Hasil untuk "Pharmaceutical industry"

R. Henderson, I. Cockburn

S. Kar, H. Sanderson, K. Roy et al.

The principles of green chemistry (GC) can be comprehensively implemented in green synthesis of pharmaceuticals by choosing no solvents or green solvents (preferably water), alternative reaction media, and consideration of one-pot synthesis, multicomponent reactions (MCRs), continuous processing, and process intensification approaches for atom economy and final waste reduction. The GC's execution in green synthesis can be performed using a holistic design of the active pharmaceutical ingredient's (API) life cycle, minimizing hazards and pollution, and capitalizing the resource efficiency in the synthesis technique. Thus, the presented review accounts for the comprehensive exploration of GC's principles and metrics, an appropriate implication of those ideas in each step of the reaction schemes, from raw material to an intermediate to the final product's synthesis, and the final execution of the synthesis into scalable industry-based production. For real-life examples, we have discussed the synthesis of a series of established generic pharmaceuticals, starting with the raw materials, and the intermediates of the corresponding pharmaceuticals. Researchers and industries have thoughtfully instigated a green synthesis process to control the atom economy and waste reduction to protect the environment. We have extensively discussed significant reactions relevant for green synthesis, one-pot cascade synthesis, MCRs, continuous processing, and process intensification, which may contribute to the future of green and sustainable synthesis of APIs.

T. Loftsson, P. Jarho, M. Másson et al.

M. Thakur, S. Bhattacharya, P. Khosla et al.

Abstract Plants need to counter continuous threats posed by the environment, such as pathogen attacks (fungi, viruses, insects, nematodes) and harsh physical conditions (drought, salinity, temperature, exposure to UV radiation). Plants recognize the threat signals through their receptors and sensors and activate defense responses to stabilize against these stresses. The responses include accumulation of secondary metabolites. Enhanced synthesis of secondary metabolites, called elicitation ensures the survival, persistence and competitiveness of the plant. Secondary metabolites include volatile oils, flavonoids, alkaloids, glycosides, tannins, resins etc that have been successfully exploited for vital sources for food additives, flavors, and industrially important pharmaceuticals. The improved production of the secondary metabolites through elicitation has unlocked a new area of research that could have significant economic benefits for the pharmaceutical and therapeutic (including neutraceutical) industry. The present review discusses about the different elicitation methods through various biotic (proteins, carbohydrates, plant growth promoting rhizobacteria, fungus, hormones) and abiotic elicitors (heavy metals, low and high temperature, light, salt, drought) that could bring about increased yield of secondary metabolites especially in medicinal plants beneficial to the medicinal and aromatic industry.

G. Mooter

N. Baenas, Miona Belović, Nebojša Ilić et al.

The recovery of pepper phytochemicals present an interesting strategy in pursuit of new bioactive compounds and natural ingredients for agro-food, cosmetic and pharma industry uses, as replacements for the synthetic compounds and also in the valorisation of plant's by-products. Besides being used as a condiment, providing characteristic pungency, colour and flavour, the new pepper-derived ingredients could be used for the preservation and extension of industrial products' lifespan, as well as additives or technological ingredients with antioxidant and antimicrobial activities. Moreover, the application of the new products in pharmaceutical formulas for the treatment of inflammatory and pain-related conditions is also a possibility, since peppers contain capsaicinoids, carotenoids, phenolic compounds, vitamin C and A, and minerals, such as iron and calcium, which have a health-promoting potential. Further studies on appropriate extraction protocols, stability, safety and bioactivity are necessary to provide novel and promising pepper ingredients for food, cosmetic, and pharmaceutical applications.

G. Salkeld, Andrew S. Mitchell, Suzanne Hill

Anthropology looks at pharmaceuticals as social and cultural phenomena. It is interested in the relationship between human beings and the medicines they produce, sell, prescribe, and consume. This entry describes the history of pharmaceutical anthropology, the “biography” and “social life” of pharmaceuticals, and the most prominent concepts and perspectives in the study of pharmaceuticals, including critical medical anthropology, agency, pharmaceuti-calization, self-medication, commodification, globalization, pharmaceutical symbolism, and resistance toward the use of pharmaceuticals. Three long-lasting debates related to pharmaceuticals are presented: the role of the industry, the placebo effect, and the controversy about the efficacy of traditional/alternative versus biomedical medicines. Lastly, the practical relevance of anthropological research of pharmaceuticals is discussed.

Bengu Ozturk, D. Mcclements

Paul N. Devine, Roger M. Howard, R. Kumar et al.

C. M. Peixoto, M. I. Días, M. Alves et al.

The bio-residues resulting from the wine industry (grape pomace made up of skins, seeds and stems) are often undervalued but constitute a potential source of bioactive phenolic compounds that can be applied in several industries. In this context, the aim of the present study was to evaluate the phenolic profile of Vitis vinifera L. grape pomace (skins, seeds and their mixture), and correlate them with its antioxidant, cytotoxic and antibacterial activities. The seeds showed the highest amount of phenolic compounds and also the highest antioxidant, cytotoxic and antibacterial activities. The skins revealed the highest levels of anthocyanins and p-coumaric acid hexoside. Strong correlations were observed between the presence of phenolic compounds and all the bioactivities studied. These by-products are good sources of phenolic compounds with high antioxidant and antibacterial activity, and also presenting a moderate cytotoxicity activity. These added-value by-products have great applicability in food, pharmaceutical and cosmetic industries.

T. Fuchs-Buder, C. Claudius, L. Skovgaard et al.

Javiera Cortés‐Ríos, Mindy Magee, Anna Sher et al.

ABSTRACT In silico clinical trials (ISCT) are computational frameworks that employ mathematical models to generate virtual patients and simulate their responses to new treatments, treatment regimens, or medical devices via simulations mirroring real‐world clinical trials. ISCTs are an important component of the model‐informed drug development (MIDD) framework for optimizing therapies, treatment personalization, informing regulatory decisions, and accelerating overall drug development by enhancing R&D productivity. However, the emergence of complex models, such as quantitative systems pharmacology (QSP) models, presents significant challenges for their effective implementation. Guidelines for conducting ISCTs have been published to address these challenges, focusing on algorithms and credibility frameworks for generating plausible virtual patients and calibrating virtual populations. However, it is not straightforward to apply existing workflows to models where parameter distributions and correlations are estimated using nonlinear mixed effects (NLME) population fitting approaches, a common practice in the pharmaceutical industry when individual‐patient‐level data is available. Here, we illustrate a modeling workflow for conducting ISCTs with NLME models, detailing key considerations, methods, and challenges at each step. We demonstrate the practical implementation of this workflow through two examples to showcase its broad applicability: (1) a simple model predicting tumor growth in response to chemotherapy and (2) a more complex mechanistic QSP model of hepatitis B virus infection that captures the physiological mechanisms underlying treatment response with standard‐of‐care therapies.

Syngeeva E. V., Lamazhapova G. P.

The paper presents the results of studying biologically active substances (BAS) in the leaves of sea buckthorn and black currant growing in the Republic of Buryatia. The analysis of the content of vitamin C, tannins, flavonoids, and the total amount of antioxidants in water-alcohol extracts obtained using ethanol of various concentrations has been carried out. It has been established that specific extraction conditions, including the optimal alcohol concentration and duration of the process, are required for the maximum extraction of individual BAS. For example, the highest content of ascorbic acid in sea buckthorn leaves is achieved using 60 % ethanol and maceration for 120 hours, while for tannins, the optimal condition is a 70 % alcohol solution with boiling for 45 minutes. In black currant leaves, the maximum concentration of vitamin C is observed after 120 hours of maceration with 50 % ethanol, and the highest yield of flavonoids has been achieved by extraction with 70 % alcohol for 60 minutes. The highest content of antioxidants in sea buckthorn leaves has been achieved using 60 % alcohol, while in black currant leaves, it has been achieved with 50 % alcohol. The content of water-soluble vitamins has also been determined in the extracts. The extract from sea buckthorn leaves contains vitamin C – 0,805 mg/g, while the extract from black currant leaves – 0,105 mg/g. Additionally, the content of B-group vitamins has been determined in the extracts from sea buckthorn and black currant leaves. The obtained data confirm the potential of using plant raw materials from Buryatia and their extracts for the development of dietary supplements, pharmaceutical preparations, and functional ingredients for the food industry. The study emphasizes the importance of optimizing technological processes to preserve the biological activity of extracts and their further application in various fields.

PENG Jiwei, CHEN Hao, XIAO Lei et al.

With the wastewater treatment project of a taurine production enterprise in Hubei as a case study, this paper analyzed the production process and wastewater quality characteristics of the enterprise, the targeted treatment process of “hydrolysis acidification+pre anoxic+aerobic biochemistry+post anoxic+secondary sedimentation” was adopted. When the average influent COD, ammonia nitrogen, and total nitrogen were 956.8, 50.6, 99.1 mg/L, respectively, the average effluent COD, ammonia nitrogen, and TN were 73.6, 1.6, 12.2 mg/L, respectively, with the average removal rates could reach 92.3%, 96.9%, and 87.7%, respectively. The effluent water quality was stable and meet the limits of water pollutants for newly built enterprises in the Chemical Synthesis Pharmaceutical Industry Water Pollutant Discharge Standard(GB 21904-2008). By adopting tapered aeration and fan frequency conversion control, energy consumption was significantly reduced, and the operating cost was 1.60 CNY/m3.

Bahareh Nowruzi, yasaman Gorani

Phycobiliproteins (PBPs) are colored and water-soluble biliproteins that are found in cyanobacteria and rhodophytes. Based on their spectral characteristics, PBPs are divided into three types: Allophycocyanin, phycocyanin and phycoerythrin. PBPs, apart from their special function as sunlight-receiving antennas in the photosynthesis process, can be used as food dyes, nutrients, cosmetics, pharmaceutical industries and fluorescent probes in immunofluorescence analysis. Since PBPs have antioxidant, anti-tumor effects, as well as potential anti-inflammatory and anti-diabetic properties, in this review article, an attempt was made to investigate the properties and medicinal potential of PBPs along with their structural features. The results of the review of recent articles showed that the PBP part of proteins is very sensitive to environmental stress and this issue limits their use in the food industry. Therefore, it is necessary to use protective and coating materials to preserve the color. Consequently, they can prevent the denaturation of the protein structure, which not only increases the antioxidant properties but also increases the half-life of the food.

Anita Ioana Visan, Irina Negut

Drug development is expensive, time-consuming, and has a high failure rate. In recent years, artificial intelligence (AI) has emerged as a transformative tool in drug discovery, offering innovative solutions to complex challenges in the pharmaceutical industry. This manuscript covers the multifaceted role of AI in drug discovery, encompassing AI-assisted drug delivery design, the discovery of new drugs, and the development of novel AI techniques. We explore various AI methodologies, including machine learning and deep learning, and their applications in target identification, virtual screening, and drug design. This paper also discusses the historical development of AI in medicine, emphasizing its profound impact on healthcare. Furthermore, it addresses AI’s role in the repositioning of existing drugs and the identification of drug combinations, underscoring its potential in revolutionizing drug delivery systems. The manuscript provides a comprehensive overview of the AI programs and platforms currently used in drug discovery, illustrating the technological advancements and future directions of this field. This study not only presents the current state of AI in drug discovery but also anticipates its future trajectory, highlighting the challenges and opportunities that lie ahead.

Veysel Gider, Cafer Budak

The effective development and design of pharmaceuticals hold fundamental importance in the fields of medicine and the pharmaceutical industry. In this process, the accurate prediction of drug molecule solubility is a critical factor influencing the bioavailability, pharmacokinetics, and toxicity of drugs. Traditionally, mathematical equations based on chemical and physical properties have been used for drug solubility prediction. However, in recent years, with the advancement of artificial intelligence and machine learning techniques, new approaches have been developed in this field. This study evaluated different modeling approaches consisting of Graph Neural Networks (GNN), Multilayer Perceptron (MLP), and traditional Machine Learning (ML) algorithms. The Random Forest (RF) model stands out as the optimal performer, manifesting superior efficacy through the attainment of minimal error rates. It attains a Root Mean Square Error (RMSE) value of 1.2145, a Mean Absolute Error (MAE) value of 0.9221, and an R-squared (R2) value of 0.6575. In contrast, GNN model displays comparatively suboptimal performance, as evidenced by an RMSE value of 1.8389, an MAE value of 1.4684, and an R2 value of 0.2147. These values suggest that the predictions of this model contain higher errors compared to other models, and its explanatory power is lower. These findings highlight the performance differences among different modeling approaches in drug solubility prediction. The RF model is shown to be more effective than other methods, while the GNN model performs less effectively. This information provides valuable insights into which model should be preferred in pharmaceutical design and development processes.

I. Romashko, S. Maikova, O. Vivcharuk et al.

There is an active search for alternative types of raw materials for the needs of the national economy. Fossil fuel reserves are noticeably depleted, the ecological condition of the environment is deteriorating, and at the same time, the amount of industrial waste that needs to be disposed of is increasing. The number of polymers for production based on natural raw materials and the need for them for the food industry, biomedical and pharmaceutical applications is constantly growing. About 250,000 liters of used vegetable oil and other fats are generated every week in catering establishments of Ukraine. The largest share belongs to spent frying fats. A significant volume of promising raw materials ends up in the sewage system. The resources of the treatment plants are excessively depleted. Also, emissions of spent fatty raw materials cause enormous damage to the environment. A study was conducted on: the dynamics of changes in quality indicators of sunflower oil during prolonged heating; evaluation of the quality indicators of the samples of the studied spent fats; dynamics of changes in cooking fat quality indicators during prolonged heating; the dynamics of changes in the quality indicators of frying fat during prolonged heating; the physico-chemical indicators of the quality of samples of experimental used fats were investigated. The possibility of using spent frying fats for the production of targeted products, which is a promising resource for the synthesis and production of polymer materials and secondary raw materials in the processes of the technical sphere and the production of biofuel, was investigated. The use of spent liquid fats as a raw material for the production of diesel fuel is appropriate, however, among the tested samples, heated sunflower oil is the least suitable. Spent deep-frying and cooking fats showed a fairly high resistance to long-term heating and after contact with a hot surface are characterized by acceptable values of thermo-oxidative stability, namely 46.5 and 44.1 %, respectively.

Elisabeth Fink, Michael Brunsteiner, Stefan Mitsche et al.

Co-amorphous systems (COAMS) have raised increasing interest in the pharmaceutical industry, since they combine the increased solubility and/or faster dissolution of amorphous forms with the stability of crystalline forms. However, the choice of the co-former is critical for the formation of a COAMS. While some models exist to predict the potential formation of COAMS, they often focus on a limited group of compounds. Here, four classes of combinations of an active pharmaceutical ingredient (API) with (1) another API, (2) an amino acid, (3) an organic acid, or (4) another substance were considered. A model using gradient boosting methods was developed to predict the successful formation of COAMS for all four classes. The model was tested on data not seen during training and predicted 15 out of 19 examples correctly. In addition, the model was used to screen for new COAMS in binary systems of two APIs for inhalation therapy, as diseases such as tuberculosis, asthma, and COPD usually require complex multidrug-therapy. Three of these new API-API combinations were selected for experimental testing and co-processed via milling. The experiments confirmed the predictions of the model in all three cases. This data-driven model will facilitate and expedite the screening phase for new binary COAMS.

Jovana Panić, Maksim Rapaić, Slobodan Gadžurić et al.

Due to their appealing physiochemical properties, particularly in the pharmaceutical industry, deep eutectic solvents (DESs) and ionic liquids (ILs) are utilized in various research fields and industries. The presented research analyzes the thermodynamic properties of a deep eutectic solvent created from natural molecules, menthol and lauric acid in a 2:1 molar ratio, and an ionic liquid based on two active pharmaceutical ingredients, benzocainium ibuprofenate. Initially, the low solubility of benzocainium ibuprofenate in water was observed, and a hydrophobic natural deep eutectic mixture of menthol:lauric acid in a 2:1 ratio was prepared to improve benzocainium ibuprofenate solubility. In order to determine the solvent properties of DESs and ILs mixtures at different temperatures and their molecular interactions to enhance the solvent performance, the apparent molar volume, limiting apparent molar expansibility, and viscosity B coefficient were estimated in temperature range from 293.15 K to 313.15 K and varying concentration of benzocainium ibuprofenate.