ArticleACS omega2025
Advanced Freeze-Drying Modeling: Validation of a Sorption-Sublimation Model.
Article in ACS omega, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Modeling freeze-drying is crucial due to the complex interplay of heat and mass transfer, which significantly impacts product quality and process efficiency. Traditional experimental approaches can be time-consuming and resource-intensive, making rigorous modeling an essential tool for optimization. Sorption-sublimation models incorporate the dynamic nature of the drying steps by accurately describing heat and mass transfer, enabling precise calculation of product temperature and residual moisture. Here, the moving boundary is mapped to the boundary of a fixed domain by the introduction of two new coordinates. Simulation results are validated by the approach from Sixt et al. The model shows good agreement with experimental data, with deviations reduced to as low as 3.9%. This represents a significant improvement over previous models, such as the pseudostationary approach, which exhibits deviations up to 42.2% for edge vials at the end of primary drying. For residual moisture, the experiment and simulation show similar error margins of 7% and the simulation deviates by only 8% from the experimental value. The model's accuracy and precision offer valuable insights for optimizing process parameters, ultimately enhancing product quality and reducing development costs. The successful validation against experimental data shows the model's potential as a robust tool for predicting process behavior in vial lyophilization, paving the way for its application in both research and industrial settings.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.