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Repertoire Analysis

deepCDR's immune repertoire analysis suite provides a combination of statistical and machine learning-powered tools for the identification of patterns in major repertoire features.

Our in-depth analysis provides novel insights into large-scale datasets based on methods developed by our team of experts with years' worth of experience in immune repertoire analysis. deepCDR's expertise in this field is applied throughout its discovery and optimization workflows and is also available directly to clients. Partners profit from detailed reports providing multi-dimensional analysis leading to efficient extraction of novel lead candidates of interest



deepCDR uses its proprietary Deep Learning and Deep Sequencing workflow to extensively and rapidly mine antibody repertoires in order to deliver highly specific antibody leads with improved binding characteristics, manufacturability properties, and an increased probability of clinical success.

Our lead time is significantly accelerated by our proprietary mammalian display method, allowing us to deliver a diverse panel of candidate antibodies within 3 month.

Our Partner's targets are screened against 1'000'000'000 possible genetic variants, and can be titrated down to only
100 antibody sequences against requirements of affinity, specificity, and manufacturability. We aim to beat the industry standard lead time by half, delivering sequence data within 3 months.



deepCDR Biologics combines mammalian display technology with advances in machine learning to move beyond experimental screening and search the entirety of the functional sequence space.

Our in silico and in vitro engineering and optimization services enable us to search billions of potential candidates. This exhaustive search results in optimized lead antibodies that have enhanced biophysical properties and affinities for their target antigen, giving our clients increased confidence with the molecules they bring forward into preclinical and clinical studies. Candidate antibodies for deepCDR optimization can either come from the deepCDR discovery process or be provided directly by the client.

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