ArticlemAbs
Predicting Antibody Developability Profiles Through Early Stage Discovery Screening.
Article in mAbs. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 135 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
135 citing papers in PubMed.
- Article
- Article
- Article
- Predicting non-specific binding of VHHs using machine learning models with cluster-aware validation.mAbs · 2026Article
- Review
- Beyond affinity: AI-supported developability assessment and multi-objective optimization in antibody development.Antibody therapeutics · 2026Review
- Recombinant Antibody Vaccines for Targeted Antigen Delivery: Design Principles and Immunological Applications.Vaccines · 2026Review
- Aligning protein-generative models to experimental fitness with ProteinDPO.Nature methods · 2026Article
- Efficient generation of epitope-targeted antibodies with Germinal.Nature biotechnology · 2026Article
- Advanced biosensing strategies for high-risk foodborne pathogens: a comprehensive review ofFood chemistry. Molecular sciences · 2026Review
- Predicting Agitation Stability of Monoclonal Antibodies during Developability Assessment.Molecular pharmaceutics · 2026Article
- Mechanistic insight into the oxidative degradation of monoclonal antibodies: relevance to developability and the design of stable pharmaceutical formulations.Biochemical Society transactions · 2026Review
- Scaling antibody language models improves structure aware representation for antibody engineering.Communications biology · 2026Article
- Impact of Amino Acid Excipients on icIEF Method Development in Protein Therapeutics: A Formulation-Aware Analytical Framework.AAPS PharmSciTech · 2026Article
- A Moderate-Affinity Antibody-Drug Conjugate Targeting B7-H3 Exerts Potent Antitumor Efficacy.Pharmaceuticals (Basel, Switzerland) · 2026Article
- Phage Display Technology: Design, Library Construction, and Panning Strategies for Antibody Development.Biomolecules & therapeutics · 2026Review
- De novo protein design: a transformative frontier in clinical protein applications.Journal of translational medicine · 2026Review
- A droplet microfluidics-based platform for generating target-specific, natively-paired immune libraries and identifying potent and developable antibodies.Scientific reports · 2026Article
- Ultra-Dilute Developability Analysis of Antibody Self-Association and Non-Specific Binding.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Artificial intelligence advancements in monoclonal antibody development technology.Frontiers in immunology · 2026Review
75 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
22 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Monoclonal antibodies play an increasingly important role for the development of new drugs across multiple therapy areas. The term 'developability' encompasses the feasibility of molecules to successfully progress from discovery to development via evaluation of their physicochemical properties. These properties include the tendency for self-interaction and aggregation, thermal stability, colloidal stability, and optimization of their properties through sequence engineering. Selection of the best antibody molecule based on biological function, efficacy, safety, and developability allows for a streamlined and successful CMC phase. An efficient and practical high-throughput developability workflow (100 s-1,000 s of molecules) implemented during early antibody generation and screening is crucial to select the best lead candidates. This involves careful assessment of critical developability parameters, combined with binding affinity and biological properties evaluation using small amounts of purified material (<1 mg), as well as an efficient data management and database system. Herein, a panel of 152 various human or humanized monoclonal antibodies was analyzed in biophysical property assays. Correlations between assays for different sets of properties were established. We demonstrated in two case studies that physicochemical properties and key assay endpoints correlate with key downstream process parameters. The workflow allows the elimination of antibodies with suboptimal properties and a rank ordering of molecules for further evaluation early in the candidate selection process. This enables any further engineering for problematic sequence attributes without affecting program timelines.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.