Antibody drugs have been remarkably successful in recent decades with more than 150 approved, providing major benefits to patients across multiple different disease areas. Looking to the future, artificial intelligence (AI) has the potential, albeit largely unrealized, to transform antibody discovery and optimization. This meeting will explore progress and challenges in the application of AI to the design of antibody drugs including immunogenicity risk assessment and mitigation. Additional goals of this meeting include: i) identifying opportunities and challenges with emerging antibody-based modalities, ii) exploring the therapeutic potential of antibody-conjugates with novel payloads including oligonucleotides, iii) evaluating conditional activation of antibodies for example to improve therapeutic index for cancer, iv) harnessing the immune system more optimally with bispecific and multispecific antibodies as well as through and engineered effector functions. We anticipate that the meeting attendees will span a broad range of different disciplines that impact antibody drugs including basic, translational and medical sciences. Participants are expected to gain a deeper understanding of some of the key emerging areas with antibody drugs. Our hope is that we can help the community to identify and begin to tackle some of the most critical challenges with antibody drugs. Fostering innovation can only bring even greater benefits to patients in the future with antibody-based drugs.