Sight Tech

Diabetic retinopathy (DR) is a significant issue globally, especially in developed countries where it stands as the primary cause of blindness among those of working age. It's estimated to impact a staggering 93 million individuals worldwide, showcasing its widespread prevalence and impact. In the United States alone, the Center for Disease Control and Prevention reports that 29.1 million people have diabetes, contributing to the substantial global estimate of 347 million individuals affected by this disease.

This eye condition is closely linked to long-standing diabetes, with approximately 40% to 45% of Americans with diabetes experiencing some stage of DR. However, the concerning aspect is that the progression to vision impairment can be slowed or prevented if DR is detected early. Unfortunately, this proves challenging as the disease often manifests few symptoms until it reaches an advanced stage, making timely treatment difficult.

Currently, the detection of DR relies heavily on manual processes, where trained clinicians analyze digital color fundus photographs of the retina. This method is not only time-consuming but also prone to delays in delivering results, leading to lost follow-ups and delayed treatment initiation.

Clinicians identify DR through specific lesions associated with vascular abnormalities caused by diabetes. While effective, this approach requires significant resources, including expertise and specialized equipment. Unfortunately, these resources are often lacking in areas with high diabetes rates, where DR detection is most critical. With the diabetes population continuously growing, the inadequacy of infrastructure for preventing DR-induced blindness is becoming increasingly apparent.

We have developed a user-friendly web system where a diagnosis is generated in less than 5 minutes using images of the fundus of the eye, with the following advantages:

1. Rapid Diagnosis: It provides quick diagnosis of a disease that has become a public health issue in Mexico due to a shortage of specialist doctors and the time-consuming nature of diagnosis.

2. User-Friendly Web Platform: The platform is easy to use and offers high accuracy in diagnosing diabetic retinopathy within seconds. This accessibility and precision are crucial for timely intervention and treatment.

3. No Specialist Required: Unlike traditional methods that rely on specialists, your platform can be utilized by general practitioners, making it more accessible and scalable. This democratization of medical technology empowers primary care physicians to efficiently diagnose and monitor patients with diabetic retinopathy, thereby improving healthcare outcomes.

Demo: 

Our solution serves multiple stakeholders:

1. **Patients**: They benefit from quick and accurate diagnosis of diabetic retinopathy, leading to timely treatment and potentially preventing vision impairment or blindness.

2. **General Practitioners**: They can utilize the platform without the need for specialist expertise, enabling them to efficiently diagnose and manage diabetic retinopathy cases in their practice.

3. **Healthcare Systems**: The solution contributes to reducing the burden on healthcare systems by streamlining the diagnostic process, optimizing resource utilization, and improving patient outcomes.

The impact of our solution on their lives includes:

- **Improved Access to Diagnosis**: Patients can receive timely diagnosis regardless of their location or the availability of specialist doctors, reducing the risk of complications.
  
- **Efficiency in Healthcare Delivery**: General practitioners can diagnose and manage diabetic retinopathy cases more efficiently, freeing up specialists' time for more complex cases and reducing overall healthcare costs.

- **Better Health Outcomes**: Early detection and intervention lead to better health outcomes for patients, preserving their vision and quality of life.

- **Public Health Benefits**: By addressing a significant public health concern like diabetic retinopathy, your solution contributes to improving population health and reducing the economic burden of managing advanced stages of the disease.

Our team is led by a seasoned technical software developer responsible for crafting artificial intelligence algorithms for detection, and a visionary ophthalmic surgeon who originated the idea. The surgeon experiences firsthand the challenges and urgency of deploying rapid, accurate diagnostic systems, especially for underserved communities. One major issue is the difficulty in returning to a diagnostic center for results.

Our software is currently operational at Mexico's Central Military Hospital and five other regional hospitals. This firsthand experience ensures a deep understanding of the problem and its implementation, driving our mission to democratize access to diagnostic healthcare systems.

We have been working on this solution for 4 years, testing the software with ophthalmology resident students, refining it to achieve its current level of accuracy. As a result, we have successfully deployed it in 5 regional hospitals where it has become an essential tool for over 10 ophthalmologists. This translates to usage among more than 10,000 patients, given the high patient volumes in these public hospitals where thousands are seen daily. This milestone was achieved since mid-2023, and in the recent period, we have been focusing our efforts on expanding to more locations in Mexico and the United States.

We are seeking to apply for opportunities to expand our network, raise awareness about our solution, and receive mentorship and support to scale and extend its reach. Our goal is not just growth but also to enhance the impact of our solution on a larger scale.

1. **Accessibility**: By creating a user-friendly web platform that doesn't require specialist expertise, your solution democratizes access to diabetic retinopathy diagnosis, especially in regions facing a shortage of specialists.

2. **Speed and Accuracy**: The quick and highly accurate diagnosis achieved in seconds through AI algorithms significantly improves the efficiency of healthcare delivery, allowing for timely interventions and better patient outcomes.

3. **Scalability**: Implementing the solution in multiple hospitals, including public healthcare facilities with high patient volumes, showcases its scalability and potential to impact a large number of patients, addressing a critical public health concern.

4. **Technological Integration**: Integrating advanced technologies like AI into the diagnostic process not only improves accuracy but also showcases a forward-thinking approach in leveraging technology for better healthcare outcomes.

1. **Ease of Use**: Our user-friendly web platform simplifies the process of diagnosing diabetic retinopathy, making it accessible even to general practitioners without specialized training. This means more patients can receive timely screenings and interventions.

2. **Speed and Accuracy**: The platform delivers rapid and highly accurate diagnoses, crucial for early detection and treatment of diabetic retinopathy. This can prevent vision loss and complications, improving overall patient outcomes.

3. **Scalability**: By implementing our solution in multiple hospitals, including those in underserved regions with high patient volumes, we can reach a larger number of individuals who may not have easy access to specialist care. This helps in addressing the public health concern more effectively.

4. **Technological Advancement**: Leveraging AI algorithms for diagnosis demonstrates a modern and efficient approach to healthcare, showcasing how technology can be harnessed to solve complex medical challenges.

The core technology powering our solution is artificial intelligence (AI). Specifically, we utilize advanced AI algorithms to analyze digital color fundus photographs of the retina. These algorithms are trained to detect and diagnose diabetic retinopathy with high accuracy and speed, enabling rapid assessment and timely intervention. The AI technology not only streamlines the diagnostic process but also enhances the overall efficiency and effectiveness of healthcare delivery for diabetic retinopathy.

1. **Clinical Trials**: We have conducted clinical trials where our AI algorithms were tested against a large dataset of fundus photographs. The results showed a high level of accuracy and reliability in detecting diabetic retinopathy.

2. **User Feedback**: We have received feedback from healthcare professionals, including ophthalmologists and general practitioners, who have used our platform. Their positive experiences and the successful diagnosis and management of diabetic retinopathy cases validate the effectiveness of our technology.

3. **Real-world Implementation**: Our technology is currently operational in several hospitals, including public healthcare facilities with high patient volumes. The fact that it is being used on a day-to-day basis by healthcare professionals and benefiting a significant number of patients demonstrates its efficacy in real-world scenarios.

5 full time staff

4 years since 2020

1. Recruitment Practices: We actively recruit from diverse backgrounds, ensuring that our team represents a variety of perspectives, experiences, and expertise. This promotes creativity, innovation, and a deeper understanding of the diverse needs of our users and stakeholders.

2. Training and Development: We provide ongoing training and development opportunities for all team members, regardless of their background or position. This helps to minimize barriers to opportunity and ensures that everyone has the chance to grow and contribute to our mission.

3. Inclusive Policies: We have established inclusive policies and practices that promote a welcoming and supportive environment for all team members. This includes policies against discrimination, harassment, and bias, as well as mechanisms for reporting and addressing any concerns that may arise.

4. Open Communication and Feedback: We foster open communication and encourage feedback from all team members. This allows us to continually improve our practices, address any issues that may arise, and create a culture of collaboration and respect.

Our business model revolves around a subscription-based payment system. Users subscribe to our platform, paying a regular fee for access to our services. This model ensures a steady revenue stream and allows us to provide ongoing support, updates, and improvements to our technology. Additionally, it aligns with our goal of democratizing access to healthcare solutions by making them affordable and accessible to a wide range of users, including healthcare professionals and institutions.

Our plan for achieving financial sustainability revolves around our subscription-based business model, where users pay a recurring fee for access to our platform. This model ensures a steady revenue stream that allows us to cover operational costs, invest in research and development, and expand our reach to new markets and users.

To demonstrate the success of this plan, we can provide several pieces of evidence:

1. **Growth in Subscribers**: We have seen a steady increase in the number of subscribers to our platform over time, indicating that our offering is valued by users and meets their needs effectively.

2. **Financial Performance**: Our financial statements show positive trends, with revenue from subscriptions covering our expenses and allowing for reinvestment in the business.

3. **Customer Retention**: Our subscription model encourages customer loyalty, as users continue to renew their subscriptions and use our platform consistently over time.

4. **Market Expansion**: We have successfully expanded our market reach, acquiring new users and entering new regions or markets, which contributes to our financial sustainability.