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Favipiravir is a potential repurpose moiety to treat COVID-19 by depletion of virus load in infectious patients. To analyze and separate Favipiravir with remarkable efficiency, X-Bridge C8 column (150 x 4.6 mm, 5 µ) and a solvent phase of 0.1% TEA and acetonitrile (40:60 v/v) with 1-mL/min flow rate were used. The eluted favipiravir and possible degradants were detected at 225 nm. Further, the process was validated by using ICH (Q2R1) guidelines to ensure the method's suitability in the pharmaceutical sector. The RT of Favipiravir was observed at 3.7 min with good linearity of 2 to 30 µg/mL. %RSD of both system and method precision was assessed in the series of 0.32 to 0.98. The mean percentage recovery of Favipiravir was in the range of 99.0–100.4%. The limit of detection (LoD) and limit of quantification (LoQ) were assessed to be 0.024 and 0.084 μg/mL for favipiravir. The outcomes confirmed that the projected approach was economical, insightful, simple and precise with better sensitivity. Investigation of Favipiravir in the incidence of a variety of stressed or forced degradation environments ensures stability indicating quality of the developed approach. © 2023, Dr. Yashwant Research Labs Pvt. Ltd.. All rights reserved.
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During the severe worldwide pandemic caused due to SARS COV-2 Corona virus, Favipiravir has been used for the treatment. It is a water insoluble anti-viral drug with poor dissolution and poor flow properties, resulting in poor oral absorption and less bioavailability. For a long time, the phrase "direct compression" was used to describe the compression of a single crystalline component into a compact without the addition of any other materials. Using excipients and solvents, the crystallo-co-agglomeration process aggregates drug crystals in the form of small spherical particles to create an intermediate product with better micromeritic and mechanical characteristics, solubility, and dissolution. Crystallo-co-agglomeration is a unique approach in which the pharmaceuticals or excipients are crystallized and agglomerated concurrently from a good solvent and/or bridging liquid by adding a non-solvent. The present study aims to formulate crystallo-co-agglomerates of Favipiravir to improve its physicochemical and mechanical properties. Results obtained during the evaluation showed that CCA technique could be successfully employed as an alternative to conventional wet agglomeration.
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The emergence of nanotechnology paves the way for improving disease therapy strategies. An investigation into the progression of the release of the medication targeting the specified predetermined location is a significant factor to consider. Due to the ability to advance existing products and to develop new products in a variety of applications, the nanotechnology industry is considered an evolving technology. Cyclodextrin-based porous nanoparticles or unique nano-sponges (NSs) which have recently been used in the pharmaceutical, biomedical, and cosmetic industries are the main elements of this growth. This superior technology can circumvent the defects of current techniques by its ability to attack and visualize tumour sites. A biodegradable and biocompatible feature along with a built-in high surface area resulting in enormous amounts of drug loading and biomimetic design, and the ability to control nanoparticles size are just a handful of good attractive attributes that find this technique as an overwhelming advantage in the field of nanomedicine. This review article is organized such that we first explored the unique features of these nanosponges and the diverse methods for synthesizing, followed by the drug loading and release principle and application based on drug delivery, targeting, boosting solubility of BCS Class II and IV drugs, others in biomedicine and more. Finally, the recent progress on the use of biomimetic nanosponge as a pandemic tool due to the SARS-CoV-2 virus briefly comes into line. Copyright © RJPT All right reserved.
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Computational tools in drug discovery involve the use of algorithms in predicting properties of potential drugs as ligands as well as biological targets in structural forms. This dates back to more than 30 years ago and have been perfected with time and advancement of technology. They are reliable to varying extents depending on the nature of the study, complexity among other factors. Computational tools help medicinal chemists, computational chemists, and structural biologists to design and optimize potential drugs as early as possible and reduce or completely avoid attrition in the drug discovery pipeline. The search for drugs to cure or manage COVID-19 is made relatively easier and more efficient by the use of computational tools to help understand the ADMET properties of possible drugs under development. This chapter demonstrates how computational tools in cheminformatics and machine learning can be used in the fight against COVID-19 from a medicinal chemistry perspective using selected parameters. © 2022 Elsevier Inc. All rights reserved.
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The design and development of supercritical carbon dioxide (sc-CO2) based processes for production of pharmaceutical micro/nanoparticles is one of the interesting research topics of pharmaceutical industries owing to its attractive advantages. The solubility of drugs in sc-CO2 at different temperatures and pressures is an essential parameter which should be determined for this purpose. Chloroquine as a traditional antirheumatic and antimalarial agent is approved as an effective drug for the treatment of Covid-19. Pishnamazi et al. (Pishnamazi et al., 2021) measured the solubility of this drug in sc-CO2 at the pressure range of 120-400 bar and temperature range of 308-338 K, and correlated the obtained data using some empirical models. In this work, a comprehensive computational approach was developed to more accurately study the supercritical solubility of Chloroquine. The thermodynamic models include two equations-of-state based models (Peng-Robinson and Soave-Redlich-Kowang) and two activity coefficient-based models (modified Wilson's and UNIQUAC)), as well as, a multi-layer perceptron neural network (MLPNN)) were used for this purpose. Also, molecular modeling was performed to study the electronic structure of Chloroquine and identify the potential centers of intermolecular interactions during the dissolution process. According to the obtained results, all of the theoretical models can predict Chloroquine solubility in sc-CO2 with acceptable accuracy. Among these models, the MLPNN model possesses the highest precision with the lowest average absolute relative deviation (AARD%) of 1.76% and the highest Radj value of 0.999.
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Chemical education laboratory practices have not been exempted from the present healthcare crisis. Learning environments have shifted from face-to-face exercises to virtual and video conferencing platforms. Here, we discuss a chemistry for health sciences course which (i) adapted the previous face-to-face laboratory exercises to 100% online using online platforms two years preceding COVID only to shift to completely remote learning and back again and (ii) highlight correlations between chemistry concepts (e.g., pH, solubility, and serial dilutions) and medical practices. Additionally, course pass/fail trends pre-COVID and during COVID are identified and discussed by the author. Regarding example laboratory teaching and learning, this article further examines the responses for two groups of students and their perspectives on 2D virtual chemistry lab experiences and parallel discussions in healthcare: (1) For group 1, students (n = 135) completed an anonymous and voluntary Likert-type questionnaire for a pH and serial dilution online lab experience with over 92% recommending the lab experience for future enrollees, and (2) for group 2, student (n = 107) results indicated 93% of the survey participants were providing the same recommendation.
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Background: Nasal route of drug administration has gained popularity nowadays specially for drugs acting on nasopulmonary area. Atazanavir is an antiviral drug which has proved efficacy in different viral infection including COVID-19. Therefore the hypothesis is, if given through intra nasal route this formulation will be able to prevent the viral infection like COVID-19 by directly acting on the virus at its entry point. Objectives: This study aims to prepare a stable mucoadhesive microcrystal formulation of this antiviral drug with good permeation for intra nasal delivery. Materials and Methods: The formulation was prepared by high-speed homogenization process. Prepared microcrystals were estimated for in vitro drug release and permeation, drug excipient interaction study by DSC, FTIR and in vitro mucoadhesiveness study on agar gel plate. A short-term stability study was conducted on all formulations for 6 months. Results: The melting point and absorbance maxima of atazanavir were found as 200.9°C and 248 nm. The DSC and FTIR study results confirmed no drug excipient interaction was there in the formulation. The particle size of the formulations was found as 5-11 µm in range. Drug release was better and faster from the microcrystals as compare to pure powder drug. The flux for microcrystal formulation was found to be 100 whereas flux for the pure drug powder was 24. Formulations had sufficient mucoadhesive strength due to incorporation of HPMC 400 polymer and they were found stable after six months stability study. Conclusion: Lastly, it can be concluded that this formulation would be a promising system for the delivery through intra nasal route as it showed good drug release and permeation during a short time span in in vitro nasal condition with a particle size range suitable for intranasal delivery. However, further in vivo studies are required to confirm the hypothesis.
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Background: As the new pandemic created by COVID-19 virus created the need of rapid acquisition of a suitable vaccine against SARS-CoV-2 to develop Immunity and to reduce the mortality, the aim of this study was to identify SARS-CoV-2 S protein and N antigenic epitopes by using immunoinformatic methods to design a vaccine against SARS-CoV-2, for which S and N protein-dependent epitopes are predicted. B cell, CTL and HTL were determined based on antigenicity, allergenicity and toxicity that were non-allergenic, non-toxic, and antigenic and were selected for the design of a multi-epitope vaccine structure. Then, in order to increase the safety of Hbd-3 and Hbd-2 as adjuvants, they were connected to the N and C terminals of the vaccine construct, respectively, with a linker. The three-dimensional structure of the structure was predicted and optimized, and its quality was evaluated. The vaccine construct was ligated to MHCI. Finally, after optimizing the codon to increase expression in E. coli K12, the vaccine construct was cloned into pET28a (+) vector. Results: Epitopes which were used in our survey were based on non-allergenic, non-toxic and antigenic. Therefore, 543-amino-acid-long multi-epitope vaccine formation was invented through linking 9 cytotoxic CTL, 5 HTL and 14 B cell epitopes with appropriate adjuvants and connectors that can control the SARS coronavirus 2 infection and could be more assessed in medical scientific researches. Conclusion: We believe that the proposed multi-epitope vaccine can effectively evoke an immune response toward SARS-CoV-2.
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Excipients are critically important in converting active pharmaceutical ingredients (API) into drug products that have optimal stability, bioavailability, manufacturability, duration of action, and therapeutic benefits. They will play even greater roles in the future to enable drug targeting, delivery of biotech products and vaccines, gene therapy, continuous manufacturing, 3D printing, and so forth. This commentary describes the author’s experience in teaching a graduate course on excipients at St. John’s University to train students on optimal selection and appropriate use of excipients in formulating dosage forms and development of drug delivery systems. The course is offered in 15 two-hour sessions over a semester, and the course materials are divided into 13 modules on chemistry of different classes of polymeric and non-polymeric excipients and their application in dosage form development, including the use as solubilizing agents, lyophilizing agents, cryoprotectants, buffers, biodegradable materials, and carriers for amorphous solid dispersions and 3D printing. The development of coprocessed excipients, the need for new excipients, and the regulatory aspects of excipients are also covered. The course includes presentations by guest speakers from the industry, and the students also watch virtual presentations from experts that are publicly available from the internet. It is a popular course at St. John’s University taken by all graduate students in the pharmaceutics program. It is recommended that such courses are introduced in other pharmacy schools and academic institutions. The course may be adapted to meet specific needs of different academic programs. Professional associations, such as AAPS and CRS, industry groups like IPEC, and the pharmaceutical industry may be able to help in introducing such courses by providing lecture materials and guest lecturers.
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Introduction: Some patients with comorbidity such as diabetes are at risk of worsening after being infected with the COVID-19 and they usually adjust their diet during the recovery process. Aim: To explore the use of Stevia rebaudiana leaves as a natural sweetener recommended for COVID-19 patients and the nanoparticle approach of S. rebaudiana extract to improve the efficacy. Methods: Four electronic databases (Google Scholar, PubMed, Scopus, and ScienceDirect) were used with specified inclusion and exclusion criteria set. Results: The glycosides produced by S. rebaudiana are 300 times sweeter than sucrose, low in calories, and can control blood sugar levels and increase insulin secretion. The application of nanoparticles in S. rebaudiana extract is a new step to maximise efficacy, increase stability and solubility. Conclusion: S. rebaudiana can be used as an alternative diet for COVID-19 diabetes patients. The application of the nanoparticles can increase the stability and solubility, thus improving the efficacy.
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BACKGROUND AND AIM: E. coli are widely used for recombinant protein development, due to its low cost, ease of manipulation, and availability of well established molecular tools and techniques. Due to a lack of sophisticated machinery to undertake posttranslational modifications, the E. coli bacterial culture is limited in its ability to express more complex proteins, resulting in low solubility of the protein of interest that is generated as inclusion bodies. Although we were able to produce the recombinant SARS-CoV-2-S1 protein at high expression levels in our earlier investigation, we were also able to obtain nearly the whole protein as inclusion body. To overcome this problem, different solubility strategies have been tried. In this study, we developed an E.coli expression strategy based on the expression of the S1 protein as a fusion of SUMO fusion protein. METHODS: The DNA sequence of S1 protein was cloned into the pET SUMO expression vector, resulting in a construct expressing a N-terminal tag SUMO fusion protein. To achieve the high-level expression of S1, small scale expression conditions were optimized in E. coli BL21 (DE3) containing pET SUMO-S1 with different induction temperatures, times and IPTG concentrations. Additionally, different medium was also tested for the expression of S1 protein. For each parameter, solubility and expression of cell lysates from uninduced and induced cultures, plus the soluble and insoluble fractions from induced cultures were analyzed by SDS-PAGE and Western Blot. RESULTS: SDS-PAGE and Western Blot analysis showed the presence of a ∼83 kDa recombinant fusion protein. The maximum level of expression of the recombinant protein was observed at 30 , 4 h after induction with 0,55 mM IPTG. CONCLUSIONS: This study showed that the use of SUMO fusion tag partially increases the production of S1 protein in the form of soluble fractions and optimization studies continue.