Soluble Beta Glucan Dosing via Anti-Body Stratification
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Solution Overview
Problem
Current soluble β-glucan immunotherapy dosing methods lack precision, as they do not account for individual variations in anti-β-glucan antibody levels, leading to inconsistent immunopharmacodynamic responses and adverse events.
Innovation Solution
A method involving the classification of subjects into subgroups based on anti-β-glucan antibody levels, with tailored dosing schedules and administration intervals to regulate acute immunopharmacodynamic responses, using β-glucans derived from yeast like β(1,6)-[poly-(1,3)-D-glucopyranosyl]-poly-β(1,3)-D-glucopyranose, to optimize dosing strategies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If fixed dosing schedules are used for soluble β-glucan immunotherapy, then treatment simplicity is maintained, but immunopharmacodynamic responses become inconsistent across subjects
Solution Approach 1:
The patent applies parameter changes by adjusting the β-glucan dose based on the subject's anti-β-glucan antibody level (a measured parameter). Subjects are classified into subgroups (e.g., low, mid, high antibody levels) and assigned different doses accordingly, transforming a fixed-dose regimen into a parameter-adjusted regimen to achieve consistent immunopharmacodynamic responses across diverse subjects.
Solution Approach 2:
The patent segments the patient population into distinct subgroups based on anti-β-glucan antibody levels. This segmentation allows for tailored dosing strategies for each subgroup, ensuring that subjects with different baseline antibody levels receive appropriate doses to achieve uniform therapeutic responses, thereby resolving the inconsistency issue.
2Reliability
If higher doses of soluble β-glucan are administered to all subjects, then immunotherapy efficacy is enhanced, but adverse events increase
Solution Approach 1:
The patent uses parameter changes to adjust the β-glucan dose based on individual subject characteristics (anti-β-glucan antibody levels). Instead of administering high doses to all subjects, the dose is optimized for each subject's specific immunological profile, maximizing efficacy while minimizing adverse events through personalized dosing.
Solution Approach 2:
The patent applies local quality by tailoring the dose to each subject's specific needs based on their antibody level. Rather than a uniform high dose for all, each subject receives a locally optimized dose appropriate to their immunological status, ensuring efficacy while reducing unnecessary exposure and associated adverse events.
3Object-affected harmful factors
If lower doses of soluble β-glucan are administered to all subjects, then adverse events are reduced, but immunotherapy efficacy decreases
Solution Approach 1:
The patent resolves this contradiction by changing the dosing parameter from a fixed low dose to a variable dose based on anti-β-glucan antibody levels. Subjects with low antibody levels receive higher doses to ensure efficacy, while subjects with high antibody levels receive lower doses to minimize adverse events, achieving both goals simultaneously through parameter-based personalization.
4Measurement precision
If individualized dosing based on anti-β-glucan antibody levels is implemented, then treatment precision is improved, but measurement and classification requirements increase
Solution Approach 1:
The patent replaces complex mechanical dosing adjustments with a biomarker-based classification system. By measuring anti-β-glucan antibody levels (a biochemical parameter) and classifying subjects into predefined subgroups, the system achieves precise dosing without requiring complex real-time adjustments during treatment, simplifying the overall implementation while maintaining high precision.
Data Source
AI summary
This disclosure provides, in one aspect, dosing strategies for soluble β-glucan immunotherapy to optimize acute immunopharmacodynamic responses for the immunotherapy and/or subject. It also provides a method for analyzing a sample from a subject for a biomarker to identify the appropriate dosing strategy for soluble β-glucan immunotherapy. Generally, the method includes obtaining a biological sample from a subject, analyzing the sample for a biomarker anti-β-glucan antibody level or immunopharmacodynamic response level, classifying the subject into a subgroup based on the biomarker anti-β-glucan antibody level or immunopharmacodynamic response level and identifying the appropriate dosing strategy based on the subgroup classification.