Northwire Canada EditionFriday, July 17, 2026
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LUN 33.59 −2.5% NTR 94.27 −1.8% LALI 0.055 −8.3% SCD 0.170 +0.0% HWY 0.370 +0.0% FCI 0.385 +1.3% GGAU 0.180 −5.3% KIRO 0.650 +1.6% LBNK 0.430 +0.0% BARU 0.040 +0.0% VCU 1.09 −4.4% NOBL 0.095 −5.0% SHL 0.355 +0.0% MTS 0.130 +0.0% FYL 0.090 +0.0% NUAG 5.55 +1.8% LUN 33.59 −2.5% NTR 94.27 −1.8% LALI 0.055 −8.3% SCD 0.170 +0.0% HWY 0.370 +0.0% FCI 0.385 +1.3% GGAU 0.180 −5.3% KIRO 0.650 +1.6% LBNK 0.430 +0.0% BARU 0.040 +0.0% VCU 1.09 −4.4% NOBL 0.095 −5.0% SHL 0.355 +0.0% MTS 0.130 +0.0% FYL 0.090 +0.0% NUAG 5.55 +1.8%
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NetraAI Study Accepted for Publication in npj Digital Medicine, Part of the Nature Portfolio

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Executive Summary

  • NetraMark Holdings announced that its peer‑reviewed paper on the NetraAI platform has been accepted for publication in npj Digital Medicine (Nature Portfolio).
  • The study demonstrates how NetraAI can identify interpretable patient subpopulations (“Personas”/MDS) to improve precision enrichment in a Phase II ketamine trial for treatment‑resistant depression.
  • Company executives highlighted the significance of explainable AI for regulatory science and clinical‑trial design.

Key Details

  • Publication: “Explainable AI-Driven Precision Clinical Trial Enrichment: Demonstration of the NetraAI Platform with a Phase II Depression Trial,” accepted by npj Digital Medicine.
  • Data Source: National Institute of Mental Health (NIMH) Phase II ketamine trial in treatment‑resistant depression.
  • Key Findings: NetraAI uncovered interpretable “Personas” that may guide precision‑enrichment strategies across psychiatry and other therapeutic areas; integration of dynamical‑systems modeling, long‑range‑memory feature learning, and LLM explainability improves decision‑making and reduces placebo interference.
  • Co‑authors: Researchers from NIMH (Dr. Elizabeth D. Ballard, Dr. Carlos A. Zarate Jr.) plus NetraMark scientists and academic collaborators.
  • Executive Comments:
  • Dr. Joseph Geraci (Chief Scientific & Technical Officer) – emphasized the paper’s role in validating the AI engine for clinical trials.
  • Dr. Luca Pani (Chief Innovation & Regulatory Officer) – noted the importance of explainability, reproducibility, and traceability for regulators and investigators.
  • Access: Full article available at https://www.nature.com/articles/s41746-025-02143-7.

Notable Quotes

“Acceptance of this paper for publication by npj Digital Medicine affirms the progress we’ve made toward building an AI engine purpose‑built for clinical trials.” – Dr. Joseph Geraci, CSO & CTO

“This publication bridges scientific innovation with the rigorous expectations of regulatory science…provides regulators and clinical investigators with credible tools designed to support modern clinical trial design and decision‑making.” – Dr. Luca Pani, Chief Innovation and Regulatory Officer

Read the original news release →

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