Breakthrough Clinical Results
Avant Technologies and its JV partner, Ainnova, announced the completion of a pre-submission meeting with the U.S. FDA regarding Ainnova's Vision AI platform for early diabetic retinopathy detection. The meeting provided valuable guidance on the clinical trial protocol, including clinic selection, retinologist requirements, and data collection. The FDA's feedback will inform the cost planning for the clinical trial, whose data will support a 510(k) submission for market clearance in the U.S. This is a significant step towards validating the platform and launching the accompanying automated retinal camera in the U.S. market.
Key Highlights
- Successful pre-submission meeting with the FDA for Ainnova's Vision AI platform.
- FDA provided guidance on the clinical trial protocol for diabetic retinopathy detection.
- Data from the U.S.-based clinical trial will support a 510(k) submission.
- The automated retinal camera is expected to improve accessibility and speed of diabetic retinopathy screenings.
Economic Burden
Economic Burden of Treating Diabetic Retinopathy in USA and Europe
United States Economic Burden
The economic burden of treating diabetic retinopathy (DR) is substantial in the USA. For the diabetic macular edema (DME) cohort (1.1 million people), the total direct benefit of treatment was $63.0 billion over 20 years, with an additional total indirect benefit of $4.8 billion. The net value (benefit minus cost) of treatment ranged from $28.1 billion to $52.8 billion.
Treatment provides significant economic value through improved vision, life expectancy, and quality of life. A treated individual with DME would experience 4-5% greater life expectancy and 9-13% more quality-adjusted life-years. Indirect benefits included 6-9% more years working, 12-19% greater lifetime earnings, and 8-16% fewer years with disability.
When comparing different treatment modalities for DME where results are equivalent, opting for less-expensive treatment options could yield cost savings of 40% to 88%.
Patient financial considerations significantly impact treatment decisions. A 2020 study found that having a copay (vs. $0) lowered the odds of receiving any treatment (odds ratio = 0.60). Copays reduced odds of receiving specific treatments: anti-VEGF treatment (OR = 0.72), bevacizumab (OR = 0.73), ranibizumab or aflibercept (OR = 0.70), and focal laser (OR = 0.44).
European Economic Burden
In the Netherlands, for people with type 1 diabetes using automated insulin delivery (AID) systems, the incremental cost-utility ratio was EUR 29,836 per QALY gained from a societal perspective. AID systems were associated with an incremental combined cost of EUR 28,635 due to higher acquisition costs, partially offset by reduced direct treatment costs for diabetes-related complications and reduced indirect costs due to less time off work.
In Cameroon, the average total expenditure for argon laser treatment of diabetic retinopathy was 86,002±67,197 f CFA per eye (approximately 131±102 euros), with transportation costs significantly contributing to the overall expense.
Global Context
Annual healthcare expenditures for diabetes treatment and complications prevention cost 727 billion USD globally in 2017, though this figure includes all diabetes complications, not just retinopathy.
Cost-Effective Approaches
Telemedicine approaches like the Joslin Vision Network can be both less costly and more effective than traditional clinic-based ophthalmoscopy for detecting proliferative diabetic retinopathy in many scenarios.
Continuous glucose monitoring (CGM) acquisition is associated with significant reductions in emergency department visits and all-cause hospitalizations among people with type 2 diabetes, which can lead to substantial cost savings.
A 2021 economic evaluation assessed cost-effectiveness of AI diabetic retinopathy screening vs. standard screening by eye care professionals (ECP) for children with diabetes. The base case scenario with 20% adherence estimated that autonomous AI would result in higher mean patient payment ($8.52 for T1D and $10.85 for T2D) than conventional ECP screening ($7.91 for T1D and $8.20 for T2D). However, autonomous AI screening became the preferred strategy when at least 23% of patients adhered to diabetic retinopathy screening.
Drug used in other indications
Vision AI Platforms Beyond Diabetic Retinopathy
The Comprehensive AI Retinal Expert (CARE) system has been evaluated for multiple retinal diseases beyond diabetic retinopathy, demonstrating promising results across various ophthalmologic conditions.
Other Indications Being Trialed
Vision AI platforms are being investigated for several conditions including:
- Age-related macular degeneration (AMD) with 89.50% sensitivity and 98.33% specificity
- Suspected glaucoma showing 91.55% sensitivity and 97.40% specificity
- Pathological myopia achieving 90.77% sensitivity and 99.10% specificity
- Retinal vein occlusion (RVO) with 81.58% sensitivity and 99.49% specificity
- Retinal detachment demonstrating 88.64% sensitivity and 99.18% specificity
- Macular hole with 83.33% sensitivity and 99.80% specificity
- Epiretinal membrane showing 82.26% sensitivity and 99.23% specificity
- Hypertensive retinopathy achieving 94.55% sensitivity and 97.82% specificity
- Myelinated fibers with 83.33% sensitivity and 99.74% specificity
- Retinitis pigmentosa demonstrating 75.00% sensitivity and 99.95% specificity
Additionally, research has shown AI applications for retinopathy of prematurity (ROP) and sickle cell retinopathy (SCR).
Intervention Models
The intervention models for these trials include:
- Disease screening and monitoring for recurrence across multiple conditions
- Quantitative analysis of treatment outcomes for conditions including AMD and retinal vascular diseases
- Prediction of treatment response for various retinal conditions
- Rapid and quantitative interpretation of retinal biomarkers observed on OCT and OCTA imaging
- Planning and performing robotic surgery as suggested by research articles
- Initial diagnostic efforts particularly beneficial in grassroots and community healthcare settings
- Enhanced tiered ophthalmic care systems where AI serves as a first-line screening tool
In the Rwanda study (2021), the AI system was designed to detect optic nerve and macular anomalies outside of diabetic retinopathy. The system considered referable cases where a vertical cup to disc ratio of 0.7 and higher and/or macular anomalies were recognized at a cut-off of 60% or higher.
Of participants referred by AI in this study, 32.0% were for diabetic retinopathy only, 39.6% for diabetic retinopathy and an anomaly, 23.6% for an anomaly only, and 4.73% for other reasons, demonstrating the AI's capability to identify multiple conditions simultaneously.
These Vision AI platforms are particularly valuable in enhancing the efficacy of tiered ophthalmic care by facilitating initial diagnostic efforts in resource-limited settings.