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Adapting therapy with repeated short-infusions to inter individual variability between patients
1Department of Polymer Chemistry, Polytechnic University, Bucharest, Romania.
This study presents a two-stage method for personalized intravenous drug therapy, adapting treatment to individual patient needs by analyzing drug concentrations and adjusting infusion parameters for optimal therapeutic outcomes.
Area of Science:
- Pharmacology
- Clinical Pharmacy
- Pharmacokinetics
Background:
- Individual patient variability significantly impacts drug response and therapeutic efficacy.
- Standard drug administration protocols may not be optimal due to inter-individual differences.
- Intravenous (IV) drug delivery allows for adjustable administration parameters in a hospital setting.
Purpose of the Study:
- To describe a therapeutic method for adapting intravenous drug therapy to individual patients.
- To present a two-stage approach for optimizing drug administration based on patient-specific pharmacokinetics.
- To introduce a method for achieving generalizable solutions using dimensionless parameters.
Main Methods:
- Stage 1: Determination of patient pharmacokinetic parameters through analysis of drug concentrations in blood after the first infusion.
- Stage 2: Repeated short infusions with adjusted dosage, infusion rate, or interval between infusions.
- Development of master curves using dimensionless numbers (e.g., time relative to half-life, peak concentration fraction) for generalizability.
Main Results:
- The described method allows for precise adaptation of drug therapy to individual patient needs.
- Pharmacokinetic parameters can be reliably determined from limited blood samples.
- Master curves provide a framework for optimizing repeated short infusion strategies across different drugs and patients.
Conclusions:
- The presented two-stage therapeutic method enables personalized intravenous drug administration.
- This approach addresses the challenge of inter-individual variability in drug response.
- The use of dimensionless parameters facilitates the development of broadly applicable therapeutic guidelines.
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