A New Discriminative Criterion for the Development of Franz Diffusion Tests for Transdermal Pharmaceuticals
Bibliographic record
Abstract
PURPOSE: In vitro skin/membrane permeation profiling of topical pharmaceuticals is an important overall quality attribute in the evaluation of product consistency and it is also used for IVIVR (in vitro - in vivo relationship) purposes in product development and change control. Franz diffusion cell (FDC) experiments are emerging as a generally accepted methodology in this field, where the choice of operational conditions requires a data-supported justification towards the discriminating power of the test. A response function is therefore proposed to objectively quantify the discriminating power. METHODS: We evaluated the usefulness of the proposed response function by studying one of the operational conditions, i.e. the influence of receptor medium composition, on the FDC in vitro penetration behaviour of the model compound testosterone formulated in four different topical preparations, using both artificial membranes and dermatomed human skin. RESULTS: From the obtained cumulative amount of testosterone in the receptor fluid versus time curves, the permeability coefficient Kp of testosterone from each formulation was calculated. The evaluation of the discriminating power of the different media was performed using our new objective response function based upon an equal spread criterion of normalised Kp values. CONCLUSION: We demonstrated significant differences in discriminating power between the different media used, with the overall best results obtained with hydroxypropyl-beta-cyclodextrine (HPBCD) containing media. The proposed new criterion was found to be useful for the rational design of an in vitro diffusion test for transdermal pharmaceuticals.
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How this classification was reachedexpand
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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".