Cannabinoid Therapy Personalization Using Multiomic Response Prediction

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Solution Overview

Problem

Current cancer therapies face challenges due to tumor heterogeneity and resistance mechanisms, with inconsistent effects of cannabis compositions on cancer cells, and there is a lack of biomarkers to predict treatment outcomes.

Innovation Solution

A method involving a holistic approach that includes determining the therapeutic efficacy of cannabinoid compositions through multiomic analysis of patient samples, predicting responses, and selecting personalized cannabis-based therapies using computational models to optimize treatment.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If cannabis compositions are used to treat cancer, then therapeutic effects are achieved, but treatment response is inconsistent due to tumor heterogeneity and resistance mechanisms

Engineering Contradiction:

Improvetreatment response consistencyVSAvoidtumor heterogeneity

Core Design Contradiction:

ReliabilityVSAdaptability or versatility

Solution Approach 1:

The patent applies parameter changes by analyzing multiple molecular parameters simultaneously through multiomic analysis (transcriptomics, proteomics, metabolomics). This comprehensive parameter assessment allows identification of specific molecular profiles that predict response to cannabinoid therapy, thereby resolving the inconsistency in treatment response caused by tumor heterogeneity.

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The patent segments the complex cancer treatment problem into distinct molecular layers (transcriptome, proteome, metabolome) that can be analyzed separately and integrated. This segmentation allows for identification of specific biomarkers at each molecular level that contribute to treatment response variability, enabling personalized therapy selection.

Inventive Principle:

Principle #1Segmentation

2Reliability

If comprehensive multiomic analysis is performed to personalize therapy, then treatment efficacy is enhanced, but analytical complexity and resource requirements increase

Engineering Contradiction:

Improvetherapeutic efficacyVSAvoidanalytical complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The patent merges multiple analytical approaches (computational biology, multiomic analysis, machine learning) into an integrated personalized medicine platform. By combining these methods, the system achieves high therapeutic efficacy through comprehensive patient profiling while managing analytical complexity through unified computational pipelines and standardized protocols.

Inventive Principle:

Principle #5Merging (Combining)

Solution Approach 2:

The patent introduces computational models and bioinformatics tools as intermediaries between raw multiomic data and clinical decision-making. These computational intermediaries process, integrate, and interpret complex multiomic datasets, translating them into actionable therapeutic recommendations without requiring direct manual analysis of all molecular parameters.

Inventive Principle:

Principle #24Intermediary (Mediator)

3Measurement precision

If computational models are used to predict patient response, then personalized therapy selection is improved, but data processing requirements increase

Engineering Contradiction:

Improveresponse prediction accuracyVSAvoiddata processing requirements

Core Design Contradiction:

Measurement precisionVSQuantity of substance

Solution Approach 1:

The patent applies preliminary action by performing comprehensive multiomic profiling and computational analysis before treatment selection. Patient samples are analyzed for transcriptomic, proteomic, and metabolomic characteristics in advance, and computational models predict treatment response beforehand, enabling informed personalization of therapy without requiring extensive data processing during clinical decision-making.

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS20260000684A1Cannabinoid compositions against cancer, their identification and personalization of cannabis-based cancer therapy

Publication Date: 2026.01.01 UNIVERZA V MARIBORU

AI summary

In a first aspect, the invention pertains to a method for identifying a therapeutic composition against cancer comprising at least one cannabinoid. It is based on a holistic approach that relies on determining its therapeutic efficacy of a composition comprising at least one cannabinoid and by performing a computational analysis on the resulting data. In additional aspects, the invention pertains to therapeutic compositions comprising at least one cannabinoid and their use for the treatment of a condition or disease. Furthermore, the invention pertains to an in-vitro method for the personalization of cannabis-based therapy. Said method relies on providing a patient sample and performing a multiomic analysis on said patient sample. After predicting the patient's response to a therapeutic composition comprising at least one cannabinoid, a therapeutic composition comprising at least one cannabinoid is selected for treatment of the patient.