Fully Autonomous AI oxygen management platform

AiroSolve was born when Julio La Torre was traveling the country as a physician serving underserved hospitals during the COVID pandemic. It was during this time one problem stood out significantly: patients with respiratory conditions and their caregivers grapple with the significant challenge of maintaining optimal oxygen levels. Globally, millions are affected, with conditions ranging from chronic obstructive pulmonary disease (COPD), Congestive Heart Failure(CHF), and pneumonia. The World Health Organization estimates that COPD alone claims 3 million lives annually. One of the pressing concerns in this arena is the issue of hyperoxemia(too much oxygen). A study published in the Lancet by Chu et al. highlights that excessive oxygen levels can significantly increase mortality rates among patients. Moreover, recent research underscores a concerning trend: patients are receiving too much oxygen a majority of the time, placing them at unnecessary and heightened risk for adverse outcomes, including death. These challenges are exacerbated by a reliance on manual intervention in oxygen titration. In many clinical environments, there’s an absence of continuous real-time oxygen saturation monitoring, leading to potential data gaps that can compromise patient care. Additionally, healthcare professionals, especially during peak times or crises, are overburdened, which can result in potential oversights in oxygen management.

AIroSolve is an innovative system that revolutionizes oxygen management in clinical settings. In essence, it’s a smart, fully autonomous AI-driven platform tailored for continuous oxygen monitoring and titration. AIroSolve seamlessly integrates with existing inpatient monitoring systems, capturing and analyzing vital data in real-time. By utilizing advanced artificial intelligence and machine learning algorithms, it automatically adjusts oxygen flow to keep levels within the optimal range for each patient. Not only does AIroSolve ensure patients receive personalized, precision care, but its intuitive interface makes it user-friendly for healthcare professionals. The system is both diagnostic and therapeutic, with the potential to identify multiple respiratory conditions even before the need for extensive imaging arises. This represents a paradigm shift in respiratory care, elevating the standards of patient safety and healthcare efficiency.

Our primary target population encompasses hospitals and healthcare facilities with limited resources, particularly those with a shortage of nursing staff. These establishments often grapple with ensuring consistent and optimal oxygen therapy, making them susceptible to complications resulting from improper oxygen titration. Furthermore, hospitals globally face an escalating challenge of oxygen shortages. AIroSolve addresses this by helping these institutions save up to 50% of their oxygen, acting as a buffer against potential shortages and ensuring continuity of care.

Moreover, AIroSolve's emphasis on personalized care addresses another significant healthcare disparity. Studies have highlighted biases in pulse oximeter data, especially concerning patients with darker skin. These biases have unfortunately resulted in substandard care for these individuals. AIroSolve's continuous data monitoring and personalization capabilities aim to rectify this. By tailoring oxygen therapy based on real-time, comprehensive data, we aim to ensure that every patient, regardless of skin tone, receives accurate and optimal respiratory care. In doing so, AIroSolve not only optimizes oxygen therapy but also advances the broader objective of equitable healthcare for all.

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Our team possesses a unique blend of on-the-ground medical experience and technical expertise, putting us in a prime position to develop and deliver AIroSolve to our target populations. 

Dr. Julio La Torre has an intimate understanding of the challenges faced by underserved hospitals. As a physician credentialed in 11 hospitals across six states, he's witnessed the disparities in healthcare resources firsthand. The conception of AIroSolve was born out of his experiences during the tumultuous period of the COVID-19 pandemic, as he traveled the country offering his expertise to the very hospitals AIroSolve aims to benefit. His continued commitment to these institutions is evident, not just in his ongoing service but also through the pilot studies he's initiated. Julio's deep-rooted relationships with these hospitals will ensure that our solution is not only effective but also embraced by the very communities we aim to serve. Julio is also a recent MBA graduate of the UCLA Anderson School of Management.  He also completed a UCLA BioDesign Fellowship at UCLA Ronald Reagan Medical Center where he learned the fundamentals of product development for medical technologies. 

Complementing Julio's medical insights, Nico Vansnick brings a decade of experience as a hardware operator to the table. Nico is the Co-Founder and former CEO of Bot Factory, a company he founded over 10 years ago while a graduate student at NYU Tandon School of Engineering. His expertise in robotics engineering is pivotal in ensuring that AIroSolve is built on a foundation of technical excellence, robustness, and scalability.

AIroSolve’s groundbreaking approach holds the potential to significantly reshape the hospital/inpatient monitoring market. In the current landscape, many hospital systems collect vast amounts of data but often fall short when it comes to correlating this information with patient outcomes. Traditional monitoring methods rely on intermittent, discrete data points, and manual interventions. These manual methods not only lack efficiency but can also introduce errors, leading to suboptimal care and jeopardizing patient safety.

AIroSolve challenges this status quo by not just passively monitoring but actively intervening. Our system not only continuously collects data but also automates the titration process, ensuring that treatments are precisely calibrated to each patient’s needs in real-time. By doing so, it bridges the gap between mere data collection and immediate therapeutic action, leading to safer and more efficient patient care. Moreover, AIroSolve provides real-time insights and diagnostic evaluations, taking monitoring to the next level. This transformation heralds the dawn of a new era in healthcare — where the hospital bedroom evolves into an integrated hub of fully autonomous AI-driven care, optimizing both treatment and diagnostics.

AiroSolve is deeply committed to the tenets of UN Sustainable Development Goal 3, advocating for Good Health and Well-Being for all.

**Addressing Target 3.B:**
While AIroSolve is not a medicine or vaccine, its underlying principle is to optimize a life-saving medical intervention, oxygen therapy. By doing so, it serves as a pivotal tool in the management of both communicable and noncommunicable diseases that plague developing countries. Oxygen therapy is fundamental in conditions like pneumonia, sepsis, and, more recently, COVID-19. With AIroSolve's advanced titration and monitoring, we ensure patients receive the right amount of oxygen, neither too much nor too little. This is particularly crucial for developing nations, where medical resources are scarce. Furthermore, our solution aims to be accessible and affordable, aligning with the Doha Declaration on the TRIPS Agreement and Public Health. By providing a smarter, more efficient means of delivering oxygen therapy, AIroSolve is ensuring that even in resource-limited settings, patients have access to top-tier care.

**Addressing Target 3.C:**
While increasing health financing is beyond the scope of our solution, AIroSolve substantially contributes to the optimization of the health workforce. In many developing countries, the nurse-to-patient ratio is alarmingly low, often leading to overwork and burnout. AIroSolve, by offering autonomous, AI-driven oxygen management, not only reduces the manual workload on these valiant healthcare professionals but also ensures that patients receive consistent, quality care. This indirectly aids in the retention of health workers by alleviating some of their daily stresses. Additionally, our platform's informative interface serves as a training tool, providing real-time insights and analytics, which can be invaluable for the ongoing development and training of healthcare personnel in these nations.

AIroSolve is pioneering the creation of a novel and proprietary dataset — the continuous oxygen flow administered to patients. This data, which we believe intricately mirrors a patient's disease course, holds untapped potential in understanding and predicting patient needs, thereby allowing for timely and effective interventions. By continuously monitoring and adjusting oxygen levels in real-time, AIroSolve captures granular data points that have historically been overlooked or deemed inconsequential in traditional care settings.

In addition to this primary dataset, our AI system integrates and cross-references oxygen flow data with other vital parameters such as pulse rate, respiratory rate, blood pressure, and more. This holistic view of patient metrics offers a comprehensive understanding of the patient's state and aids in creating a multi-dimensional perspective, enriching our proprietary dataset's value.

Our strategy for acquiring quality, curated data involves a multi-pronged approach: We actively collaborate with our partner hospitals, leveraging the wealth of patient data they produce daily. The pilot studies at underserved hospitals not only validate our solution's effectiveness but also ensure that our data is diverse, representative, and exhaustive. Moreover, with robust data preprocessing and curation methods in place, we aim to refine this raw data into valuable insights, driving AIroSolve's continuous learning and optimization process. As our system is deployed in more diverse settings and handles a broader range of conditions, the richness and scope of our dataset will grow exponentially, reinforcing the efficacy and intelligence of AIroSolve.

Ensuring the ethical and responsible use of AI is paramount in our development of AIroSolve. Recognizing the historical biases in healthcare data, we've incorporated mechanisms within AIroSolve to actively mitigate these biases. Our primary aim is to ensure that care recommendations are equitable for all patients, irrespective of their backgrounds. Beyond that, AIroSolve's AI components are consistently monitored and updated to align with the latest medical knowledge and research. This commitment to ongoing learning ensures our system remains both relevant and precise. Furthermore, to root our solution in ethical foundations, we actively engage with a diverse range of stakeholders, including clinicians, patients, and ethicists. Their invaluable feedback shapes AIroSolve, ensuring its ethical integrity.

Addressing potential risks, we're acutely aware of the possibility of healthcare providers becoming overly reliant on AIroSolve, potentially compromising their clinical judgment. As such, we underscore that AIroSolve serves as a decision-support tool, not a replacement for human expertise. Additionally, understanding the potential for algorithmic errors, AIroSolve integrates various fail-safes and alert mechanisms. These systems are designed to notify healthcare providers if sensor readings or AI predictions appear to deviate from expected norms, ensuring that AIroSolve remains a trusted and reliable tool in the healthcare landscape.

In the upcoming year, AIroSolve is poised to take significant strides in refining and validating our solution. Our immediate agenda is anchored around a multi-phase pilot study which is designed to evaluate both the reliability and efficacy of our device. This structured study will serve dual purposes: first, to gather a rich dataset that will inform and improve our AI algorithms; and second, to provide a robust proof of concept that showcases the tangible benefits of AIroSolve in real-world clinical settings. We are dedicated to the principles of transparency and peer validation; hence, we anticipate publishing our study findings in a prestigious medical journal, a move that will not only attest to the credibility of our work but also engage the wider medical community in a productive dialogue about the future of oxygen therapy.

Looking ahead to the next five years, AIroSolve’s roadmap is both ambitious and strategic. Our immediate post-pilot phase will focus on intensive research, aimed at refining our device based on the pilot feedback and exploring new avenues of application. Protecting our intellectual property will be a paramount objective, ensuring that the innovative aspects of AIroSolve are well shielded and our stakeholders’ interests are safeguarded. With rigorous research as our backbone, we will navigate the meticulous process of FDA clearance, asserting the safety and effectiveness of our device. Once we achieve this significant milestone, our focus will shift to a more expansive phase: deploying AIroSolve in hospitals across the U.S. As we solidify our presence domestically, our horizon will broaden to encompass hospitals worldwide, 

2 full time

1 part time. 

2 years

At AIroSolve, our commitment to diversity, equity, and inclusivity is both intrinsic and intentional. Our leadership echoes this sentiment, spearheaded by our founder, Julio La Torre. A first-generation American with parents who immigrated to Peru and Mexico, Julio offers a distinctive cultural vantage point, further augmented by his bilingual abilities in English and Spanish. Our advisory board is another testament to our inclusive ethos. Comprising three formidable women, an African American member and spanning the fields of clinical medicine, industry, finance, politics and Artificial Intelligence: our board is a dynamic amalgamation of varied backgrounds and experiences. This diversity not only solidifies our core values but also continually motivates us to elevate our standards of equity and inclusivity in every aspect of our work.

AIroSolve operates on a pragmatic and strategically designed operational model that harnesses the strength of collaboration and innovation. Central to our approach is the effective utilization of established networks with hospitals, given my active involvement and affiliations with several of them. This unique vantage point not only offers guidance but also provides us with invaluable avenues for pilot studies. Already, we have made strides by securing an IRB at Brooklyn Hospital Center. With the prospect of additional funding, our intent is to acquire more IRBs, facilitating a more comprehensive data collection process.

Structurally, as a C-corp, we are primed for growth and scalability. Our strategy for funding is multifaceted. We aim to attract angel investors and capitalize on government grants, all while ensuring that the core objectives and mission of AIroSolve are upheld.

Our board is a true reflection of the diverse and abundant talent that drives our vision. Among our board members is a seasoned physician entrepreneur with a commendable track record of ushering multiple products through the complex stages of patenting, FDA clearance, and eventual market introduction. This journey culminated in a successful exit, providing us with invaluable insights into the product lifecycle. We are further bolstered by the expertise of an industry stalwart from Edwards Lifesciences, bringing in-depth industry knowledge and a web of connections that can propel our initiatives. Moreover, our board features the former director of MedTech Innovator and an academic luminary in pulmonology, currently serving as a professor at UCLA. Their vast academic and industry experience will guide our research and implementation phases, ensuring our solutions are both innovative and grounded. Complementing this ensemble is a globally recognized data scientist, whose expertise will be instrumental in refining and optimizing our AI-driven solutions.

Collectively, the vast experience, expertise, and networks our board brings to the table not only fills any potential operational gaps but also positions us to seamlessly navigate the intricate landscape of medical technology. By leveraging these resources, AIroSolve is poised to deliver on its promises, make transformative changes, and achieve our defined impact goals.

Our primary revenue stream will be based on a subscription service targeted at hospitals. Upon implementation, hospitals will be charged an initial installation fee. This approach allows us to cover the upfront costs associated with equipment, software, and training. Beyond the initial setup, we will implement a modest yearly subscription fee. This structure ensures that hospitals can forecast and budget for our service, strengthening our long-term partnerships with them.

To further bolster our financial stability and ensure consistent revenue inflow, we will introduce a recurring revenue model based on actual usage. Essentially, hospitals will be billed per use, creating an alignment between the value they derive from our system and their expenditure. This model not only incentivizes hospitals to maximize their utilization of our system but also allows AIroSolve to benefit from increased adoption rates over time.

By coupling the upfront installation and yearly fees with the per-use revenue model, we aim to establish a predictable and stable income stream. This dual approach ensures that AIroSolve remains financially sustainable, allowing us to reinvest in research, development, and continuous improvement, while also ensuring our commitment to providing cost-effective solutions to hospitals.

Our present operating costs are modest given the bootstrapped nature of our venture. Both my co-founder and I have chosen to forgo salaries, channeling the majority of our resources directly into device development and intellectual property-related expenses.

Looking ahead, we project that our operating costs for the upcoming year will significantly increase as we aim to amplify our reach and further the development of our solution. A minimum budget of $50,000 would sustain our current trajectory. However, with an optimized budget closer to $200,000, we would be better positioned to amplify our impact. This enhanced budget would enable us to deploy AIroSolve in multiple sites, facilitating broader data collection and faster iteration. Additionally, it would afford us the capacity to bring on board part-time software engineers and data scientists. These professionals will play an instrumental role in fine-tuning our system, ensuring it remains at the cutting edge of medical AI solutions.

We are seeking the full $100,000 in funding to continue our work in 2024. This figure was carefully chosen based on our projected expenses and the scale of the impact we aim to achieve. The allocated funding will primarily be channeled into device deployment across multiple sites, which is crucial for expansive data collection and system refinement. In tandem, it will allow us to hire part-time software engineers and data scientists, whose expertise will be paramount in evolving our AI-driven solutions. Funds will also be used to strengthen and file IP. 

While this funding will significantly accelerate our progress, I recognize that our optimized budget projects costs beyond the $100,000 mark. To bridge this gap, I am committed to supplementing the difference with personal savings. Additionally, we are actively engaging with angel investors who have shown keen interest in our initiative. Their potential contributions, combined with the requested funds, will place us in a strong position to realize AIroSolve's full potential in the coming year.

We recognize that our endeavor with AIroSolve is nothing short of ambitious. It weaves together multifaceted domains, ranging from hardware/device development to intricate data analytics, diagnostics, treatment algorithms, and refining user experiences. While we are proud of the dynamic team of founders and advisors we've assembled, we remain grounded in the understanding that there are gaps in our expertise. 

Though our team carries vast experience and insights, we recognize that there are areas where we could benefit immensely from targeted mentorship and guidance. One clear gap lies in the realm of clinical AI—navigating its regulation, understanding the nuances of clinical implementation, ensuring safety, and grappling with the challenges of ethics, bias, and fairness. We are also acutely aware of our limitations when it comes to device interoperability, a crucial component to ensure seamless integration of our solution into existing medical systems.

Located a few blocks from my apartment in midtown Manhattan, I’m looking forward to establishing Cures headquarters as home to AiroSolve for the next year!  I am particularly drawn to the mentorship component. Engaging with industry veterans would not only shed light on our existing challenges but also preempt potential pitfalls. The lab space would be very useful for further product iteration particularly in the presence of other innovators. Educational programming will provide the tools to bridge our knowledge gaps, while networking opens doors to invaluable collaborations.