NETRAMARK HOLDINGS INC. – Market validation of the NetraAI clinical solution through the signing of five contracts with biopharmaceutical companies –
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– Presented results demonstrating the power of NetraAI to identify novel biomarkers and improve clinical trial success rates at two prominent scientific conferences –
"In leading the way for AI-based solutions to drive clinical trial success, 2024 is shaping up to be transformational for NetraMark," said
Corporate Updates
- Launched NetraAI Lab to make it easier and more affordable for biopharmaceutical companies to experience how NetraMark's proprietary NetraAI solution can improve clinical trial success rates and inform the protocol design for a subsequent phase, highlights include:
- Analyzes customer's clinical data to identify key variables that drive protocol design insights around efficacy, toxicity, and placebo response in four weeks.
- Uniquely engineered to include mathematically based focus mechanisms that separate small datasets into explainable and unexplainable subsets with the potential to provide highly statistically significant insights.
- As previously announced, signed contracts with leading biopharmaceutical companies totaling $1M CDN
- Revenue will be recognized over a period of time, as services are delivered commencing in the fiscal quarter ending
March 31, 2024 .
- Revenue will be recognized over a period of time, as services are delivered commencing in the fiscal quarter ending
- Demonstrates growing industry recognition of the potential for NetraAI's differentiated self-learning approach to improve clinical trial success rates.
- Generates insights based on companies' own clinical data rather than large training data sets that are not optimized to identify variables.
- Potential to improve efficacy size effects while reducing placebo and toxicity effects, increasing clinical trial success rates.
- Highlights NetraMark's business development capabilities and supports growth of the Company's referral and new prospect network.
Data Presentations
- Presented results at AD/PD™
International Conference on Alzheimer's and Parkinson's Diseases 2024, further establishing NetraAI's clinical ability to identify highly relevant disease subtypes that drive clinical trial success or failure.- NetraAI identified genetic drivers within specific Parkinson's disease (PD) patient subpopulations and uncovered pivotal disease pathways, enhancing understanding of disease and treatment strategies.
- NetraAI identified genetic drivers within specific Parkinson's disease (PD) patient subpopulations and uncovered pivotal disease pathways, enhancing understanding of disease and treatment strategies.
- Announced results at the
International Society for CNS Clinical Trials and Methodology (ISCTM) 20th Annual Meeting, validating NetraAI's capacity to enable more efficient clinical development of therapies to treat patient populations with complex psychiatric disorders (research posters found here)- Data from a schizophrenia clinical trial use case showed that NetraAI delivered insights regarding variables driving placebo and drug responses.
- While only 30% of the subpopulation identified by these variables was explainable, the application of these variables to a model of a larger trial is predicted to have a substantial impact on statistical significance — a reduction in p-value from 0.04 to 0.0019.
- Data from a schizophrenia clinical trial use case showed that NetraAI delivered insights regarding variables driving placebo and drug responses.
- Published peer-reviewed data in Frontiers in Computational Neuroscience validating the evidence behind NetraAI's ability to provide key insights that drive clinical trial success.
- NetraAI detected novel potential therapeutic targets for amyotrophic lateral sclerosis (ALS) that were not identified using other AI-based methods.
- Identified well-defined subpopulations that could improve ALS clinical trial outcomes.
- Results were derived from 116 patients, demonstrating the unique power of the platform compared with other AI methods that required large data inputs.
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 have the potential to 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.
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).
This press release contains "forward-looking information" within the meaning of applicable Canadian securities legislation including statements regarding the Company's objectives under the
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
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