Ai-Milli-POWERED CLINICAL RESEARCH DEVICE

     The problem we are trying to solve is Enhancing Efficiencies in Clinical Trials and Research. This is the section under Enhance Efficiencies in Clinical Trials and Research, including Data Collection and Sharing.

     The scale of the problem is not a global warming problem. The scale of the problem is not heart disease problem. Those are huge problems. This is a small-scale problem…it is why it’s called a rare disease. The FDA reports over 7,000 rare diseases impacting 30 million Americans. While this may seem like a large number, the patient population for each disease is often relatively small, making it less of a concern for the pharmaceutical industry. However, if you have it, it’s a huge problem.

     The challenges to a patient with a rare disease are threefold: [1] they cannot find a qualified physician to help them in some way; [2] usually the disease is not properly diagnosed; and [3] the high costs for disease-specific medications. We will focus on #3. Three challenges contribute to #3 (i..e., research inefficiencies in…) and we are here to solve #3 with our technology. The three challenges contributing to high costs for disease-specific medications are:

      PROBLEM 1: Research inefficiencies are due toredundancies due to trends and funding dictated by institutions such as the National Institutes of Health (NIH) and the National Science Foundation (NSF). For example, multiple organizations may publish redundant articles on the same topic, each with a slightly different title.

     PROBLEM 2: Research inefficiencies are due toinadequate sharing of data, which limits profess in the field. For instance, some clinical trial doctors have demanded ownership of all patients' data, prioritizing their careers over patients' lives. “A consortium of over 280 clinical trial doctors calling themselves ‘The International Consortium of Investigators for Fairness in Trial Data Sharing’ demanded ownership of all patients’ data…it is deeply upsetting that there are more than 280 researchers who are more concerned about their own careers than the lives of the patients on whom those careers are built. Bettina Ryll, M.D., Ph.D., Melanoma Patient Network Europe [New England Journal of Medicine]. This lack of data sharing also results in legal battles wasting research funds: the Alzheimer's Disease Cooperative Study was marred by a court battle between the University of California-San Diego and the University of Southern California, which fought over control of patient data for financial gain. And the winner was….not the patients!

     PROBLEM 3: Research inefficiencies are due tothe over-reliance on animal models in developing human trials. This is a failure. More than 100,000 mouse models are currently in use, yet they often fail to generate relevant data for eventual human trials. In the future, the Food and Drug Administration (FDA) may explore more relevant pre-human trial models that can generate more useful data.

We are eager for the chance to pursue our low-risk, high-reward endeavor and make meaningful progress.

Our solutions aim to address the three challenges noted previously in developing effective treatments for rare diseases.

• The first solution involves using our AI device, which focuses on achieving tangible results without being constrained by external pressures or redundancies, as noted previously in Problem 1.
• The second solution utilizes our comprehensive data-sharing process that utilizes MatLab software to facilitate personalized medicine, enabling more effective collaboration in the biotech and pharma industries, as noted previously in Problem 2.
• Finally, our third solution is the development of our AMP technology, which combines artificial intelligence and millifluidics-powered devices to improve the efficiency and effectiveness of clinical trials and research, as noted previously in Problem 3.

      Our AMP technology enables researchers to overcome the limitations of animal models in terms of human relevance and cost-effectiveness, particularly in rare disease clinical research. By leveraging innovative technologies like AMP, we can improve the efficiency and effectiveness of research and develop better treatments for patients. The combination of AI and millifluidics-powered devices can revolutionize clinical trials and research by offering more relevant and efficient alternatives to animal models. 

     To optimize the development of millifluidics devices, we will use a simulation platform based on Model-Based Design. We will use software tools such as MatLab, Simulink, Simscape, Simscape Fluids, and Simscape Electrical to create a virtual environment for testing (i.e., synthetic data generation with a simulator) and predictive maintenance, which will reduce the need for physical prototyping. We have current academic access to MatLab and Simulink with limited but functional access to Simscape apps to initially test the approach we want to take. This dramatically reduces hand-coding (i.e., creating a model offline that then generates the code like C/C++ to deploy a detector to verify real-time performance with live data). We will also use this platform for data preparation, data cleaning, and data filtering. This Model-Based Design approach has been successful in reducing implant surgical time from four hours to 30 minutes for Parkinson's patients. Our model relies on Ai and robotics and is designed for a low-workforce-high-skill facility (known as a Dark Facilities Model). While high-throughput systems for sample analysis and data processing already exist, our approach is focused on improving efficiency for clinical trials = system of modules + turnkey solutions (i.e., devices tailored to vertical applications, here being rare diseases) + the cloud (i.e., data management).

     In summary, the use of AMP is our moonshot goal having the potential to significantly improve the efficiency and effectiveness of clinical trials and research, from data collection and sharing to decision-making based on comprehensive and accurate data. It will be a great scientific achievement rather than a skillful engineering accomplishment. Its scalable design also enhances partnership potential, paving the way for greater collaboration and innovation in the field. As such, AMP represents a promising tool for advancing the state of clinical research and ultimately improving patient outcomes. But we cannot do this alone…this is where the program we are applying to comes into play.

The rare disease arena poses significant economic challenges, with patient populations often too small to attract the attention of mega-organizations, 4,000+ per disease (from over 7,000 rare diseases affecting 30 million Americans). While some organizations have created closed-system mega-databases based on pre-clinical animal data, these approaches have proven insufficient for patients with rare diseases.

     Our organization is tackling this problem by developing an innovative technology that eliminates animal trials, which often fail to predict human outcomes. By leveraging cutting-edge technologies such as artificial intelligence and human organoid models, we aim to accelerate the development of effective treatments for rare diseases, where a low population size is a reality. Our approach focuses on personalized medicine, where each patient's unique condition is considered, rather than relying solely on large population-level data. Our AMP device represents a significant step forward in rare disease research, providing a more efficient and cost-effective way to develop effective treatments that benefit patients.

     Speaking with folks with rare diseases, even with those with a rare disease plus another disease like Parkinson's disease, is that nothing is working, whether here in New Mexico, or the perceived biotech centers of the world like in California. The problems still exist for patients. What we are focusing is on the #3 problem noted previously, as undertaking all three is too much to undertake, even with giants like the Gates Foundation on the non-profit side, or Genentech on the for-profit side.

     "No one is listening to use because we are just a few, and a few in medicine doesn't count."
 

     This is where we want to come in, not human bloated or building bloated or admin bloated or ..., but with that Dark Facilities (i.e., robotics and Ai) mentally to economically survive to pursue the rare diseases arena. This includes doing things in-house and not farming out for self-sufficiency (e.g., look at Oppo as an example for being fabless = not doing in-house xyz).       
    

We're at the pretotyping [yes, a real word] and prototyping phases. What really helps is those visual simulations developed in MatLab for example. In parallel we are working on the business side using Ai tech from what we learned in customer discovery from the National Science Foundation I-Corps program = customer focused not product development.

We are applying to the Prize to overcome initial financial and market barriers that we hope to overcome with the Prize. Specifically, having full access to MatLab capabilities, and patent [intellectual property = IP] directions. We also have an IP direction we want to go through, therefore, IP legal help would be useful as well.

It is really not a local community issue, it is a U.S.-local community issue given the numbers and economics associated with rare diseases. It is not going to help just the local community, but the local community called rare diseases community.

    Doing it in-house using Ai and robotics, that Dark Facilities approach, keeps costs and development time way down compared to the traditional and current costly approaches. Look at a vehicle assembly line with just robotics...our approach is similar, except instead of automatically changing the color from red to green, we automatically change from rare disease 1 to rare disease 2. When it works for rare disease 1, it can be applied to rare disease 2, and so forth.

     Ultimately, we have adopted this approach for brain issues with the elderly using FDA-cleared instruments for non-invasive processes at a small local clinic. This is to adapt to rural clinics and clinics in Reservations to serve their population. This is especially helpful in communities that are considered Medical Deserts.

By months 28 to 32, we expect to be out of the internal prototyping for others in the U.S. [and globally if we cannot find a facility that deals with x rare disease] to use and real-world test the devices, where we then can modify are device "on-a-dime." This is where others come into help the process, as we cannot do it ourselves [heck, even the giant Gates Foundation or Genentech can't do things alone].

Again, nothing is currently working, and "hoping is not a solution" as one patient stated to us, and anything projected beyond that is a fantasy (Richard spoke to Dennis Fernandez...Patent Attorney at Fernandez & Associates: http://iploft.com/).

We measure progress by the simulations developed and by those we move forward in prototyping for real-time testing. The IP part is a matter of going from proprietary to patents. To help us with this process, we use Milestones Professional. It doesn't have to be more complicated than that.

    To get something that helps folks with rare diseases sooner than later...that's our moonshot purpose. This approach then can be used for other diseases that are considered NOT rare diseases. You don't need to build a kingdom for this..even though many exist.

We will use Ai [software & simulators] + microcontrollers + 3D printing.

Ai we want to use has been shown to work in Space technologies [https://www.geospatialworld.ne...]. Simulators we want to use have been used for surgical procedures with Parkinson's patients [https://www.mathworks.com/comp...]. Millifluidics have been used to reduce animal models [https://www.ncbi.nlm.nih.gov/p...]. Now we are combining those core technologies to adapt to rare diseases.

"People have come to the erroneous conclusion that if they’re not willing to start something separate, world-changing, and risky, they have no business starting anything. Somehow, we’ve fooled ourselves into believing that the project has to have a name, a building, and a stock ticker symbol to matter.” Seth Godin

Currently five. Don't need more, it's that Dark Facilities approach.

Since 2022.

We have women, an African American, Native Americans, an Asian, and a Hispanic in the group. We also have those suffering from diseases and identity-based human attributes, but do not want to be known publicly to feel [remain] safe...that's a reality.

Those wanting to help those with rare diseases that are trying to figure out how to help. This is not a point-of-care device, it is a device that will eventually help those "few" with one of 7,000+ diseases classified as rare by the FDA. As noted previously, that will be with out AMP device.

Through 100% licensing initially, then 30% through direct sales + 70% licensing related to the AMP.

We have an Excel database that has more than 500 components to help us address the above. Attached is a fraction of the database, but the + gives you an idea of the extent of the database.

     Once we have that one, it will be easier to ask others for access to this or that. If we have many funders we would not have applied here unless you are just throwing money or access to xyz away.

     In your eyes, we don’t have a past to anchor to. So naturally, we want you to think then of our future partnership. This kind of reverse chronology, the future partnership, fosters the kind of unconstrained thinking leading to this low-risk, high-impact program stated in the proposal. We view future partnerships as school dances. During school dances, students wait for someone to get on the dance floor before they jump in to dance as well. Once that first person jumps in, invariably most jump in thereafter. Being the first is always frightful, especially when there is no past to anchor to. Granted, reverse chronology is not foolproof, but a future-focused mindset will continue to be an important driver in programs having true impacts, not just temporary ones to fulfill funders’ paperwork requirements.  This durability approach to development challenges rarely involves one player implementing a quick fix, even if that is a technology one. This is where your organization comes into play. So, this is why we want you to be first on that dance floor, then others can follow your lead on this low-risk, high-reward program.