For the past seven years, the Computational Drug Development (CDD) for Biologics Summit has united computational and structural biologists, together with protein and antibody engineers, to bring to the fore emerging computational programs and models with the long-term goal of revolutionizing biologics drug discovery and development.

Following large language models like ChatGPT gaining huge traction across all industries, deep learning natural language models for protein sequence processing becoming more transformative, and next-generation deep learning methods being developed, the community is energized to innovate.

As the industry progresses rapidly, the need for more clarity on best practice, and a medium to explore the latest and greatest in new computational method also increases.


The 8th annual event will return to Boston in 2023 to continue to help drug developers of all sizes further their novel biotherapeutics discovery and development. Diving into the latest innovations in the industry, this year’s summit will highlight methods and best-practices to extrapolate data & leverage deep learning for novel, complex biologics pipeline progression.

With fresh new content covering computational and structural biology, together with protein and antibody engineering, here’s what’s exciting this year:

  • Case studies: Delve into expert case studies that leverage AI/ML to extrapolate complex data for in silico discovery & development through to predicting biotherapeutic pharmacology and downstream developability
  • Gain high-level insights into different modalities: Explore strategies to overcome data shortages in bi-specifics discovery, and unravel safety predictions in antibodies
  • Networking: You will have the unique opportunity to exchange challenges, inspire solutions with leading industry experts across dedicated speed-networking sessions as well as assess the latest technologies over the last 12 months
  • Novel topics: Deep dive into brand-new insights covering improving de novo antibody design to optimizing clinical candidate selection by working to reduce costs, save time and ensure translatability into humans
  • Form meaningful partnerships: Meet and network with selected CROs, model developers and academics to hear their latest platforms that will optimize your workflows
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