The procedure for learning and creating a new medicine is widely seen as a drawn-out and costly endeavor. Different rational strategies are considered, depending on their requirements, as potential ways; nevertheless, techniques to designing drugs based on structure and ligands are well acknowledged as very practical and potent tactics in drug discovery. Computational approaches help decrease the need for Medicinal research with animals, helping to develop fresh, safe therapeutic concepts via rational design and positioning of existing products and supporting pharmaceutical scientists and medicinal chemists during the medication development process. Computer-aided drug discovery (CADD) methods are useful for reducing the time and cost of drug discovery and development and understanding the molecular mechanisms of drug action and toxicity. Molecular docking is a technique that predicts a ligand’s binding mode and affinity to a target protein. At the same time, QSAR is a technique that establishes mathematical relationships between the structural features and biological activities of a series of compounds. This study reviews the current state and applications of CADD methods, focusing on molecular docking and quantitative structure–activity relationship (QSAR) techniques. This study reviews the principles, advantages, limitations, and challenges of these methods, as well as some recent advances and examples of their applications in drug discovery for various diseases. The study also discusses the future prospects and directions of CADD methods in the era of big data and artificial intelligence.
In a recent article in Intelligent Pharmacy, a portion of the text appears to have been generated by a generative artificial intelligence (AI) system. The usage of AI is not documented in the article. If AI was used, therefore, the article is in violation of the journal’s policy on generative AI use and declaration.
The utilization of pharmaceuticals in medical and veterinary treatment has not only improved human and animal health but has also boosted food-production and economic welfare. However, the release of pharmaceuticals in the environment through various pathways, such as manufacturing, human excretion, and substandard disposal, can have detrimental effects on ecosystems and various biological entities associated with these systems. High levels of pharmaceutical residues have been detected further downstream of manufacturing facilities, and untreated veterinary medication leftovers can end up in waterbodies. Methods utilizing artificial intelligence (AI) and machine learning (ML) have been employed to establish connections between chemical structure and biological activity, referred to as quantitative structure–activity relationships (QSARs) for the compounds. QSAR models use chemical structures to predict hazardous activity when experimental data is lacking, thereby helping prioritize chemicals for testing and compilation. Combinatorial chemistry, by enabling high-throughput compound synthesis, accelerates the generation of targeted molecules for testing across various fields. Green chemistry helps in creating, designing, and implementing chemical products and procedures with the aim of minimizing or eradicating the generation and subsequent utilization of harmful substances. In addition, pharmaceutical sensor technologies (PST) are critical tools in modern medicine, enabling precise detection and monitoring of various biochemical and physiological markers and parameters. The synergy between AI, ML, QSAR modeling, and the implementation of combinatorial and green chemistry methodologies is pivotal in driving the development of innovative products and PST in pharmaceutics. This interdisciplinary approach is crucial for creating solutions with reduced toxicity in pharmaceutical processes, thereby ensuring enhanced public safety and promoting the sustainability of environmental resources. By integrating these advanced methodologies, the pharmaceutical industry can achieve greater detection accuracy, efficiency in production of eco-friendly products, ultimately leading to safer pharmaceutics and a healthier planet.
This comprehensive review explores modern granulation techniques in pharmaceutical dosage forms along with conventional methods, focusing on dry granulation and wet granulation. Dry granulation techniques, including slugging, roller compaction, and pneumatic dry granulation, are dissected with thorough analyses of their processing methods, advantages, disadvantages, and diverse applications. The article delves into eleven wet granulation techniques, offering insights into high-shear granulation, low-shear granulation, fluidized bed granulation, reverse wet granulation, steam granulation, moisture-activated dry granulation, melt granulation, freeze-dry granulation, foam granulation, thermal adhesion, and twin screw wet granulation. Each method is scrutinized, providing a comprehensive understanding of its processing steps, merits, drawbacks, and practical applications in pharmaceutical manufacturing. The article serves as a valuable resource for researchers, pharmaceutical professionals, and students, offering a nuanced exploration of diverse granulation techniques vital in drug formulation. This synthesis of information aims to enhance the understanding of granulation processes, facilitating informed decision-making in pharmaceutical development and manufacturing.
Objective: To conduct a comprehensive evaluation of PD-1 inhibitors for the treatment of advanced non-small cell lung cancer on the market in China, using A Quick Guideline for Drug Evaluation and Selection in Chinese Medical Institutions (Second Edition), and to provide a reference for the selection of and decision-making on clinical drugs in hospitals.
Method: The Sanzhi drug evaluation and selection system was used to evaluate the PD-1 inhibitors for the treatment of advanced non-small cell lung cancer on the market in China, according to five characteristics: pharmaceutical characteristics, efficiency, safety, economy, and others.
Results: Based on the above evaluation criteria, the scores of all PD-1 inhibitors were above 61 points. The main difference among the five characteristics were efficiency and economy. The difference between the other characteristics was relatively small. Sintilimab injection had the highest score due to the advantages among characteristics except the other attributes. Nivolumab injection (100 mg/10 mL (10 mg/mL)) had the lowest total score due to its low effectiveness and economy scores.
Conclusion: PD-1 inhibitors are effective therapeutic drugs for immunotherapy in patients with advanced non-small cell lung cancer. Different PD-1 inhibitors have different advantages in clinical treatment. The comprehensive evaluation of PD-1 inhibitors for the treatment of advanced non-small cell lung cancer on the market in China through A Quick Guide for Drug Evaluation and Selection of Chinese Medical Institutions (Second Edition) can provide a basis for drug selection and scientific, reasonable, and safe drug use in medical institutions.
According to the Global Burden of Disease Study and the World Health Organization, dental caries is one of the most prevalent oral diseases globally. It is well known that dental caries are associated with cariogenic bacteria and their biofilm. Many preventive strategies and therapeutic compounds have been proposed for decades. Among them, various plant-based phytochemical compounds have been investigated against cariogenic bacteria. In this review, we plan to show the effectiveness of Zingiber officinale to reduce dental caries. Z. officinale in ginger is a bioactive spice compound that shows antimicrobial activity. Therefore, it is reasonable to consider the antimicrobials and biofilm inhibition properties of bioactive Z. officinale to rationalize its potential in reducing dental caries. While the literature highlights the general antimicrobial properties of Z. officinale, this review focuses on Z. officinale’s capability against cariogenic microbes and their biofilms. Reported results of minimum inhibition concentration (MIC), minimum bactericidal concentration (MBC), and biofilm inhibition (glucans and adhesion) were systematically reviewed. Common search engines like PubMed, Science Direct, and the Web of Science database are used to retrieve data using the keywords “Zingiber officinale” and “dental caries”. Out of 122 resulting reports, 11 of them were included in this review. It can be concluded that Z. officinale effect against cariogenic bacteria varies depending on microbial and analytical factors. However, translational advanced studies have not yet been conducted to verify its clinical application.
This paper examines the transformative impact of artificial intelligence (AI) on pharmacogenomics, signaling a paradigm shift in personalized medicine. With a focus on enhancing drug response prediction and treatment optimization, AI, particularly machine learning and deep learning algorithms, navigates the complexity of genomic data. By elucidating intricate relationships between genetic factors and drug responses, AI augments the identification of genetic markers and contributes to the development of comprehensive models. The review emphasizes AI’s role in guiding treatment decisions, minimizing adverse reactions, and optimizing drug dosages in clinical settings. Ethical considerations, challenges, and future directions are also discussed. This work underscores the synergy of AI and pharmacogenomics, offering a more effective and patient-centric approach to drug therapy, marking a significant advancement in the field of personalized medicine.
Aims: Cardiovascular disease is the primary cause of mortality and morbidity, and its terminal phase is chronic heart failure. The present study aimed to examine the protective impact of rosuvastatin on isoproterenol-induced chronic heart failure and investigate plausible related mechanisms. Rosuvastatin, a drug with multiple pleiotropic properties, has been examined for its cardioprotective effects in heart failure induced by isoproterenol.
Methods: Male Sprague Dawley rats were given isoproterenol 5 mg/kg once a day for 7 days to establish heart failure by subcutaneous injection. Simultaneously, rosuvastatin (10 mg/kg) was orally administrated from day 1 to day 14. Protective effects were evaluated by heart grading and gross morphology, hemodynamic parameter, cardiac troponin I, heart mitochondrial enzyme and lysosomal hydrolases and pro inflammatory cytokines levels were analyzed.
Results: Rosuvastatin (10 mg/kg) significantly attenuated isoproterenol-induced hypertrophy, remodeling and dysfunction of the ventricle, reduced the heart mitochondrial enzyme and lysosomal hydrolases and normalized the increased hemodynamic and pro inflammatory cytokines levels.
Conclusions: The study highlights the preventive effects of, rosuvastatin, against heart failure. The results of the research indicate that rosuvastatin has cardioprotective effects on the experimental model, which were supported by several characteristics. However, further research is required to identify the precise molecular mechanisms and signalling pathways of rosuvastatin’s impact on heart failure.
Vernonia cinerea L., also known as purple fleabane, is a plant with medicinal properties that have been traditionally used to treat respiratory infections, digestive disorders, and skin conditions. Its antimicrobial and anti-inflammatory properties make it a potential candidate for treating various infections and inflammatory diseases. The plant contains alkaloids, flavonoids, and essential oils, which possess antimicrobial properties, making it a promising candidate for treating bacterial and fungal infections. Its anti-inflammatory properties have shown potential for managing inflammatory diseases like arthritis and dermatitis. Additionally, the plant's analgesic and antipyretic effects suggest its potential for pain management and fever reduction. Its antioxidant properties make it a potential candidate for preventing and treating oxidative stress-related diseases like cardiovascular disorders and neurodegenerative conditions. However, more studies are needed to determine its optimal dosage, safety profile, and potential drug interactions before widespread use in medical practice.
Mimusops elengi, a widely distributed tree species in tropical regions, has been used for centuries in traditional medicine due to its numerous therapeutic properties. In this study, we conducted a comprehensive analysis of the phytocompounds present in various parts of Mimusops elengi, including leaves, bark, and flowers using advanced analytical techniques. The objective was to identify and quantify the bioactive compounds responsible for the plant’s medicinal attributes. Our findings revealed a diverse range of phytochemicals in Mimusops elengi. The analysis detected various classes of compounds, including alkaloids, flavonoids, tannins, phenolic compounds, terpenoids and glycosides. Notably, the leaves contained a significant concentration of alkaloids, particularly elengioside, which has demonstrated potential anti-inflammatory and analgesic properties. Additionally, the flowers were rich in flavonoids and tannins, such as quercetin and catechin, known for their antioxidant and anticancer activities. Furthermore, the bark of Mimusops elengi exhibited the presence of terpenoids, including lupeol and betulinic acid, which have been associated with anti-inflammatory and antiviral properties. These compounds may contribute to the plant’s traditional use for treating various ailments, including skin disorders and respiratory issues. This review provides valuable insights into the phytochemical composition of Mimusops elengi, shedding light on its potential therapeutic applications. Mimusops elengi holds promise as a valuable source of natural compounds with health-promoting benefits.
Sea buckthorn (Hippophae rhamnoides L.) is a plant with various nutritional and medicinal properties. It contains vitamins, carotenoids, polyphenols, fatty acids, and phytosterols, which have antioxidant, anticancer, anti-hyperlipidemic, anti-obesity, anti-inflammatory, antimicrobial, antiviral, dermatological, neuroprotective, and hepatoprotective effects. Sea buckthorn can be used as a functional food or a dietary supplement for the prevention and treatment of chronic diseases. This review summarizes the phytochemistry, health benefits, and food applications of sea buckthorn, and highlights the potential and challenges for its further development and utilization. Sea buckthorn not only has greatmedicinal and therapeutic potential, but also is a promising economic plant. The potential of seabuckthorn in the human food industry has attracted the research interest of researchers and pro- ducers. The present review mainly summarizes the phytochemistry, nutrients, health benefits, andfood applications of sea buckthorn. Overall, sea buckthorn is a dietary source of bioactive ingredi- ents with the potential to be developed into functional foods or dietary supplements for the pre- vention and treatment of certain chronic diseases, which deserves further research.
Current clinical research suggests that inhibitors of protein arginine deiminase 4 (PAD4), major histocompatibility complex (MHC) class II HLA-DQ-ALPHA chain, and thyrotropin receptor (or TSH receptor) which are of biological and therapeutic interest, may show potential in treating rheumatoid arthritis, type 1 diabetes, Graves’ disease and other autoimmune disorder. In the present study, a comprehensive analysis was conducted on a collection of 32 compounds concerning their anti-rheumatoid arthritis activity as inhibitors of PAD4. This analysis represents the first instance in which these compounds were computationally examined, employing an in-silico approach that considered 2D-3D QSAR modeling, and molecular docking and was further validated through molecular dynamics and ADMET properties assessment. A credible 2D QSAR (Q_LOO^2 = 0.6611 and R^2 = 0.7535) model was constructed and verified using an external validation test set, Y-randomization, variance inflation factor (VIF), mean effect (MF), and William’s plot applicability domain (AD). Ligand-based alignment was implemented in the 3D-QSAR examination. The outcomes demonstrated that CoMFA (uvepls) (Q2LOO = 0.5877; R2 = 0.9983) possess remarkable stability and foresight. The internal validation indicated that CoMFA (uvepls) MIFs display superior predictive capability compared to COMFA (ffdsel). Structural criteria determined by the contour maps of the model and molecular docking simulations were strategically employed to computationally develop 10 new, non-toxic autoimmune disease inhibitors with increased efficacy. Docking tests were done on the newly developed compounds to illustrate their binding mechanism and to identify critical interaction residues inside the active region of rheumatoid arthritis (PDB id: 3BLU). In addition, docking results of the selected designed compounds inside the active sites of type 1 diabetes receptor (6DFX), and Graves’ disease receptor (4QT5) demonstrated their rheumatoid arthritis (PDB id: 3BLU) selectivity. A molecular dynamics simulation and binding free energy calculations using the MM/GBSA technique confirmed the stability of the proposed compound D4 inside the rheumatoid arthritis (3BLU) receptor active site. In summary, the results of our investigation might give considerable insight into the future design and development of new autoimmune disease inhibitors.
Employing the Internet of Things (IoT) in healthcare provides many advantages for patient monitoring and analysis of the patient’s health with the help of generated data. The basic role of IoT in healthcare is to ease the patient’s life by giving them a monitor over their medical condition. The use of IoT in medical devices requires a focus on the end-user. Medical devices such as glucose meters are designed to record the data of the patient and their vital signs. The generated information can be used to enhance decision-making for the physician. The collected information about the patient can be at risk due to certain security issues during the transferring of information can compromise the identity and social life of the patient. This review explores the IoT regarding its structural requirement and its role in various fields with special emphasis on healthcare. The security and privacy issues than can hinder the utilization of IoT at its potential and ways to overcome these issues are being addressed.
Objective: To evaluate the clinical efficacy of different species of polymyxin drugs in the treatment of Carbapenem-Resistant Gram-negative bacilli (CR-GNB) resistant to ceftazidime-avibactam (CZA).
Methods: Patients infected by CR-GNB strains and treated with polymyxin drugs were selected and divided into colistin methanesulfonate (CMS) group and colistin sulfate/polymyxin B (CSPB) group to observe clinical efficacy and safety.
Results: 65 patients were eventually included (CMS group, n = 29; CSPB group, n = 36). The clinical efficacy, microbiological eradication rate and 28-day mortality between the two groups were similar, with no statistical significance (51.72% vs. 50.00%, p = 0.890; 55.17% vs. 52.78%, p = 0.847; 17.24% vs. 25.00%, p = 0.449). With regard to renal safety, the incidence of acute kidney injury (AKI) in the CMS group was significantly higher than that in the CSPB group (34.48% vs. 5.56%, p = 0.003). Among them, the incidence of AKI grade 3 in the CMS group tended to be higher than that in the CSPB group (24.14% vs. 5.56%, p = 0.066).
Conclusion: The results based on small sample size from a single center showed that clinical response to the treatment of ceftazidime-avibactam resistant Gram-negative bacillus infections is similar for CMS and Colistin Sulfate/Polymyxin B, but the nephrotoxicity of CMS is greater than that of polymyxin sulfates.
Dengue fever is a mosquito-borne illness that affects millions of people worldwide. Artificial intelligence (AI) is being employed in the battle against it. AI is being used to analyse dengue immune repertoires, which may yield hitherto unheard-of insights into the complexities of dengue adaptive immunity, help in the development of novel treatments, and influence the creation of vaccines. This AI-driven strategy may contribute to the creation of dengue fever therapies that are more potent.
Dengue is a most important mosquito-borne viral illnesses. The disease is caused by dengue viruses that have four serotypes: dengue 1, dengue 2, dengue 3 and dengue 4. Primary infection usually results in milder illness, while more severe disease occurs in cases of repeated infection with different serotypes. Nanoparticles can offer significant advantages over the conventional drug delivery in terms of high stability, high specificity, high drug carrying capacity, ability for controlled release, possibility to use in different route of administration and the capability to deliver both hydrophilic and hydrophobic drug molecules. Due to the high prevalence of dengue viruses, it is required to develop novel treatment strategies and provide the site-specific delivery of drug reservoirs.
Since the dawn of time, people have used herbal medications to both prevent and treat a variety of illnesses. Numerous illnesses, including diabetes, skin conditions, and most seriously cancer, have been claimed to be successfully treated by Acacia Arabica. According to Indian traditional medicine, the fresh sections of Acacia Arabica have beneficial nutritional properties as well as astringent, demulcent, aphrodisiac, anthelmintic, antibacterial, and antidiarrheal properties. The ethnobotanical and therapeutic benefits of Acacia Arabica are briefly reviewed in this article along with information about the plants. This is an attempt to gather and record data regarding many facets of Acacia Arabica and its prospective applications. Before using Acacia Arabica’s therapeutic potential, more research is required.
One form of uncommon cancer that develops in the smooth muscles is called leiomyosarcoma, or LMS. The body’s hollow organs, such as the stomach, bladder, intestines, and blood vessels, contain smooth muscles. The three main components of conventional therapy are surgery, chemotherapy, and radiotherapy. These treatments have numerous drawbacks, including insufficient surgical resection, drug resistance to chemotherapy, radiotherapy insensitivity, and postoperative bone defects. Because of their easy modification, targeting, and other characteristics, along with their unique physicochemical properties, nanoparticles have been used extensively in research on anti-leiomyosarcoma treatment. Inhibiting the onset and progression of leiomyosarcoma, nanoparticles can have a variety of effects on the growth of leiomyosarcoma cells. We provide a brief overview of the development of nanoparticle research closely associated with leiomyosarcoma treatment in this review.
Cancer drug resistance is a serious issue in Bangladesh that must be addressed with effective solutions. The growth of resistant bacterial strains, inappropriate use of antimicrobials, and inadequate healthcare standards in Bangladesh have resulted in a severe problem with cancer medication resistance. A comprehensive strategy will be needed to address these problems, one that includes expanding knowledge of antibiotic resistance, bettering healthcare system regulation, and developing more potent cancer therapies.