How to Use DELPHI Antibody Developability Prediction
Commercially Available Online Web Server
Use DELPHI online to screen antibody PSR and SEC developability.
DELPHI is an antibody developability platform from the Institute for Protein Innovation. This workflow uses its released neural-network predictors to estimate the probability that paired antibodies pass PSR polyreactivity and SEC monomer-purity filters. It is useful for comparing candidates before experimental characterization.
How DELPHI Antibody Developability Prediction Works
Upload an Antibody Dataset CSV with BARCODE, HSEQ, LSEQ, and CDR3 columns. Use paired heavy and light variable domains and HCDR3 without the leading framework cysteine. Select PSR, SEC, or both. The default ABlang2 Transformer computes antibody language-model embeddings; other Transformer and CNN models are available under Advanced Options.
predictions.csv contains each antibody's pass probability, predicted PASS/FAIL class, and decision threshold. Classification uses the unrounded probability and the threshold stored in the released model; models without a stored threshold use 0.5. Display probabilities are rounded to three decimal places. summary.csv reports pass/fail counts and mean pass probability per assay. Treat these predictions as comparative screening signals and confirm promising candidates experimentally.
What is Neurosnap?
Neurosnap is the leading platform for bioinformatics and computational science focused on expanding access to powerful modeling and simulation tools. Because many state-of-the-art machine learning systems remain complex to install, configure, and scale, Neurosnap offers a clean, browser-based workspace that removes the burden of infrastructure management, dependency conflicts, and command-line tooling.
Built for biologists, chemists, and cross-disciplinary scientists, the platform enables advanced computational workflows without requiring expertise in software engineering or cloud architecture. Researchers can launch analyses through an intuitive interface, connect programmatically through a comprehensive API, and rely on automated resource management to scale workloads efficiently. By taking care of the underlying compute and operational complexity, Neurosnap allows teams to devote their energy to scientific progress and faster iteration. Security and data protection remain foundational principles, with clear safeguards outlined in our Terms of Use and Privacy Policy to ensure your work stays protected.
Advancing Discovery with DELPHI Antibody Developability Prediction on Neurosnap
Using DELPHI Antibody Developability Prediction on Neurosnap could drastically accelerate paired-antibody developability screening before experimental PSR and SEC assays.
- Two assay filters: Evaluate polyreactivity and monomer-purity predictions together.
- Paired-domain inputs: Score VH/VL candidates with explicit HCDR3.
- Released predictors: Compare Transformer and CNN model choices without training a new model.
- Batch screening: Export clear probabilities, classes, and assay summaries for candidate prioritization.
How to Use DELPHI Antibody Developability Prediction on Neurosnap
To harness the capabilities of DELPHI Antibody Developability Prediction, researchers can follow this streamlined workflow within Neurosnap:
- Access Neurosnap: Start by logging in to the Neurosnap website.
- Select Tool: From the list of available tools, choose DELPHI Antibody Developability Prediction.
- Provide Inputs: Provide all the inputs specified within the submission panel and optionally configure the tool as desired.
- Run Tool: Submit the DELPHI Antibody Developability Prediction job and Neurosnap will execute it in the cloud, automatically notifying you as soon as your results are ready.
- Review Output: Explore your results through rich visualizations, including figures, plots, and interactive views designed to help you analyze findings with clarity and confidence.
Citations
Please cite the original work when using DELPHI Antibody Developability Prediction in publications or research outputs.
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Institute for Protein Innovation. DELPHI: Deep End-to-end Learning Platform for antibody Developability with High Interpretability. https://github.com/proteininnovation/delphi. |
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Neurosnap Inc. (2022). Neurosnap: An online platform for computational biology and chemistry. Available at: https://neurosnap.ai/ |
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