Avant Technologies and Ainnova Tech Enhance Patient Recruitment for Diabetic Retinopathy AI Platform Clinical Trial

Analysis reveals significant industry trends and economic implications

Release Date

2025-08-13

Category

Clinical Trial Event

Reference

Source

Breakthrough Clinical Results

Avant Technologies and its joint venture partner, Ainnova Tech, announced an enhanced patient recruitment strategy for their Vision AI platform clinical trial. The trial, planned for 8-10 US clinical sites, will focus on recruiting approximately 1,000 multiethnic patients with diabetes from community clinics and primary care facilities. This approach aims to gather real-world data reflecting the diverse diabetic retinopathy population. Ainnova is collaborating with Fortrea, a CRO specializing in ophthalmology, to ensure a rigorous and inclusive study, supporting their FDA 510(k) submission. The success of this trial is crucial for marketing the Vision AI platform in the US market.

Key Highlights

  • Enhanced patient recruitment strategy for Vision AI platform clinical trial.
  • Targeting 1,000 multiethnic diabetic patients from community clinics.
  • Collaboration with Fortrea, a CRO specializing in ophthalmology.
  • Aims to support FDA 510(k) submission for Vision AI platform.

Incidence and Prevalence

Latest Estimates of Diabetic Retinopathy Prevalence and Incidence

Global Prevalence

According to recent data, diabetic retinopathy (DR) remains a significant public health concern with varying prevalence rates across different populations:

  • The estimated prevalence of diabetic retinopathy among US adults with diabetes aged 40 years and older was 28.5% (95% confidence interval [CI], 24.9%-32.5%)
  • Vision-threatening diabetic retinopathy had a prevalence of 4.4% (95% CI, 3.5%-5.7%) in this population
  • Based on 2022 data, the prevalence of diabetic retinopathy in patients with type 2 diabetes was 28.2% (371 participants out of 1316)
  • A 2016 Chinese study of 1,972 patients with type 2 diabetes found 819 patients had diabetic retinopathy
  • A 2010 screening study in the upper Rhine (France) found that among 1,050 diabetic patients, 18% had diabetic retinopathy, with 1.5% having proliferative or serious nonproliferative forms and 74.2% having mild nonproliferative forms

Demographic Variations

Gender differences: - DR was slightly more prevalent among men than women with diabetes (31.6% vs 25.7%; P = .04) - Male sex was independently associated with the presence of diabetic retinopathy (odds ratio [OR], 2.07; 95% CI, 1.39-3.10) - In an Iranian study, incidence was 96.1 (95% CI: 76.7, 118.0) in males and 86.6 (95% CI: 74.5, 99.9) in females per 1000 person-years

Ethnic differences: - Non-Hispanic black individuals had a higher crude prevalence than non-Hispanic white individuals of diabetic retinopathy (38.8% vs 26.4%; P = .01) - Vision-threatening diabetic retinopathy was also more prevalent in non-Hispanic blacks (9.3% vs 3.2%; P = .01) - A 2002 study found retinopathy prevalence was higher in black people (35.4%) than white (16.0%) - A 1999 study found retinopathy occurred more often among black than white participants (50% vs. 19%)

Incidence Data

  • In a 2007 study of Iranian non-insulin-dependent diabetic patients, diabetic retinopathy was found in almost half of the patients after a mean 5-year follow-up
  • The incidence of any retinopathy in this Iranian population was 89.4 (95% CI: 79.0, 101.0) per 1000 person-years based on 2786 person-years of follow-up
  • A 2005 study in Barbados found that the 9-year cumulative incidence of DR was higher in persons with longer diabetes duration

Risk Factors

Several factors increase the risk of developing diabetic retinopathy: - Higher hemoglobin A1c level (OR, 1.45; 95% CI, 1.20-1.75) - Longer duration of diabetes (OR, 1.06 per year duration; 95% CI, 1.03-1.10) - Insulin use (OR, 3.23; 95% CI, 1.99-5.26) - Higher systolic blood pressure (OR, 1.03 per mm Hg; 95% CI, 1.02-1.03)

Studies show that strict blood-glucose control reduces the progression of retinopathy better than standard control and leads to reduced oxidative tissue damage both systemically and locally in the eye, and reduced proliferative activity.

Economic Burden

Economic Burden of Treating Diabetic Retinopathy in USA and Europe

United States Economic Burden

Recent estimates reveal significant financial implications for diabetic retinopathy treatment in the United States. In 2022, if all patients with center-involved diabetic macular edema (CI-DME) and good baseline visual acuity received aflibercept initially, 10-year costs were projected to be $28.80 billion. Alternative management approaches showed potential cost reductions, with initial laser treatment estimated at $14.42 billion or initial observation (adding aflibercept only if visual acuity worsened) at $15.70 billion.

The broader context of diabetes care in the United States is also substantial, with diabetes treatment and complications prevention costing 727 billion USD globally in 2023, though this figure encompasses all diabetes-related care, not just retinopathy.

Historical data provides additional perspective on cost-effectiveness. A 1996 analysis indicated that screening and treatment of diabetic eye disease costs $3190 per quality-adjusted life-year (QALY) saved. The same study estimated potential savings exceeding $US600 million annually from proper detection and treatment of diabetic eye disease.

Insurance status significantly impacts both treatment costs and disease severity at presentation. A 2021 study found higher rates of proliferative diabetic retinopathy (DR) among uninsured patients (62%) compared to those with discount plans (42%) or Medicare/Medicaid (33%). Total median costs varied significantly between discount plan patients ($1258) and both Medicare patients ($751) and Medicaid patients ($593).

European Economic Burden

In Europe, Italian data provides insight into the economic burden of diabetic retinopathy. Annual costs associated with the condition in Italy ranged from €4,050 to €5,799 per patient, varying based on disease severity and treatment approach. Notably, non-medical and indirect costs such as lost productivity and caregiving expenses constitute a significant portion of the overall financial burden for Italian patients.

In Sweden, potential savings of 36 million SEK might be realized through proper detection and treatment programs.

Cost-Effectiveness Considerations

Multiple studies highlight the cost-effectiveness of early intervention. A 2013 study indicated that when treatment results for diabetic macular edema (DME) are equivalent, selecting less-expensive treatment options could yield cost savings of 40% to 88%.

The Joslin Vision Network, a non-mydriatic digital tele-ophthalmology system, was found to be both less costly and more effective than traditional clinic-based ophthalmoscopy in most scenarios according to a 2006 study.

Prevention programs aimed at improving eye care for persons with diabetes not only reduce vision loss but also provide a financial return on investment of public funds. Detection and treatment of diabetic eye disease in both the United States and Scandinavia is not only cost-effective but cost-saving from the governmental perspective.

Vision AI Platforms Beyond Diabetic Retinopathy

Based on the available information, Vision AI platforms are being trialed for several indications beyond diabetic retinopathy. These include:

  • Age-related macular degeneration (AMD) is being investigated for AI applications in retinal imaging, with research publications from 2023 and 2024 documenting these efforts
  • Central serous chorioretinopathy is another condition being explored for AI-based diagnosis and monitoring according to a 2023 publication
  • Diabetic macular edema (DME) is being studied for AI applications in screening, diagnosis, and management as noted in multiple recent publications from 2023-2024
  • Dry eye disease (DED) is being investigated for AI applications including machine learning algorithms, imaging technologies, and diagnostic platforms to enhance diagnostic accuracy and personalize treatment approaches, as documented in 2024
  • Retinal neovascularization (NV) assessment in conditions like retinopathy of prematurity and retinal vein occlusion is being explored through AI applications, as mentioned in a 2021 publication

The intervention models for these trials focus on several key approaches:

  1. Lesion detection and analysis - AI tools are being developed to identify and characterize specific pathological features in retinal images
  2. Disease progression prediction - Vision AI platforms aim to model and forecast how these conditions may evolve over time
  3. Treatment response models - AI systems are being designed to predict and evaluate how patients might respond to various interventions

The integration of AI into ophthalmology has significant potential to revolutionize the management of these conditions by offering more efficient and precise diagnostic tools. These Vision AI platforms represent a promising advancement in ophthalmic care, potentially improving early detection and treatment planning across multiple eye conditions beyond the established applications in diabetic retinopathy.