NeuBIo is a precision Neurobiology company.

NeuBio has discovered new biomarkers that will transform the detection and treatment of neurological diseases.

NeuBio’s IP portfolio comprises 141 mRNA biomarkers with the highest accuracy and reproducibility ever documented across:

i) Parkinson’s Disease (“PD”)

ii) Alzheimer’s Disease (“AD”)

iii) Amyotrophic Lateral Sclerosis (“ALS” or “Lou Gehrig's Disease”)

NeuBio is developing the world’s first objective blood tests for PD, AD, and ALS.

In parallel, a subset of NeuBio’s biomarker discoveries have been identified as novel drug targets. NeuBio is investigating these drug targets and prioritizing them by utility and druggability.

Neurological diseases are the #1 cause of global disability.

Conditions such as Parkinson’s Disease (PD), Alzheimer’s Disease (AD), and Amyotrophic Lateral Sclerosis (ALS) remain uncurable and lack disease-modifying treatments and early-stage detection and diagnostic tests.

Neurological diseases are highly diverse and complex, with many different genetic and physical factors contributing to their development. To date, medical approaches have focused on the later stages of these diseases when they are clinically observational.

The challenge with this is it’s too late, the diseases have taken hold, symptom management is the patient focus and disease-modifying efforts lack the knowledge of the underlying biology. This lack of understanding has led to Neurology having the highest failure rate in clinical trials in all of healthcare, over 95%.

Tackling the unmet needs in Neurology requires a paradigm shift in focus to understanding the early prodromal stages and the root biology of these diseases.

Disease modeling and technology have led to the emergence of precision medicine, NeuBio has found the solution to create Precision Neurology, more specifically Precision Neurobiology.

Because there is no biological understanding of neurological disorders the window into neurological disorders is limited to symptomologies such as Tremors or Cognitive Decline and Familial Genetic Mutations.

The challenge for patients, pharma, payors, and physicians is this is too late and too little In the case of PD, for example, the disease can take be present for 20 years prior to the onset of visible symptoms such as tremors. Similarly, AD can be present in a patient for many years prior to the onset of detectible cognitive decline.

Familial genetic mutations are involved in a very small percentage of overall disease incidence.

Exacerbating things further is our ability to detect and diagnose these disorders is limited to subjective modalities such as clinical observation, and costly, inaccurate imaging procedures, which rely on subject interpretation. Both carry unacceptably high misdiagnosis rates and diagnosis can take years.

The absence of objective diagnostic tools represents one of the single largest obstacles to successful drug development and clinical trials.

There are currently 1,000+ active clinical trials across AD, PD, and ALS. With pharma spending an average of ~$200k per patient per trial, and misdiagnosis/trial failure rates higher than any other field of medicine, the market need for objective diagnostics is acute and significant.

NeuBio's intellectual property represents a breakthrough in understanding the complex variables driving neurological disorders and their progression. The company's blood tests offer accurate and objective diagnoses, as well as precise predictions of disease progression and patient stratification. These diagnostic tests are designed to be standard, non-invasive blood tests that do not require new technology or specialized equipment, making them easily deployable on a large scale.

NeuBio's biomarker discoveries provide invaluable insights into the biological, environmental, and behavioral factors driving disease causality and progression, which is critical for the development of effective therapies. Additionally, NeuBio's biomarkers are the first known biological compounds to reproduce across both whole blood and post-mortem brain tissue, providing unprecedented accuracy and reproducibility.

The company's biomarkers have been extensively validated against six distinct NIH-published datasets, demonstrating superior accuracy compared to the original authors' biomarker discoveries. NeuBio's biomarkers underwent three separate validation phases on each of the six datasets, providing a total of 18 validation steps for their Parkinson's disease biomarkers alone. This rigorous validation process ensures the reliability and accuracy of NeuBio's diagnostic and prognostic pipeline of products.

Overall, NeuBio's tools provide a reliable and effective means of de-risking drug development, rescuing failed drugs, and ensuring the right patients are in the right trials at the right time. Furthermore, these tools do not require the development or use of new technology or standards, making them accessible and easy to implement in a variety of clinical settings.

AI is everywhere, couldn't other A.I. methodologies, neural networks, and other and statistical techniques accomplish the same thing as NeuBio seems to be a reasonable question.

Neural networks are often lauded for their ability to approximate any function. However, their accuracy is limited in a significant and consequential way. The resulting algorithms are not true models, and their accuracy is restricted to circumstances where new input data falls within the same range as the training data.

To illustrate this limitation, consider predicting cannonball distances based on cannon firing data (angle, muzzle velocity, and wind). If the neural network is trained on data with cannon angles between 12 and 75 degrees, it may perform well within this range. However, when predicting distances for angles outside this range, the algorithm is likely to fail. This is due to the fact that all the parameters (angle, velocity, wind) can vary greatly, and it is unlikely that new circumstances will fit within the training data ranges for the combinations of these three inputs.

This limitation is not hypothetical. In a simplified ballistics dataset that did not include wind as a factor, all other AI, machine learning, and statistics approaches failed on the out-of-sample (outside of training) cannon data. However, NeuBio's technology partner was able to use the same training data to produce an exact mathematical equivalent of the cannonball trajectory.

Neural networks must approximate because they lack access to math functions that reflect real-world dynamics. To model physical phenomena accurately, these networks require the necessary math functions to be available to them, which is often not the case in biology and medicine.

This issue is especially important in biological modeling, as traditional methods like regression and neural networks struggle to capture complex interactions between variables. They also have difficulty modeling exponential, logarithmic, or discontinuous relationships between variables and outcomes, resulting in reduced accuracy. These methods approximate relationships seen in training data, which may fail when new data falls outside the training range.

In healthcare, this limitation can have severe consequences. When new patients have biomarker measurements outside the training range, the approximation is likely to fail catastrophically. This is especially true for patients at the extremes, such as those in the early or severe stages of a disease, where treatment opportunities are greatest, or failure to diagnose can be deadly.

To address these challenges, NeuBio leverages a "model-free architecture" that does not require prior assumptions about the model structure, necessary math, variables, or constants. This flexibility allows for a better representation of complex biological interactions and relationships, providing a more reliable alternative, particularly in the early or severe stages of a disease.

Neurobiology is the scientific study of the nervous system, including the brain, spinal cord, and peripheral nervous system. This field is interdisciplinary, drawing on concepts from biology, neuroscience, psychology, and genetics to understand how the nervous system works at the molecular, cellular, and systems levels.

Neurobiologists investigate a wide range of topics related to the nervous system, including the structure and function of neurons, the mechanisms of neuronal communication, the development of the nervous system, and the neural basis of behavior and cognition. They use a variety of techniques to study the nervous system, including electrophysiology, neuroimaging, molecular biology, and genetic engineering.

Neurobiology has important applications in a variety of fields, including medicine, psychology, and artificial intelligence. Understanding the nervous system is essential for developing treatments for neurological disorders, such as Alzheimer's disease and Parkinson's disease, and for developing new technologies that are inspired by the brain, such as neural prosthetics and brain-machine interfaces.

Biomarkers are measurable characteristics of the human body, indicative of disease, infection, and environmental exposure.

Biomarkers are the fundamental guideposts for the medical community to understand disease and inform research and enable effective diagnostic and drug development.

There are a variety of reasons as to why NeuBio focuses on mRNA:

• mRNA serves as a reflection of the body's response to behavior and environment, revealing links to DNA and proteins related to diseases.

• mRNA corresponds to the entire profile of patient populations affected by neurological disorders. DNA mutations account for merely 10-25% of Parkinson's disease (PD), Amyotrophic Lateral Sclerosis (ALS), and Alzheimer's disease (AD) patients and are neither diagnostic nor prognostic indicators.

• Unlike mRNA, DNA remains unchanged throughout an individual's life and does not represent the body's response to behavior or environment.

• mRNA circulates through various organs and can be non-invasively collected and accurately measured from peripheral blood. The company has demonstrated its ability to use the same mRNA across multiple organs to identify patients with specific disorders.

• mRNA has direct protein analogs, meaning that when the company identifies mRNA, it also pinpoints the corresponding protein, which is then included in its intellectual property filings.

• The mRNA diagnostic technology field has undergone significant advancements in the past five years. The standard equipment and methodologies needed to develop an assay that accurately measures biomarkers are now both cost-effective and increasingly efficient.