CASM Temporal-Interaction Scoring for Individualized Drug Dosing
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Solution Overview
Problem
Conventional mathematical and statistical methods are inadequate for quantifying how complex adaptive systems, such as living beings, function in the time dimension, limiting progress in drug development and medicine by failing to provide precise and individualized drug dosing.
Innovation Solution
A complex adaptive systems metrology (CASM) platform that processes multivariate time series data to compute universally standardized temporal-interaction scores, accounting for temporal interactions and adaptivity, enabling precise drug targeting and treatment evaluation for individual patients.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional mathematical and statistical methods are used, then measurement and analysis can be performed, but they are inadequate for quantifying how complex adaptive systems function in the time dimension
Solution Approach 1:
The patent introduces new computational parameters including temporal-interaction scores, adaptivity indices, and complexity metrics that transform conventional static measurements into dynamic temporal assessments. These parameter changes enable precise quantification of how complex adaptive systems function over time while maintaining adaptability to individual system characteristics.
Solution Approach 2:
The patent employs computational algorithms as intermediaries that bridge conventional mathematical methods and complex adaptive system analysis. These algorithms process multivariate time series data to extract temporal interaction patterns, enabling precise measurement of system function without requiring fundamental changes to underlying mathematical frameworks.
2Measurement precision
If physical science methods are used, then targeting can be achieved for physical entities, but they are less successful for targeting drugs to individuals
Solution Approach 1:
The patent segments the complex task of individualized drug targeting into distinct computational components: data acquisition from multivariate time series, temporal-interaction score calculation, adaptivity index computation, and treatment recommendation generation. This segmentation manages system complexity while achieving precise individualized targeting through systematic processing of each component.
Solution Approach 2:
The patent transforms conventional treatment parameters into individualized parameters by computing temporal-interaction scores and adaptivity indices specific to each patient's multivariate time series data. This parameter transformation enables precise drug targeting to individuals while managing complexity through standardized computational procedures.
3Adaptability or versatility
If conventional methods are used, then general treatment protocols can be established, but they fail to provide precise and individualized drug dosing
Solution Approach 1:
The patent enables self-service individualization where each patient's multivariate time series data automatically generates their own temporal-interaction scores and adaptivity indices without requiring manual customization. This self-service approach achieves precise individualized dosing while maintaining productivity through automated computational processes that scale efficiently.
Solution Approach 2:
The patent changes dosing parameters from fixed conventional values to dynamic individualized parameters derived from each patient's temporal-interaction scores. This parameter change enables precise individualized dosing while improving productivity through automated calculation of personalized parameters from routine clinical data.
Data Source
AI summary
Methods and systems are described for a computer-implemented complex adaptive systems metrology (CASM) technique for generating universally and mathematically standardized scores that quantify longitudinal evidence for either temporal-interaction scores or temporal-interaction benefit-and-harm scores to determine a quantitative significance estimate of scores for either standardized temporal-interaction scores or the standardized temporal-interaction benefit-and-harm scores.


