Validation and application of a liquid chromatography–tandem mass spectrometric method for the determination of GDC‐0834 and its metabolite in human plasma using semi‐automated 96‐well protein precipitation
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Bibliographic record
Abstract
A liquid chromatographic-tandem mass spectrometric (LC-MS/MS) method was developed and validated for the determination of GDC-0834 and its amide hydrolysis metabolite (M1) in human plasma to support clinical development. The method consisted of semi-automated 96-well protein precipitation extraction for sample preparation and LC-MS/MS analysis in positive ion mode using TurboIonSpray® for analysis. D6-GDC-0834 and D6-M1 metabolite were used as internal standards. A linear regression (weighted 1/concentration(2) ) was used to fit calibration curves over the concentration range of 1 - 500 ng/mL for both GDC-0834 and M1 metabolite. The accuracy (percentage bias) at the lower limit of quantitation (LLOQ) was 5.20 and 0.100% for GDC-0834 and M1 metabolite, respectively. The precision (CV) for samples at the LLOQ was 3.13-8.84 and 5.20-8.93% for GDC-0834 and M1 metabolite, respectively. For quality control samples at 3, 200 and 400 ng/mL, the between-run CV was ≤ 7.38% for GDC-0834 and ≤ 8.20% for M1 metabolite. Between run percentage bias ranged from -2.76 to 6.98% for GDC-0834 and from -6.73 to 2.21% for M1 metabolite. GDC-0834 and M1 metabolite were stable in human plasma for 31 days at -20 and -70°C. This method was successfully applied to support a GDC-0834 human pharmacokinetic-based study.
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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 | 0.001 | 0.002 |
| 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