H.)
| | - Brendan R. Amer
- Amgen Inc., Thousand Oaks, CA 91320, USA; (Y.W.); (B.R.A.); (E.M.P.-O.); (J.H.)
| | | | - Joon Huh
- Amgen Inc., Thousand Oaks, CA 91320, USA; (Y.W.); (B.R.A.); (E.M.P.-O.); (J.H.)
| | - Jeremy D. Schmit
- Department of Physics, Kansas State University, Manhattan, KS 66506, USA;
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Billups M, Minervini M, Holstein M, Feroz H, Ranjan S, Hung J, Zydney AL. The role of intermolecular interactions on monoclonal antibody filtration through virus removal membranes. Biotechnol J 2023; 18:e2300265. [PMID: 37641433 DOI: 10.1002/biot.202300265] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Revised: 07/31/2023] [Accepted: 08/23/2023] [Indexed: 08/31/2023]
Abstract
The removal of viruses by filtration is a critical unit operation to ensure the overall safety of monoclonal antibody (mAb) products. Many mAbs show very low filtrate flux during virus removal filtration, although there are still significant uncertainties regarding both the mechanisms and antibody properties that determine the filtration behavior. Experiments were performed with three highly purified mAbs through three different commercial virus filters (Viresolve Pro, Viresolve NFP, and Pegasus SV4) with different pore structures and chemistries. The flux decline observed during mAb filtration was largely reversible, even under conditions where the filtrate flux with the mAb was more than 100-fold smaller than the corresponding buffer flux. The extent of flux decline was highly correlated with the hydrodynamic diameter of the mAb as determined by dynamic light scattering (DLS). The mAb with the lowest filtrate flux for all three membranes showed the largest attractive intermolecular interactions and the greatest hydrophobicity, with the latter determined by binding to a butyl resin in an analytical hydrophobic interaction chromatography (HIC) column. These results strongly suggest that the flux behavior is dominated by reversible self-association of the mAbs, providing important insights into the design of more effective virus filtration processes and in the early identification of problematic mAbs/solution conditions.
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Affiliation(s)
- Matthew Billups
- Department of Chemical Engineering, The Pennsylvania State University, University Park, Pennsylvania, USA
| | - Mirko Minervini
- Department of Chemical Engineering, The Pennsylvania State University, University Park, Pennsylvania, USA
| | - Melissa Holstein
- Bristol Myers Squibb, Biologics Process Development, Global Product Development and Supply, Devens, Massachusetts, USA
| | - Hasin Feroz
- Bristol Myers Squibb, Biologics Process Development, Global Product Development and Supply, Devens, Massachusetts, USA
| | - Swarnim Ranjan
- Bristol Myers Squibb, Biologics Process Development, Global Product Development and Supply, Devens, Massachusetts, USA
| | - Jessica Hung
- Bristol Myers Squibb, Biologics Process Development, Global Product Development and Supply, Devens, Massachusetts, USA
| | - Andrew L Zydney
- Department of Chemical Engineering, The Pennsylvania State University, University Park, Pennsylvania, USA
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Shrivastava A, Mandal S, Pattanayek SK, Rathore AS. Rapid Estimation of Size-Based Heterogeneity in Monoclonal Antibodies by Machine Learning-Enhanced Dynamic Light Scattering. Anal Chem 2023; 95:8299-8309. [PMID: 37200383 DOI: 10.1021/acs.analchem.3c00650] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/20/2023]
Abstract
Aggregation of monoclonal antibody therapeutics is a serious concern that is believed to impact product safety and efficacy. There is a need for analytical approaches that enable rapid estimation of mAb aggregates. Dynamic light scattering (DLS) is a well-established technique for estimating the average size of protein aggregates or for evaluating sample stability. It is usually used to measure the size and size distribution over a wide range of nano- to micro-sized particles using time-dependent fluctuations in the intensity of scattered light arising from the Brownian motion of particles. In this study, we present a novel DLS-based approach that allows us to quantify the relative percentage of multimers (monomer, dimer, trimer, and tetramer) in a monoclonal antibody (mAb) therapeutic product. The proposed approach uses a machine learning (ML) algorithm and regression to model the system and predict the amount of relevant species such as monomer, dimer, trimer, and tetramer of a mAb in the size range of 10-100 nm. The proposed DLS-ML technique compares favorably to all potential alternatives with respect to the key method attributes, including per sample cost of analysis, per sample time of data acquisition along with ML-based aggregate prediction (<2 min), sample requirements (<3 μg), and user-friendliness of analysis. The proposed rapid method can serve as an orthogonal tool to size exclusion chromatography, which is the current industry workhorse for aggregate assessment.
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Affiliation(s)
- Anuj Shrivastava
- Department of Chemical Engineering, IIT Delhi, Hauz Khas, New Delhi 110016, India
| | - Shyamapada Mandal
- Department of Chemical Engineering, IIT Delhi, Hauz Khas, New Delhi 110016, India
| | - Sudip K Pattanayek
- Department of Chemical Engineering, IIT Delhi, Hauz Khas, New Delhi 110016, India
| | - Anurag S Rathore
- Department of Chemical Engineering, IIT Delhi, Hauz Khas, New Delhi 110016, India
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Design, Production, Characterization, and Use of Peptide Antibodies. Antibodies (Basel) 2023; 12:antib12010006. [PMID: 36648890 PMCID: PMC9844468 DOI: 10.3390/antib12010006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Revised: 10/10/2022] [Accepted: 12/26/2022] [Indexed: 01/15/2023] Open
Abstract
Antibodies are key reagents in diagnostics, therapeutics, and experimental biology, capable of detecting numerous targets [...].
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Mieczkowski C, Zhang X, Lee D, Nguyen K, Lv W, Wang Y, Zhang Y, Way J, Gries JM. Blueprint for antibody biologics developability. MAbs 2023; 15:2185924. [PMID: 36880643 PMCID: PMC10012935 DOI: 10.1080/19420862.2023.2185924] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/08/2023] Open
Abstract
Large-molecule antibody biologics have revolutionized medicine owing to their superior target specificity, pharmacokinetic and pharmacodynamic properties, safety and toxicity profiles, and amenability to versatile engineering. In this review, we focus on preclinical antibody developability, including its definition, scope, and key activities from hit to lead optimization and selection. This includes generation, computational and in silico approaches, molecular engineering, production, analytical and biophysical characterization, stability and forced degradation studies, and process and formulation assessments. More recently, it is apparent these activities not only affect lead selection and manufacturability, but ultimately correlate with clinical progression and success. Emerging developability workflows and strategies are explored as part of a blueprint for developability success that includes an overview of the four major molecular properties that affect all developability outcomes: 1) conformational, 2) chemical, 3) colloidal, and 4) other interactions. We also examine risk assessment and mitigation strategies that increase the likelihood of success for moving the right candidate into the clinic.
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Affiliation(s)
- Carl Mieczkowski
- Department of Protein Sciences, Hengenix Biotech, Inc, Milpitas, CA, USA
| | - Xuejin Zhang
- Department of Protein Sciences, Hengenix Biotech, Inc, Milpitas, CA, USA
| | - Dana Lee
- Department of Protein Sciences, Hengenix Biotech, Inc, Milpitas, CA, USA
| | - Khanh Nguyen
- Department of Protein Sciences, Hengenix Biotech, Inc, Milpitas, CA, USA
| | - Wei Lv
- Department of Protein Sciences, Hengenix Biotech, Inc, Milpitas, CA, USA
| | - Yanling Wang
- Department of Protein Sciences, Hengenix Biotech, Inc, Milpitas, CA, USA
| | - Yue Zhang
- Department of Protein Sciences, Hengenix Biotech, Inc, Milpitas, CA, USA
| | - Jackie Way
- Department of Protein Sciences, Hengenix Biotech, Inc, Milpitas, CA, USA
| | - Jean-Michel Gries
- President, Discovery Research, Hengenix Biotech, Inc, Milpitas, CA, USA
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Makowski EK, Schardt JS, Tessier PM. Improving antibody drug development using bionanotechnology. Curr Opin Biotechnol 2021; 74:137-145. [PMID: 34890875 DOI: 10.1016/j.copbio.2021.10.027] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2021] [Revised: 10/25/2021] [Accepted: 10/31/2021] [Indexed: 12/20/2022]
Abstract
Monoclonal antibodies are being used to treat a remarkable breadth of human disorders. Nevertheless, there are several key challenges at the earliest stages of antibody drug development that need to be addressed using simple and widely accessible methods, especially related to generating antibodies against membrane proteins and identifying antibody candidates with drug-like biophysical properties (high solubility and low viscosity). Here we highlight key bionanotechnologies for preparing functional and stable membrane proteins in diverse types of lipoparticles that are being used to improve antibody discovery and engineering efforts. We also highlight key bionanotechnologies for high-throughput and ultra-dilute screening of antibody biophysical properties during antibody discovery and optimization that are being used for identifying antibodies with superior combinations of in vitro (formulation) and in vivo (half-life) properties.
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Affiliation(s)
- Emily K Makowski
- Department of Pharmaceutical Sciences, University of Michigan, Ann Arbor, MI 48109, USA; Biointerfaces Institute, University of Michigan, Ann Arbor, MI 48109, USA
| | - John S Schardt
- Department of Pharmaceutical Sciences, University of Michigan, Ann Arbor, MI 48109, USA; Department of Chemical Engineering, University of Michigan, Ann Arbor, MI 48109, USA; Biointerfaces Institute, University of Michigan, Ann Arbor, MI 48109, USA
| | - Peter M Tessier
- Department of Pharmaceutical Sciences, University of Michigan, Ann Arbor, MI 48109, USA; Department of Chemical Engineering, University of Michigan, Ann Arbor, MI 48109, USA; Departmant of Biomedical Engineering, University of Michigan, Ann Arbor, MI 48109, USA; Biointerfaces Institute, University of Michigan, Ann Arbor, MI 48109, USA.
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