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Peripheral nerve injuries (PNIs) are common, costly, and cause significant pain. Effective management of PNIs involves tailoring medications to the injury type as well as understanding the pharmacokinetics/pharmacodynamics to support nerve regeneration and reduce pain. Opioids act on opioid receptors to significantly reduce pain for many patients, but there are significant addiction risks and side effects. In addition, opioids may exacerbate pain sensitivity and affect nerve regeneration. Non‐steroidal anti‐inflammatory drugs or acetaminophen act on cyclooxygenase enzymes and are commonly used for nerve pain, with 34.7% of people using them for neuropathic pain. While effective for mild pain, they are often combined with opioids, gamma‐aminobutyric acid (GABA) analogs, lidocaine, or corticosteroids for more severe pain. Corticosteroids, mimicking adrenal hormones like cortisol, treat PNI‐related inflammation and pain. Their pharmacokinetics are complex, often requiring local injections in order to minimize systemic risks while effectively treating PNIs. Lidocaine, a common local anesthetic, blocks ion channels in the central nervous system (CNS) and peripheral nerves, providing strong analgesic and anti‐inflammatory effects. If used improperly, lidocaine can cause neuronal toxicity instead of anesthetic effect. GABA acts as an inhibitory neurotransmitter in the CNS and its drug analogs like pregabalin and gabapentin can alleviate neuropathic pain by binding to voltage‐gated Ca2+ channels, inhibiting neurotransmitter release. These pain medications are commonly prescribed for PNIs despite a limited guidance on their effects on nerve regeneration. This review will discuss these drug's mechanisms of action, pharmacokinetics/pharmacodynamics, and their clinical application to highlight their effect on the PNI recovery. [ABSTRACT FROM AUTHOR]

Background/Objectives: Numerical simulation plays an important role in pharmaceutical preparation recently. Mechanistic models, as a type of numerical model, are widely used in the study of pharmaceutical preparations. Mechanistic models are based on a priori knowledge, i.e., laws of physics, chemistry, and biology. However, due to interdisciplinary reasons, pharmacy researchers have greater difficulties in using computer models. Methods: In this paper, we highlight the application scenarios and examples of mechanistic modelling in pharmacy research and provide a reference for drug researchers to get started. Results: By establishing a suitable model and inputting preparation parameters, researchers can analyze the drug preparation process. Therefore, mechanistic models are effective tools to optimize the preparation parameters and predict potential quality problems of the product. With product quality parameters as the ultimate goal, the experiment design is optimized by mechanistic models. This process emphasizes the concept of quality by design. Conclusions: The use of numerical simulation saves experimental cost and time, and speeds up the experimental process. In pharmacy experiments, part of the physical information and the change processes are difficult to obtain, such as the mechanical phenomena during tablet compression and the airflow details in the nasal cavity. Therefore, it is necessary to predict the information and guide the formulation with the help of mechanistic models. [ABSTRACT FROM AUTHOR]

The characteristics of subvisible particles (SbVPs) are critical quality attributes of injectable and ophthalmic solutions in pharmaceutical manufacturing. However, current compendial SbVP testing methods, namely the light obstruction method and the microscopic particle count method, are destructive and wasteful of target samples. In this study, we present the development of a non-destructive SbVP analyzer aiming to analyze SbVPs directly in drug product (DP) containers while keeping the samples intact. Custom sample housings are developed and incorporated into the analyzer to reduce optical aberrations introduced by the curvature of typical pharmaceutical DP sample containers. The analyzer integrates a light-sheet microscope structure and models the side scattering event from a particle with Mie scattering theory with refractive indices as prior information. Equivalent spherical particle size under assigned refractive index values is estimated, and the particle concentration is determined based on the number of scattering events and the volume sampled by the light sheet. The resulting analyzer's capability and performance to non-destructively analyze SbVPs in DP containers were evaluated using a series of polystyrene bead suspensions in ISO 2R and 6R vials. Our results and analysis show the particle analyzer is capable of directly detecting SbVPs from intact DP containers, sorting SbVPs into commonly used size bins (e.g. ≥ 2 µm, ≥ 5 µm, ≥ 10 µm, and ≥ 25 µm), and reliably quantifying SbVPs in the concentration range of 4.6e2 to 5.0e5 particle/mL with a margin of ± 15 % error based on a 90 % confidence interval. [ABSTRACT FROM AUTHOR]

Abstract Recently, increased attention has been paid to the raw materials of plants as a source of biologically active substances. Black rosehip (Rosa pimpinellifolia L.) fruits could be a good resource for potential functional components in the food, cosmetic and pharmaceutical industries. Also, drying can influence the composition of heat-sensitive phytochemicals. However, less attention is given to comparing black rosehip bioactive compounds particularly compositions of fatty acid, amino acids, and phenolic content in fresh and dried fruits. So in this study, the amino acid constituents (by amino acid analyzer), fatty acids (by GC–MS), mineral elements (by atomic absorption spectrometer), antioxidant (by DPPH) and phenolic compounds (by HPLC) present in fresh and dried fruits of black rosehip naturally grown in Iran were comprehensively investigated. The results showed that dried fruits had a lower level moisture by 51.55%, and a higher level of total phenolic compounds and total sugar by 786.20 mg GAE/100 g and 15.77 g/100 g, respectively. Chlorogenic acid and gallic acid were the major phenolic compounds (109.3 mg/g). Whilst, linoleic acid, oleic acid, and arachidic acid (85.34%) were the most dominant fatty acids. The most dominant amino acids were glutamic acid, phenylalanine, and arginine (29.41 g/100 g). Also, Fe and Mn as micro-elements were the most dominant elements. In general, the results illustrated the potentials and differences of black rosehip fruits grown in the Arasbaran region as promising resources for food sources, pharmaceutics, cosmetics, and breeding programs. Also, these findings confirm that black rosehip fruits contain significant amounts of secondary metabolites that may positively affect human health.

Abstract Antibiotics, improper food, and stress have created a dysbiotic state in the gut and almost 81% of the world’s population has been affected due to the pandemic of COVID-19 and the prevalence of dengue virus in the past few years. The main intent of this study is to synthesize nanosynbiotics as nu traceuticals by combining probiotics, and prebiotics with nanoformulation. The effectiveness of the nanosynbiotics was evaluated using a variety of Nutra-pharmacogenetic assays leading to an AI-integrated formulation profiling was assessed by using machine learning methods. Consequently, Acetobacter oryzoeni as a probiotic and inulin as a prebiotic has been chosen and iron-mediated nanoformulation of symbiotic is achieved. Nanosynbiotics possessed 89.4, 96.7, 93.57, 83.53, 88.53% potential powers of Nutra-pharmacogenetic assays. Artificial intelligent solid dispersion formulation of nanosynbiotics has high dissolution, absorption, distribution, and synergism, in addition, they are non-tox, non-allergen and have a docking score of − 10.83 kcal/mol, implying the best interaction with Pregnane X receptor involved in dysbiosis. The potential of nanosynbiotics to revolutionize treatment strategies through precise targeting and modulation of the gut microbiome for improved health outcomes and disease management is promising. Their transformational influence is projected to be powered by integration with modern technology and customized formulas. Further in-vivo studies are required for the validation of nanosynbiotics as nutraceuticals.

Recently, increased attention has been paid to the raw materials of plants as a source of biologically active substances. Black rosehip (Rosa pimpinellifolia L.) fruits could be a good resource for potential functional components in the food, cosmetic and pharmaceutical industries. Also, drying can influence the composition of heat-sensitive phytochemicals. However, less attention is given to comparing black rosehip bioactive compounds particularly compositions of fatty acid, amino acids, and phenolic content in fresh and dried fruits. So in this study, the amino acid constituents (by amino acid analyzer), fatty acids (by GC–MS), mineral elements (by atomic absorption spectrometer), antioxidant (by DPPH) and phenolic compounds (by HPLC) present in fresh and dried fruits of black rosehip naturally grown in Iran were comprehensively investigated. The results showed that dried fruits had a lower level moisture by 51.55%, and a higher level of total phenolic compounds and total sugar by 786.20 mg GAE/100 g and 15.77 g/100 g, respectively. Chlorogenic acid and gallic acid were the major phenolic compounds (109.3 mg/g). Whilst, linoleic acid, oleic acid, and arachidic acid (85.34%) were the most dominant fatty acids. The most dominant amino acids were glutamic acid, phenylalanine, and arginine (29.41 g/100 g). Also, Fe and Mn as micro-elements were the most dominant elements. In general, the results illustrated the potentials and differences of black rosehip fruits grown in the Arasbaran region as promising resources for food sources, pharmaceutics, cosmetics, and breeding programs. Also, these findings confirm that black rosehip fruits contain significant amounts of secondary metabolites that may positively affect human health. [ABSTRACT FROM AUTHOR]

Antibiotics, improper food, and stress have created a dysbiotic state in the gut and almost 81% of the world's population has been affected due to the pandemic of COVID-19 and the prevalence of dengue virus in the past few years. The main intent of this study is to synthesize nanosynbiotics as nu traceuticals by combining probiotics, and prebiotics with nanoformulation. The effectiveness of the nanosynbiotics was evaluated using a variety of Nutra-pharmacogenetic assays leading to an AI-integrated formulation profiling was assessed by using machine learning methods. Consequently, Acetobacter oryzoeni as a probiotic and inulin as a prebiotic has been chosen and iron-mediated nanoformulation of symbiotic is achieved. Nanosynbiotics possessed 89.4, 96.7, 93.57, 83.53, 88.53% potential powers of Nutra-pharmacogenetic assays. Artificial intelligent solid dispersion formulation of nanosynbiotics has high dissolution, absorption, distribution, and synergism, in addition, they are non-tox, non-allergen and have a docking score of − 10.83 kcal/mol, implying the best interaction with Pregnane X receptor involved in dysbiosis. The potential of nanosynbiotics to revolutionize treatment strategies through precise targeting and modulation of the gut microbiome for improved health outcomes and disease management is promising. Their transformational influence is projected to be powered by integration with modern technology and customized formulas. Further in-vivo studies are required for the validation of nanosynbiotics as nutraceuticals. [ABSTRACT FROM AUTHOR]

Diffuse midline glioma (DMG), including tumors diagnosed in the brainstem (diffuse intrinsic pontine glioma - DIPG), is the primary cause of brain tumor-related death in pediatric patients. DIPG is characterized by a median survival of <12 months from diagnosis, harboring the worst 5-year survival rate of any cancer. Corticosteroids and radiation are the mainstay of therapy; however, they only provide transient relief from the devastating neurological symptoms. Numerous therapies have been investigated for DIPG, but the majority have been unsuccessful in demonstrating a survival benefit beyond radiation alone. Although many barriers hinder brain drug delivery in DIPG, one of the most significant challenges is the blood-brain barrier (BBB). Therapeutic compounds must possess specific properties to enable efficient passage across the BBB. In brain cancer, the BBB is referred to as the blood-brain tumor barrier (BBTB), where tumors disrupt the structure and function of the BBB, which may provide opportunities for drug delivery. However, the biological characteristics of the brainstem's BBB/BBTB, both under normal physiological conditions and in response to DIPG, are poorly understood, which further complicates treatment. Better characterization of the changes that occur in the BBB/BBTB of DIPG patients is essential, as this informs future treatment strategies. Many novel drug delivery technologies have been investigated to bypass or disrupt the BBB/BBTB, including convection enhanced delivery, focused ultrasound, nanoparticle-mediated delivery, and intranasal delivery, all of which are yet to be clinically established for the treatment of DIPG. Herein, we review what is known about the BBB/BBTB and discuss the current status, limitations, and advances of conventional and novel treatments to improving brain drug delivery in DIPG. [Display omitted] [ABSTRACT FROM AUTHOR]

Due to the transformation of artificial intelligence (AI) tools and technologies, AI-driven drug discovery has come to the forefront. It reduces the time and expenditure. Due to these advantages, pharmaceutical industries are concentrating on AI-driven drug discovery. Several drug molecules have been discovered using AI-based techniques and tools, and several newly AI-discovered drug molecules have already entered clinical trials. In this review, we first present the data and their resources in the pharmaceutical sector for AI-driven drug discovery and illustrated some significant algorithms or techniques used for AI and ML which are used in this field. We gave an overview of the deep neural network (NN) models and compared them with artificial NNs. Then, we illustrate the recent advancement of the landscape of drug discovery using AI to deep learning, such as the identification of drug targets, prediction of their structure, estimation of drug-target interaction, estimation of drug-target binding affinity, design of de novo drug, prediction of drug toxicity, estimation of absorption, distribution, metabolism, excretion, toxicity; and estimation of drug-drug interaction. Moreover, we highlighted the success stories of AI-driven drug discovery and discussed several collaboration and the challenges in this area. The discussions in the article will enrich the pharmaceutical industry.

Artificial intelligence has brought crucial changes to the whole field of natural sciences. Myriads of machine learning algorithms have been developed to facilitate the work of experimental scientists. Molecular property prediction and drug synthesis planning become routine tasks. Moreover, inverse design of compounds with tunable properties as well as on-the-fly autonomous process optimization and chemical space exploration became possible in silico. Affordable robotic platforms exist able to perform thousands of experiments every day, analyzing the results and tuning the protocols. Despite this, most of these developments get trapped at the stage of code or overlooked, limiting their use by experimental scientists. Meanwhile, visibility and the number of user-friendly tools and technologies available to date is too low to compensate for this fact, rendering the development of novel therapeutic compounds inefficient. In this Review, we set the goal to bridge the gap between modern technologies and experimental scientists to improve drug development efficacy. Here we survey advanced and easy-to-use technologies able to help medical chemists at every stage of their research, including those integrated in technological processes during COVID-19 pandemic motivated by the need for fast yet precise solutions. Moreover, we review how these technologies are integrated by industry and clinics to streamline drug development and production. These technologies already transform the current paradigm of scientific thinking and revolutionize not only medicinal chemistry, but the whole field of natural sciences.

Copyright of Baghdad Science Journal is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background/Objectives: Numerical simulation plays an important role in pharmaceutical preparation recently. Mechanistic models, as a type of numerical model, are widely used in the study of pharmaceutical preparations. Mechanistic models are based on a priori knowledge, i.e., laws of physics, chemistry, and biology. However, due to interdisciplinary reasons, pharmacy researchers have greater difficulties in using computer models. Methods: In this paper, we highlight the application scenarios and examples of mechanistic modelling in pharmacy research and provide a reference for drug researchers to get started. Results: By establishing a suitable model and inputting preparation parameters, researchers can analyze the drug preparation process. Therefore, mechanistic models are effective tools to optimize the preparation parameters and predict potential quality problems of the product. With product quality parameters as the ultimate goal, the experiment design is optimized by mechanistic models. This process emphasizes the concept of quality by design. Conclusions: The use of numerical simulation saves experimental cost and time, and speeds up the experimental process. In pharmacy experiments, part of the physical information and the change processes are difficult to obtain, such as the mechanical phenomena during tablet compression and the airflow details in the nasal cavity. Therefore, it is necessary to predict the information and guide the formulation with the help of mechanistic models.

Background: External parasites, particularly ticks and fleas, are among the most common problems affecting dogs. Chemical medicines are commonly used to prevent and eliminate such external parasites, but their improper use can cause adverse reactions, and the toxins they contain may remain in the environment. Objectives: The objective of this study was to investigate the in vitro efficacy of Zanthoxylum limonella, citronella, clove, peppermint, and ginger essential oils against dog ticks and fleas and to test the sensitivity of dogs' skin to these essential oils. Methods: The five essential oils were tested for in vitro efficacy against ticks and fleas, and the two most effective essential oils were then tested on the dogs' skin. Results: The results revealed that these five essential oils at 16% concentrations effectively inhibited the spawning of female engorged ticks. In addition, all five essential oils had a strong ability to kill tick larvae at concentrations of 2% upward. Furthermore, 4% concentrations of the five essential oils quickly eliminated fleas, especially clove oil, which killed 100% of fleas within 1 h. A 50%, 90%, and 99% lethal concentration (LC50, LC90, and LC99) for the essential oils on tick larvae in 24 h were found to be low values. LC50, LC90, and LC99 for the essential oils on flea in 1 h was lowest values. Clove oil at 16% concentration was the most satisfactory essential oil for application on dogs' skin, with a low percentage of adverse effects. Conclusions: This study confirmed the effectiveness of essential oils for practical use as tick and flea repellents and eliminators. Essential-oil-based pharmaceutical can replace chemical pesticides and provide benefits for both consumers and the environment. [ABSTRACT FROM AUTHOR]

Eculizumab, a monoclonal antibody against complement C5, is a novel therapy to treat refractory myasthenia gravis (MG). The present review was undertaken to study the role of eculizumab in MG. This includes the drug's mechanism, pharmacokinetics, clinical trial findings, tolerability, side effects, safety, dosage, administration, and cost. An English-language search for relevant items was undertaken using Embase and PubMed from 1946 to present. Clinical trial registries/databases and websites were also searched for relevant data. Keywords were eculizumab and MG. The present review found 103 articles after initial screening. Current data support eculizumab as an effective, safe, and tolerable drug in cases of refractory MG. However, its cost can prevent it from being widely accessible to a majority of the general population. [ABSTRACT FROM AUTHOR]

Cytochrome P450s (CYPs) are heme‐thiolated enzymes that catalyze the oxidation of C‐H bonds in a regio‐ and stereo‐selective manner. CYPs are widely present in the biological world. With the completion of more biological genome sequencing, the number and types of P450 enzymes have increased rapidly. P450 in microorganisms is easy to clone and express, rich in catalytic types, and strong in substrate adaptability, which has good application potential. Although the number of P450 enzymes found in microorganisms is huge, the function of most of the microorganism P450s has not been studied, and it contains a large number of excellent biocatalysts to be developed. This review is based on the P450 groups in microorganisms. First, it reviews the distribution of P450 groups in different microbial species, and then studies the application of microbial P450 enzymes in the pharmaceutical industry, chemical industry and environmental pollutant treatment in recent years. And focused on the application fields of P450 enzymes of different families to guide the selection of suitable P450s from the huge P450 library. In view of the current shortcomings of microbial P450 in the application process, the final solution is the most likely to assist the application of P450 enzymes in large‐scale, that is, whole cell transformation combined with engineering, fusion P450 combined with immobilization technology. [ABSTRACT FROM AUTHOR]

Copyright of Baghdad Science Journal is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In the creation of solid dosage forms in the pharmaceutical industry, crystallization has a large impact on the properties of the payloads and matrix, such as melting point, polymorphic form, and crystallinity. Control of the crystallization of the drugs and the material in the matrix using a process of crystallization under confinement to achieve desirable properties is challenging. Emulsions allow the encapsulation of drugs for use in pharmaceutical applications. The limited volume available for crystallization under confinement in emulsions has a significant effect on the crystallization of the payloads and matrices. We discuss here advances in improving the characteristics of pharmaceutical products through the use of crystallization under confinement created by an emulsion. We also review the methods for preparing emulsions, in which the droplets act as a template for the crystallization under confinement. In addition, the influences of crystallization in emulsions on solubility, release profile of payloads, permeability, and polymorphism are reviewed. [ABSTRACT FROM AUTHOR]

Human struggle against the deadly disease conditions is continued since ages. The contribution of science and technology in fighting against these diseases cannot be ignored exclusively due to the invention of novel procedure and products, extending their size ranges from micro to nano. Recently nanotechnology has been gaining more consideration for its ability to diagnose and treat different cancers. Different nanoparticles have been used to evade the issues related with conservative anticancer delivery systems, including their nonspecificity, adverse effects and burst release. These nanocarriers including, solid lipid nanoparticles (SLNs), liposomes, nano lipid carriers (NLCs), nano micelles, nanocomposites, polymeric and magnetic nanocarriers, have brought revolutions in antitumor drug delivery. Nanocarriers improved the therapeutic efficacy of anticancer drugs with better accumulation at the specific site with sustained release, improved bioavailability and apoptosis of the cancer cells while bypassing the normal cells. In this review, the cancer targeting techniques and surface modification on nanoparticles are discussed briefly with possible challenges and opportunities. It can be concluded that understanding the role of nanomedicine in tumor treatment is significant, and therefore, the modern progressions in this arena is essential to be considered for a prosperous today and an affluent future of tumor patients. [ABSTRACT FROM AUTHOR]

AbstractHuman struggle against the deadly disease conditions is continued since ages. The contribution of science and technology in fighting against these diseases cannot be ignored exclusively due to the invention of novel procedure and products, extending their size ranges from micro to nano. Recently nanotechnology has been gaining more consideration for its ability to diagnose and treat different cancers. Different nanoparticles have been used to evade the issues related with conservative anticancer delivery systems, including their nonspecificity, adverse effects and burst release. These nanocarriers including, solid lipid nanoparticles (SLNs), liposomes, nano lipid carriers (NLCs), nano micelles, nanocomposites, polymeric and magnetic nanocarriers, have brought revolutions in antitumor drug delivery. Nanocarriers improved the therapeutic efficacy of anticancer drugs with better accumulation at the specific site with sustained release, improved bioavailability and apoptosis of the cancer cells while bypassing the normal cells. In this review, the cancer targeting techniques and surface modification on nanoparticles are discussed briefly with possible challenges and opportunities. It can be concluded that understanding the role of nanomedicine in tumor treatment is significant, and therefore, the modern progressions in this arena is essential to be considered for a prosperous today and an affluent future of tumor patients.

The past two decades have witnessed the enormous success and progress of electrospinning, as well as its broad and useful applications in pharmaceutics as a laboratory pharmaceutical nanotechnology. Everything in the past is a preface, in which the large screen opens for electrospinning and electrospun nanofibers (particularly those multiple-fluid electrospinning processes and the related multiple-chamber nanostructures) to stride into a new stage and the real commercial applications. In this commentary, four hot regions are identified for the further progress of the applications of electrospinning in pharmaceutics, in which electrospinning and its products can provide more and better services to the development of pharmaceutics. [ABSTRACT FROM AUTHOR]

Natural ingredients have been used for centuries for skin treatment and care. Interest in the health effects of plants has recently increased due to their safety and applicability in the formulation of pharmaceuticals and cosmetics. Long-known plant materials as well as newly discovered ones are increasingly being used in natural products of plant origin. This review highlights the beneficial effects of plants and plant constituents on the skin, including moisturizing (e.g., Cannabis sativa, Hydrangea serrata, Pradosia mutisii and Carthamus tinctorius), anti-aging (e.g., Aegopodium podagraria, Euphorbia characias, Premna odorata and Warburgia salutaris), antimicrobial (e.g., Betula pendula and Epilobium angustifolium), antioxidant (e.g., Kadsura coccinea, Rosmarinus officinalis, Rubus idaeus and Spatholobus suberectus), anti-inflammatory (e.g., Antidesma thwaitesianum, Helianthus annuus, Oenanthe javanica, Penthorum chinense, Ranunculus bulumei and Zanthoxylum bungeanum), regenerative (e.g., Aloe vera, Angelica polymorpha, Digitaria ciliaris, Glycyrrihza glabra and Marantodes pumilum), wound healing (e.g., Agrimonia eupatoria, Astragalus floccosus, Bursera morelensis, Jatropha neopauciflora and Sapindus mukorossi), photoprotective (e.g., Astragalus gombiformis, Calea fruticose, Euphorbia characias and Posoqueria latifolia) and anti-tyrosinase activity (e.g., Aerva lanata, Bruguiera gymnorhiza, Dodonaea viscosa, Lonicera japonica and Schisandra chinensis), as well as their role as excipients in cosmetics (coloring (e.g., Beta vulgaris, Centaurea cyanus, Hibiscus sabdariffa and Rubia tinctiorum), protective and aromatic agents (e.g., Hyssopus officinalis, Melaleuca alternifolia, Pelargonium graveolens and Verbena officinalis)). [ABSTRACT FROM AUTHOR]

Airway mucus is a complex viscoelastic gel composed mainly of water, glycoproteins, lipids, enzymes, minerals, etc. Among them, glycoproteins are the main factors determining mucus's gel-like rheology. Airway mucus forms a protective barrier by secreting mucin, which represents a barrier for absorption, especially for more lipophilic drugs. It rapidly removes drugs from the airway through the physiological mucus clearance mechanism so drugs cannot remain in the lungs or reach the airway epithelial tissue for a long time. Significant progress has been made in enhancing drug lung deposition recently, but strategies are still needed to help drugs break through the lung mucosal barrier. Based on the physiopathological mechanisms of airway mucus, this paper reviews and summarizes strategies to enhance drug penetration and retention in the airway mucosa mediated by nano-delivery systems, including mucosal permeation systems, mucosal adhesion systems, and enzyme-modified delivery systems. On this basis, the potential and challenges of nano-delivery systems for improving airway mucus clearance are revealed. New ideas and approaches are provided for designing novel nano-delivery systems that effectively improve drug retention and penetration in the airway mucus layer. [ABSTRACT FROM AUTHOR]

[Display omitted] Chronic wounds affect millions of people annually and have emotional and financial implications in addition to health issues. The current treatment for chronic wounds involves the repeated use of bandages and drugs such as antibiotics over an extended period. A cost-effective and convenient solution for wound healing is the development of drug-incorporated bandages. This study aimed to develop a biocompatible bandage made of drug-incorporated poly (lactic-co-glycolic acid) (PLGA) microparticles (MPs) and eggshell membrane (ESM) for cornea wound healing. ESM has desirable properties for wound healing and can be isolated from eggshells using acetic acid or ethylenediaminetetraacetic acid (EDTA) protocols. Fluorescein isothiocyanate-labelled Bovine Serum Albumin (FITC-BSA) was used as a model drug, and the PLGA MPs were fabricated using a solvent extraction method. The MPs were successfully attached to the fibrous layer of the ESM using NaOH. The surface features of the ESM samples containing MPs were studied using a field emission scanning electron microscope (FESEM) and compared with blank ESM images. The findings indicated that the MPs were attached to the ESM fibres and had similar shapes and sizes as the control MPs. The fibre diameters of the MPs samples were assessed using Fiji-ImageJ software, and no significant changes were observed compared to the blank ESM. The surface roughness, Ra values, of the MPs incorporated ESM samples were evaluated and compared to the blank ESM, and no significant changes were found. Fourier transform infrared (FTIR) spectroscopy was used to analyse the chemical Composition of the bandage, and the spectra showed that the FBM were effectively incorporated into the ESM. The FTIR spectra identified the major peaks of the natural ESM and the PLGA polymer in the bandage. The bandage was transparent but had a reduced visibility in the waterproof test card method. The bandage achieved sustained drug release up to 10 days and was found to be biocompatible and non-toxic in a chorioallantoic membrane (CAM) assay. Overall, the drug-incorporated PLGA MPs-ESM bandage has great potential for treating chronic wounds. [ABSTRACT FROM AUTHOR]

Field-flow fractionation (FFF) is a family of single-phase separative techniques exploited to gently separate and characterize nano- and microsystems in suspension. These techniques cover an extremely wide dynamic range and are able to separate analytes in an interval between a few nm to 100 µm size-wise (over 15 orders of magnitude mass-wise). They are flexible in terms of mobile phase and can separate the analytes in native conditions, preserving their original structures/properties as much as possible. Molecular biology is the branch of biology that studies the molecular basis of biological activity, while biotechnology deals with the technological applications of biology. The areas where biotechnologies are required include industrial, agri-food, environmental, and pharmaceutical. Many species of biological interest belong to the operational range of FFF techniques, and their application to the analysis of such samples has steadily grown in the last 30 years. This work aims to summarize the main features, milestones, and results provided by the application of FFF in the field of molecular biology and biotechnology, with a focus on the years from 2000 to 2022. After a theoretical background overview of FFF and its methodologies, the results are reported based on the nature of the samples analyzed. [ABSTRACT FROM AUTHOR]

In the present paper, Mn/UiO-66 material was synthesized by hydrothermal process. The obtained material was characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), energy dispersive X-ray (EDX) with mapping and nitrogen adsorption/desorption techniques. The doped manganese was shown to highly disperse and might be grafted into the lattice of UiO-66. A simple, fast, and inexpensive differential pulse voltammetric (DPV) method were developed using Mn/UiO-66 as an electrode modifier for the simultaneous determination of acetaminophen (ACE) and codeine (CDE) in pharmaceutical formulations. The experimental parameters, which might affect the peak currents of ACE and CDE, such as the pH of the solution, accumulation time, and scan rate, were optimized. Under optimal conditions, this technique provided low limits of detection for the quantification of ACE and CDE, of 0.45 and 0.31 μM, respectively. The proposed DPV method was successfully applied to simultaneously determine ACE and CDE in samples of three pharmaceutical formulation with acceptable recoveries. Clearly, the proposed method might be an alternative option for the simultaneous determination of ACE and CDE. [ABSTRACT FROM AUTHOR]

Applications of Artificial Intelligence in medical informatics solutions risk sharing have social value. At a time of ever-increasing cost for the provision of medicines to citizens, there is a need to restrain the growth of health care costs. The search for computer technologies to stop or slow down the growth of costs acquires a new very important and significant meaning. We discussed the two information technologies in pharmacotherapy and the possibility of combining and sharing them, namely the combination of risk-sharing agreements and Machine Learning, which was made possible by the development of Artificial Intelligence (AI). Neural networks could be used to predict the outcome to reduce the risk factors for treatment. AI-based data processing automation technologies could be also used for risk-sharing agreements automation. [ABSTRACT FROM AUTHOR]

Platelets are blood components traditionally believed to have fundamental roles in vascular hemostasis and thrombosis. In recent years, platelets have received new attention for their roles in tumorigenesis and progression. On the one hand, platelets are actively recruited by various tumors and comprise a crucial part of the tumor microenvironment (TME), thus inspiring the use of platelets for tumor-targeted drug delivery. To this end, various platelet-based devices have been proposed, such as natural platelets, engineered platelets, platelet membranes, and platelet-derived microparticles. On the other hand, platelets are involved in tumor immunosuppression mechanisms, by directing and/or assisting various tumor-associated immune cells. However, in the context of inflammation and autoimmune diseases, platelets can amplify immune responses by promoting immune cell mobilization and activation, thereby exacerbating tissue damage. Thus, interest is growing in the use of tumor-associated platelets as targets for therapeutic modulation of the TME and augmenting anti-tumor immune responses. In this review, we summarize current advances in exploiting platelets for both antitumor drug delivery and immune modulation of the TME.

Objective: To assess student perceptions regarding: 1) exercises designed to enhance student comprehension of the roles of pharmaceutical excipients in dosage forms and 2) the use of resources to identify the roles of excipients. Description: In-class exercises regarding the roles of excipients were implemented in a foundational pharmaceutics course. The exercises covered the topics of liquid single-phase systems, liquid multiphase systems, drug delivery to the skin, and parenteral, ophthalmic, and nasal dosage forms. Students were introduced to resources to identify the roles of excipients. The exercises included the presentation of pharmaceutical preparations with various fundamental excipients, followed by student polling and class discussion. A survey was administered to evaluate student perceptions regarding the exercises about the roles of excipients and the use of resources to identify the roles of excipients. Findings: Eighty students participated in the study (response rate = 99%). Student perceptions indicated that the exercises helped them understand the material better and enhanced their performance in the non-sterile compounding course taught concurrently with the pharmaceutics course. Students indicated that the resources they used during the exercises were lecture notes from the course (95%), lists with excipients that the instructor provided (24%), a Web search, e.g., Google, Bing (20%), the sixth edition of the Handbook of Pharmaceutical Excipients (18%), Micromedex/Martindale (16%), and the International Journal of Pharmaceutical Compounding (6%). Conclusion. Targeted excipient exercises are a practical approach to enhance student understanding and can be utilized in pharmaceutics and non-sterile compounding courses across various pharmacy curricula.

This research focuses on investigating the solubility of tolfenamic acid in SC-CO2 (supercritical carbon dioxide) and the density of SC-CO2 solvent via theoretical artificial intelligence method. The study involves analyzing the relationship between temperature, pressure, and the corresponding mentioned outputs for the process. Three different predictive models, namely Multi-layer Perceptron (MLP), Polynomial Regression (PR), and Extra Trees (ET) are utilized to forecast the solubility of drug and the density of solvent (SC–CO2). The models are fine-tuned with hyper-parameters using the Dragonfly Algorithm (DA) to ensure accurate predictions. The solubility prediction is remarkably accurate using the MLP model, showing a high score of 0.98329 in terms of R-squared. The maximum error is 0.2474, and the MAE is 0.1095, demonstrating the model's high precision in estimating tolfenamic acid's solubility in SC-CO2. The PR model demonstrates exceptional accuracy, yielding a score of 0.99844 by R-squared metric, a maximum error of 0.068, and an MAE of 0.0314. The ET model also performs well, with an R-squared score of 0.90977, a maximum error of 0.445, and an MAE of 0.1665. Regarding density prediction, MLP outperforms the other techniques, achieving a significant R2 parameter of 0.99919, an MSE of 12.663, and a mean MAPE of 0.0037.

Preparation of small-molecule API (Active Pharmaceutical Ingredient) at submicron size would be of great benefit for pharmaceutical engineering, as the drug particles at submicron size possess higher solubility in water. Indeed, the drug bioavailability can be enhanced when the nanomedicine is prepared. In this study, the solubility of the drug desoxycorticosterone acetate (DA) is being examined to assess its viability of nanonization using supercritical operation. Two inputs are temperature and pressure which were considered for machine learning modeling in this study. The drug's solubility is the only output to be estimated by the optimized models. This dataset has 45 rows of data that were gathered at 5 different pressure and temperature levels. Support vector machine (SVM) is used as the core of the models built in this research. Epsilon-SVR and nu-SVR are models based on this concept, which together with two different polynomial and RBF kernels form the four models built in this research for estimation of DA drug solubility. The models are also optimized with the help of a new TLCO method. All four final models have an R2 score higher than 0.9, and among them, the Epsilon-SVR model with RBF kernel has the best performance with 0.967.

This paper investigates the application of Support Vector Regression with Quadratic Kernel (QSVR) for modeling the solubility of lornoxicam in supercritical carbon dioxide. The dataset comprises temperature (T) and pressure (P) as input variables, while the solubility (Y) of lornoxicam serves as the output variable entire the modeling. The temperature is measured in Kelvin (K), and the pressure is measured in bar as the inputs of models. To improve the predictive performance of the QSVR model, three distinct hyper-parameter optimization techniques, namely Genetic Algorithm (GA), Tabu Search (TS), and Bayesian Hyperparameter Optimization (BHO) are employed. These optimization methods are utilized to fine-tune the hyper-parameters of the QSVR model and enhance its predictive accuracy. The BHO-QSVR model achieved an impressive R2 score of 0.96725, indicating a strong fit between the predicted and actual solubility values. Additionally, it exhibited a Mean Absolute Error (MAE) of 1.75666E-05 and a maximum error of 3.02849E-05. Comparatively, the GA-QSVR and TS-QSVR models also performed well, achieving R2 scores of 0.95346 and 0.95882, respectively. The GA-QSVR model achieved an MAE of 1.56725E-05 and a maximum error of 4.92382E-05, while the TS-QSVR model exhibited an MAE of 1.84075E-05 and a maximum error of 5.02443E-05.

Large-scale use of nitrofurans is associated with a number of risks related to a growing resistance to these compounds and the toxic effects following from their increasing presence in wastewater and the environment. The aim of the study was to investigate an impact of natural surfactant, saponins from Sapindus mukorossi, on antimicrobial properties of nitrofuran antibiotics. Measurements of bacterial metabolic activity indicated a synergistic bactericidal effect in samples with nitrofurantoin or furazolidone, to which saponins were added. Their addition led to more than 50% greater reduction in viable cells than in the samples without saponins. On the other hand, no toxic effect against human colon epithelial cell was observed. It was found that exposure to antibiotics and surfactants caused the cell membranes to be dominated by branched fatty acids. Moreover, the presence of saponins reduced the hydrophobicity of the cell surface making them almost completely hydrophilic. The results have confirmed a high affinity of saponins to the cells of Pseudomonas strains. Their beneficial synergistic effect on the action of antibiotics from the nitrofuran group was also demonstrated. This result opens promising prospects for the use of saponins from S. mukorossi as an adjuvant to reduce the emission of antibiotics into the environment. [ABSTRACT FROM AUTHOR]

The latest approach to pharmaceutical quality is Quality by Design. This article introduces Pharmaceutical Quality by Design (QbD) and shows how Quality by Design is used to assure pharmaceutical quality. A description of Quality by Design is given, as well as some of its components. Each unit operation's process parameters and quality characteristics are identified. The advantages, possibilities, and steps involved in Pharmaceutical Quality by Design are outlined. The goal of pharmaceutical development is to create a high-quality product and manufacturing method that consistently delivers the product's expected performance. Quality cannot be tested into items; instead, it should be designed into them. The Quality target product profile, crucial quality traits, and major features of Quality by Design are all included. It also compares product quality based on end-of-life testing with product quality based on Quality by Design. The ICH Guidelines are the cornerstone of Quality by Design. It is based on the International Conference on Harmonization (ICH) Guidelines Q8 for pharmaceutical development, Q9 for quality risk management, and Q10 for pharmaceutical quality systems. It also discusses how Quality by Design might be used in product development and manufacturing. [ABSTRACT FROM AUTHOR]

The moisture content of pharmaceutical powder is a key parameter contributing to tablet sticking during the tableting process. This study investigates powder moisture behavior during the compaction phase of the tableting process. Finite element analysis software COMSOL Multiphysics® 5.6 was used to simulate the compaction microcrystalline cellulose (VIVAPUR PH101) powder and predict temperature and moisture content distributions, as well as their evolution over time, during a single compaction. To validate the simulation, a near-infrared sensor and a thermal infrared camera were used to measure tablet surface temperature and surface moisture, respectively, just after ejection. The partial least squares regression (PLS) method was used to predict the surface moisture content of the ejected tablet. Thermal infrared camera images of the ejected tablet showed powder bed temperature increasing during compaction and a gradual rise in tablet temperature along with tableting runs. Simulation results showed that moisture evaporate from the compacted powder bed to the surrounding environment. The predicted surface moisture content of ejected tablets after compaction was higher compared to that of loose powder and decreased gradually as tableting runs increased. These observations suggest that the moisture evaporating from the powder bed accumulates at the interface between the punch and tablet surface. Evaporated water molecules can be physiosorbed on the punch surface and cause a capillary condensation locally at the punch and tablet interface during dwell time. Locally formed capillary bridge may induce a capillary force between tablet surface particles and the punch surface and cause the sticking. [ABSTRACT FROM AUTHOR]

Dihydromyricetin (DHM) is an important natural flavonoid that has attracted much attention because of its various functions such as protecting the cardiovascular system and liver, treating cancer and neurodegenerative diseases, and anti-inflammation effect, etc. Despite its great development potential in pharmacy, DHM has some problems in pharmaceutical applications such as low solubility, permeability, and stability. To settle these issues, extensive research has been carried out on its physicochemical properties and dosage forms to produce all kinds of DHM preparations in the past ten years. In addition, the combined use of DHM with other drugs is a promising strategy to expand the application of DHM. However, although invention patents for DHM preparations have been issued in several countries, the current transformation of DHM research results into market products is insufficient. To date, there is still a lack of deep research into the pharmacokinetics, pharmacodynamics, toxicology, and action mechanism of DHM preparations. Besides, preparations for combined therapy of DHM with other drugs are scarcely reported, which necessitates the development of dosage forms for this application. Apart from medicine, the development of DHM in the food industry is also of great potential. Due to its multiple effects and excellent safety, DHM preparations can be developed for functional drinks and foods. Through this review, we hope to draw more attention to the development potential of DHM and the above challenges and provide valuable references for the research and development of other natural products with a similar structure-activity relationship to this drug.

Nano-drug delivery strategies have been highlighted in cancer treatment, and much effort has been made in the optimization of bioavailability, biocompatibility, pharmacokinetics profiles, and in vivo distributions of anticancer nano-drug delivery systems. However, problems still exist in the delicate balance between improved anticancer efficacy and reduced toxicity to normal tissues, and opportunities arise along with the development of smart stimuli-responsive delivery strategies. By on-demand responsiveness towards exogenous or endogenous stimulus, these smart delivery systems hold promise for advanced tumor-specificity as well as controllable release behavior in a spatial-temporal manner. Meanwhile, the blossom of nanotechnology, material sciences, and biomedical sciences has shed light on the diverse modern drug delivery systems with smart characteristics, versatile functions, and modification possibilities. This review summarizes the current progress in various strategies for smart drug delivery systems against malignancies and introduces the representative endogenous and exogenous stimuli-responsive smart delivery systems. It may provide references for researchers in the fields of drug delivery, biomaterials, and nanotechnology.

Periodontitis is an inflammatory disease of the gums characterized by the degeneration of periodontal ligaments, the formation of periodontal pockets, and the resorption of the alveolar bone, which results in the destruction of the teeth's supporting structure. Periodontitis is caused by the growth of diverse microflora (particularly anaerobes) in the pockets, releasing toxins and enzymes and stimulating the immune system. Various approaches, both local and systemic, have been used to treat periodontitis effectively. Successful treatment depends on reducing bacterial biofilm, bleeding on probing (BOP), and reducing or eliminating pockets. Currently, the use of local drug delivery systems (LDDSs) as an adjunctive therapy to scaling and root planing (SRP) in periodontitis is a promising strategy, resulting in greater efficacy and fewer adverse effects by controlling drug release. Selecting an appropriate bioactive agent and route of administration is the cornerstone of a successful periodontitis treatment plan. In this context, this review focuses on applications of LDDSs with varying properties in treating periodontitis with or without systemic diseases to identify current challenges and future research directions. [ABSTRACT FROM AUTHOR]

Modified polymeric gels, including nanogels, which play not only the role of a bioinert matrix, but also perform regulatory, catalytic, and transport functions due to the active fragments introduced into them, can significantly advance the solution to the problem of targeted drug delivery in an organism. This will significantly reduce the toxicity of used pharmaceuticals and expand the range of their therapeutic, diagnostic, and medical application. This review presents a comparative description of gels based on synthetic and natural polymers intended for pharmaceutical-targeted drug delivery in the field of therapy of inflammatory and infectious diseases, dentistry, ophthalmology, oncology, dermatology, rheumatology, neurology, and the treatment of intestinal diseases. An analysis was made of most actual sources published for 2021–2022. The review is focused on the comparative characteristics of polymer gels in terms of their toxicity to cells and the release rate of drugs from nano-sized hydrogel systems, which are crucial initial features for their further possible application in mentioned areas of biomedicine. Different proposed mechanisms of drug release from gels depending on their structure, composition, and application are summarized and presented. The review may be useful for medical professionals, and pharmacologists dealing with the development of novel drug delivery vehicles. [ABSTRACT FROM AUTHOR]

Background: Fast disintegrating tablet (FDT) of ondansetron has better patient compliance as it is easy to swallow for the treatment of nausea and vomiting. Moreover, fast absorption, rapid onset, reduced loss of drugs, and enhanced bioavailability are making oral dispersible systems a better drug delivery system. This research was conducted with the objective to formulate and evaluate the oral FDT of ondansetron HCl using natural polymers. Methods: The tablets were formulated employing the direct compression technique using different ratios of natural super disintegrants such as spray-dried banana powder, ispaghula husk powder, and combination of both polymers. The developed powders were subjected to the pre-compression parameters and the powders were punched using a single-head rotatory compression machine. The formulated 200 mg tablets were subjected to post-compression evaluation. Results: The Fourier-transform infrared spectroscopy studies showed no chemical interaction between pure drugs, natural super disintegrants, and other excipients. Formulation F6 containing ispaghula husk powder in a 1:4 ratio demonstrated 98.60±0.003% of drug release within 10 minutes indicating the best formulation. Conclusion: FDT of ondansetron was considered the best formulation in the drug delivery system which followed the Higuchi model with the Fickian release.

Modeling and simulations based on machine learning techniques were conducted in this research for determination of pharmaceutical solubility in supercritical solvent for the sake of green processing development in the area of pharmaceutics. By this method, drug nanoparticles can be formed and controlled for better solubility and consequently bioavailability. We modeled the solubility of the drug namely desoxycorticosterone acetate (DA). The temperature and pressure are two inputs for the developed models, whereas the target output is the solubility of DA in the solvent. Indeed, models with two inputs and one output are developed in this study. This dataset contains 45 rows of data collected at five distinct temperatures and nine pressure levels. Three novel models are employed here including: HHO-MLP, HHO-RR, and HHO–KNN for theoretical determination of the drug solubility in the solvent. They are in fact MLP, Ridge Regression, and KNN models coupled with Harris Hawks optimizer (HHO) for hyper-parameter optimization. The HHO-MLP model has the best performance among models with R2 of 0.995, RMSE error rate of 0.194 and maximum error equal to 0.327. The model's findings can be used for estimation of the solubility data in wide range of T and P.