Ophthalmology faces a persistent challenge: what works in animals often fails in humans. As delivery technologies grow more complex and regulatory expectations tighten, the gap between preclinical success and clinical relevance is widening. Especially in drug-device combinations, anatomical mismatch and data inconsistency are delaying or derailing promising innovations.

• Where should we be selecting larger, more appropriate models for ocular implants and injectables, and where do small animals still offer value for early screening?
• How are companies navigating the limitations of conventional models when testing delivery systems and what do regulators actually expect for safety and efficacy data?
• Why is there a lack of transparency and shared learning across early-stage studies and how industry leaders are beginning to bridge the gap?