
- Antibody sequence analysis how to#
- Antibody sequence analysis install#
- Antibody sequence analysis software#
- Antibody sequence analysis trial#
Antibody sequence analysis trial#
We also offer support analytics to help you to demonstrate consistency or comparability of manufactured batches or as release tests for clinical trial materials or on-going GMP batch release tests. These analytics can be tailored to address your specific needs throughout development and the production and product lifecycle with a focus on monitoring relevant critical quality attributes (CQAs), to demonstrate that process changes do not impact physicochemical properties and structure, the presence of product-related impurities or process-related impurities. Monographs) to design strategic packages pertinent to your need and phase of development from preclinical-phase characterization studies through to Good Manufacturing Practice (cGMP) manufacture and beyond. With our high level of expertise in antibody and mAb analysis and characterization, we apply our experience, industry, and regulatory knowledge (in particular EMA and ICH guidelines, Ph. "ASAP-SML: An antibody sequence analysis pipeline using statistical testing and machine learning." PLoS computational biology 16.4 (2020): e1007779.Expert support services in the analysis and characterization of antibodies and mAbs
Antibody sequence analysis software#
This software is written by Xinmeng Li, James Van Deventer, Soha Hassoun ( "ASAP-SML: An Antibody Sequence Analysis Pipeline Using Statistical Testing and Machine Learning" Reference set is from the Protein Data Bank (PDB) and it consists of human and murine antibody sequences that do not bind or inhibit MMPs. MMP-targeting set is composed of publicly available antibody sequence data. ASAP/DesignRecommendation.py - functions to generate design recommendation trees for specific targeting antibody sequences.ĭata to run ASAP: BLOSUM-62 substitution matrix and Canonical Structure Definitionĭata to run ASAP on MMP-targeting example: MMP-targeting and reference set. ASAP/SequenceAndFeatureAnalysis.py - functions for sequence and feature analysis on antibody sequences. ASAP/FeatureExtraction.py - functions for feature extraction on Chothia numbered antibody sequences. Or, run the whole notebook in a single step byĪSAP.ipynb : main script for running ASAP pipeline Once you have set the parameters, run the notebook document step-by-step (one cell a time) by Parameters are set based on the users choice. To run the script, open the terminal and go to the project directory, then run:
Antibody sequence analysis how to#
This repository contains an example of how to run the ASAP pipeline on the MMP-targeting and reference antibody sequence set. We recommend installing using Anaconda as follows:Ĭonda create -name asap -file enviroment.ymlĮxample: Matrix Metalloproteinases (MMP) targeting and reference antibody sequence set Jupyter notebook is required to run the ipynb examples.
Antibody sequence analysis install#
How to install Requirements:Īn Anaconda python environment is recommmended.Ĭheck the environment.yml file, but primarily: When applied to an MMP-targeting set, ASAP identifies salient features and recommends features to use when designing novel MPP-targeting antibody sequences. Machine-learning and statistical significance testing are applied to antibody sequences and feature fingerprints to identify distinguishing feature values and combinations thereof. The pipeline first extracts germline, CDR canonical structure, isoelectric point and frequent positional motifs features from sequences and creates an antibody feature fingerprint. ASAP-SML: An Antibody Sequence Analysis Pipeline Using Statistical Testing and Machine LearningĪntibody Sequence Analysis Pipeline Using Statistical Testing and Machine Learning (ASAP-SML) is a pipeline to identify distinguishing features in targeting antibody set when compared to a reference non-targeting set.
