Automated Real-Time Tumor Pharmacokinetic Profiling in 3D Models: A Novel Approach for Personalized Medicine
Jan F Joseph1, Leonie Gronbach2, Jill García-Miller2
1Freie Universität Berlin, Core Facility BioSupraMol, 14195 Berlin, Germany.
Abstract:
Cancer treatment often lacks individual dose adaptation, contributing to insufficient efficacy and severe side effects. Thus, personalized approaches are highly desired. Although various analytical techniques are established to determine drug levels in preclinical models, they are limited in the automated real-time acquisition of pharmacokinetic profiles. Therefore, an online UHPLC-MS/MS system for quantitation of drug concentrations within 3D tumor oral mucosa models was generated. The integration of sampling ports into the 3D tumor models and their culture inside the autosampler allowed for real-time pharmacokinetic profiling without additional sample preparation. Docetaxel quantitation was validated according to EMA guidelines. The tumor models recapitulated the morphology of head-and-neck cancer and the dose-dependent tumor reduction following docetaxel treatment. The administration of four different docetaxel concentrations resulted in comparable courses of concentration versus time curves for 96 h. In conclusion, this proof-of-concept study demonstrated the feasibility of real-time monitoring of drug levels in 3D tumor models without any sample preparation. The inclusion of patient-derived tumor cells into our models may further optimize the pharmacotherapy of cancer patients by efficiently delivering personalized data of the target tissue.
Insights
This study introduces a novel online UHPLC-MS/MS system for real-time drug monitoring in 3D tumor models. This innovation enables personalized cancer therapy by tracking drug concentrations and effects in oral mucosa cancer models.
Area of Science:
- Pharmacology
- Analytical Chemistry
- Oncology
Background:
- Cancer therapy often lacks individualized dosing, leading to suboptimal outcomes and toxicity.
- Current methods for drug level analysis in preclinical models struggle with real-time pharmacokinetic profiling.
- Personalized medicine approaches are crucial for improving cancer treatment efficacy.
Purpose of the Study:
- To develop and validate an online ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) system.
- To enable real-time pharmacokinetic profiling of drugs within 3D tumor oral mucosa models.
- To assess docetaxel's efficacy and concentration-time dynamics in a head-and-neck cancer model.
Main Methods:
- Integration of sampling ports into 3D tumor models for direct, in-situ analysis.
- Culturing of 3D tumor models within the autosampler for automated, real-time sample acquisition.
- Quantitation of docetaxel concentrations using validated UHPLC-MS/MS methods according to EMA guidelines.
Main Results:
- The developed system achieved real-time pharmacokinetic profiling without sample preparation.
- The 3D oral mucosa tumor models accurately mimicked head-and-neck cancer morphology.
- Docetaxel treatment demonstrated dose-dependent tumor reduction, with comparable concentration-time profiles observed over 96 hours.
Conclusions:
- This proof-of-concept study validates the feasibility of real-time drug level monitoring in 3D tumor models.
- The system offers a promising tool for optimizing cancer pharmacotherapy through personalized data acquisition.
- Future integration of patient-derived cells could further enhance the clinical relevance of this approach for targeted cancer treatment.
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