Mr. Josh Spiegel reports

NETRAMARK SIGNS CONTRACT WITH PHARMACEUTICAL COMPANY TO DELIVER CLINICAL TRIAL INSIGHTS REGARDING EFFICACY AND PLACEBO RESPONSE

Netramark Holdings Inc. has signed a NetraAI lab contract with a pharmaceutical company (the sponsor) to use NetraAI to analyze phase 2 clinical trial data, and deliver key insights and testable hypotheses with the potential to derisk further development of the sponsor's asset.

"We recently launched the NetraAI lab offering with the intention of demonstrating our ability to quickly prove the value of NetraAI to analyze customer's clinical data, and identify key variables that drive efficacy, toxicity and placebo responses in only four weeks. This contract demonstrates the interest by the industry to use their own data to validate leading-edge solutions such as ours," said Josh Spiegel, president of Netramark. "NetraAI is uniquely designed to address clinical trial challenges by identifying the key variables that drive efficacy and placebo response and provide testable hypotheses that explain these findings. We believe that insights generated through our analysis of the data can potentially de-risk the future clinical development of one of the pharmaceutical company's assets and support their effort to bring new therapies to patients."

Under the scope of this project, the sponsor has provided Netramark with data from patients who participated in a completed phase 2 clinical trial of a specific therapy and Netramark applied its proprietary NetraAI clinical solution to the data to achieve five key objectives:

• Characterizing the drivers of placebo and treatment responses;
• Feature significance testing;
• Extracting personas that characterize placebo responders/treatment non-responders (PRTNR) and placebo non-responders/treatment responders (PNRTR);
• Creating probability-density distribution maps of key factors across all patients in placebo and treatment arms, in order to enable enrichment criteria for future trials;
• Establishing a data environment that enables continued exploration of the data.

Netramark will identify key inclusion/exclusion criteria that are predicted with high statistical confidence. Use of these criteria in future trials is expected to increase the number of PNRTR subjects while reducing the number of PRTNR subjects, enabling the trial to potentially demonstrate significant efficacy in a smaller, better-defined patient population.

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 Holdings Inc.

Netramark is a company focused on being a leader in the development of generative artificial intelligence/machine learning 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 data sets and accurately segment diseases into different types as well as accurately classify patients for sensitivity to drugs and/or efficacy of treatment.

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