Hasil untuk "Pharmaceutical industry"

Kamila Zduńska, Agnieszka Dana, A. Kołodziejczak et al.

D. Erdemir, Alfred Y Lee, A. Myerson

A. Basso, S. Serban

Abstract The use of immobilized enzymes is now a routine process for the manufacture of many industrial products in the pharmaceutical, chemical and food industry. Some enzymes, such as lipases, are naturally robust and efficient, can be used for the production of many different molecules and have a wide range of industrial applications thanks to their broad selectivity. As an example, lipase from Candida antarctica (CalB) has been used by BASF to produce chiral compounds, such as the herbicide Dimethenamide-P, which was previously made chemically. The use of the immobilized enzyme has provided significant advantages over a chemical process, such as the possibility to use equimolar concentration of substrates, obtain an enantiomeric excess > 99%, use relatively low temperatures ( 1 ]. Some more specific enzymes, like transaminases, have required protein engineering to become suitable for applications in production of APIs (Active Pharmaceutical Ingredients) in conditions which are extreme for a wild type enzyme. The process developed by Merck for sitagliptin manufacture is a good example of challenging enzyme engineering applied to API manufacture. The previous process of sitagliptin involved hydrogenation of enamine at high pressure using a rhodium-based chiral catalyst. By developing an engineered transaminase, the enzymatic process was able to convert 200 g/l of prositagliptin in the final product, with e.e. >99.5% and using an immobilized enzyme in the presence of DMSO as a cosolvent [ 2 ]. For all enzymes, the possibility to be immobilized and used in a heterogeneous form brings important industrial and environmental advantages, such as simplified downstream processing or continuous process operations. Here, we present a series of large-scale applications of immobilized enzymes with benefits for the food, chemical, pharmaceutical, cosmetics and medical device industries, some of which have been scarcely reported on previously. In general, all enzymatic reactions can benefit from the immobilization, however, the final choice to use them in immobilized form depends on the economic evaluation of costs associated with their use versus benefits obtained in the process. It can be concluded that the benefits are rather significant, since the use of immobilized enzymes in industry is increasing.

P. Hajduk, J. Greer

D. Mcclements, E. Decker, J. Weiss

Jaya Baranwal, Brajesh Barse, A. Fais et al.

Biopolymers are a leading class of functional material suitable for high-value applications and are of great interest to researchers and professionals across various disciplines. Interdisciplinary research is important to understand the basic and applied aspects of biopolymers to address several complex problems associated with good health and well-being. To reduce the environmental impact and dependence on fossil fuels, a lot of effort has gone into replacing synthetic polymers with biodegradable materials, especially those derived from natural resources. In this regard, many types of natural or biopolymers have been developed to meet the needs of ever-expanding applications. These biopolymers are currently used in food applications and are expanding their use in the pharmaceutical and medical industries due to their unique properties. This review focuses on the various uses of biopolymers in the food and medical industry and provides a future outlook for the biopolymer industry.

S. Frokjaer, D. Otzen

D. Batish, H. Singh, R. Kohli et al.

G. Martău, M. Mihai, D. Vodnar

Nowadays, biopolymers as intelligent and active biopolymer systems in the food and pharmaceutical industry are of considerable interest in their use. With this association in view, biopolymers such as chitosan, alginate, pectin, cellulose, agarose, guar gum, agar, carrageenan, gelatin, dextran, xanthan, and other polymers have received significant attention in recent years due to their abundance and natural availability. Furthermore, their versatile properties such as non-toxicity, biocompatibility, biodegradability, and flexibility offer significant functionalities with multifunctional applications. The purpose of this review is to summarize the most compatible biopolymers such as chitosan, alginate, and pectin, which are used for application in food, biotechnological processes, and biomedical applications. Therefore, chitosan, alginate, and pectin are biopolymers (used in the food industry as a stabilizing, thickening, capsular agent, and packaging) with great potential for future developments. Moreover, this review highlights their characteristics, with a particular focus on their potential for biocompatibility, biodegradability, bioadhesiveness, and their limitations on certain factors in the human gastrointestinal tract.

O. Afanasyev, E. Kuchuk, D. Usanov et al.

Reductive amination plays a paramount role in pharmaceutical and medicinal chemistry owing to its synthetic merits and the ubiquitous presence of amines among biologically active compounds. It is one of the key approaches to C-N bond construction due to its operational easiness and a wide toolbox of protocols. Recent studies show that at least a quarter of C-N bond-forming reactions in the pharmaceutical industry are performed via reductive amination. This Review concisely compiles information on 71 medical substances that are synthesized by reductive amination. Compounds are grouped according to the principle of action, which includes drugs affecting the central nervous system, drugs affecting the cardiovascular system, anticancer drugs, antibiotics, antiviral and antifungal medicines, drugs affecting the urinary system, drugs affecting the respiratory system, antidiabetic medications, drugs affecting the gastrointestinal tract, and drugs regulating metabolic processes. A general synthetic scheme is provided for each compound, and the description is focused on reductive amination steps. The green chemistry metric of reaction mass efficiency was calculated for all reactions.

Peter Groves, Basel Kayyali, D. Knott et al.

C. Beres, G. N. Costa, I. Cabezudo et al.

Grape is the main fruit crop in several countries. Although many grape-based food products can be found in the market, studies have shown that around 75% of the world grape production is destined for the wine industry. Grape pomace is an abundant by-product from the wine industry, which consists of the remaining skin, seeds and stalks and represents around 25% of total grape weight used in the winemaking process. In countries such as Italy, France and Spain, where wine production is more relevant, the annual grape pomace generation can reach nearly 1200 tonnes per year. In order to reach a sustainable winemaking process there is a need of a waste reduction policy. Several studies explore this subject using grape pomace as a source of healthy and technological compounds that could be applied in animal feed, pharmaceutical, cosmetic or food industry to improve stability and nutritional characteristics, and in cosmetic industry, where grape seeds oil is widely used. This review aims to approach the recent winemaking scenario and the benefits achieved when a waste management policy is implemented, as well as to compare available extractive technologies and a wide alternative of uses for grape pomace.

V. Chandel, Deblina Biswas, Swarup Roy et al.

Pectin is a heterogeneous hydrocolloid present in the primary cell wall and middle lamella in all dicotyledonous plants, more commonly in the outer fruit coat or peel as compared to the inner matrix. Presently, citrus fruits and apple fruits are the main sources for commercial extraction of pectin, but ongoing research on pectin extraction from alternate fruit sources and fruit wastes from processing industries will be of great help in waste product reduction and enhancing the production of pectin. Pectin shows multifunctional applications including in the food industry, the health and pharmaceutical sector, and in packaging regimes. Pectin is commonly utilized in the food industry as an additive in foods such as jams, jellies, low calorie foods, stabilizing acidified milk products, thickener and emulsifier. Pectin is widely used in the pharmaceutical industry for the preparation of medicines that reduce blood cholesterol level and cure gastrointestinal disorders, as well as in cancer treatment. Pectin also finds use in numerous other industries, such as in the preparation of edible films and coatings, paper substitutes and foams. Due to these varied uses of pectin in different applications, there is a great necessity to explore other non-conventional sources or modify existing sources to obtain pectin with desired quality attributes to some extent by rational modifications of pectin with chemical and enzymatic treatments.

Wendie Levasseur, P. Perré, Victor Pozzobon

This work reviews applications of high added value molecules produced from microalgae. Older forms of valorization - health food and quality feed, polyunsaturated fatty acids, pigments, carbohydrates - are currently penetrating their markets. They are driven by desirable properties: texturer and dye for food industry, antioxidant for cosmetics and the appetite of the general public for biosourced compounds. Most recent developments, such as peptides, vitamins, polyphenols, phytosterols and phytohormones, are struggling to meet their market and reach economical competitiveness. Still they are pushed forward by the very powerful driver that is pharmaceutical industry. In addition this work also proposes to link microalgae phyla and related potential applications. This is done through highlighting of which bioactive compounds can be found in which phyla. While some seem to be restricted to aquaculture, Cyanobacteria, Chlorophyta and Rhodophyta show great promises.

M. Alhnan, T. Okwuosa, M. Sadia et al.

T. Brennan, D. Rothman, L. Blank et al.

Jorge Martinez-Gil, Mario Pichler, Nefeli Bountouni et al.

We present a novel framework for Industry 5.0 that simplifies the deployment of AI models on edge devices in various industrial settings. The design reduces latency and avoids external data transfer by enabling local inference and real-time processing. Our implementation is agent-based, which means that individual agents, whether human, algorithmic, or collaborative, are responsible for well-defined tasks, enabling flexibility and simplifying integration. Moreover, our framework supports modular integration and maintains low resource requirements. Preliminary evaluations concerning the food industry in real scenarios indicate improved deployment time and system adaptability performance. The source code is publicly available at https://github.com/AI-REDGIO-5-0/ci-component.

Xuanming Zhang

Industrial carbon emissions are a major driver of climate change, yet modeling these emissions is challenging due to multicollinearity among factors and complex interdependencies across sectors and time. We propose a novel graph-based deep learning framework DGL to analyze and forecast industrial CO_2 emissions, addressing high feature correlation and capturing industrial-temporal interdependencies. Unlike traditional regression or clustering methods, our approach leverages a Graph Neural Network (GNN) with attention mechanisms to model relationships between industries (or regions) and a temporal transformer to learn long-range patterns. We evaluate our framework on public global industry emissions dataset derived from EDGAR v8.0, spanning multiple countries and sectors. The proposed model achieves superior predictive performance - reducing error by over 15% compared to baseline deep models - while maintaining interpretability via attention weights and causal analysis. We believe that we are the first Graph-Temporal architecture that resolves multicollinearity by structurally encoding feature relationships, along with integration of causal inference to identify true drivers of emissions, improving transparency and fairness. We also stand a demonstration of policy relevance, showing how model insights can guide sector-specific decarbonization strategies aligned with sustainable development goals. Based on the above, we show high-emission "hotspots" and suggest equitable intervention plans, illustrating the potential of state-of-the-art AI graph learning to advance climate action, offering a powerful tool for policymakers and industry stakeholders to achieve carbon reduction targets.

Jorge A. Arroyo

I study how first sizable industry entries reshape local and neighboring labor markets in Puerto Rico. Using over a decade of quarterly municipality--industry data (2014Q1--2025Q1), I identify ``first sizable entries'' as large, persistent jumps in establishments, covered employment, and wage bill, and treat these as shocks to local industry presence at the municipio--industry level. Methodologically, I combine staggered-adoption difference-in-differences estimators that are robust to heterogeneous treatment timing with an imputation-based event-study approach, and I use a doubly robust difference-in-differences framework that explicitly allows for interference through pre-specified exposure mappings on a contiguity graph. The estimates show large and persistent direct gains in covered employment and wage bill in the treated municipality--industry cells over 0--16 quarters. Same-industry neighbors experience sizable short-run gains that reverse over the medium run, while within-municipality cross-industry and neighbor all-industries spillovers are small and imprecisely estimated. Once these spillovers are taken into account and spatially robust inference and sensitivity checks are applied, the net regional 0--16 quarter effect on covered employment is positive but modest in magnitude and estimated with considerable uncertainty. The results imply that first sizable entries generate substantial local gains where they occur, but much smaller and less precisely measured net employment gains for the broader regional economy, highlighting the importance of accounting for spatial spillovers when evaluating place-based policies.

Zhongsheng Wang, Sijie Wang, Jia Wang et al.

In the design of customer relationship management (CRM) systems, accurately identifying customer types and offering personalized services are key to enhancing customer satisfaction and loyalty. However, this process faces the challenge of discerning customer voices and intentions, and general pre-trained automatic speech recognition (ASR) models make it difficult to effectively address industry-specific speech recognition tasks. To address this issue, we innovatively proposed a solution for fine-tuning industry-specific ASR models, which significantly improved the performance of the fine-tuned ASR models in industry applications. Experimental results show that our method substantially improves the crucial auxiliary role of the ASR model in industry CRM systems, and this approach has also been adopted in actual industrial applications.