About NeuropathIQ
We built NeuropathIQ because the connections that could accelerate neuroscience research already exist in the literature — they're just invisible. A Parkinson's researcher doesn't read ALS papers. An ALS team doesn't track MS trials. The biology doesn't respect those silos. NeuropathIQ finds what falls between them.
NeuropathIQ transforms publicly available neurological research into structured evidence intelligence—helping researchers discover meaningful cross-disease connections, generate stronger hypotheses, and explore every insight with complete scientific transparency.
Tyler Green founded NeuropathIQ after recognizing a growing challenge during his neuroscience education: the volume of biomedical research has expanded beyond what any individual researcher can realistically synthesize. Important discoveries often remain isolated across diseases, journals, biomarkers, biological pathways, and clinical trials—not because the evidence doesn't exist, but because it is difficult to connect.
He holds a Bachelor of Science in Biology with a concentration in Neurobiology and a Minor in Psychology from the University of Victoria. His academic training included molecular biology, genetics, neuroscience, physiology, cell biology, and psychology, providing a multidisciplinary scientific foundation for understanding neurological disease.
To complement his neuroscience background with advanced computational methods, Tyler completed Stanford University's Certificate in Fundamentals of AI/ML in Precision Medicine, offered through the Department of Genetics and Stanford Data Ocean. The program explored the application of artificial intelligence, machine learning, genomics, transcriptomics, Python, R, and statistical methods to biomedical research and precision medicine.
Inspired by the opportunity to bridge neuroscience and artificial intelligence, Tyler founded NeuropathIQ to organize publicly available biomedical knowledge into a structured evidence architecture built upon biomedical ontologies, knowledge graphs, and explainable AI. The platform is designed to help researchers identify meaningful biological relationships, generate stronger hypotheses, and explore scientific evidence with complete traceability back to the original sources.
Today, Tyler leads the company's strategic vision, scientific direction, and product development with the goal of creating a trusted evidence intelligence platform that supports neurological research worldwide.
Our Vision
NeuropathIQ is building an evidence intelligence platform that helps researchers navigate an increasingly complex scientific landscape with greater speed, confidence, and transparency.
By integrating biomedical literature, clinical trials, biomarkers, biological pathways, ontologies, and explainable artificial intelligence into a unified evidence architecture, NeuropathIQ aims to support researchers in discovering meaningful biological relationships that may accelerate scientific progress across neurological disease.
We believe the future of neurological research will not be defined solely by generating more data—but by connecting existing knowledge in ways that reveal new opportunities for discovery.
"The next neurological breakthrough may already exist within today's scientific evidence. Our mission is to help researchers discover the connections that bring it to light."
— Tyler Green, Founder & CEO, NeuropathIQ
The problem we're solving
There are 35 million neuroscience papers on PubMed. 480,000 clinical trials on ClinicalTrials.gov. $50 billion in NIH grants. Every week, 1,800 new papers are published across neurology. No individual researcher, and no research team, can read everything relevant to their work — let alone everything relevant to a different disease that shares the same biological mechanism.
The result is that connections that could accelerate every program by years go undiscovered. A shared RNA delivery mechanism between ALS and Huntington's trials. A glymphatic clearance pathway connecting Parkinson's and Alzheimer's research. A neuroinflammation biomarker panel validated in MS trials that nobody has tested in ALS. NeuropathIQ finds them.
How the platform works
NeuropathIQ runs a nightly pipeline that pulls from public data sources, normalizes every record into a unified schema, and surfaces AI-identified patterns across diseases. Every connection displays the specific papers and trials that support it. Confidence tiers (Exploratory / Emerging / Supported) tell researchers exactly how much independent verification each insight requires.
Critically, NeuropathIQ never reproduces copyrighted full text. We display titles, authors, abstracts (where permitted), DOIs, and links to the original source. All AI insights are original derived analysis — not reproduced publisher content.
Important disclaimer
For research inquiries or partnership opportunities, visit our contact page or email hello@neuropathiq.ai.