Intra-Network Tracking & Intel (INTI) Platform

According to a study published in the National Library of Medicine, contact tracing intervention was closely associated with patient recovery in cases of infectious disease transmitted by human-to-human contact. In fact, it was seen that contact tracing was associated with improving the outcomes of recovery in at least one subsequent patient in 69.33% of cases of COVID-19, tuberculosis, HIV, STIs, and measles, regardless of when throughout the spread of the disease that it was implemented. International travel and business ventures are at the highest rates ever, which means there are significantly higher opportunities for disease to be transmitted in the process.

As we saw most recently with COVID-19, contact tracing is only implemented when there is an active outbreak or there is thought to be an immediate reason to do so. There is a large portion of time lost by the time is it declared necessary to actively contact trace for new outbreaks or diseases, time that could've been used to preventatively manage the spread.

Our solution, INTI, allows stakeholders to establish a contact tracing system that begins at the first detection of a disease, even before an individual may realize they have contracted it. This retrofitted waste-water contact tracing solution does not have to apply only to global pandemics though, it can be effective on a local scale when tracking the spread of the seasonal flu around a classroom or office building. 

By reducing the barrier to collecting and distributing this information, you reduce transmission rates, reduce transmission ranges (in the cases of flights), and provide earlier detection, which can lead to better treatments and lower mortality rates in patients across the board.

Tikal's Intra-Network & Intel (INTI) platform is an AI-backed, Raman spectroscopy-based sensor. This is a two-part solution, with a base hardware, that is deployed in a wastewater setting and a software cloud/database, which can be remotely accessed. The hardware is designed to be attached to existing wastewater systems and continuously monitor the wastewater for contaminants of interest. The lab-on-chip system is designed to detect contaminants ranging from viruses, bacterias, narcotics, hormones, etc. 

INTI uses a system of pumps to autonomously pull a sample of wastewater and add the necessary sampling reagents. Once collected, the system excites the sample with a built-in laser and collects the Raman scattered light through a series of optics and a sensor. The use of Raman spectroscopy allows the sensor to gather specific and detailed data on the vibrational modes of potential contaminants within the collected wastewater. These Raman spectra can be analyzed remotely to determine the presence of any previously identified contaminants, such as pathogens, drugs, and environmental contaminants. Currently, the analysis algorithm is hosted on the Azure cloud, for additional security and regulation compliance, which allows for remote analysis. This also allows the team to remotely update new contaminants into the database, without adjusting the hardware. The current analysis is done using a random forest and support vector machine learning algorithm to match acquired spectra to previously taken samples of the contaminant; if a contaminant is matched by the algorithm, a notification can be sent to the central client dashboard. 

The team is currently developing a more sophisticated neural network-based, deep learning algorithm to tackle situations where multiple contaminants of interest and their associated signals need to be analyzed simultaneously while minimizing the number of samples taken by the hardware. The development of a new algorithm would also allow the system to preprocess and optimize the sampling parameters autonomously to maximize the quality of the captured data. 

The target population for INTI encompasses the entire community or a specific demographic within that community. This could include urban or rural populations, areas with limited healthcare infrastructure, or regions facing specific public health challenges. Anyone who is affected by a human-to-human transmitted disease of any sort could benefit from wastewater-based epidemiology, especially a cheaper and hands-off solution like INTI. It would be especially suitable for populations or individuals who have medical conditions that could make them more susceptible to transmittable diseases.

The INTI solution serves as an early warning system for potential disease outbreaks. By detecting the presence of pathogens in wastewater, public health officials can implement timely interventions, such as targeted testing, contact tracing, and public awareness campaigns (distribution of resources, vaccination campaigns, or public health education programs). This also ensures that resources such as testing kits, medical personnel, and treatment facilities are strategically deployed where they are most needed.

There is significant distrust when it comes to global pandemics, so providing publically available data year-round, prior to a health concern, can prioritize community engagement to build trust and ensure transparent communication. INTI can help prevent and control the spread of contagious diseases, monitor general public health concerns within an area, and provide critical data within underfunded communities.  

Tikal Industries is located in Chicago, the third-largest city in the United States. We are also very central in the country, being one of the most travelled-through cities in the country as well. Our office is a few miles from both major train stations in the city and a short 20-minute drive from each of the two airports in the city. One of those airports is O'Hare International Airport, the fourth-busiest airport in the entire world. The city sees almost 50 million tourists from around the world annually, and there are countless events and conferences that draw people in on business as well. As concerns of the next global pandemic and next seasonal illness are frequently in the media after COVID-19, being located in Chicago gives Tikal a great opportunity to partner with any number of public transportation companies and begin to help a large population with its first line of defense against what may come next.

Tikal is already in early discussions with multiple airlines and travel hubs in Chicago to facilitate testing and pilot studies with the INTI device. We plan to use these results in some of the most well-travelled places in the city, and apply them to a wider audience as more INTI units are deployed.

The aircraft wastewater testing program was successful in identifying asymptomatic COVID-19 cases. In fact, a study by the CDC found that the program identified an average of 2% of asymptomatic cases that would not have been identified through other testing methods. The program was also successful in helping to track the spread of the virus. For example, the program identified an increase in COVID-19 cases in the United States in the winter of 2020-2021, which helped to warn public health officials and inform their decision-making.

Currently, the WBE process is conducted using the following steps: (1) samples are collected manually or using automated samplers from WWTPs or other sewer systems; (2) wastewater samples are prepared for analysis by removing solids and other debris; (3) Samples are analyzed using a variety of methods, including polymerase chain reaction (PCR), immunoassays, and chromatography; (4) results of the analysis are interpreted to determine the presence and prevalence of diseases and other health-related substances in the population.  Most of the process is completed manually; this requires expensive lab equipment, technical support to analyze/interpret the data, and has a delayed response time. 

Our solution, INTI, provides a cheaper autonomous testing option that can collect, handle, and test samples locally. This is done by attaching the INTI hardware unit to any wastewater pipe or tank. The hardware system is triggered to pull a 5ml sample at a certain time interval, after an event, or can be triggered manually. Since the entire test only takes 3 minutes from start to finish, multiple tests can be taken throughout the duration of the flight and again immediately upon landing (during the taxiing process). Once the flight is back on the ground, that data can be sent to the cloud, such as Azure, and displayed on a comprehensive and publicly accessible data tracker dashboard or privately accessible dashboard for local authorities/CDC. This is critical because that means that stakeholders do not have to wait 2-8 hours after plane docking for the CDC to receive lab data, instead local institutions can react prior to deboarding so mitigation can be prioritized.

Prior to the deplaning process, local authorities can make strategic decisions based on the data. These aggregated results protect privacy, and the cost affordability allows a high installation rate by even non-aviation stakeholders. By creating an ecosystem of connected devices, we can aggregate diverse data to identify cross-functional public health trends and, in return, improve the existing infrastructure, track subtle trends, geomap contamination, train disease models, and create emergency plans. The testing adds roughly three extra minutes to aircraft maintenance, does not require swabbing passengers, and can be scaled up as needed. INTI is a valuable tool for public health surveillance because it provides a non-invasive and cost-effective way to track the health of a population. The platform technology can also be used to generate data in real-time, which makes it a valuable tool for early detection and rapid response to outbreaks. 

INTI will address the following 5 Targets and Indicators of the UN Sustainable Development Goal 3 for Good Health and Well-Being by acting as a contact tracing and early detection system:

• Target 3.3: The INTI solution will enable quick and early detection of cases for any of the epidemics that are being targeted. The system is run in the wastewater line, so the spread of any waterborne diseases, as well as AIDS, tuberculosis, malaria, neglected tropical diseases, and hepatitis can all be effectively tracked, monitored, and intercepted with INTI
• Target 3.8: INTI will be able to assist in the push for universal, affordable health coverage through earlier detection of diseases, which will lead to a reduction in hospital visits; and therefore, less incurred costs for hospitals treating patients. The earlier detection of diseases could also provide additional time for the study of diseases, giving more time to develop effective vaccines and ensure they are widely available to everyone.
• Target 3.b: Similar to Target 3.8, with the earlier detection and more effective tracking of diseases, we can support the research and development of vaccines and medicines by gaining insight into additional data on the disease, such as trends in transmission, the rate at which they spread, and even help anticipate where the next outbreak would occur.
• Target 3.d: INTI can be the international solution for a non-invasive early warning system for any potential future pandemics, as well as national, day-to-day transmission tracking for diseases and illnesses that are constantly around. This will enable countries to better-prepare for and manage national health risks, and be prepared to immediately start collaborating on mitigation of future global health risks.

The INTI platform's ultimate use of AI technology is the use of a convolutional neural network for the control sampling system and data analysis at a local and system level. Neural networks have been proven to be a valuable tool when used alongside Raman spectroscopy, as it allow the system to optimize the sampling parameters such as the laser strength and integration time, and the preprocessing steps of filtering, principal component analysis, and baseline correction to name a few. Once the data is collected,  a separate neural network algorithm can be used to analyze the data, identifying key features in the Raman spectra that can be used to identify the presence of a contaminant and quantify the amount present. This neural network is particularly useful in cases of environmental or wastewater analysis where the base water sample is likely to vary in composition, turbidity, pH, etc. which will increase the complexity of gathering and analyzing the sample data.

At a system scale, the use of cloud-native computing allows for the INTI hardware to remain relatively simple compared to existing Raman analyzers. Cloud hosting of the sample database and algorithm also allows for continued training of the model and integration into larger systems. All deployed INTI devices will have a communication protocol with the central database, including information on the location and timestamp of the sample taken, this information can be used to create a map of the contamination, allowing for a view and analysis of spread, concurrent occurrences, and environmental data. The cloud database can also be integrated with publicly available databases such as water contamination maps, weather patterns, and air quality maps, creating a holistic view and analysis of the intersection of various environmental parameters and wastewater data.

In developing our INTI solution for monitoring the spread of diseases like COVID-19, we prioritize ethical and responsible AI use. Privacy concerns are addressed through rigorous data anonymization techniques, ensuring personally identifiable information is protected. We adhere to legal standards, including data protection laws like GDPR, and conduct regular privacy impact assessments. Our solution incorporates robust security measures, employing encryption for data transmission and storage, with periodic security audits to identify and address vulnerabilities.

In light of the FAA's Emergency Order for aircraft wastewater testing, we recognize the importance of transparent and explainable AI. The solution utilizes interpretable models to enhance understanding and trust in decision-making processes. Informed consent is a key aspect, and clear communication channels are established with stakeholders, including passengers, to explain the purpose of data collection and provide options for explicit consent. Moreover, ongoing risk assessments involve diverse stakeholders, including legal experts and ethicists, to address emerging challenges and ensure responsible AI practices. We are committed to protecting passenger privacy and limiting data use to public health purposes, aligning with ethical frameworks and legal regulations. As we continue to develop and refine our solution, we remain vigilant in addressing potential risks and contributing to the responsible use of AI in wastewater epidemiology.

Our goal in the next year is to successfully deploy the INTI system in multiple pilot studies to help acquire data for our database and continue to improve our deep learning algorithm.

In the next 5 years, our goal is to be fully-deployed in as many airports, bus terminals, train stations, and public transportation hubs as we can. This will allow us to be completely autonomous and begin our full-time contact tracing for prevention and contimination of the next global pandemic and current national health risks across the globe.

We have 3 individuals working on our team full-time and 3 working part-time. We will be bringing on 2 contractors in the coming weeks to help with some tasks temporarily.

After a company pivot in late 2022, we have been working on this solution for just about 11 months.

Tikal was founded by an Asian/Middle Eastern woman and an Indigenous/Mexican man. We leverage and promote diversity in two predominate ways: (1) Hire multidisciplinary teams that have diverse expertise, identities, ages, skills, and experiences to create a welcoming space where everyone is empowered to share their insight and experience; and (2) Create a cross-functional collaborative space where open dialogue and diverse perspectives enrich discussions and lead to better outcomes. In today's world, embracing diversity is not just the right thing to do, but also a strategic advantage that propels a company's growth, innovation, and overall success.

Tikal is projected to get a total annual gross revenue, including hardware and software sales, of $96,313,145 by 2026. This is based on 7559 INTI base devices being deployed over the next four years, with a 1 rental to 3 purchase ratio in 2026. The pricing for the base unit is $5,800, $9 for consumables, $5 for software platform access per INTI unit, and $6,000 for database access. If a customer chooses to rent the INTI base unit, it is $400/month. Rental contracts are provided in three-month intervals, resulting in $1,200 per device per contract. The current COGS for the hardware are $1,384.49 for the base unit and $6.38 for the consumables; this required 2.71 months for the hardware to break even in the rental model.

1. Hardware Sales: INTI generates revenue by selling its base hardware unit at a price of $5,800 each (COGS: $3,384.49). Customers can purchase these units outright, providing a one-time source of revenue. The INTI platform also has satellite sensor blocks, for air (humidity, CO, NO2, VOC, etc.) and qualitative water monitoring (pH, temp, turbidity, DO, etc.). These are priced at $390/unit (COGS: ~$175/unit). Cost of both are expected to go down once manufacturing is transferred from in-house to contract manufacturers/OEM.

2. Consumable Sales: INTI also generates revenue from the sale of testing cartridges, priced at $650 per unit (COGS: $140). This provides an ongoing source of revenue as customers periodically need to replenish these consumables. This equates to a COGS of $0.0024 per testing panel, assuming no additional fluorescents are required, for a cartridge that can be last for up to 100,000 tests.

3. Software Platform Access Fees: Customers are charged a monthly fee of $5 per deployed base unit for access to INTI's software platform. This subscription-based model ensures a recurring revenue stream as long as customers continue to use the platform.

4. Database Access Fees: INTI charges customers a monthly fee of $6,000 for access to its database.

5. Rental Fees: INTI offers customers the option to rent the base hardware unit for $400 per month, with rental contracts provided in three-month intervals, resulting in $1,200 per device per contract. This rental model generates regular monthly revenue as long as customers choose to rent the hardware.

Tikal Industries is currently working to bring in funding through a combination of two avenues: venture backing and applying for grants. We are in the process of raising a seed round of capital investment and will be going through a Series A raise after that in mid- to late-2024. Additionally, we have a company-wide goal of applying at least 6 grants each quarter to open up some possibilities more for funding.

Long-term, the plan is to use the revenue from the INTI enterprise software subscription to continue to be financially stable. We will be providing the hardware at cost, and relying on our SaaS to make up the losses from the hardware.

Currently, our operating costs are $48k, including human capital, prototyping materials, software subscription services, and business operation costs. Next year, we anticipate a bump in costs to $170k. This will be used in the same way, with the addition of successful deployment of pilots.

An additional $100k in funds will provide us with resources to do additional product development, customer outreach, and general operations in the next year. We will need to purchase additional components and materials for our prototype, as well as our lab bench for data analyzation, keep up our current software subscriptions, fund some customer outreach, and continue using some for human capital.

Having access to The Cure Residency would be an absolutely incredible opportunity for Tikal Industries. The team would be most excited about the mentorship and networking opportunities. Given that our team is small, we are always eager to learn new skills, and the mentorship would definitely provide us with many opportunities the acquire new knowledge about the startup product development process. The networking opportunities would be also be amazing. Building up Tikal's network could help open up some doors to potential pilot testing opportunities or customers, and we would love to be able to return the favor as well down the road.