Abbey AI

Genetic Alliance

Our solution addresses the significant challenges faced by the rare disease community, particularly in accessing accurate information, coordinating care, and connecting with support resources. The immense scale of this problem can be categorized into, but not limited to the following:

1. Rare disease is globally prevalent. Rare diseases collectively affect over 300 million people worldwide, or 3.5-5.9% of the global population. This equates to 1:17 to 1:29 people living with a rare disease. Language barriers often prevent patients from gathering helpful knowledge and outreach.

2. Patients are faced with prolonged diagnostic delays. The average rare disease patient consults with 7.3 physicians over 4.8 years before receiving an accurate diagnosis. Due to the rarity of their condition and limited knowledge among healthcare professionals, patients are faced with biases. This prolonged "diagnostic odyssey" exacerbates medical and emotional burdens on patients and families. 

3. Fragmented care leads to inconsistencies in treatment. Once diagnosed with a rare disease, the “odyssey” does not end. 78% of rare disease patients see 3 or more different specialists for their condition, with 38% seeing 5 or more. This lack of coordination increases the burden on families to manage complex care.

4. There is a lack of centralized and accurate information. With over 7,000 identified rare diseases, 72% of which are genetic and 70% starting in childhood, there is a severe lack of centralized, accurate information resources. 72% of patients and caregivers struggle to find reliable and up-to-date information about their condition. This issue presents itself in research as well, where hurdles such as limited funding, small patient populations, and a lack of natural history data hinders progress in rare disease research. 

5. People are not connected to appropriate programs. Only 15% of rare disease patients are connected to their disease-specific support groups or patient advocacy organizations that could provide valuable assistance. The same problem is seen in clinical trials, where there are logistical challenges with patient recruitment.

Our AI-powered platform aims to tackle these interconnected issues by providing personalized information access in 50+ languages, automating care coordination tasks, facilitating connections to support resources, and enhancing overall accessibility for the rare disease community. By addressing these core challenges, we hope to significantly improve quality of life and health outcomes for millions of individuals and families affected by rare diseases globally. 

Our solution is an AI-powered patient-centered chatbot and automated AI web agent designed to automate information retrieval, knowledge extraction, and web browsing for rare diseases, addressing the significant challenges faced by patients and caregivers. It will leverage Genetic Alliance's existing tools and the open-source solutions of its network partners. We have named it Abbey AI after Abbey Meyers, the founder of NORD and Genetic Alliance who led the initiative for rare diseases in the US.

Key Features:

1. Information retrieval 

   1. The AI chatbot accesses scientific papers and trusted web sources to provide accurate, up-to-date information on rare diseases. It uses novel low-data citation methods, ensuring reliability even in understudied areas.

   2. Users can click on any sentence in the AI-generated response to view a ranked list of citations according to a relevance score between 0 and 1 and expert source quality rating graded on a letter scale. Furthermore, users can access the original source by clicking on the given URL for further interpretation.

   3. By using Disease InfoSearch, a crowd-sourced information repository of Genetic Alliance, the AI agent informs patients of their disease and connects patients to their respective patient organizations.

2. Knowledge extraction

   1. The AI agent extracts relevant personal and medical information from patient health records to tailor its responses. For example, it can identify the user's geographic location to find local specialists or use medical data to narrow down potential rare diseases based on symptoms.

   2. The AI agent is also effective at parsing documents and websites, curating this information, and generating summaries related to user queries.

   3. Like a case manager, the AI agent will be eventually able to organize and schedule appointments with healthcare providers, helping reduce the chance patients miss the care they need due to a logistical issue.

3. Automated Web Browsing

   1. The AI agent handles web tasks such as filling out forms and organizing outreach, significantly reducing the logistical burden on patients and caregivers. Importantly, the agent does not need to be supervised while accomplishing these tasks.

   2. This feature is particularly beneficial for those with cognitive or physical impairments, who often face barriers in accessing support programs.

   3. When deployed on a task, the AI agent can be enabled to speak to the user using Deepgram’s text-to-speech API. Similarly, leveraging speech-to-text, the user can speak to instruct and correct the agent between steps.This is both a novel user experience requiring 0 graphical interface, but also an important accessibility feature for those with motor issues.

   4. Multiple AI agents can also be deployed at once, allowing multiple tasks to be accomplished in parallel, multiplying the productivity of patients and caregivers for bureaucratic tasks.

Our AI-powered web agent aims to significantly improve the quality of life and health outcomes for millions of individuals and families affected by rare diseases globally, providing a comprehensive, accessible, and continuously improving resource.

In 2020, a father of a boy who had around 100 seizures a day reached out to Genetic Alliance. Our goal was to reduce the number of seizures per day. Through Community-Driven Innovation™, an online patient platform, the families found immediate interventions that could be widely adopted to improve the children's quality of life. For instance, excessive drooling was impeding their development, but Genetic Alliance found that salivary gland Botox injections reduced drooling, enabling the children to sit and crawl without choking. Additionally, special teas were found to reduce constipation and lower the number of seizures. While these discoveries were significant, it took months to discover, disseminate, and put them into practice. Abbey AI, our AI platform consisting of a patient-oriented chatbot and automated web browsing agent will significantly reduce the time, resources, and complexity required for these patients and caregivers to access the information they need hidden in our existing systems.

Our patient-centered chatbot has several innovative features designed to help people at different stages of the diagnostic process. Currently, individuals have to search through various sources, which can sometimes provide conflicting information, and then try to make sense of it all on their own. With our advanced causal citation and patient feedback alignment algorithms, newly diagnosed patients can access a large amount of information instantly, process it, and receive verified, accurate, and useful information. Disease InfoSearch, a crowdsourced repository from Genetic Alliance, will be a primary source, ensuring that the information is verified by experts: disease advocates who have the most current and accurate information about a specific condition. This is a significant improvement over the outdated and inaccurate information available on the internet and from general-purpose chatbots like ChatGPT. With data and patient testimonials from our Community Driven Innovation™ platform, those further along can easily access practical care management tips. Making this data more accessible to patients will also facilitate the exchange of information throughout the biomedical ecosystem, including clinicians and researchers. For undiagnosed patients, querying our diverse bank of patient testimonials across 2000 of diseases provides grounded experiences that they can reference to generate hypotheses along their diagnostic odyssey. Our patient-oriented chatbot has key innovations over existing resources only possible due to our previous initiatives spanning 38 years.

Our solution, Abbey AI, also includes automated web browsing capabilities designed to assist undiagnosed patients in accessing critical resources. For example, if a patient needs free genetic testing resources, Abbey AI's web agent can search the web, fill out necessary forms, and summarize both the findings and any encountered issues, all autonomously. This significantly reduces the bureaucratic burden on patients and caregivers. Users can initialize the agent by specifying their objectives or using pre-existing workflows. Additionally, multiple agents can operate simultaneously, enabling parallel exploration. We hope this parallelization will speed up the diagnostic odyssey. In theory, Abbey AI can autonomously complete web tasks concerning any condition in over 50 languages, potentially benefiting hundreds of millions of people worldwide.

Genetic Alliance has developed more than 20 resources and tools since 1986. These include DiseaseInfoSearch.org, a comprehensive directory of rare diseases, as well as registries, biobanks, and tools like the advocacy bootcamp. We offer services such as matchmaking, referrals to advocacy and support organizations, and train-the-trainer programs. Additionally, we operate iHope Genetic Health, a program dedicated to diagnosing undiagnosed children in underserved communities worldwide. These tools were created before and during the early days of the internet. Integrating the very specific and highly trained AI tool into these resources will significantly enhance their availability and effectiveness.

In terms of Abbey AI, we have built a fully working patient-centered chatbot and begun testing our AI web agent on real-world tasks. The data pipeline for the chatbot (ingestion of PDFs & patient testimonials, parsing, chunking, embedding, retrieval algorithm, evaluation) has been built out in its entirety for one rare disease. Multiple citation mechanisms have been implemented (Cohere Rerank, Context-Cite). Feedback mechanisms such as thumbs-up, thumbs-down and context feedback mechanisms have been implemented in our frontend and logged using LangSmith in the backend. The reinforcement learning from human feedback algorithms on the backend have not yet been written given the early stage of the project and current lack of user data. Evaluations on LLM hallucination rate, factual recall ability, document relevance, and answer helpfulness have begun using LangSmith for logging and LLM-as-a-judge techniques for scoring.

Our agent currently has been built and works on toy tasks. We have completed adding speech-to-text and text-to-speech capabilities and frontend integration for creating new agents. We are currently testing the boundaries of this new and exciting but still immature technology for this problem.

Innovations and Impact

• Accessibility to knowledge is greatly enhanced.

  • Our AI model, GPT-4o, supports real-time voice translation for over 50 languages. This makes our model accessible to a global audience. 

  • We include text-to-speech for the visually impaired and speech-to-text for those with motor disabilities, ensuring inclusivity in the services the agent can provide.

• The model reaches a wider audience in the diagnostic odyssey, including undiagnosed patients.

  • The solution serves as a go-to resource for patients who have yet to receive a clear diagnosis, potentially reducing the average 6 physician visits before an accurate diagnosis. As a starting guide, patients are able to be connected to potential care-providers and advocacy groups, avoiding the hassle of doing the research themselves.

• Automated AI web browsing significantly reduces bureaucratic barriers for patients

  • AI web agents are currently cutting-edge innovative technology. In a world where AI web agents significantly cut down on logistical tasks, rare disease patients and caregivers would get care faster, more consistently, and at better times.

  • Organizations working with other groups of less-abled and disadvantaged people will learn from our example, seeing the value that these agents bring to those who have difficulty advocating and managing their own lives while navigating systems. 

• Human biases are reduced.

  • The AI provides an objective perspective, reducing human bias in the diagnostic process. This immensely mitigates the average 4-year delay in rare disease diagnosis. This can improve diversity by increasing accessibility to communities that are wary of the medical system.

• Model continuously learns to improve tailored responses from simple feedback

  • Through user interactions and feedback input, the agent improves over time by providing better solutions for the patient communities it works for. This ensures that the solutions provided are tailored to meet the specific needs of each rare disease group, while also learning personalized responses to fit a user’s needs.

  • Importantly, we expect our feedback mechanism to scale better than previous technologies. As a wiki, Disease InfoSearch is updated when users write and edit the page. But this need for active maintenance often leads to disrepair. In contrast, generative AI models are maintained simply by usage. These models easily generate content. Instead, this content needs to be aligned with facts and values. To do so, we use Reinforcement Learning from Human Feedback (RLHF) algorithms that employ a binary thumbs-up and thumbs-down, textual annotated feedback, and user engagement metrics to align the models. This means all users provide feedback for the product through usage and simple feedback forms. We see this innovation in feedback as being key to our success due to the difficulty of performing manual maintenance at scale as a nonprofit group.

1. We  have mature and relevant tools deployed in the rare disease community,. These will greatly benefit from a high tech solution stitching them together, reducing the burden to use them, and iteratively improving them without the enormous amount of real time person-power needed at this time.

2. Financial Support:  Our team would have the resources to advance the development and deployment of our AI-powered solution, ultimately enhancing its impact on the rare disease community. The prize money would also help accelerate the delivery of our innovative solution to those who need it the most.

3. Validation and Credibility: The Amgen Prize lends significant credibility to our solution, as this recognition can open doors to additional funding opportunities, partnerships, and collaborations, which are critical for solving this complex challenge.

4. Overcoming Market and Adoption Barriers: This field suffers from significant market and adoption barriers due to the diverse patient populations, and limited knowledge and awareness. The recognition and support from a prominent organization like Amgen can help overcome these barriers by facilitating partnerships, excess to networks and potentially opening doors to new markets or distribution channels.

5. Collaboration and Access to Expertise: MIT Solve network provides us with the opportunity to build integration with like-minded innovators and to have the opportunity to engage with subject matter experts, researchers, and industry professionals.

Genetic Alliance, a community-based organization, provides training and capacity building for thousands of communities who serve those affected by this “diagnostic odyssey”. Since 1986, Genetic Alliance’s members and leadership have worked tirelessly to alleviate this suffering, drawing on their personal experiences of their own children who have struggled to be diagnosed. They help accelerate the diagnosis process and access to services. Genetic Alliance also creates scalable tools and trains advocacy organizations. They work directly with inner-city, rural, and indigenous communities and partner with community leaders to better understand their community's needs. They enable communities to collect data, influence policy-makers, pass legislation, and equip local clinicians and community health organizations with specific technologies such as genome sequencing. Genetic Alliance matches individuals and families with available services and builds community-based services where they do not exist or require improvement. As a result, communities determine health priorities, drive the agenda, “build the table” (rather than secure a seat at the table) in health services and research, and advance policies to improve their communities' health.

Partnership is key to Genetic Alliance’s work. We work with over 2,000 advocacy organizations and thousands of other grassroots communities. We provide training, tools, and resources to build their capacity. In addition, we partner with major professional societies in healthcare and research. We serve on various committees and councils for the National Institutes of Health, the Health Resources and Services Administration, Centers for Disease Control and Prevention, and Food and Drug Administration. We provide a conduit for other organizations to reach thousands of communities about various policy issues in our network. 

Sharon Terry, CEO. In 1994 her children were diagnosed with a genetic condition after a diagnostic odyssey. Within days of their diagnosis, she realized competition and greed were impeding health. Without any science training, she gathered the community of people affected by PXE, solicited their priorities, built a robust scientific system for the condition. Parents of children with other conditions asked that she help them. She joined Genetic Alliance and scaled these solutions to enable thousands of other communities to advance research. Together they advanced community advocacy wherein the people control of the process of determining priorities for their communities.

Next Year:

1. Increase Access to Reliable Information:

   1. Goal: Ensure that 50,000 rare disease patients and caregivers have access to accurate, personalized information through our AI-powered platform. 

   2. Measurement: Track the number of unique users accessing the platform and the number of information queries successfully answered. 

   3. Achievement Strategy: Collaborate with non-profit organizations and patient advocacy groups to promote the platform and integrate it into their support services.

2. Enhance Care Coordination:

   1. Goal: Improve care coordination for 10,000 rare disease patients by automating appointment scheduling and specialist searches. 

   2. Measurement: Monitor the number of care coordination tasks completed by the AI and user feedback on the ease of managing their care. 

   3. Achievement Strategy: Develop partnerships with healthcare providers and integrate the AI system into their patient management workflows.

3. Facilitate Access to Support Programs:

   1. Goal: Connect 5,000 patients with relevant outreach, education, and social support programs. 

   2. Measurement: Using a customer satisfaction model built into the website, track the number of patients successfully connected to support programs and the utilization rate of these programs. We assume only 10% will answer the survey.

   3. Achievement Strategy: Work with a subset of Genetic Alliance’s 2000 patient advocacy groups to identify and integrate support programs into the AI platform.

Next Five Years:

1. Global Reach and Multilingual Support: 

   1. Goal: Expand the platform to support 1 million users globally, with multilingual capabilities in over 80 languages. 

   2. Measurement: Track the number of users from different countries and the number of languages supported by the platform. 

   3. Achievement Strategy: Continuously update the AI's language capabilities and collaborate with international rare disease organizations to promote the platform. Integrate Abbey AI into Genetic Alliance’s iHope Genetic Health program - diagnosing the world’s undiagnosed children (50,000 a year).

2. Reduce Diagnostic Delays:

   1. Goal: Reduce the average diagnostic delay for rare disease patients from 4 years to 2 years. 

   2. Measurement: Collect data on the time taken from initial symptoms to accurate diagnosis for users on the platform. 

   3. Achievement Strategy: Enhance the AI's diagnostic capabilities by integrating more comprehensive medical data and collaborating with healthcare providers to streamline the diagnostic process.

3. Improve Quality of Life:

   1. Goal: Enhance the quality of life for 500,000 rare disease patients and caregivers by providing comprehensive support and reducing the burden of care. 

   2. Measurement: Conduct surveys to assess improvements in patients' and caregivers' quality of life, including emotional well-being and financial stability. 

   3. Achievement Strategy: Continuously refine the AI's features based on user feedback and expand partnerships with organizations that provide financial and emotional support.

Indicators for Measuring Progress:

1. User Engagement

   1. Number of unique users accessing the platform. 

   2. Frequency and volume of information queries.

2. Task Automation

   1. Number of care coordination tasks completed by the AI. 

   2. User feedback on the ease of managing care.

3. Support Program Utilization

   1. Number of patients connected to support programs. 

   2. Utilization rate of these programs.

4. Diagnostic Efficiency

   1. Average time from initial symptoms to accurate diagnosis. 

   2. Number of diagnostic queries successfully resolved.

5. Quality of Life Improvements

   1. Survey results on emotional well-being and financial stability. 

   2. User testimonials and case studies.

By setting these impact goals and using specific indicators to measure progress, we aim to create a transformational impact on the lives of rare disease patients and their caregivers, ensuring they receive the support and information they need to manage their conditions effectively.

Immediate Outputs

1. Enhanced Information Access:

   1. Patients and caregivers receive accurate, up-to-date information on rare diseases through the AI chatbot. 

   2. Users can access original sources for further interpretation, ensuring transparency and trust.

2. Improved Care Coordination:

   1. The AI automates appointment scheduling and specialist searches, reducing the logistical burden on patients and caregivers. 

   2. Personalized responses based on extracted health data improve the relevance and accuracy of information provided.

3. Increased Support Program Utilization:

   1. The platform connects patients with relevant outreach, education, and social support programs, increasing awareness and utilization.

Longer-Term Outcomes

1. Reduced Diagnostic Delays:

   1. By providing accurate information and personalized responses, we anticipate that our platform will help reduce the average diagnostic delay for rare disease patients from 4 years to almost 2 years. [Ref]

2. Improved Quality of Life:

   1. Enhanced care coordination and access to support programs reduce the emotional and financial burden on patients and caregivers [ref?]. 

   2. Surveys and user feedback will be used to correlate improvements in emotional well-being and financial stability.

3. Global Reach and Inclusivity:

   1. The platform supports 50+ languages, making it accessible to a global audience.

   2. Accessibility features will ensure inclusivity for users with cognitive and physical impairments.

Evidence Supporting the Theory of Change

1. Third-Party Research:

   1. Studies show that rare disease patients visit an average of 6 physicians before consulting an expert, with an average delay of 4 years from symptom onset to expert referral. 

   2. The use of AI in healthcare has been shown to improve diagnostic accuracy and care coordination.

2. Process and Impact Evaluations:

   1. Continuous monitoring of user engagement, task automation, and support program utilization provides data to evaluate the platform's effectiveness. 

   2. Surveys and user feedback help assess improvements in quality of life and diagnostic efficiency.

3. Collaborations:

   1. Partnerships with Non-Profit organizations and patient advocacy groups will ensure that the platform meets the needs of the rare disease community and integrates seamlessly into existing support services offered by these organizations.

By linking these activities to immediate outputs and longer-term outcomes, our solution aims to create a transformational impact on the lives of rare disease patients and their caregivers. The AI-powered platform provides a comprehensive, accessible, and continuously improving resource that addresses the unique challenges faced by this underserved population.

Genetic Alliance staff includes the CEO, Sharon Terry, the director of Disease InfoSearch Vilma Whittier, and the regulatory assistant director in charge of the Genetic Alliance Institutional Review Board, Georgia Boley, 6 part-time fellows John, Shubham, Uhitha, Reza, Annie, Yunseo. In addition, Genetic Alliance’s IT partner Aretetic, will provide assistance for optimal integration.

The organization has been working on rare disease support for 38 years. The current Genetic Alliance team has been in place for 24 of those years. The Fellows have worked with us intensively for 3 months.

Genetic Alliance has partnered with disability organizations in policy and programmatic work since our founding in 1986. We have had strong partnerships with LGBTQIA2S+ organizations for the past two decades. Genetic Alliance’s primary focus is people who experience disabilities due to diagnosed and undiagnosed genetic conditions. We have always embraced diversity, equity, and inclusion of all individuals, families, and communities. We advocated for the Americans with Disabilities Act (ADA) passage in 1990. Many of our members are in wheelchairs, use assistive devices, and need accommodations, so this was an early priority. From the very beginning, it was clear that individuals from underserved and under-resourced communities faced increased discrimination. For our BIPOC and LGBTQIA2S+ members, lack of access and often harmful or inappropriate interventions are key challenges. Genetic Alliance held annual conferences to combat these inequities and quickly learned that while we could provide the infrastructure and connections, marginalized communities must lead these gatherings. We became the audience of our own meetings. 

We have had dozens of non-digital, on-the-ground programs in partnership with organizations in underserved communities around the USA. We have worked with the incredible community action collaborative, the Village Team in Westchester Country NY, and with communities in Appalachia, Harlem, inner city New Haven Connecticut, rural Louisiana and Alabama, Washington DC, and the Federally Qualified Health Centers.

Our team has actively worked to amplify the voices of BIPOC and other historically underserved communities in major federal projects, including PCORI and the Surgeon General’s Health History program, as well as within academic medical centers. We are proud to have led social issues and ethics committees for respected organizations such as the American Society of Human Genetics and the American College of Medical Genetics to ensure that these important initiatives are inclusive and representative of all communities. By partnering with Black and Brown communities, we have helped to facilitate the collection of data that supports critical policy issues affecting these communities.

Abbey AI’s business model centers on delivering significant value to rare disease patients, caregivers, healthcare professionals, and researchers through an AI-powered platform that streamlines information retrieval, personalizes knowledge extraction, and automates care coordination tasks, ultimately improving the quality of life for the rare disease community.

Rare disease patients and caregivers are our primary beneficiaries. They often encounter prolonged diagnostic delays, fragmented care, and a lack of centralized, accurate information. Abbey AI mitigates these issues by offering accurate, up-to-date information, personalized responses based on patient health records, and assistance with logistical tasks such as appointment scheduling and form filling. This comprehensive support reduces the emotional and financial burdens on patients and caregivers, making their healthcare journey more manageable and less stressful.

Healthcare professionals, including doctors, specialists, and clinicians, benefit from Abbey AI by gaining access to reliable and current information on rare diseases. This enables them to provide better, more informed care to their patients. Additionally, the platform's automation of care coordination tasks, such as finding specialists and scheduling appointments, helps streamline their workflow, allowing them to focus more on patient care. We aim to act as a clinical reference similar to "Up-To-Date," which charges $500 per user per month and achieves substantial revenue. Our pricing strategy is yet to be determined, but even at a conservative estimate of $50 per user per month, we expect to effectively recover our costs and sustain our operations.

Patient advocacy groups also play a crucial role in our business model. Genetic Alliance is a coalition of 2,000 advocacy organizations and 8,000 other health communities.  These organizations support and advocate for patients with specific rare diseases, and Abbey AI enhances their efforts by providing a centralized repository of accurate information and tools for better patient engagement. The platform also connects patients to relevant support programs, improving their access to vital resources. By integrating Abbey AI into their services, advocacy groups can serve their communities more effectively and efficiently. We will not charge advocacy groups. Instead, we will enter into a symbiotic relationship. They contribute to our product and get our services for free, allowing other users to have better information about this disease.

Our business model includes multiple revenue streams to sustain and grow our platform. We offer subscription plans for healthcare organizations, research institutions, and pharmaceutical companies to access advanced features and analytics. These subscriptions provide steady revenue while offering value to our partners. We actively seek grants from government sources, non-profits, and foundations focused on rare disease research and patient support. These funds help us develop and expand our platform, ensuring it remains a cutting-edge resource for the rare disease community. Additionally, we collaborate with patient advocacy groups and healthcare organizations, receiving sponsorships to support the development and deployment of our platform. These partnerships enhance our reach and impact, benefiting all parties involved. We also plan to contract with pharmaceutical companies to match patients for clinical trials, providing them with a valuable service while generating revenue for our platform.

Our plan for becoming financially sustainable involves a multifaceted approach to revenue generation that combines subscription fees, service contracts, grants, and partnerships. This is all predicated on Genetic Alliance successful fundraising for the past 38 years - we have raised in excess of $40M for our tools, resources, and services development and deployment. This strategy ensures diverse and stable income streams to cover our expected expenses and support our long-term growth.

1. Subscription Fees: We aim to offer subscription plans for healthcare organizations, research institutions, and pharmaceutical companies to access advanced features and analytics on our platform. By providing valuable services that enhance their operations and patient care, we can justify a subscription fee. For instance, acting as a clinical reference similar to "Up-To-Date," which charges $500 per user per month, we plan to offer our service at a competitive rate. Even at a conservative estimate of $50 per user per month, we could effectively recover our costs and generate significant revenue.

2. Service Contracts: We plan to contract with pharmaceutical companies to match patients for clinical trials. This service not only provides value to pharmaceutical companies by facilitating their research and development efforts but also generates a steady revenue stream for us. Our ability to efficiently connect patients with relevant clinical trials can significantly reduce the time and cost associated with patient recruitment for these companies.

3. Grants and Funding: We actively seek grants from government sources, non-profits, and foundations focused on rare disease research and patient support. These grants provide essential funding for the development and expansion of our platform. Our history of securing grants for various projects demonstrates our capability to attract and manage funding effectively. Notably, our team members have received funding of $8,200 from the MIT DHIVE program to work on this project for the summer, illustrating our success in obtaining financial support.

4. Partnerships and Sponsorships: Collaborating with patient advocacy groups and healthcare organizations allows us to receive sponsorships that support the development and deployment of our platform. These partnerships enhance our reach and impact, benefiting all parties involved. By integrating Abbey AI into the services offered by these organizations, we can ensure sustained financial support while providing them with a valuable resource.

Evidence of Success: Our extended team has a proven track record of managing similar projects and securing funding. For example, Genetic Alliance has successfully developed and deployed over 20 resources and tools since its founding in 1986. These include DiseaseInfoSearch.org and other valuable assets for the rare disease community. This experience and established credibility position us well to achieve financial sustainability with Abbey AI.