Platform

Objective measurement of subretinal delivery performance

Our AI-assisted platform converts routine surgical video into quantitative measures of instrument behavior during the critical delivery step.

What we measure

Precision

How steady and controlled the cannula or instrument tip remains during subretinal delivery.

Smoothness

How fluid the motion is, rather than abrupt, jerky, or corrective.

Instability

Abrupt or outlier motion events that may reflect loss of fine control.

Tremor

Oscillatory motion that may affect controlled cannula positioning or delivery.

Supporting measures

Correction burden

Small recovery or repositioning movements.

What these measurements can be compared with

DexteraAI measurements can be analyzed against sponsor-defined procedural and clinical outcomes, including reflux, retinotomy behavior, bleb behavior, delivery success, procedure-related adverse events, OCT structural changes, visual outcomes, durability, and rescue-treatment burden.

Use Cases

How DexteraAI is applied across the trial lifecycle

Four applications spanning pre-pivotal analysis through post-market surgeon quality assurance.

Before pivotal

Retrospective Phase 1/2 or Phase 2 analysis

Evaluate whether delivery-performance metrics are associated with sponsor-defined procedural, safety, imaging, or clinical endpoints.

During pivotal

Prospective surgeon/site consistency monitoring

Track whether technical-performance profiles remain stable across surgeons, sites, cases, and time.

After pivotal

Interpretation of heterogeneous outcomes

Assess whether surgical technical variability may have contributed to efficacy, safety, or durability variability.

Launch

Surgeon training and quality assurance

Support objective, video-derived feedback for surgeon onboarding, credentialing, retraining, and post-market monitoring.

Patent-pending AI-enabled surgical video analytics for subretinal therapeutic trials.