BioPhi 2021 Publication

️❗️ For BioPhi application, see the BioPhi repository ❗️

This repository contains scripts, data and jupyter notebooks used to produce the evaluation results in the BioPhi 2021 publication:

David Prihoda, Jad Maamary, Andrew Waight, Veronica Juan, Laurence Fayadat-Dilman, Daniel Svozil & Danny A. Bitton (2022) BioPhi: A platform for antibody design, humanization, and humanness evaluation based on natural antibody repertoires and deep learning, mAbs, 14:1, DOI: https://doi.org/10.1080/19420862.2021.2020203

Data

All data files are found in data.

See more about each evaluation task in data/tasks:

• OASis: humanness evaluation using IMGT/mAb-DB
• OASis: humanness evaluation using immunogenicity data
• Sapiens: humanization evaluation using Hu-mAb 25 pairs
• Sapiens: humanization evaluation using rediscovery of 152 therapeutics
• Sapiens: attention analysis
• Sapiens: training scripts available on request ([email protected])
  • The trained model is available in the Sapiens repository or through BioPhi

This data is processed and visualized using the provided notebooks.

Notebooks

Final evaluation notebooks are found in notebooks/reports.

Data processing is done using notebooks found in notebooks/processing and using the provided Makefile.

Run the notebooks in your browser using Binder:

Reproducing

Install the conda environment using the provided environment.yml file or simply using:

make condaenv

Data processing steps are defined in the Makefile and in the processing notebooks.

Acknowledgements

IMGT/GENE-DB: Giudicelli, V., Chaume, D., & Lefranc, M. P. (2005). IMGT/GENE-DB: A comprehensive database for human and mouse immunoglobulin and T cell receptor genes. Nucleic Acids Research, 33(DATABASE ISS.), D256–D261. https://doi.org/10.1093/nar/gki010

IMGT/mAb-DB: Poiron C., Wu Y., Ginestoux C., Ehrenmann F., Duroux P., L. M.-P. (2010). IMGT/mAb-DB: the IMGT®database for therapeutic monoclonal antibodies. Journées Ouvertes de Biologie, Informatique et Mathématiques (JOBIM), Montpellier, 11. Retrieved from http://www.imgt.org/mAb-DB/

Thera-SAbDab: Raybould, M. I. J., Marks, C., Lewis, A. P., Shi, J., Bujotzek, A., Taddese, B., & Deane, C. M. (2019). Thera-SAbDab: the Therapeutic Structural Antibody Database. Nucleic Acids Research, 48, 383–388. https://doi.org/10.1093/nar/gkz827

Observed Antibody Space: Kovaltsuk, A., Leem, J., Kelm, S., Snowden, J., Deane, C. M., & Krawczyk, K. (2018). Observed Antibody Space: A Resource for Data Mining Next-Generation Sequencing of Antibody Repertoires. The Journal of Immunology, 201(8), 2502–2509. https://doi.org/10.4049/jimmunol.1800708

Hu-mAb: Chin, M., Marks, C., & Deane, C. M. (2021). Humanization of antibodies using a machine learning approach on large-scale repertoire data. BioRxiv, 2021.01.08.425894. https://doi.org/10.1101/2021.01.08.425894

MG Score: Clavero-Álvarez, A., Di Mambro, T., Perez-Gaviro, S., Magnani, M., & Bruscolini, P. (2018). Humanization of Antibodies using a Statistical Inference Approach. Scientific Reports, 8(1), 1–11. https://doi.org/10.1038/s41598-018-32986-y