☆ 4.5 Review

Approaches to expand the conventional toolbox for discovery and selection of antibodies with drug-like physicochemical properties

MABS (2023)

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Review Chemistry, Medicinal

Surface-Induced Protein Aggregation and Particle Formation in Biologics: Current Understanding of Mechanisms, Detection and Mitigation Strategies

Marie R. G. Kopp et al.

Summary: Protein stability against aggregation is a major concern in biopharmaceutical production. Interactions between proteins and interfaces, such as air-water and silicone oil-water interfaces, as well as materials from processing units, storage containers, and delivery devices, play a significant role in protein aggregation. However, the key determinants and analytical methods for monitoring and predicting protein instability at these interfaces remain difficult to identify. This review discusses the mechanisms, potential harmful materials, mitigation strategies, and current methods for studying surface-induced protein instability, aiming to aid early-stage screening and formulation development of biologics.

JOURNAL OF PHARMACEUTICAL SCIENCES (2023)

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Article Biochemical Research Methods

ABlooper: fast accurate antibody CDR loop structure prediction with accuracy estimation

Brennan Abanades et al.

Summary: In this study, the researchers developed a deep learning-based tool called ABlooper for predicting the structure of CDR loops in antibodies. ABlooper accurately predicts the structure of CDR-H3 loops, which are known for their sequence and structural variability. The tool provides high accuracy predictions and confidence estimates for each prediction.

BIOINFORMATICS (2022)

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Article Chemistry, Medicinal

Nucleation in Protein Aggregation in Biotherapeutic Development: A look into the Heart of the Event

Tapan K. Das et al.

Summary: Protein aggregation is a challenging phenomenon in the field of biologics research and development. Nucleation is the core step that initiates protein aggregation. Understanding nucleation is crucial for avoiding undesired protein aggregation. This review article discusses the latest progress in protein aggregation research, including nucleation events, identification of protein aggregation sources, and development of analytical tools. It also highlights significant gaps in the analysis and understanding of nucleation in non-native protein aggregation.

JOURNAL OF PHARMACEUTICAL SCIENCES (2022)

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Article Chemistry, Medicinal

Oxidation and Deamidation of Monoclonal Antibody Products: Potential Impact on Stability, Biological Activity, and Efficacy

Surbhi Gupta et al.

Summary: Therapeutic proteins, especially monoclonal antibodies (mAbs), play a significant role in human health. The physical and chemical degradation, particularly oxidation and deamidation, can affect the properties and efficacy of the products.

JOURNAL OF PHARMACEUTICAL SCIENCES (2022)

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Article Chemistry, Medicinal

Particles in Biopharmaceutical Formulations, Part 2: An Update on Analytical Techniques and Applications for Therapeutic Proteins, Viruses, Vaccines and Cells

Alexandra Roesch et al.

Summary: Particles in biopharmaceutical formulations have been a hot topic in drug product development. This review provides a comprehensive overview of novel particle analysis techniques for particulate impurities in therapeutic protein formulations and biopharmaceutical formulations, discussing their applications, specific analytical approaches, and the advantages and drawbacks of currently available techniques.

JOURNAL OF PHARMACEUTICAL SCIENCES (2022)

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Review Medicine, Research & Experimental

Current advances in biopharmaceutical informatics: guidelines, impact and challenges in the computational developability assessment of antibody therapeutics

Rahul Khetan et al.

Summary: This article provides an overview of antibody informatics tools for the prediction of developability issues and evaluates the opportunities and challenges of using biopharmaceutical informatics for drug discovery and optimization. Furthermore, it discusses the potential of developability guidelines based on in silico metrics.

MABS (2022)

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Article Biochemistry & Molecular Biology

SAbDab in the age of biotherapeutics: updates including SAbDab-nano, the nanobody structure tracker

Constantin Schneider et al.

Summary: The Structural Antibody Database (SAbDab) was released in 2013 as a publicly available repository of experimentally determined antibody structures. In response to the growing interest in antibodies as biotherapeutics, the database has implemented improvements such as the development of SAbDab-nano, a sub-database tracking nanobodies. Both databases are updated weekly, annotated with the latest features, and freely accessible online.

NUCLEIC ACIDS RESEARCH (2022)

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Review Biochemistry & Molecular Biology

Antibody display technologies: selecting the cream of the crop

Bernhard Valldorf et al.

Summary: Antibody display technologies have enabled the successful isolation of antigen-specific antibodies with therapeutic potential, with genotype-phenotype coupling being a key feature. While phage display is the most established system, newer technologies like mammalian display have also matured in recent years.

BIOLOGICAL CHEMISTRY (2022)

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Article Chemistry, Medicinal

Miniaturized Forced Degradation of Therapeutic Proteins and ADCs by Agitation-Induced Aggregation Using Orbital Shaking of Microplates

Florian Johann et al.

Summary: Microplate-based orbital shaking is a powerful method for screening stabilizing excipients for therapeutic proteins. This study investigated critical parameters for this method and found that shaker quality and liquid-seal contact significantly impact aggregation during shaking. An optimized method was developed to achieve uniform sample treatment and agreement with vial shaking results.

JOURNAL OF PHARMACEUTICAL SCIENCES (2022)

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Article Chemistry, Medicinal

Combining Machine Learning and Backgrounded Membrane Imaging: A Case Study in Comparing and Classifying Different Types of Biopharmaceutically Relevant Particles

Christopher P. Calderon et al.

Summary: This study investigates the application of backgrounded membrane imaging (BMI) combined with convolutional neural networks (CNNs) for the study of subvisible particles in protein biopharmaceuticals and synthetic model particle samples. The study demonstrates that CNN based methods can effectively extract morphological information from brightfield BMI particle images and distinguish between particles of different compositions. The fingerprinting analysis method is shown to be useful for comparing morphological differences and similarities in different drug products and laboratory prepared samples.

JOURNAL OF PHARMACEUTICAL SCIENCES (2022)

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Article Chemistry, Medicinal

Qualitative High-Throughput Analysis of Subvisible Particles in Biological Formulations Using Backgrounded Membrane Imaging

Markela Ibo Murphy et al.

Summary: The high-throughput analysis of low-volume samples for detecting subvisible particles in biologic formulations is still a need in the pharmaceutical industry. This study evaluated backgrounded membrane imaging (BMI) as an alternative method for subvisible particle analysis and identified critical experimental parameters. The results showed that BMI could be used as an orthogonal method for particle characterization when sample material is limited.

JOURNAL OF PHARMACEUTICAL SCIENCES (2022)

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Article Medicine, Research & Experimental

Reduction of therapeutic antibody self-association using yeast-display selections and machine learning

Emily K. Makowski et al.

Summary: This study reports a high-throughput protein engineering method for rapidly identifying antibody candidates with low self-association and high affinity. By conjugating quantum dots to strongly self-associating antibodies, the researchers were able to detect other high self-association antibodies. Using this method, rare variants with co-optimized levels of low self-association and high affinity were identified, and several of these variants also displayed improved folding stability and reduced nonspecific binding.

MABS (2022)

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Review Biochemistry & Molecular Biology

Designing antibodies as therapeutics

Paul J. Carter et al.

Summary: Antibody therapeutics have significant health benefits and are rapidly expanding. This article provides an overview of current antibody therapeutics, including formats, targets, therapeutic areas, and administration routes. It also highlights emerging directions in antibody design, such as enhancing antibodies for cancer treatment and delivering antibodies to specific organs. In addition, the challenges of antibody developability and the potential of machine learning in antibody discovery are discussed.

CELL (2022)

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Review Chemistry, Multidisciplinary

Non-specificity as the sticky problem in therapeutic antibody development

Hannes Ausserwoger et al.

Summary: This article reviews the physicochemical origins of non-specific interactions in antibodies and discusses the role of surface patches in inducing these interactions. These non-specific interactions have an impact on macroscopic development issues such as the physical stability and in vivo half-life of drugs. The article highlights the challenges and opportunities for optimizing protein binding specificity and minimizing non-specificity.

NATURE REVIEWS CHEMISTRY (2022)

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Article Multidisciplinary Sciences

Co-optimization of therapeutic antibody affinity and specificity using machine learning models that generalize to novel mutational space

Emily K. Makowski et al.

Summary: Therapeutic antibody development requires the selection and engineering of molecules with high affinity and other drug-like properties. This study demonstrates the use of machine learning models to simplify the co-optimization of antibody properties, such as affinity and specificity, leading to the development of highly potent antibodies. The models trained on binary labeled datasets enable the prediction of continuous metrics strongly correlated with antibody properties, and deep learning features allow the prediction of novel antibody mutations that surpass the capabilities of the original antibody library.

NATURE COMMUNICATIONS (2022)

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Article Immunology

NanoNet: Rapid and accurate end-to-end nanobody modeling by deep learning

Tomer Cohen et al.

Summary: Antibodies are a rapidly growing class of therapeutics, and single domain camelid VHH antibodies and nanobody domain Nb have emerged as cost-effective and highly stable alternatives. To enable high-throughput epitope mapping, we have developed a deep learning model called NanoNet, which can generate three-dimensional coordinates of the entire VH domain directly from a sequence. NanoNet demonstrates high accuracy in testing and allows for rapid and efficient structure modeling.

FRONTIERS IN IMMUNOLOGY (2022)

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Article Pharmacology & Pharmacy

Understanding opalescence measurements of biologics-A comparison study of methods, standards, and molecules

Patrick Kunz et al.

Summary: Opalescence measurements are widely used in assessing the quality and stability of biopharmaceutical products, but the comparability of results obtained from different instruments and methods can vary significantly. By studying the application of different methods in the biopharmaceutical field, a better understanding and guidance can be provided.

INTERNATIONAL JOURNAL OF PHARMACEUTICS (2022)

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Article Medicine, Research & Experimental

Simultaneous affinity maturation and developability enhancement using natural liability-free CDRs

Andre A. R. Teixeira et al.

Summary: This article presents a sequence agnostic method to improve antibody affinities while simultaneously eliminating sequence liabilities and retaining the same epitope binding as the parental antibody.

MABS (2022)

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Article Medicine, Research & Experimental

Systematic analysis of the varied designs of 819 therapeutic antibodies and Fc fusion proteins assigned international nonproprietary names

Ian Wilkinson et al.

Summary: By assembling a dataset of amino acid sequences of antibody-related therapeutics, this study provides insights into trends in antibody engineering and a guide to frequently tested designs.

MABS (2022)

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Review Biochemical Research Methods

Monoclonal antibody therapies for COVID-19: lessons learned and implications for the development of future products

Brian Kelley et al.

Summary: Several companies were authorized to treat COVID-19 patients with monoclonal antibodies within 1-2 years of the start of the pandemic. These products were developed and approved at an unprecedented speed, reducing clinical trial time by 75% or more without compromising safety. The therapies have successfully reduced hospitalization and death rates, benefiting hundreds of thousands of patients. The development strategies employed in this process have set a new precedent for speed, safety, and clinical benefit and are expected to have a lasting impact on future monoclonal antibody therapies.

CURRENT OPINION IN BIOTECHNOLOGY (2022)

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Article Biochemical Research Methods

Computational counterselection identifies nonspecific therapeutic biologic candidates

Sachit Dinesh Saksena et al.

Summary: This study introduces a computational counterselection method that uses machine learning models to remove nonspecific sequences from pools of candidate biologics. By validating the method with sequencing data from antibody affinity selection, the research found that computational counterselection outperforms molecular counter selection in retaining on-target, specific antibodies and identifying and eliminating off-target, nonspecific antibodies.

CELL REPORTS METHODS (2022)

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Article Chemistry, Multidisciplinary

An antibody scanning method for the detection of α-synuclein oligomers in the serum of Parkinson's disease patients

Klara Kulenkampff et al.

Summary: The study developed a panel of antibodies using an antibody scanning approach to investigate soluble alpha-synuclein aggregates in biofluids from Parkinson's disease patients, providing a promising route for antibody development and characterization of these aggregates.

CHEMICAL SCIENCE (2022)

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Article Computer Science, Artificial Intelligence

Deciphering the language of antibodies using self-supervised learning

Jinwoo Leem et al.

Summary: This article introduces a novel antibody-specific language model called AntiBERTa, which can predict the properties of BCR sequences and outperforms existing tools in predicting antigen binding sites.

PATTERNS (2022)

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Article Biotechnology & Applied Microbiology

Simultaneous Maturation of Single Chain Antibody Stability and Affinity by CHO Cell Display

Ruiqi Luo et al.

Summary: This study developed a thermo-resistant cell display system for improving both the stability and affinity of antibodies. By culturing and labeling cells at high temperatures, antibody mutants with the highest affinities and display levels were successfully enriched. The affinity and stability of three antibodies were simultaneously improved in the experiments.

BIOENGINEERING-BASEL (2022)

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Article Immunology

Functional Changes of Therapeutic Antibodies upon Exposure to Pro-Oxidative Agents

Maxime Lecerf et al.

Summary: Therapeutic monoclonal antibodies have had a transformative impact on clinical practice, but developing therapeutic antibodies remains complex. This study revealed the vulnerability of immunoglobulins to oxidation and the development of polyreactivity in a substantial number of therapeutic antibodies. The induction of polyreactivity was found to be correlated with somatic mutations in the variable domains of immunoglobulin chains. These findings can contribute to the selection of antibody therapeutics with suitable developability profiles.

ANTIBODIES (2022)

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Article Computer Science, Artificial Intelligence

Antibody structure prediction using interpretable deep learning

Jeffrey A. Ruffolo et al.

Summary: DeepAb is a deep learning method that accurately predicts antibody FV structures from sequences. It outperforms alternative methods on diverse and therapeutically relevant antibodies and offers interpretable predictions by introducing an attention mechanism. Additionally, a mutant scoring metric derived from network confidence improves binding affinity for a specific antibody.

PATTERNS (2022)

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Review Pharmacology & Pharmacy

Machine Learning for Biologics: Opportunities for Protein Engineering, Developability, and Formulation

Harini Narayanan et al.

Summary: Successful biologics must meet requirements of both activity and physicochemical features, which can be optimized with the help of artificial intelligence and machine learning to reduce development time and costs. Machine learning is currently applied in biologics discovery and development, particularly in areas such as protein engineering, early biophysical screening, and formulation.

TRENDS IN PHARMACOLOGICAL SCIENCES (2021)

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Article Multidisciplinary Sciences

Disulfide-compatible phage-assisted continuous evolution in the periplasmic space

Mary S. Morrison et al.

Summary: Directed evolution of antibodies has led to important research tools and therapeutic agents. The development of a pPACE platform for continuous evolution of protein-protein interactions in the disulfide-compatible E. coli periplasm demonstrates the potential to optimize proteins containing disulfide bonds.

NATURE COMMUNICATIONS (2021)

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Article Medicine, Research & Experimental

Combining Unfolding Reversibility Studies and Molecular Dynamics Simulations to Select Aggregation-Resistant Antibodies

Carolin Berner et al.

Summary: Efficient development of therapeutic antibodies relies on developability assessment using biophysical and computational methods to identify molecules with drug-like properties, particularly resistance to aggregation. This study demonstrates that three straightforward techniques – ReFOLD assay, Modulated Scanning Fluorimetry (MSF), and molecular dynamics (MD) simulations – can be used to select aggregation-resistant antibodies. Antibodies resistant to aggregation at 40 degrees Celsius exhibited common features such as higher tendency to refold to monomers, higher onset temperature of irreversible unfolding, and unfolding of aggregation-prone sequences at higher temperatures in MD simulations.

MOLECULAR PHARMACEUTICS (2021)

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News Item Biotechnology & Applied Microbiology

FDA approves 100th monoclonal antibody product

Asher Mullard

Summary: After 35 years since the FDA approved the first monoclonal antibody, these biologics now make up nearly one fifth of the agency's new drug approvals each year.

NATURE REVIEWS DRUG DISCOVERY (2021)

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Review Biotechnology & Applied Microbiology

Animal Immunization, in Vitro Display Technologies, and Machine Learning for Antibody Discovery

Andreas H. Laustsen et al.

Summary: The debate on the benefits and drawbacks of antibody discovery through animal immunization versus in vitro selection from nonanimal-derived recombinant repertoires has persisted for years. While some argue that using recombinant display libraries can reduce animal consumption, the number of animals sacrificed during preclinical studies far exceeds those used in immunization campaigns. Therefore, improving quality control before in vivo studies will have a larger impact on animal consumption. Both animal immunization and recombinant repertoires offer unique advantages for discovering fit-for-purpose antibodies. Additionally, machine learning is expected to play a significant role in refining current antibody discovery practices.

TRENDS IN BIOTECHNOLOGY (2021)

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Article Multidisciplinary Sciences

Protein design and variant prediction using autoregressive generative models

Jung-Eun Shin et al.

Summary: The authors introduce a deep generative alignment-free model for sequence design applied to highly variable regions and design and test a diverse nanobody library with improved properties for selection experiments.

NATURE COMMUNICATIONS (2021)

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Article Engineering, Biomedical

Optimization of therapeutic antibodies by predicting antigen specificity from antibody sequence via deep learning

Derek M. Mason et al.

Summary: The optimization of therapeutic antibodies can be achieved by predicting antigen specificity using deep learning, resulting in the identification of optimized antibody variants. This approach may facilitate antibody engineering and optimization.

NATURE BIOMEDICAL ENGINEERING (2021)

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Article Biology

Interaction of clinical-stage antibodies with heme predicts their physiochemical and binding qualities

Maxime Lecerf et al.

Summary: In a study of over 100 samples with variable region sequences matching clinical-stage antibodies, Lecerf et al. show that many antibodies interact with heme. Those that do exhibit specific sequence traits associated with increased hydrophobicity, self-binding, and intrinsic polyreactivity, suggesting that heme interaction is a predictor for important therapeutic qualities.

COMMUNICATIONS BIOLOGY (2021)

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Article Biochemical Research Methods

Reversibility and irreversibility in the temperature denaturation of monoclonal antibodies

Arne Schon et al.

Summary: This study found that the temperature denaturation of the CH2 domain of monoclonal antibodies is reversible, only becoming irreversible after denaturation of the Fab domain. A mixed denaturation model was developed to explain the experimental data and account for the pH dependence of the heat capacity function of 17b and other monoclonal antibodies. This more detailed analysis of monoclonal antibody stability is expected to contribute to the development of better approaches for understanding and optimizing the structural viability of therapeutic macromolecules.

ANALYTICAL BIOCHEMISTRY (2021)

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Article Medicine, Research & Experimental

Ultradilute Measurements of Self-Association for the Identification of Antibodies with Favorable High-Concentration Solution Properties

Charles G. Starr et al.

Summary: CS-SINS is a method that measures colloidal self-interactions at ultradilute antibody concentrations, predicting antibody developability issues at high concentrations, enabling large-scale, high-throughput selection of developable antibodies during early discovery stages.

MOLECULAR PHARMACEUTICS (2021)

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Article Medicine, Research & Experimental

Design of Biopharmaceutical Formulations Accelerated by Machine Learning

Harini Narayanan et al.

Summary: The article introduces a Bayesian optimization algorithm to accelerate the design of biopharmaceutical formulations, optimizing drug formulations in a small number of experiments. It also demonstrates the advantages of this method over traditional approaches, efficiently utilizing historical information and simultaneously optimizing multiple biophysical properties.

MOLECULAR PHARMACEUTICS (2021)

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Article Biochemistry & Molecular Biology

Rapid generation of potent antibodies by autonomous hypermutation in yeast

Alon Wellner et al.

Summary: AHEAD is a synthetic recombinant antibody generation technology that mimics somatic hypermutation inside engineered yeast, enabling the continuous mutation of antibody repertoires through simple cycles of yeast culturing and enrichment for antigen binding to produce high-affinity clones in a short timeframe.

NATURE CHEMICAL BIOLOGY (2021)

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Intrinsic physicochemical profile of marketed antibody-based biotherapeutics

Lucky Ahmed et al.

Summary: By analyzing the physicochemical descriptors of Fv regions in marketed antibody-based biotherapeutics, this study derived a set of descriptors that can help guide hit selection, lead identification, and optimization of biotherapeutic candidates. The research found that 33% of CST antibodies deviate in physicochemical properties from currently marketed biotherapeutics, providing valuable information for risk assessment and collaborations.

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2021)

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Editorial Material Multidisciplinary Sciences

Bispecific antibodies

Ulrich Brinkmann et al.

SCIENCE (2021)

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Drug-like antibodies with high affinity, diversity and developability directly from next-generation antibody libraries

Andre Azevedo Reis Teixeira et al.

Summary: This paper introduces a new antibody library format that generates high-affinity binders with drug-like developability properties directly from initial selections, reducing the need for further engineering or affinity maturation. This innovative design is expected to accelerate drug development processes by reducing the failure rate of leads due to poor antibody affinities and developability.

MABS (2021)

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Review Medicine, Research & Experimental

Polyreactivity and polyspecificity in therapeutic antibody development: risk factors for failure in preclinical and clinical development campaigns

Orla Cunningham et al.

Summary: Antibody-based drugs are widely used in therapeutic modality, but the risk of off-target binding exists. Current understanding of the structural mechanisms underlying antibody polyreactivity and polyspecificity is still incomplete, requiring further research to minimize risks and build necessary tools collectively.

MABS (2021)

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Computational maturation of a single-domain antibody against Aβ42 aggregation

Jiacheng Lin et al.

Summary: The expansion of structural databases and the increase in computing power enable approaches for antibody discovery based on computational design. Through computational design of mutational variants, potentiated antibody variants can be obtained, as demonstrated in the case targeting A beta 42 aggregation.

CHEMICAL SCIENCE (2021)

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Discovery-stage identification of drug-like antibodies using emerging experimental and computational methods

Emily K. Makowski et al.

Summary: Developing monoclonal antibodies as therapeutic agents for diverse human disorders has sparked intense interest. Key recent advances in high-throughput methods for identifying antibodies with desirable properties have shown great promise in rational antibody design and prediction of drug-like behaviors, but outstanding challenges remain in fully realizing their potential to minimize development times and improve success rates in the clinic.

MABS (2021)

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Structure-based charge calculations for predicting isoelectric point, viscosity, clearance, and profiling antibody therapeutics

Nels Thorsteinson et al.

Summary: This study evaluates structure-based charge descriptors for their predictive performance on antibody pI, viscosity, and clearance data. Four rules for therapeutic antibody profiling were devised to address development issues related to hydrophobicity and charged-based solution behavior. Discussions on strategy differences for optimizing solution behavior of human IgG1 antibodies versus IgG2 and IgG4 isotypes and the impact of pH alterations in formulation are also provided.

MABS (2021)

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Backgrounded Membrane Imaging (BMI) for High-Throughput Characterization of Subvisible Particles During Biopharmaceutical Drug Product Development

Constanze Helbig et al.

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Phase-Appropriate Application of Analytical Methods to Monitor Subvisible Particles Across the Biotherapeutic Drug Product Life Cycle

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Accelerated Aggregation Studies of Monoclonal Antibodies: Considerations for Storage Stability

Ruben Waelchli et al.

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Taking Subvisible Particle Quantitation to the Limit: Uncertainties and Statistical Challenges With Ophthalmic Products for Intravitreal Injection

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Advancing Therapeutic Protein Discovery and Development through Comprehensive Computational and Biophysical Characterization

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A Nanoparticle-Based Assay To Evaluate Surface-Induced Antibody Instability

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MOLECULAR PHARMACEUTICS (2020)

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An in vivo platform to select and evolve aggregation-resistant proteins

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Modulated Scanning Fluorimetry Can Quickly Assess Thermal Protein Unfolding Reversibility in Microvolume Samples

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Physicochemical Rules for Identifying Monoclonal Antibodies with Drug-like Specificity

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Developing therapeutic monoclonal antibodies at pandemic pace

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A single molecular descriptor to predict solution behavior of therapeutic antibodies

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Formulations That Suppress Aggregation During Long-Term Storage of a Bispecific Antibody are Characterized by High Refoldability and Colloidal Stability

Hristo L. Svilenov et al.

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Potently neutralizing and protective human antibodies against SARS-CoV-2

Seth J. Zost et al.

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Rational design of a conformation-specific antibody for the quantification of Aβ oligomers

Francesco A. Aprile et al.

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Toward Drug-Like Multispecific Antibodies by Design

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Format chain exchange (FORCE) for high-throughput generation of bispecific antibodies in combinatorial binder-format matrices

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Structure, Function, and Therapeutic Use of IgM Antibodies

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Phage display derived therapeutic antibodies have enriched aliphatic content: Insights for developability issues

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A comprehensive search of functional sequence space using large mammalian display libraries created by gene editing

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Deamidation and isomerization liability analysis of 131 clinical-stage antibodies

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