TORONTO, Feb. 18, 2025 /CNW/ - NetraMark Holdings Inc. (the "Company" or "NetraMark") (CSE: AIAI) (OTCQB: AINMF) (Frankfurt: 8TV) a generative AI software leader in clinical trial analytics, announces that it will present new data supporting its mathematically augmented machine learning (ML) tools that enhance predictive modeling and patient stratification in psychiatric clinical trials. The data will be presented at the International Society for CNS Clinical Trials and Methodology (ISCTM) 21st Annual Scientific Meeting, February 19-21 in Washington, DC.
NetraMark Holdings Inc. logo (CNW Group/NetraMark Holdings Inc.)
Dr. Larry Alphs, Chief Medical Officer (CMO) of NetraMark, will present new data from well known major depressive disorder (MDD) and schizophrenia studies, which will be reported in two poster presentations.
"This innovative AI-driven approach has the potential to transform the way CNS clinical trials are designed and analyzed. By harnessing the power of advanced ML, NetraAI can deconstruct heterogenous patient populations into actionable subgroups, leading to more accurate predictions with the opportunity to identify more effective treatments for patients with psychiatric disorders," said Dr. Larry Alphs, CMO of NetraMark.
Poster Presentation Information Title: Novel machine learning approach outperforms traditional approaches in major depressive disorder clinical trials: Identifying subpopulations based on treatment response
Date and Time: Thursday, February 20, 2025, 5:45pm
Key Insights: CNS disorder clinical trials struggle with patient heterogeneity, reducing the ability to identify effective treatments. Traditional ML models show moderate accuracy in predicting treatment responses in MDD. NetraMark's sub-insight learning approach, powered by dynamical systems and attention mechanisms, improved model accuracy by approximately 28% and significantly increased specificity, sensitivity, and AUC scores.
Title: Predictive biomarker discovery in schizophrenia using advanced machine learning to decode heterogeneity: Analysis of the CATIE schizophrenia trial.
Date and Time: Thursday, February 20, 2025, 5:45pm
Key Insights: Heterogeneity of schizophrenia makes identifying treatment-responsive subpopulations difficult with traditional ML methods. Using data from the CATIE schizophrenia trial, NetraMark's sub-insight learning approach identified clinically meaningful subpopulations characterizing olanzapine or perphenazine response based on key variables. A rigorous replication study was performed to evaluate NetraAI's ability to produce robust models that ensure separation between control and drug arms.
About NetraAI In contrast with other AI-based methods, NetraAI is uniquely engineered to include focus mechanisms that separate small datasets into explainable and unexplainable subsets. Unexplainable subsets are collections of patients that can lead to suboptimal overfit models and inaccurate insights due to poor correlations with the variables involved. The NetraAI uses the explainable subsets to derive insights and hypotheses (including factors that influence treatment and placebo responses, as well as adverse events) that can significantly increase the chances of a clinical trial success. Other AI methods lack these focus mechanisms and assign every patient to a class, even when this leads to "overfitting" which drowns out critical information that could have been used to improve a trial's chance of success.
About NetraMark NetraMark is a company focused on being a leader in the development of Generative Artificial Intelligence (Gen AI)/Machine Learning (ML) solutions targeted at the Pharmaceutical industry. Its product offering uses a novel topology-based algorithm that has the ability to parse patient data sets into subsets of people that are strongly related according to several variables simultaneously. This allows NetraMark to use a variety of ML methods, depending on the character and size of the data, to transform the data into powerfully intelligent data that activates traditional AI/ML methods. The result is that NetraMark can work with much smaller datasets and accurately segment diseases into different types, as well as accurately classify patients for sensitivity to drugs and/or efficacy of treatment.
For further details on the Company please see the Company's publicly available documents filed on the System for Electronic Document Analysis and Retrieval (SEDAR).
Forward-Looking Statements This press release contains "forward-looking information" within the meaning of applicable Canadian securities legislation including statements regarding the potential improvements and success arising from NetraAI and its ability to improve patient outcomes, the identification of effective treatments, operational results and the design clinical trials, which are based upon NetraMark's current internal expectations, estimates, projections, assumptions and beliefs, and views of future events. Forward-looking information can be identified by the use of forward-looking terminology such as "expect", "likely", "may", "will", "should", "intend", "anticipate", "potential", "proposed", "estimate" and other similar words, including negative and grammatical variations thereof, or statements that certain events or conditions "may", "would" or "will" happen, or by discussions of strategy. Forward-looking information includes estimates, plans, expectations, opinions, forecasts, projections, targets, guidance, or other statements that are not statements of fact. The forward-looking statements are expectations only and are subject to known and unknown risks, uncertainties and other important factors that could cause actual results of the Company or industry results to differ materially from future results, performance or achievements. Any forward-looking information speaks only as of the date on which it is made, and, except as required by law, NetraMark does not undertake any obligation to update or revise any forward-looking information, whether as a result of new information, future events, or otherwise. New factors emerge from time to time, and it is not possible for NetraMark to predict all such factors.
When considering these forward-looking statements, readers should keep in mind the risk factors and other cautionary statements as set out in the materials we file with applicable Canadian securities regulatory authorities on SEDAR at www.sedarplus.ca including our Management's Discussion and Analysis for the year ended September 30, 2024. These risk factors and other factors could cause actual events or results to differ materially from those described in any forward-looking information.
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