Virtual Clinical Trial Using A 3D Virtual Eye Simulation Analyzer To Predict Effectiveness Of Laser Scleral Microporation For Progressive Presbyopia

To evaluate predictive power in a blind virtual clinical trial (VCT). A Proprietary 3D Finite Element Model – Virtual Eye Simulation Analyzer (VESA) – was used to predict outcomes from previously reported human clinical data of presbyopic patients treated with Laser Scleral Microporation (LSM) therapy.

AceVision Group, Silver Lake, OH

We conducted a VCT in a virtual ecosystem using artificial intelligence (AI) and deep machine learning. We recreated in silico virtual human eyes with age and patient-Human clinical data of 26 eyes of 13 subjects ages 52-58 yrs old were recreated in silico to validate the predictive power of a Virtual Simulation Eye Analyzer proprietary model. Results of VESA simulations for Change in DCNVA  in silico after LSM procedure were analyzed. VESA engineers and study coordinators were blind to the results. A novel conversion formula was utilized logMar for computational comparison.

Diopter conversion to LogMar was calculated using a proprietary Ray tracing statistical method. Inclusion criteria for LSM subjects was preop DCNVA of 0.4 LogMar or worse. VESA was calibrated to the subjects’ pre LSM DCNVA. VESA predicted in silico outcomes of DCNVA of a change rom 0.4 LogMar to  0.27 (OD) and 0.4 LogMar to 0.30 (OS).Actual Human clinical results showed changes from 0.4 LogMar to 0.20(OD); and 0.4 LogMar to 0.17(OS). The prediction for OD was not significantly different from the clinical values (P=0.08), small differences were noted  for OS (P<0.001).VESA further demonstrated visualization of age-related biomechanical changes contributing to the loss of central optical power (COP).

VESA was able to predict Pre LSM baseline DCNVA and showed statistically significant prediction of DCNVA post LSM. -a priori in in virtual reality when compared to actual human clinical data.  VCT’s offer the opportunity to quantify problems, test assumptions, increase predictability, improve decision-making, and  will likely play a larger role in the development of improved treatment solutions.