ArticleCommunications biology2026
Characterising nanobody developability to improve therapeutic design using the Therapeutic Nanobody Profiler.
Article in Communications biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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.
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Who cites it
7 citing papers in PubMed.
- Beyond affinity: AI-supported developability assessment and multi-objective optimization in antibody development.Antibody therapeutics · 2026Review
- Nanobodies Open New Avenues in Cancer Treatment: From Molecular Engineering to Therapeutic Platforms.Cell biochemistry and biophysics · 2026Review
- Efficient generation of epitope-targeted antibodies with Germinal.Nature biotechnology · 2026Article
- 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
- Review
- Efficient generation of epitope-targetedbioRxiv : the preprint server for biology · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Developability optimisation is an important step for successful biotherapeutic design. For monoclonal antibodies, developability is relatively well characterised. However, progress for novel biotherapeutics such as nanobodies is more limited. Differences in structural features between antibodies and nanobodies render current antibody computational methods unsuitable for direct application to nanobodies. Following the principles of the Therapeutic Antibody Profiler (TAP), we have built the Therapeutic Nanobody Profiler (TNP), an open-source computational tool for characterising nanobody developability. Tailored specifically for nanobodies, it accounts for their unique properties compared to conventional antibodies for more efficient development of this novel therapeutic format. We calibrate TNP metrics using the 36 currently available sequences from clinical-stage nanobody-based drugs. We also collected experimental developability data for 108 nanobodies expressed as IgG constructs and examine how these results are related to the TNP guidelines. TNP is available as a web application at opig.stats.ox.ac.uk/webapps/tnp.
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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.