Enpicom, a bioinformatics software company, has announced the upcoming expansion of the capabilities of the IGX platform to unlock seamless analysis of antibody panning data. This development will allow researchers to analyse antibody display data in an intuitive and visual way, easily perform multi-dataset comparisons, and identify a diverse set of enriched candidates with the best characteristics.
“Our customer-centric approach to product development gives us a close-up view of the complex analysis workflows required for antibody display screening and how a single, scalable tool can immensely improve speed of analysis and quality of the selected candidates," said Jos Lunenberg, co-founder and CEO. "Due to limited, inefficient workflows researchers often have to discard the vast majority of the available NGS data and focus on a small pool of the most frequent clones. We are launching the new IGX-Track app so that our customers can look beyond the tip of the iceberg and make informed decisions with a complete view of their data. Custom analysis workflows and visualisations can be created with a few clicks so scientists can simply select better antibodies faster."
Enabling streamlined enrichment analysis
Display technologies empower antibody discovery by screening millions of candidates against potential targets. By including different panning round conditions and a variety of antigens, researchers can obtain a robust candidate pool with diverse binding profiles. However, complex analysis workflows – including operations like intersecting, joining, or subtracting datasets – that match the panning campaign design are needed to fully take advantage of the powerful combination of NGS and display screening.
The new IGX-Track app extends the antibody discovery capabilities of the IGX Platform and provides a fast, flexible way to discover a diverse set of enriched candidates with the best characteristics. Scientists can effortlessly compose enrichment analysis workflows that match the design of their panning campaigns and discover candidates that otherwise would have been overlooked.
