ENPICOM, a bioinformatics software company, announced at the Biologics UK conference new IGX Platform capabilities to accurately annotate exposed liabilities, perform structural modeling of antibodies at scale and determine developability profiles using customizable penalties. This major development allows researchers to improve their candidate selection by making accurate developability predictions for thousands of sequences at the same time, in a secure, intuitive environment.
“The spectacular progress in the field of antibody discovery calls for more powerful tools to effectively leverage all generated data. ENPICOM has tackled the challenge of candidate pool expansion with the launch of the Antibody Discovery Module earlier this year. The new liability analysis capabilities we are adding today will enable scientists to easily select better antibodies with even greater confidence”, said Jos Lunenberg, co-founder and CEO at ENPICOM.
From thousands of sequences to that needle-in-a-haystack antibody
Existing approaches to predict developability and identify sequence liabilities that are based on simple sequence analysis scale well in terms of the required computational resources, but do not provide sufficient accuracy, as they fail to consider the 3D structure of the antibody. Structural modeling, on the other hand, provides detailed insight into the surface exposure of unwanted motifs, leading to highly reliable liability predictions. Performing these predictions in a high-throughput manner is incredibly challenging and time-consuming, as it requires significant computational resources and specialized software infrastructure. ENPICOM solves these challenges by integrating SAbPred directly into the IGX Platform. SAbPred is developed by the Oxford Protein Informatics Group and is a validated, peer-reviewed, and globally recognized toolbox for accurate and efficient structural analysis of antibodies.
“The three main challenges in the analysis of liabilities we aim to address are accuracy, throughput and ease of use,” said Dr Nicola Bonzanni, co-founder and chief product officer at ENPICOM. “The IGX Platform enables researchers to fully utilize the added value of NGS data. You can accurately predict exposed liabilities for thousands of sequences at once, easily assess the developability of candidates and proceed with your selection with confidence.”
The new IGX-Annotate App enables scientists to accurately predict exposed liabilities, configure custom liability penalties and integrate developability information throughout their entire workflow. In addition, researchers can now better gauge antibody developability by comparing characteristics of newly discovered antibody candidates to those already brought to the market.
The new Select page provides a flexible environment to compare and rank the most promising antibody candidates based on user-defined characteristics. It brings antibody sequences, experimental metadata and in silico predictions together into one comprehensive overview, making it easy to select the best candidates to express in the lab or move further down the development pipeline.
Scientists using the IGX Platform can now:
- Use a validated tool to independently perform structural modeling analysis and accurately annotate liabilities.
- Increase candidate success by flagging exposed liabilities early in the discovery phase and identify antibodies with the best developability properties.
- Annotate structural liabilities for thousands of sequences and integrate the developability information throughout their entire workflow.
- Configure their own liability penalties through an intuitive UI to compute scores that align with their de-risking strategy.
- Benchmark candidate developability profiles against a database of clinically validated antibodies.
- Overlay developability characteristics on information-rich visualizations like phylogenetic trees to prioritize and select the best candidates.
The IGX Platform and the Antibody Discovery Module provide an end-to-end cloud solution that enables researchers to easily perform complicated tasks such as clustering, phylogeny and prediction of exposed liabilities in a secure and scalable environment. With the addition of these new tools, researchers can now expand their candidate pool and improve their antibody selection.
To learn more about performing accurate liability predictions and de-risking antibody development with the IGX Platform, join the free webinar on September 28, 2021.
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