Dr. Luca Pani reports

NETRAMARK COMMENTS ON U.S. EXECUTIVE ORDER TO ACCELERATE TREATMENTS FOR SERIOUS MENTAL ILLNESS AND HIGHLIGHTS THE NEED FOR REGULATORY-GRADE TRIAL DESIGN IN PSYCHEDELIC DEVELOPMENT

Netramark Holdings Inc. has commented on the April 18, 2026, U.S. Executive Order, "Accelerating Medical Treatments for Serious Mental Illness," which outlines federal actions intended to accelerate research, evidence generation and appropriate regulatory pathways for certain investigational psychedelic drugs for serious mental illness, including programs involving ibogaine compounds.

The executive order references several measures intended to support responsible development, including U.S. Food and Drug Administration (FDA) review prioritization mechanisms for psychedelic drugs that have received breakthrough therapy designation and actions to expand evidence generation and clinical trial participation through collaboration among the U.S. Department of Health and Human Services (HHS), the FDA, and the Department of Veterans Affairs.

Netramark believes these developments underscore a broader shift in mental health drug development: accelerated interest in novel mechanisms must be matched by more rigorous and modern clinical trial design, particularly in central nervous system (CNS) indications where heterogeneity, expectancy effects and placebo response can obscure true treatment effects.

"Speed is important, but in regulatory science the real objective is credible evidence," said Dr. Luca Pani, chief innovation and regulatory officer at Netramark. "Psychedelic trials are among the most methodologically sensitive in medicine, highly dependent on patient heterogeneity, site effects and placebo/expectancy dynamics. If we want faster access for patients while preserving FDA's evidentiary bar, we need prospectively defined analytic strategies that improve signal detection without sacrificing interpretability: prespecified subgroup hypotheses, disciplined control of multiplicity and Type I error, and transparent, auditable methods that regulators and clinicians can interrogate."

Netramark's proprietary NetraAI platform is designed to address these challenges by seeking to identify explainable patient subpopulations that may drive differential treatment response. By aiming to isolate compact sets of interacting variables that characterize distinct outcome patterns, NetraAI supports the development of prospectively testable hypotheses and seeks to inform trial design options such as stratified randomization, prespecified subgroup analyses and enrichment strategies where appropriate.

As clinical development activity expands for psychedelic drug programs and other emerging CNS therapeutics, Netramark believes that advanced, explainable analytics will become increasingly important to help sponsors design studies that are both more efficient and more reliable supporting evidence packages that stand up to regulatory scrutiny and translate into real-world clinical value.

About NetraAI

In contrast to other AI-based (artificial intelligence) methods, NetraAI is uniquely engineered to include focus mechanisms that separate small data sets 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. NetraAI uses explainable subsets to derive insights and hypotheses (including factors that influence treatment and placebo responses and adverse events), potentially increasing the likelihood of a clinical trial's success. Many other AI methods lack these focus mechanisms and assign every patient to a class, often leading 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 (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 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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