Dose Optimization Using Bayesian Minimum Effective Dosing

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Solution Overview

Problem

The inefficiency in administering medications due to over-dosing, which exacerbates scarcity and leads to negative health implications and wastefulness, is not adequately addressed by existing methods.

Innovation Solution

A method for determining a minimum dose with satisfactory efficacy (MDSE) using a dose-response model and Bayesian prior to optimize medication administration, ensuring efficient use of scarce resources.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If higher doses of medication are administered to ensure efficacy, then treatment reliability is improved, but drug scarcity is exacerbated and waste increases

Engineering Contradiction:

Improvetreatment reliabilityVSAvoiddrug waste

Core Design Contradiction:

ReliabilityVSLoss of substance

Solution Approach 1:

The system dynamically adjusts the dosage parameter based on individual patient characteristics (weight, age, genetics, disease severity) rather than using fixed dosing regimens. This allows optimization of the dose to achieve minimum effective dosage for each patient, reducing overall drug waste while maintaining treatment reliability

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The system incorporates real-time feedback mechanisms where treatment response data is continuously monitored and fed back into the dosing algorithm. This enables dynamic adjustment of dosage to maintain efficacy while minimizing excess administration, thereby reducing drug waste without compromising treatment reliability

Inventive Principle:

Principle #23Feedback

2Ease of operation

If standardized dosing protocols are used for simplicity, then ease of operation is improved, but inefficiency and over-dosing increase

Engineering Contradiction:

Improvedosing simplicityVSAvoidmedication efficiency

Core Design Contradiction:

Ease of operationVSProductivity

Solution Approach 1:

The system enables automated self-adjustment of dosing regimens through algorithms that automatically calculate optimal doses based on patient data. This maintains ease of operation by reducing manual calculation complexity while simultaneously improving medication efficiency through precision dosing

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system transforms fixed dosing parameters into dynamic, patient-specific parameters. By automatically adjusting dosage based on individual characteristics, it maintains operational simplicity while eliminating the inefficiencies of standardized dosing protocols

Inventive Principle:

Principle #35Parameter changes

3Quantity of substance

If rapid production of scarce drugs is pursued, then supply availability is improved, but the fundamental allocation inefficiency remains unresolved

Engineering Contradiction:

Improvedrug supplyVSAvoidallocation waste

Core Design Contradiction:

Quantity of substanceVSLoss of substance

Solution Approach 1:

The system changes the allocation parameter from fixed standardized doses to dynamic patient-specific doses. This optimization ensures that each unit of drug produced is utilized at maximum efficiency, addressing the root cause of allocation waste rather than merely increasing production capacity

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS12499983B2Methods, systems, and apparatuses for dose optimization

Publication Date: 2025.12.16 THE UNITED STATES OF AMERICA AS REPRESENTED BY THE DEPT OF VETERANS AFFAIRS

AI summary

Methods, systems and apparatuses for dose optimization is disclosed. A predetermined threshold may be assigned to a medication. Dose-responses from each subject of a plurality of subjects may be collected and evaluated so that a determination may be made regarding whether a particular dose is equal to a true minimum dose with satisfactory efficacy value.