Sweet-Jones, James;
(2025)
Computational Developability Triaging of Antibody Libraries for Discovery of New Therapeutics.
Doctoral thesis (Ph.D), UCL (University College London).
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Abstract
Therapeutic monoclonal antibodies (mAbs) are a successful class of biologics in the treatment of cancers, autoimmune diseases and others. However since the first antibody treatments were developed in 1986, only about 144 mAbs have gained clinical approval from regulatory bodies at the time of writing. A contributing factor to this is that their discovery pipelines and clinical trials can be subject to late-stage failures due to developability issues, which, in brief are a mAb’s intrinsic ability to be produced at scale and tolerated by the patient. Concurrently, libraries of paired heavy and light chain antibody sequences have been collected from next generation sequencing of human, or genetically engineered mice, repertoires. This thesis hypothesises that by using antibody language models, the developability features of clinically approved mAbs and library antibodies can be compared and used to screen library antibodies for new therapeutics. As a result, a triaging pipeline has been constructed where a library of antibody sequences are input, and undergo the following processes: physiochemical feature triaging based on sequence statistics; unsupervised learning to identify antibodies with similar features to clinical mAbs; prediction of physiochemical properties using linear models and supervised learning to predict which would pass clinical trials, and which are therefore good candidates for new therapeutics. This pipeline hopes to improve the chances of a given mAb to reach the clinic through identifying candidates with good developability profiles early in the selection process. Furthermore this thesis has worked to develop upon antibody annotation languages where a graphical drawing program for multispecific antibodies was written in order to encourage their development and improve the consistency of cataloguing their formats. This work has already been employed by the World Health Organisation International Non-proprietary Names Committee and is applied to new and historic applicants to clinical trials.
| Type: | Thesis (Doctoral) |
|---|---|
| Qualification: | Ph.D |
| Title: | Computational Developability Triaging of Antibody Libraries for Discovery of New Therapeutics |
| Open access status: | An open access version is available from UCL Discovery |
| Language: | English |
| Additional information: | Copyright © The Author 2025. Original content in this thesis is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) Licence (https://creativecommons.org/licenses/by-nc/4.0/). Any third-party copyright material present remains the property of its respective owner(s) and is licensed under its existing terms. Access may initially be restricted at the author’s request. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Div of Biosciences |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10202962 |
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