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Benchling for Antibody Therapeutics R&D

Track immunogenicity, model novel antibody workflows, integrate next-gen screening and discovery tools, and access advanced analytics to hit development milestones faster.

Antibody R&D is now more streamlined than ever, but several factors continue to contribute to its complexity.

This paper outlines the critical needs and complexities faced during both research and development phases, and how Benchling has helped address these challenges for leading antibody companies.
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Antibody Therapeutics Research

  • Improve immunogenicity profile of antibody lead candidates

    • Seamlessly integrate in-silico, in-vitro, and in-vivo screening
    • Establish feedback loop for antibody candidate optimization
    • Continuously improve in-silico predictive methods with access to more results
  • Handle multiple types of novel antibodies

    • Design and analyze all types of antibodies
    • Create customized antibody definitions with sequence-level intelligence
    • Share data and insights across antibody formats and programs
  • Integrate next-gen approaches to antibody screening and discovery workflows

    • Leverage the full power of cutting edge mol bio tools
    • Embed deep sequencing, CRISPR editing, and other technologies into existing workflows
    • Flexibly scale and adapt to rapidly changing research needs

Agenus: Building a global informatics infrastructure

Learn how Benchling replaced Agenus's multiple informatics systems with a single platform across discovery, screening, and characterization.

Antibody Therapeutics Development

  • Perform developability risk assessment early

    • Identify developability liabilities and critical quality attributes of antibodies
    • Design and execute experiments to thoroughly assess antibody liabilities
    • Generate actionable insights to mitigate potential developability risks
  • Leverage advanced analytics to manage large-scale equipment

    • Unify upstream and downstream production operations
    • Integrate large-scale equipments with PAT tools
    • Optimize bioprocessing with real-time insights
  • Seamlessly support DOE functionality in antibody process development

    • Identify critical quality attributes for antibodies
    • Model and execute DOE studies to understand CQA and process parameter relationships
    • Define production process design space

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