Package: ethz-snow
SNOW (StochasticNucleationOfWater) is an open source modeling framework to simulate the freezing process in a large number of vials, tailored towards pharmaceutical freeze-drying processes. SNOW was developed as part of a research collaboration between ETH Zurich's Separation Processes Laboratory and Janssen (pharmaceutical companies of J&J). It is brought to you by Leif-Thore Deck, Andraž Košir and Dr. David Ochsenbein.DescriptionSNOW is a model capable of simulating the entire freezing process for a batch of vials, from the liquid state to the completely frozen state. It combines balance equations, thermodynamics and a stochastic approach to ice nucleation to provide a comprehensive view of freezing and is entirely derived from first principles.In addition to the simulation of the thermal evolution of vials during freezing, SNOW tracks a number of characteristic quantities of the freezing process for each vial. These quantities are the nucleation time, the nucleation temperature and the solidification time. Both nucleation and solidification are correlated with attributes of the frozen product such as the mean crystal size and the product activity of an API. Variability in these quantities among vials may thus be used as surrogate for batch heterogeneity. SNOW consequently may be used in process design and optimization to identify suitable cooling protocols with sufficiently small batch heterogeneity.A more detailed description of the modeling framework is presented in a recent publication, which is publicly accessible underhttps://doi.org/10.1016/j.ijpharm.2021.121276While version 1.0 is tailored towards simulations of the freezing stage in freeze-drying, version 1.1. was developed for pallet freezing; pallet freezing is for example used in the manufacturing of the Janssen COVID-19 vaccine, which served as case study for the model. Version 1.1 and the case study on the COVID-vaccine are discussed in detail in a recent scientific publication:https://doi.org/10.1016/j.ijpharm.2022.122051An extension of the modeling framework for the simulation of the freezing process with spatial resolution within individual containers has been implemented in version 2.0 and is discussed in detail within the scope of a recent scientific publication:https://doi.org/10.1016/j.cej.2024.148660.Additional features supported by version 2.0Spatial simulation of freezing within individual containers with different dimensionalities (0D, 1D, 2D)Simulation of three process configurations (shelf-ramped freezing, vacuum-induced surface freezing, jacket-ramped freezing)Additional features supported by version 1.1Simulation of systems comprising vials arranged in three spatial dimensionsArbitrary initial temperature of the vialsImprovements in the numerical implementation (Second method to compare the initial amount of ice formed, faster data saving)Features supported as of version 1.0Simulation of the thermal evolution and ice formation for a batch with arbitrary number of vialsArbitrary cooling protocols (i.e., user may choose cooling rate, integrate holding steps and controlled nucleation)Tracking of nucleation times, temperatures and solidification times for all vialsStochastic nucleation in the form of a Monte Carlo approach as well as controlled nucleation in the form of forced initiation of nucleation at a certain point in timeCubic geometry of vial and rectangular arrangement on the shelfFeatures in preparationHexagonal arrangement of vials on the shelf for freeze-dryingAdditional modes of heat transfer (e.g. thermal radiation)Alternative vial / vessel geometriesBug reportsPlease report bugs asGithub issuesor viaEmail, preferably
including a screenshot that illustrates the problem.Copyright (c) 2021-2024 Leif-Thore Deck, Andraž Košir, David OchsenbeinThe snow package logo has been designed using resources from Flaticon.com.