Understanding effect of filtration and washing on dried product: Paracetamol case study

Integrated Filtration and Washing Modeling: Optimization of Impurity Rejection for Filtration and Washing of Active Pharmaceutical Ingredients

A digital design tool that can transfer material property information between unit operations to predict the product attributes in integrated purification processes has been developed to facilitate end-to-end integrated pharmaceutical manufacturing. This work aims to combine filtration and washing operations frequently using active pharmaceutical ingredient (API) isolation. This is achieved by coupling predicted and experimental data produced during the upstream crystallization process. To reduce impurities in the isolated cake, a mechanistic model-based workflow was used to optimize an integrated filtration and washing process model. The Carman-Kozeny filtration model has been combined with a custom washing model that incorporates diffusion and axial dispersion mechanisms. The developed model and approach were applied to two systems, namely, mefenamic acid and paracetamol, which are representative compounds, and various crystallization and wash solvents and related impurities were used. The custom washing model provides a detailed evolution of species concentration during washing, simulating the washing curve with the three stages of the wash curve: constant rate, intermediate stage, and diffusion stage. A model validation approach was used to estimate cake properties (e.g., specific cake resistance, cake volume, cake composition after washing, and washing curve). A global systems analysis was conducted by using the calibrated model to explore the design space and aid in the setup of the optimization decision variables. Qualitative optimization was performed in order to reduce the concentration of impurities in the final cake after washing. The findings of this work were translated into a final model to simulate the optimal isolation conditions.

Quality-by-control of intensified continuous filtration-drying of active pharmaceutical ingredients

Continuous manufacturing and closed-loop quality control are emerging technologies that are pivotal for next-generation pharmaceutical modernization. We develop a process control framework for a continuous carousel for integrated filtration-drying of crystallization slurries. The proposed control system includes model-based monitoring and control routines, such as state estimation and real-time optimization, implemented in a hierarchical, three-layer quality-by-control (QbC) framework. We implement the control system in ContCarSim, a publicly available carousel simulator. We benchmark the proposed control system against simpler methods, comprising a reduced subset of the elements of the overall control system, and against open-loop operation (the current standard in pharmaceutical manufacturing). The proposed control system demonstrates superior performance in terms of higher consistency in product quality and increased productivity, proving the benefits of closed-loop control and of model-based techniques in pharmaceutical manufacturing. This study represents a step forward toward end-to-end continuous pharmaceutical processing, and in the evolution of quality-by-design toward quality-by-control.

Mathematical modeling and digital design of an intensified filtration-washing-drying unit for pharmaceutical continuous manufacturing

This paper introduces a comprehensive mathematical model of a novel integrated filter-dryer carousel system, designed for continuously filtering, washing and drying a slurry stream into a crystals cake. The digital twin includes models for dead-end filtration, cake washing and convective cake drying, based on dynamic multi-component mass, energy and momentum balances. For set of feed conditions and control inputs, the model allows tracking the solvents and impurities content in the cake (critical quality attributes, CQAs) throughout the whole process. The model parameters were identified for the isolation of paracetamol from a multi-component slurry, containing a non-volatile impurity. The calibrated model was used for identifying the probabilistic design space and maximum throughput for the process, expressing the combinations of the carousel feed conditions and control inputs for which the probability of meeting the target CQAs is acceptable.

A Novel Integrated Workflow for Isolation Solvent Selection Using Prediction and Modeling

A predictive tool was developed to aid process design and to rationally select optimal solvents for isolation of active pharmaceutical ingredients. The objective was to minimize the experimental work required to design a purification process by (i) starting from a rationally selected crystallization solvent based on maximizing yield and minimizing solvent consumption (with the constraint of maintaining a suspension density which allows crystal suspension); (ii) for the crystallization solvent identified from step 1, a list of potential isolation solvents (selected based on a series of constraints) is ranked, based on thermodynamic consideration of yield and predicted purity using a mass balance model; and (iii) the most promising of the predicted combinations is verified experimentally, and the process conditions are adjusted to maximize impurity removal and maximize yield, taking into account mass transport and kinetic considerations. Here, we present a solvent selection workflow based on logical solvent ranking supported by solubility predictions, coupled with digital tools to transfer material property information between operations to predict the optimal purification strategy. This approach addresses isolation, preserving the particle attributes generated during crystallization, taking account of the risks of product precipitation and particle dissolution during washing, and the selection of solvents, which are favorable for drying.

Understanding API Static Drying with Hot Gas Flow: Design and Test of a Drying Rig Prototype and Drying Modeling Development

Developing a continuous isolation process to produce a pure, dry, free-flowing active pharmaceutical ingredient (API) is the final barrier to the implementation of continuous end-to-end pharmaceutical manufacturing. Recent work has led to the development of continuous filtration and washing prototypes for pharmaceutical process development and small-scale manufacture. Here, we address the challenge of static drying of a solvent-wet crystalline API in a fixed bed to facilitate the design of a continuous filter dryer for pharmaceutical development, without excessive particle breakage or the formation of interparticle bridges leading to lump formation. We demonstrate the feasibility of drying small batches on a time scale suitable for continuous manufacturing, complemented by the development of a drying model that provides a design tool for process development. We also evaluate the impact of alternative washing and drying approaches on particle agglomeration. We conclude that our approach yields effective technology, with a performance that is amenable to predictive modeling.