CBD Product Certification Using Remote Self-Assessment Data
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Medical studies for substances like herbal remedies and cannabis are unreliable due to limited sample sizes, participant reluctance, and variability in substance sourcing and potency, making it difficult to gather reliable data on their effects.
Innovation Solution
A system that enlists participants via a computer network to report self-assessment data on substance effects, allowing remote monitoring and analysis of large-scale data to determine substance interactions and efficacy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional medical studies are used to test substance effects, then scientific rigor can be maintained, but sample sizes are limited and participant recruitment is difficult
Solution Approach 1:
The system enables participants to self-report their own substance use and effects without requiring researcher intervention. Participants autonomously complete surveys, track their usage patterns, and provide feedback on symptom changes, eliminating the need for controlled clinical trials while gathering large-scale data.
Solution Approach 2:
The patent replaces traditional mechanical clinical trial systems with an electronic self-assessment system. Instead of physical presence in controlled environments, participants use computers or mobile devices to complete digital surveys and report effects, enabling remote data collection from diverse populations.
2Reliability
If controlled clinical trials are conducted, then data reliability improves, but participant reluctance and variability in substance sourcing persist
Solution Approach 1:
The system dynamically adapts to different substance types, dosages, and usage patterns without requiring standardized controlled conditions. Participants can report on various cannabinoid products with different cannabinoid profiles, allowing the system to handle substance variability while maintaining data collection consistency through standardized self-assessment protocols.
3Reliability
If large-scale participant enrollment is pursued, then data reliability improves, but system complexity and data processing requirements increase
Solution Approach 1:
The system segments data collection into distinct modular components: substance use tracking, symptom assessment, effect reporting, and certification evaluation. Each module operates independently and can be processed separately, reducing overall system complexity while enabling large-scale data collection through distributed participant contributions.
Data Source
AI summary
In accordance with one embodiment, a method can be implemented that includes enlisting via a computer network a plurality of participants to report one or more effects of their respective usage of a substance; confirming that a prospective participant is located in a state where use of the substance is legal; receiving from each of the one or more participants via the computer network one or more self-assessment reports of any physical, emotional, or mental responses or any combination thereof to the substance; and processing the one or more self-assessment reports with a computer processor to determine if the substance has an effect on a particular symptom or condition.