Development and Validation of Valganciclovir and its Active Metabolite Ganciclovir Determination in Human Plasma by HPLC-MS/MS Method
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Introduction. Currently, physicochemical methods of quantification are actively used to determine the content of drugs in biological fluids. High-performance liquid chromatography with various detection methods is particularly widespread. One of the most difficult practical tasks is the chromatographic separation of so-called poorly retained compounds – drug substances poorly retained on the chromatographic column. Valganciclovir and Ganciclovir are among such substances. Aim. The aim of this study is to develop a method for valganciclovir and ganciclovir in human plasma by high performance liquid chromatography with tandem mass-spectrometry (HPLC-MS/MS) for pharmacokinetic studies. Materials and methods. Determination of valganciclovir and ganciclovir in plasma by HPLC-MS/MS. The samples were processed by acetonitrile protein precipitation. Results and discussion. This method was validated by next parameters: selectivity, matrix effect, calibration curve, accuracy, precision, recovery, lower limit of quantification, carry-over and stability. Conclusion. The method of the determination of valganciclovir and ganciclovir in human plasma was developed and validated by HPLC-MS/MS. The linearity in plasma sample was achieved in the concentration range of 5.00–1000.00 ng/ml for valganciclovir and 50.00–10000.00 ng/ml for ganciclovir. Method could be applied to valganciclovir and ganciclovir determination in plasma for PK and BE studies.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it