Measurement of Free Drug Concentration from Biological Tissue by Solid-Phase Microextraction: In Silico and Experimental Study
Bibliographic record
Abstract
In this article, the use of an SPME technique is reported for the first time for direct measurement of free drug concentration in solid tissue. In our investigations, we considered doxorubicin (DOX) spiked in homogenized tissue matrix at transient and equilibrium extraction conditions, with subsequent assessment of obtained experimental results by an in silico approach using mathematical models developed in COMSOL Multyphysics. In silico studies were performed on the basis of transported diluted species (tds) and reaction engineering (re) modules from COMSOL Multiphysics, using the same conditions as those used to attain experimental results. To determine the apparent binding affinity of DOX to the tissue matrix which contains multiple binding species, the experimentally determined binding affinity of DOX with human serum albumin (HSA) was considered to simplify the mathematical calculations. Here, the value of the binding affinity was considered for a single binding site and adjusted by fitting the experimental results with the mathematical model. Bovine lung tissue homogenate was selected as a surrogate matrix, and a biocompatible C-8 commercial SPME fiber was used for extraction of DOX. In total, four mathematical models were herein developed to describe the mass transfer kinetics of solid coatings: in agar gel at static conditions, in PBS solution with agitated conditions, extraction in PBS solution in the presence of an HSA binding matrix, and static extraction in homogenized lung tissue. For all conditions, simulated results were in good agreement with experimental results. The developed mathematical model allows for measurements of free drug concentrations inside the tissue matrix and facilitates calculations of local depletion of DOX by a solid SPME coating. Results of the investigations indicate that local depletion of the free form of DOX, even at the kinetic stage, is negligible for tissue extraction, as the release of the heavily bound analyte (over 99% binding to tissue matrix) is very rapid, thus easily compensating for the loss of the drug to the SPME coating. This indicates that the dissociation rate constant of DOX from lung tissue components is very rapid; therefore, the mass transfer of drug to the fiber coating via free from is very efficient. Our results also indicate that thin coating SPME fibers provide a good way to measure drug distribution after dosing, as extractions via thin coating SPME fibers do not affect the free concentration of the drug, which is responsible for drug distribution in tissue.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".