Personalized Neuropsychiatric Treatment and Risk Assessment Platform

Publication ID: 24-11857322_0010_PTD

Published: November 07, 2025

Category:Future Evolutions & Paradigm Shifts

Legal Citation

pr1or.art Inc., “Personalized Neuropsychiatric Treatment and Risk Assessment Platform,” Published Technical Disclosure No. 24-11857322_0010_PTD, Published November 07, 2025, available at https://archive.pr1or.art/24-11857322_0010_PTD

This technical disclosure describes improvements that would be readily apparent to a Person Having Ordinary Skill In The Art (PHOSITA) when considered in combination with the foundational architecture disclosed in U.S. Patent No. 11,857,322.

Summary of the Inventive Concept

A next-generation platform integrating genomics, machine learning, and wearable technology to revolutionize neuropsychiatric diagnosis, treatment, and prevention.

Background and Problem Solved

The original patent disclosed systems and methods for screening, diagnosing, and stratifying patients with neuropsychiatric diseases. However, these methods relied on traditional Bayesian decision lists and lacked the precision and personalization offered by modern genomics and machine learning. The new inventive concept addresses this limitation by leveraging cutting-edge technologies to provide more accurate and effective treatment plans.

Detailed Description of the Inventive Concept

The platform consists of four interconnected components: (1) a neural network trained on genomic data and patient outcomes, predicting optimal treatment regimens; (2) a machine learning algorithm analyzing genomic data and medical history to generate a neuropsychiatric disease risk score; (3) a wearable device tracking physiological and behavioral responses to treatment, with a cloud-based analytics platform adapting the treatment plan accordingly; and (4) a graph-based machine learning algorithm identifying novel therapeutic targets for neuropsychiatric diseases. These components enable personalized treatment planning, real-time monitoring, and adaptation of treatment plans.

Novelty and Inventive Step

The new claims introduce a paradigm shift in neuropsychiatric diagnosis and treatment by integrating genomics, machine learning, and wearable technology. The inventive concept's novelty lies in its ability to provide personalized treatment plans based on unique genomic profiles, predict disease risk scores, and adapt treatment plans in real-time.

Alternative Embodiments and Variations

Alternative embodiments may include the use of different machine learning algorithms, integration with electronic health records, or incorporation of additional data sources such as environmental or lifestyle factors. Variations may also include the development of specialized platforms for specific neuropsychiatric diseases or the creation of a decentralized platform for secure data sharing and collaboration.

Potential Commercial Applications and Market

The personalized neuropsychiatric treatment and risk assessment platform has vast commercial potential in the healthcare industry, particularly in the fields of precision medicine, digital therapeutics, and genomic research. The target market includes pharmaceutical companies, research institutions, and healthcare providers seeking to improve patient outcomes and reduce treatment costs.

Section 103 Obviousness Analysis (PHOSITA)

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Field of Art

Neuropsychiatric diagnostic systems, machine learning for medical diagnostics, and computational healthcare technologies involving predictive analytics and personalized medicine

Person of Ordinary Skill (PHOSITA) Profile

A skilled practitioner with expertise in machine learning, computational biology, medical informatics, and neural network design, typically holding a PhD or equivalent industry experience in biomedical engineering or computer science with specialization in healthcare AI

Obviousness Rationale

A PHOSITA would recognize that the PTD's disclosed variations represent predictable extensions of the source patent's foundational diagnostic methodology by applying standard machine learning techniques to enhance patient screening and treatment recommendation systems. The integration of genomic data, wearable technology, and adaptive machine learning algorithms represents a natural progression of the source patent's computational diagnostic approach. These variations would be considered obvious improvements using known techniques in computational healthcare and personalized medicine.

Obvious Combinations & Variations

Source Patent Element

Bayesian Decision List for evaluating mental health conditions using input features

PTD Variation

Neural network trained on genomic data to predict treatment regimens

Obviousness Reasoning

Extending a Bayesian decision framework to a neural network is a predictable application of machine learning techniques for improving diagnostic accuracy, representing a known method of enhancing probabilistic medical decision systems

Source Patent Element

System for determining mental health conditions using input features

PTD Variation

Machine learning algorithm generating neuropsychiatric disease risk scores

Obviousness Reasoning

Transforming discrete diagnostic determination into a probabilistic risk scoring system is an obvious refinement using standard predictive analytics techniques in medical diagnostics

Source Patent Element

Control system configured to output mental health condition diagnoses

PTD Variation

Wearable device tracking physiological responses with cloud-based adaptive analytics

Obviousness Reasoning

Augmenting a diagnostic system with continuous monitoring represents a predictable technological evolution using standard IoT and machine learning integration techniques

Source Patent Element

Cognitive task outcome measures as input features

PTD Variation

Graph-based machine learning algorithm identifying genetic variants associated with disease susceptibility

Obviousness Reasoning

Expanding input feature analysis from cognitive tasks to genomic data represents an obvious extension of computational diagnostic methodologies using known machine learning approaches

Source Patent Element

System for evaluating patient mental health using computational methods

PTD Variation

Virtual reality platform for adaptive neuropsychiatric therapy

Obviousness Reasoning

Introducing interactive therapeutic technologies represents a predictable design variation for enhancing patient treatment methodologies using known computational and psychological intervention techniques

35 U.S.C. § 103 Summary: Based on the teachings of US Patent 11857322 and the disclosed technological variations, a person of ordinary skill in the art would find the claimed innovations obvious and therefore unpatentable. The presented published technical disclosure demonstrates that the claimed neuropsychiatric diagnostic and treatment methodologies represent predictable combinations of known computational techniques applied to medical diagnostic systems, rendering subsequent claims obvious and lacking in non-obvious inventive characteristics.

Original Patent Information

Patent Number	US 11,857,322
Title	Systems and methods for screening, diagnosing, and stratifying patients
Assignee(s)	Neumora Therapeutics, Inc.