Webinar

Library to Lead: Rapid In-Lab Sequencing Technologies for Expanding Antibody Discovery

In this joint webinar, experts from Illumina, Twist Bioscience, and ENPICOM will explore an end-to-end workflow for accelerating scFv discovery, from sequencing to synthetic library design to AI-driven analysis.

Together, these technologies form a unified discovery workflow that accelerates timelines and improves downstream outcomes across antibody engineering programs.

Discussion topics

  • Illumina’s first-ever longer-read kit, the MiSeq™ i100 kit (25M, 1000 cycles), brings high-quality sequencing of variable regions and full scFv constructs to its most accessible platform, addressing long-standing challenges in AIRR-seq workflows.
  • Using long-read sequencing for full-length VH/VL characterization enables finer enrichment analysis, improved clustering, accurate germline pairing, and faster identification of promising clones — richer clonal resolution that supports more confident selection and rapid advancement of antibody discovery programs.
  • Computational pipelines accelerate scFv analysis, from sequence curation and clustering to generative models that propose novel variants and integrate directly with sequencing outputs.

Speakers

Kavita Shah

Kavita Shah

Sr. Staff Product Manager, Illumina

Robin Bombardi

Robin Bombardi

Sr. Staff Scientist, Illumina

Max Stefan

Max Stefan

Director, Antibody Engineering, Twist Bioscience

Piotr van Rijssel

Piotr van Rijssel

Director Business Development & Strategic Partnerships, ENPICOM

Relevant resources

White paper

AI in biologics discovery and engineering: A practical guide to driving adoption

Discover how AI can transform biologics discovery and overcome challenges like fragmented workflows, infrastructure limitations, and underutilized models.

Press release

ENPICOM joins the Pistoia Alliance

Membership deepens ENPICOM’s commitment to advancing AI and autonomous agent infrastructure for life sciences R&D.

Panel discussion

An honest conversation about what it takes to make ML work in biotherapeutics

Experts from Sanofi, Eli Lilly, Amgen, AbbVie, and Genmab share real-world lessons from adopting AI/ML in biologics discovery and engineering.