- Publication strengthens NetraMark's case for biomarker-guided enrichment, individualized response modeling, and explainable AI for trial design in psychedelic clinical development.
TORONTO, April 09, 2026 (GLOBE NEWSWIRE) -- NetraMark Holdings Inc. (the “Company” or “NetraMark”) (TSX: AIAI) (OTCQB: AINMF) (Frankfurt: PF0), a premier artificial intelligence (AI) company transforming clinical trials with AI-powered precision analytics in the pharmaceutical industry, today announced the recent publication of a new peer-reviewed article, “Psychedelics and the Quantum Brain: A Falsifiable Hypothesis on Posner Molecules and Spin-Dependent Pharmacology,” in Frontiers in Pharmacology.
The paper can be found here: Frontiers in Pharmacology.
The publication was led by NetraMark’s Founder and Chief Scientific Officer, Joseph Geraci, PhD, and co-authored by NetraMark’s Chief Innovation and Regulatory Officer, Luca Pani, MD, alongside other academic collaborators. The publication presents a speculative but mechanistically grounded and experimentally testable framework for understanding psychedelic drug response.
The publication’s proposed hypothesis explores whether psychedelic treatment effects in clinical trials may arise from complex, multi-scale biological processes involving calcium signaling, phosphate metabolism, and potentially spin-dependent molecular interactions. Importantly, it examines potential connections between these mechanistic layers and a central but unresolved issue in drug development: substantial inter-individual variability in treatment response.
A key contribution of the publication is its framing of this variability as structured biological heterogeneity, rather than statistical noise. The publication in Frontiers in Pharmacology outlines a translational pathway from:
- mechanistic biological processes,
- to measurable patient-level variability,
- to biomarker-informed clinical trial design and patient stratification.
This framework directly reflects the type of structured biological heterogeneity that NetraMark’s platform is designed to address.
NetraMark’s NetraAI platform is designed to identify explainable, model-derived patient subpopulations within complex clinical datasets. By analyzing relationships across all collected variables simultaneously, NetraAI is designed to uncover structured patterns that define responders, non-responders, and placebo-sensitive groups—supporting prospective incorporations of these insights into clinical trial design and regulatory strategy.
The publication supports a broader potential industry shift: clinical trial success, particularly in central nervous system disorders and emerging areas such as psychedelic therapeutics, may increasingly depend on the ability to identify and act on patient-level heterogeneity, rather than relying on population averages.
For investors, this highlights a growing opportunity tied to technologies that can potentially translate biological complexity into actionable clinical trial strategy.
As pharmaceutical companies are expected to continue to face rising development costs, high failure rates, and increasing regulatory expectations, there is a structural need for technologies that can:
- improve signal detection in small and complex datasets,
- reduce trial risk through better patient selection, and
- support more precise, data-driven development strategies.
NetraMark’s approach focuses on this intersection—aiming to bridge advanced biological insight, AI-driven analytics, and regulatory-aligned clinical trial design.
While the paper introduces a testable hypothesis at the mechanistic level, its broader implication is independent of that hypothesis: future clinical trials stand to benefit from being designed around patient-level variability.
“What this work shows is that variability in clinical trials isn’t a problem—it’s the key to unlocking better outcomes,” said Joseph Geraci. “If you can identify which patients are driving response and why, you can potentially design smarter, more successful trials. That’s the shift we’re focused on potentially enabling with NetraAI.”
NetraMark believes this publication further strengthens the role of explainable AI and precision analytics as essential components of next-generation drug development.
About NetraAI
In contrast to 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. 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
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 design and intended capabilities of NetraMark’s NetraAI platform, including its ability to identify explainable, model‑derived patient subpopulations and uncover structured patterns of patient‑level variability; the potential for insights derived from such analyses to support biomarker‑informed clinical trial design, patient stratification and regulatory strategy; the view that future clinical trials may benefit from being designed around patient‑level variability; the potential growing opportunity for technologies addressing patient‑level heterogeneity; expectations that pharmaceutical companies will face rising development costs, high failure rates and increasing regulatory expectations; and NetraMark’s objective of bridging advanced biological insight, AI‑driven analytics and regulatory‑aligned clinical trial design, 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.com including our Annual Information Form for the year ended September 30, 2025. These risk factors and other factors could cause actual events or results to differ materially from those described in any forward- looking information. The Toronto Stock Exchange does not accept responsibility for the adequacy or accuracy of this release.
Contact Information:
Swapan Kakumanu - CFO | swapan@netramark.com | 403-681-2549
Or
Adam Peeler – Investor Relations | adam.peeler@loderockadvisors.com | 416-427-1235
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