ReviewAntibody therapeutics2023
Developability assessment at early-stage discovery to enable development of antibody-derived therapeutics.
Review in Antibody therapeutics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers.
What it found
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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
46 citing papers in PubMed, 56 citations in OpenAlex.
- Article
- Multidimensional maturation of antibody variable domains with machine-learning assistance.mAbs · 2026Article
- Predicting non-specific binding of VHHs using machine learning models with cluster-aware validation.mAbs · 2026Article
- Review
- Article
- 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
- Advances and Future Directions in Antibody-Drug Conjugates: From Paradigm Shifts to Data-Driven Design.Cancers · 2026Review
- Mechanistic insight into the oxidative degradation of monoclonal antibodies: relevance to developability and the design of stable pharmaceutical formulations.Biochemical Society transactions · 2026Review
- Analytical Development and Testing Strategy of Antibody-Drug Conjugates.AAPS PharmSciTech · 2026Review
- Developability Evaluation of Single-Domain Antibody-Chelator Conjugates for Diagnostic Radiotracers.Antibodies (Basel, Switzerland) · 2026Article
- Disulphide and sequence-encoded conformational priors guide nanobody structure prediction.bioRxiv : the preprint server for biology · 2026Article
- De novo protein design: a transformative frontier in clinical protein applications.Journal of translational medicine · 2026Review
- Characterising nanobody developability to improve therapeutic design using the Therapeutic Nanobody Profiler.Communications biology · 2026Article
- Discovering Novel Therapeutic VbioRxiv : the preprint server for biology · 2026Article
- A droplet microfluidics-based platform for generating target-specific, natively-paired immune libraries and identifying potent and developable antibodies.Scientific reports · 2026Article
- Discovering novel therapeutic VFrontiers in immunology · 2026Article
- Artificial intelligence advancements in monoclonal antibody development technology.Frontiers in immunology · 2026Review
- Comparative Analysis of Glycan Composition in Therapeutic Antibodies via Glycan Profiling and Intact Mass Analysis.Molecules (Basel, Switzerland) · 2025Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Developability refers to the likelihood that an antibody candidate will become a manufacturable, safe and efficacious drug. Although the safety and efficacy of a drug candidate will be well considered by sponsors and regulatory agencies, developability in the narrow sense can be defined as the likelihood that an antibody candidate will go smoothly through the chemistry, manufacturing and control (CMC) process at a reasonable cost and within a reasonable timeline. Developability in this sense is the focus of this review. To lower the risk that an antibody candidate with poor developability will move to the CMC stage, the candidate's developability-related properties should be screened, assessed and optimized as early as possible. Assessment of developability at the early discovery stage should be performed in a rapid and high-throughput manner while consuming small amounts of testing materials. In addition to monoclonal antibodies, bispecific antibodies, multispecific antibodies and antibody-drug conjugates, as the derivatives of monoclonal antibodies, should also be assessed for developability. Moreover, we propose that the criterion of developability is relative: expected clinical indication, and the dosage and administration route of the antibody could affect this criterion. We also recommend a general screening process during the early discovery stage of antibody-derived therapeutics. With the advance of artificial intelligence-aided prediction of protein structures and features, computational tools can be used to predict, screen and optimize the developability of antibody candidates and greatly reduce the risk of moving a suboptimal candidate to the development stage.
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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.