Rapid Room-Temperature Aerosol Dehydration Versus Spray Drying: A Novel Paradigm in Biopharmaceutical Drying Technologies.

To ensure the high quality of biopharmaceutical products, it is imperative to implement specialized unit operations that effectively safeguard the structural integrity of large molecules. While lyophilization has long been a reliable process, spray drying has recently garnered attention for its particle engineering capabilities for the pulmonary route of administration. However, maintaining the integrity of biologics during spray drying remains a challenge. To address this issue, we explored a novel dehydration system based on aerosol-assisted room-temperature drying of biological formulations recently developed at Princeton University, called Rapid Room-Temperature Aerosol Dehydration. We compared the quality attributes of the bulk powder of biopharmaceutical products manufactured using this drying technology with that of traditional spray drying. For all the fragment antigen-binding formulations tested, in terms of protein degradation and aerosol performance, we were able to achieve a better product quality using this drying technology compared to the spray drying technique. We also highlight areas for improvement in future prototypes and prospective commercial versions of the system. Overall, the offered dehydration system holds potential for improving the quality and diversity of biopharmaceutical products and may pave the way for more efficient and effective production methods in the biopharma industry.

Sensitivity and Uncertainty Analysis of Micro-Flow Imaging for Sub-Visible Particle Measurements Using Artificial Neural Network.

PURPOSE: During biopharmaceutical drug manufacturing, storage, and distribution, proteins in both liquid and solid dosage forms go through various processes that could lead to protein aggregation. The extent of aggregation in the sub-micron range can be measured by analyzing a liquid or post-reconstituted powder sample using Micro-Flow Imaging (MFI) technique. MFI is widely used in biopharmaceutical industries due to its high sensitivity in detecting and analyzing particle size distribution. However, the MFI's sensitivity to various factors makes accurate measurement challenging. Therefore, in light of the inherent variability of the method, this work aims to explore the capabilities of an adopted coupled sensitivity analysis and machine learning algorithm to quantify the influencing factors on the formed sub-visible particles and method variability. METHODS: The proposed algorithm consists of two interconnected components, namely a surrogate model with a neural network and a sensitivity analyzer. A machine learning tool based on artificial neural networks (ANN) is constructed with MFI data. The best fit with an optimized configuration is found. Sensitivity and uncertainty analysis is performed using this network as the surrogate model to understand the impacts of input parameters on MFI data. RESULTS: Results reveal the most impactful reconstitution preparation factors and others that are masked by the instrument variabilities. It is shown that instrument inaccuracy is a function of size category, with higher variabilities associated with larger size ranges. CONCLUSION: Utilizing this tool while assessing the sensitivity of outputs to various parameters, measurement variabilities for analytical characterization tests can be quantified.

Multicomponent Droplet Drying Modeling Based on Conservation and Population Balance Equations.

The aim of this work is to present a modeling tool to describe drying kinetics and delineate evolving physical and chemical behavior of multicomponent droplets during drying. Conservation equations coupled with population balance equations (PBE) are used to achieve this goal. Modeling results are gauged with single salt-water droplet drying from literature and show congruent trends. This model is then extended to a more complex system: various droplet sizes containing methanol (solvent), Felodipine (active ingredient), and PVP (polyvinylpyrrolidone as excipient). The FIB-SEM (Focused-Ion Beam Scanning Electron Microscopy) imaging results from spray-dried particles produced with similar formulation and processing conditions are consistent with phase behavior predicted by the model. The results show competing impacts of transport phenomena on the intermittent shell formation process and final particle structure and chemical heterogeneity. Solute diffusion, solvent efflux, and intra-drop flow impact the model system. It is found that shell formation follows a fluctuating profile where the initial precipitation of the dissolved species on the droplet surface is dampened, and nucleated particles become dispersed periodically until the shell becomes strong enough to withstand internal circulations. These internal effects are dependent on droplet size and are pronounced for larger droplets. That is, the particle phase behavior and physical nature are functions of the atomized droplet size. Stemming understating from this study would inform an optimized unit, operating in target design space. This would provide better product quality control and minimize discrepancies observed in process development during the early phase vs. commercial scale.

Are traditional small-scale screening methods reliable to predict pharmaceutical spray drying?

Driven by the new trend to build quality into products and reducing empiricism, small-scale screening techniques have been frequently used to evaluate, thermodynamic of drug solubility in the polymer, and drug-polymer kinetic amorphous miscibility. In this paper, these methods have been overviewed to shed light on their liabilities in predicting spray-dried amorphous solid dispersions' (ASDs) properties. By scrutinizing relevant open literature, several inconsistencies have been recognized, deemed to be due to the inability of conventional miniaturized means to simulate the spray drying process operations/constraints in formulating active pharmaceutical ingredients (APIs). Given the complex interplay of thermodynamics of mixing, heat and mass transfer, and fluid dynamics in this process, scaling rules have been introduced to remedy arisen issues in conventional miniaturized tools. Accordingly, spray drying process is analyzed considering the fundamental physical transformations involved, i.e. atomization and drying. Each transformation is explored from a scaling perspective with an emphasis on key response factors, and ways to retain them for each transformation across scales. Prospective bifurcated developments may improve the odds of successful formulations/process conditions later on during development stages.

Scale-up of pharmaceutical spray drying using scale-up rules: A review.

Spray drying is one of the widely used manufacturing processes in pharmaceutical industry. While there are voluminous experimental studies pertaining to the impact of various process-formulation parameters on the quality attributes of spray dried powders such as particle size, morphology, density, and crystallinity, there is scant information available in the literature regarding process scale-up. Here, we first analyze salient features of scale-up attempts in literature. Then, spray drying process is analyzed considering the fundamental physical transformations involved, i.e., atomization, drying, and gas-solid separation. Each transformation is scrutinized from a scale-up perspective with non-dimensional parameters & multi-scale analysis, and comprehensively discussed in engineering context. Successful scale-up entails similar key response variables from each transformation across various scales. These variables are identified as droplet size distribution, outlet temperature, relative humidity, separator pressure loss coefficient, and collection efficiency. Instead of trial-and-error-based approaches, this review paper advocates the use of mechanistic models and scale-up rules for establishing design spaces for the process variables involved in each transformation of spray drying. While presenting a roadmap for process development and scale-up, the paper demonstrates how to bridge the current gap in spray drying scale-up via a rational understanding of the fundamental transformations.