Diversity matters: Widening the chemical space in organic solvent nanofiltration

Organic Solvent Nanofiltration in Pharmaceutical Applications

Separation and purification in organic solvents are indispensable procedures in pharmaceutical manufacturing. However, they still heavily rely on the conventional separation technologies of distillation and chromatography, resulting in high energy and massive solvent consumption. As an alternative, organic solvent nanofiltration (OSN) offers the benefits of low energy consumption, low solid waste generation, and easy scale-up and incorporation into continuous processes. Thus, there is a growing interest in employing membrane technology in the pharmaceutical area to improve process sustainability and energy efficiency. This Review comprehensively summarizes the recent progress (especially the last 10 years) of organic solvent nanofiltration and its applications in the pharmaceutical industry, including the concentration and purification of active pharmaceutical ingredients, homogeneous catalyst recovery, solvent exchange and recovery, and OSN-assisted peptide/oligonucleotide synthesis. Furthermore, the challenges and future perspectives of membrane technology in pharmaceutical applications are discussed in detail.

Hollow Fiber Membrane for Organic Solvent Nanofiltration: A Mini Review

Organic solvents take up 80% of the total chemicals used in pharmaceutical and related industries, while their reuse rate is less than 50%. Traditional solvent treatment methods such as distillation and evaporation have many disadvantages such as high cost, environmental unfriendliness, and difficulty in recovering heat-sensitive, high-value molecules. Organic solvent nanofiltration (OSN) has been a prevalent research topic for the separation and purification of organic solvent systems since the beginning of this century with the benefits of no-phase change, high operational flexibility, low cost, as well as environmental friendliness. Especially, hollow fiber (HF) OSN membranes have gained a lot of attention due to their high packing density and easy scale-up as compared with flat-sheet OSN membranes. This paper critically reviewed the recent research progress in the preparation of HF OSN membranes with high performance, including different materials, preparation methods, and modification treatments. This paper also predicts the future direction of HF OSN membrane development.

Chemometric Analysis of NMR Spectra and Machine Learning to Investigate Membrane Fouling

Efficient membrane filtration requires the understanding of the membrane foulants and the functional properties of different membrane types in water purification. In this study, dead-end filtration of aquaculture system effluents was performed and the membrane foulants were investigated via nuclear magnetic resonance (NMR) spectroscopy. Several machine learning models (Random Forest; RF, Extreme Gradient Boosting; XGBoost, Support Vector Machine; SVM, and Neural Network; NN) were constructed, one to predict the maximum transmembrane pressure, for revealing the chemical compounds causing fouling, and the other to classify the membrane materials based on chemometric analysis of NMR spectra, for determining their effect on the properties of the different membrane types tested. Especially, RF models exhibited high accuracy; the important chemical shifts observed in both the regression and classification models suggested that the proportional patterns of sugars and proteins are key factors in the fouling progress and the classification of membrane types. Therefore, the proposed strategy of chemometric analysis of NMR spectra is suitable for membrane research, which aims at investigating comprehensively the fouling phenomenon and how the foulants and environmental conditions vary according to the filtration systems.