IGC Pharma Expands AI Platform With Advanced Diagnostic Model for Alzheimer's and Dementia Detection

Rhea-AI Summary

IGC Pharma has announced the development of a new AI-driven diagnostic model for improved detection of Alzheimer's disease and other forms of dementia. The model aims to address current diagnostic challenges that often rely on invasive procedures and subjective assessments.

The AI platform integrates clinical datasets from leading research databases including NACC, ADNI, and PPMI. It analyzes multiple data points such as neuroimaging biomarkers, cognitive assessments, genetic risk factors, and medical history using transformer-based neural networks to deliver personalized diagnostic insights.

With dementia affecting over 55 million people worldwide and Alzheimer's accounting for 60-80% of cases, this initiative represents part of IGC Pharma's broader AI strategy in neurodegenerative disease research. The company aims to reduce misdiagnosis rates and enable earlier, more accurate treatment interventions.

Positive

• Development of new AI diagnostic platform for potential market expansion
• Strategic positioning in the growing neurodegenerative disease market
• Access to multiple established research databases for AI model training

Negative

• No immediate revenue impact mentioned
• Model still in development phase with no proven clinical validation
• Uncertain timeline for commercial implementation

POTOMAC, MD / ACCESS Newswire / March 4, 2025 / IGC Pharma, Inc. ("IGC" or the "Company") (NYSE American:IGC) today announced an advancement in its Artificial Intelligence ("AI") platform with the development of a new AI-driven model designed to improve the diagnosis of Alzheimer's disease (AD) and other causes of dementia. With Alzheimer's accounting for approximately 60-80% of all dementia cases, alongside other conditions such as vascular disease, Lewy body disease, and frontotemporal degeneration, accurate diagnosis is critical to ensuring the right treatment strategy.

Dementia affects over 55 million people worldwide, causing progressive cognitive decline, memory loss, and behavioral changes. Despite its widespread impact, current diagnostic methods often rely on invasive procedures, expensive imaging, and subjective clinical assessments, leading to high rates of misdiagnosis and delayed treatment.

IGC Pharma's cutting-edge AI model is designed to address these challenges by integrating vast clinical datasets and leveraging deep learning algorithms to distinguish between the different diseases that cause dementia. By reducing false negatives and misdiagnoses, the model has the potential to significantly improve early detection, ensuring patients receive the right treatment at the right time.

The AI model is being trained on multi-modal clinical data from leading public research databases, including the National Alzheimer's Coordinating Center (NACC), the Alzheimer's Disease Neuroimaging Initiative (ADNI), and the Parkinson's Progression Markers Initiative (PPMI), among others.

By analyzing neuroimaging biomarkers, cognitive assessments, genetic risk factors, medical history, neurological exams, and demographic information, IGC Pharma's AI-driven approach enables a more precise and scalable diagnostic framework. Using state-of-the-art transformer-based neural networks, the model's architecture is designed to process diverse patient data while compensating for missing information-delivering reliable, personalized insights across different patient populations.

"The AI model is a potential game changer for our growth strategy. Our AI platform is a key driver of IGC Pharma's long-term growth strategy, reinforcing our commitment to precision medicine and targeted treatments for neurodegenerative diseases," said Ram Mukunda, CEO of IGC Pharma. "Misdiagnosis remains a significant challenge, often delaying treatment for patients who need it most. Our AI-driven model aims to close this gap, ultimately improving patient outcomes."

This initiative is part of IGC Pharma's broader AI strategy, positioning the company at the forefront of innovation in Alzheimer's research. The development of an AI foundation model for Alzheimer's disease and dementia detection represents a transformative step forward, not only in advancing medical breakthroughs but also in enhancing the Company's long-term value and leadership in AI-driven healthcare solutions.

About IGC Pharma (dba IGC):
IGC Pharma is an AI-powered, clinical-stage biotechnology company focused on developing innovative treatments for Alzheimer's disease and transforming patient care with fast-acting, safe, and effective solutions. Our portfolio includes the TGR family, including TGR-63, which targets amyloid plaques, a hallmark of Alzheimer's. The IGC-C and IGC-M platforms are advancing in preclinical studies, focusing on metabolic disorders, tau proteins, early plaque formation, and multiple disease hallmarks. Our lead therapeutic candidate, IGC-AD1, is a cannabinoid-based treatment currently in a Phase 2 trial for agitation in dementia ("CALMA") associated with Alzheimer's (clinicaltrials.gov, IGC Pharma Phase II). Interim data for IGC-AD1 demonstrated that it has the potential to transform patient care by offering faster-acting and more effective relief compared to traditional medications. Additionally, our AI models are designed to predict potential biomarkers for the early detection of Alzheimer's, optimize clinical trials, and predict receptor affinity, among others. With 32 patent filings and a commitment to innovation, IGC Pharma is dedicated to advancing pharmaceutical treatments and improving the lives of those affected by Alzheimer's and related conditions. The Company operates a wellness brand offering scientifically formulated products under the brand Holiby™ and as white-labeled formulations.

Forward-Looking Statements
This press release contains forward-looking statements. These forward-looking statements are based largely on IGC Pharma's expectations and are subject to several risks and uncertainties, certain of which are beyond IGC Pharma's control. Actual results could differ materially from these forward-looking statements as a result of, among other factors, the Company's failure or inability to commercialize one or more of the Company's products or technologies, including the products or formulations described in this release, or failure to obtain regulatory approval for the products or formulations, where required, or government regulations affecting AI or the AI algorithms not working as intended or producing accurate predictions; general economic conditions that are less favorable than expected; the FDA's general position regarding cannabis- and hemp-based products; and other factors, many of which are discussed in IGC Pharma's U.S. Securities and Exchange Commission ("SEC") filings. IGC incorporates by reference its Annual Report on Form 10-K filed with the SEC on June 24, 2024, and on Form 10-Q filed with the SEC on August 7, 2024, as if fully incorporated and restated herein. Considering these risks and uncertainties, there can be no assurance that the forward-looking information contained in this release will occur.

Contact Information
Rosalyn Christian / Walter Frank
IMS Investor Relations
igc@imsinvestorrelations.com
(203) 972-9200

SOURCE: IGC Pharma, Inc.

View the original press release on ACCESS Newswire

FAQ

What is IGC Pharma's new AI diagnostic model designed to detect?

The AI model is designed to detect and distinguish between Alzheimer's disease and other forms of dementia through analysis of clinical data and biomarkers.

Which databases is IGC's AI model being trained on?

The model is being trained on data from the National Alzheimer's Coordinating Center (NACC), Alzheimer's Disease Neuroimaging Initiative (ADNI), and Parkinson's Progression Markers Initiative (PPMI).

What types of data does IGC's AI diagnostic platform analyze?

It analyzes neuroimaging biomarkers, cognitive assessments, genetic risk factors, medical history, neurological exams, and demographic information.

How does IGC's new AI model aim to improve current dementia diagnosis methods?

It aims to reduce false negatives and misdiagnosis by using deep learning algorithms to process diverse patient data, offering more precise and scalable diagnostics compared to traditional invasive procedures.