Pharmaceutical Research Research Articles

Review on MALDI Imaging for Direct Tissue Imaging and its Application in Pharmaceutical Research

Matrix-Assisted Laser Desorption/Ionization (MALDI) imaging has emerged as a powerful analytical technique, enabling direct tissue imaging in pharmaceutical research. This review provides an in-depth exploration of the principles, methodologies, and applications of MALDI imaging in the context of studying drug distribution and molecular changes within tissues. provides a structured approach to exploring the principles, methodologies, applications, challenges, and future directions of MALDI Imaging in pharmaceutical research. Each section aims to contribute to a comprehensive understanding of the technique’s significance and potential for transformative contributions to the field. The study begins by elucidating the underlying principles of MALDI imaging, highlighting the role of matrix-assisted laser desorption/ionization in generating spatially resolved mass spectra from biological samples. Special emphasis is placed on advancements in instrumentation and sample preparation techniques that have enhanced the spatial resolution and sensitivity of MALDI imaging. The application of MALDI imaging in pharmaceutical research is comprehensively explored, focusing on its pivotal role in drug development, pharmacokinetic studies, and toxicity assessments. Case studies and examples illustrate how MALDI imaging facilitates the visualization of drug distribution within tissues, offering valuable insights into drug metabolism, biodistribution, and pharmacodynamics.

An overview of the applications of total reflection X-ray fluorescence spectrometry in food, cosmetics, and pharmaceutical research

Ensuring reliable elemental analysis in food, cosmetic and pharmaceutical research is a prerequisite to human safety. Here we report on the use of total reflection X-ray fluorescence spectrometry, its state-of the art and challenges in those fields.

Evolutionary trend analysis of the pharmaceutical management research field from the perspective of mapping the knowledge domain.

Pharmaceutical management is a new frontier subject between pharmacy, law and management, and related research involves the whole process of drug development, production, circulation and use. With the development of medical systems and the diversification of patients' drug needs, research in the field of pharmaceutical management is becoming increasingly abundant. To clarify the development status of this field, this study conducted a bibliometric analysis of relevant literature in the field based on the knowledge graph method for the first time and explored the evolutionary trends of research hotspots and frontiers. Literature was obtained from the Web of Science Core Collection database. CiteSpace 6.2.R4 (Advanced), VOSViewer, Scimago Graphica, Pajek and the R programming language were used to visualize the data. A total of 12,771 publications were included in the study. The publications in the field of pharmaceutical management show an overall increasing trend. In terms of discipline evolution, early research topics tended to involve the positioning of pharmacists and pharmaceutical care and the establishment of a management system. From 2000 to 2005, this period tended to focus on clinical pharmacy and institutional norms. With the development of globalization and the market economy, research from 2005 to 2010 began to trend to the fields of drug markets and economics. From 2010 to 2015, research was gradually integrated into health systems and medical services. With the development of information technology, after 2015, research in the field of pharmaceutical management also began to develop in the direction of digitalization and intelligence. In light of the global pandemic of COVID-19, research topics such as drug supply management, pharmaceutical care and telemedicine services under major public health events have shown increased interest since 2020. Based on the knowledge mapping approach, this study provides a knowledge landscape in the field of pharmaceutical management research. The results showed that the reform of pharmacy education, the challenge of drug management under the COVID-19 pandemic, digital transformation and the rise of telemedicine services were the hot topics in this field. In addition, the research frontier also shows the broad prospects of the integration of information technology and pharmaceutical management, the practical value of precision pharmaceutical services, the urgent need of global drug governance, and the ethical and legal issues involved in the application of artificial intelligence technology in drug design, which points out the direction for the future development of pharmaceutical practice.

Current analytical approaches for characterizing nanoparticle sizes in pharmaceutical research

Current analytical approaches for characterizing nanoparticle sizes in pharmaceutical research

Anti-inflammatory Activity and Computational Biology Study of Indole/Pyrimidine Hybrids

Abstract: This research paper embarks on an interdisciplinary exploration encompassing synthetic chemistry, pharmacology, and computational biology. The development of novel anti-inflammatory agents is an imperative endeavor within pharmaceutical research. Pyrimidines and thienopyrimidines are class of heterocyclic compounds that have gained prominence for their diverse pharmacological properties, including potential anti-inflammatory effects. When augmented with an indole moiety, these compounds exhibit structural diversity that can profoundly influence their biological activities. The integration of computational biology specifically molecular docking, plays a crucial role in predicting and understanding the binding interactions between these compounds and select protein targets associated with inflammatory pathways. This computational approach expedites the screening of potential drug candidates and elucidates the molecular underpinnings of their anti-inflammatory actions. Pyrimidine and thienopyrimidines tethering indole scaffold were obtained according to our reported methods. Subsequently, in vivo evaluation of anti-inflammatory is indispensable to gauge the anti-inflammatory potential of these compounds and establish structure-activity relationships. The experimental and computational biology studies of the target indole-pyrimidines hybrids revealed that these compounds can serve as anti-inflammatory agents. This paper can potentially open new avenues for therapeutic strategies against inflammation-associated disorders. The synergy of synthetic innovation, pharmacological evaluation, and computational insights offers a holistic approach to advance our understanding of pyrimidines with an indole moiety as potential agents for mitigating inflammation.

Considering the Professionalism of Pharmacists from the Perspective of Pharmacists Working in Government and Industry

Through many years' experience in pharmaceutical administration, we believe that when pharmacists active in various workplaces are involved in research and development (especially clinical development) and post-marketing (especially proper usage and safety measures), they can better meet patients' hopes and expectations based on actual conditions in clinical practice and other settings by means of mutual communication and collaboration. The International Pharmaceutical Federation believes that for the benefit of patients, pharmaceutical researchers and pharmacists should work together and that the three pillars of research, practice, and education are closely and inseparably integrated. In today's rapidly evolving society, it is necessary-and beneficial-for pharmacists working in both government and industry to be better connected toward achieving better health care.

Recent developments and applications of ambient mass spectrometry imaging in pharmaceutical research: an overview.

The application of ambient mass spectrometry imaging "MSI" is expanding in the areas of fundamental research on drug delivery and multiple phases of the process of identifying and developing drugs. Precise monitoring of a drug's pharmacological workflows, such as intake, distribution, metabolism, and discharge, is made easier by MSI's ability to determine the concentrations of the initiating drug and its metabolites across dosed samples without losing spatial data. Lipids, glycans, and proteins are just a few of the many phenotypes that MSI may be used to concurrently examine. Each of these substances has a particular distribution pattern and biological function throughout the body. MSI offers the perfect analytical tool for examining a drug's pharmacological features, especially in vitro and in vivo effectiveness, security, probable toxic effects, and putative molecular pathways, because of its high responsiveness in chemical and physical environments. The utilization of MSI in the field of pharmacy has further extended from the traditional tissue examination to the early stages of drug discovery and development, including examining the structure-function connection, high-throughput capabilities in vitro examination, and ex vivo research on individual cells or tumor spheroids. Additionally, an enormous array of endogenous substances that may function as tissue diagnostics can be scanned simultaneously, giving the specimen a highly thorough characterization. Ambient MSI techniques are soft enough to allow for easy examination of the native sample to gather data on exterior chemical compositions. This paper provides a scientific and methodological overview of ambient MSI utilization in research on pharmaceuticals.

Palladium/XuPhos-catalyzed enantioselective cascade Heck/intermolecular C(sp2)-H alkylation reaction.

Palladium-catalyzed enantioselective domino Heck/intramolecular C-H functionalization reaction, as a valuable strategy for creating molecular diversity, has remained a prominent challenge. Here, we describe a Pd/XuPhos catalyst for asymmetric domino Heck/intermolecular C-H alkylation of unactivated alkenes with diverse polyfluoro- and heteroarenes in a highly chemo- and enantioselective manner. This process enables efficient synthesis of various dihydrobenzofurans, indolines and indanes, which are of interest in pharmaceutical research and other areas. Late-stage modifications of the core structures of natural products are also well showcased. Moreover, synthetic transformations create a valuable platform for preparing a series of functionalized molecules. Several control experiments for mechanistic study are conducted to pursue a further understanding of the reaction.

Niosome as a promising tool for increasing the effectiveness of anti-inflammatory compounds.

Niosomes are drug delivery systems with widespread applications in pharmaceutical research and the cosmetic industry. Niosomes are vesicles of one or more bilayers made of non-ionic surfactants, cholesterol, and charge inducers. Because of their bilayer characteristics, similar to liposomes, niosomes can be loaded with lipophilic and hydrophilic cargos. Therefore, they are more stable and cheaper in preparation than liposomes. They can be classified into four categories according to their sizes and structures, namely small unilamellar vesicles (SUVs), large unilamellar vesicles (LUVs,), multilamellar vesicles (MLVs), and multivesicular vesicles (MVVs). There are many methods for niosome preparation, such as thin-film hydration, solvent injection, and heating method. The current study focuses on the preparation methods and pharmacological effects of niosomes loaded with natural and chemical anti-inflammatory compounds in kinds of literature during the past decade. We found that most research was carried out to load anti-inflammatory agents like non-steroidal anti-inflammatory drugs (NSAIDs) into niosome vesicles. The studies revealed that niosomes could improve anti-inflammatory agents' physicochemical properties, including solubility, cellular uptake, stability, encapsulation, drug release and liberation, efficiency, and oral bioavailability or topical absorption. See also the graphical abstract(Fig. 1).

Harnessing machine learning for efficient large-scale interatomic potential for sildenafil and pharmaceuticals containing H, C, N, O, and S.

In this study a cutting-edge approach to producing accurate and computationally efficient interatomic potentials using machine learning algorithms is presented. Specifically, the study focuses on the application of Allegro, a novel machine learning algorithm, running on high-performance GPUs for training potentials. The choice of training parameters plays a pivotal role in the quality of the potential functions. To enable this methodology, the "Solvated Protein Fragments" dataset, containing nearly 2.7 million Density Functional Theory (DFT) calculations for many-body intermolecular interactions involving protein fragments and water molecules, encompassing H, C, N, O, and S elements, is considered as the training dataset. The project optimizes computational efficiency by reducing the initial dataset size according to the intended application. To assess the efficacy of the approach, the sildenafil citrate, iso-sildenafil, aspirin, ibuprofen, mebendazole and urea, representing all five relevant elements, serve as the test bed. The results of the Allegro-trained potentials demonstrate outstanding performance, benefiting from the combination of an appropriate training dataset and parameter selection. This notably enhanced computational efficiency when compared to the computationally intensive DFT method aided by GPU acceleration. Validation of the produced interatomic potentials is achieved through Allegro's own evaluation mechanism, yielding exceptional accuracy. Further verification is carried out through LAMMPS molecular dynamics simulations. Structural optimization by energy minimization and NPT Molecular Dynamics simulations are performed for each potential, assessing relaxation processes and energy reduction. Additional structures, including urea, ammonia, uracil, oxalic acid, and acetic acid, are tested, highlighting the potential's versatility in describing systems containing the aforementioned elements. Visualization of the results confirms the scientific accuracy of each structure's relaxation. The findings of this study demonstrate strong scaling and the potential for applications in pharmaceutical research, allowing the exploration of larger molecular structures not previously amenable to computational analysis at this level of accuracy The success of the machine learning approach underscores its potential to revolutionize computational solid-state physics.

A Review on The Impurity Profile of Pharmaceuticals

A collection of analytical procedures known collectively as “impurity profiling” are intended to detect, identify, clarify the structure of, and quantify both organic and inorganic impurities as well as residual solvents in pharmaceutical formulations and bulk pharmaceuticals. This is the main task of contemporary drug analysis since it is the most effective approach to describe the stability and quality of pharmaceutical formulations and bulk pharmaceuticals. To keep an eye on them, specific analytical techniques must be created. When modifications are made to the synthesis, formulation, or production processes, even if they are done to improve them, new purities could be seen. The identification of impurities in Active Pharmaceutical Ingredients (APIs) and the need for purity are being emphasised by a number of regulatory bodies, including the Canadian Drug and Health Agency (CDHA), the United States Food and Drug Administration (FDA), and the International Conference on Harmonisation (ICH). Pharmaceutical products can contain impurities from a variety of sources, including reagents, heavy metals, ligands, catalysts and other materials like charcoal, filter aids, and the like. Degraded end products from hydrolysis, photolytic cleavage, oxidative degradation, decarboxylation, and other processes can also contain impurities, as can enantiomeric impurities. The various pharmacopoeias, including the Indian, American, and British pharmacopoeias, are gradually adding restrictions to the permissible concentrations of contaminants found in APIs or formulations. Capillary electrophoresis, electron paramagnetic resonance, gas-liquid chromatography, gravimetric analysis, high performance liquid chromatography, solidphase extraction techniques, liquid-liquid extraction techniques, mass spectrometry, ultraviolet spectrometry, infrared spectroscopy, supercritical fluid extraction column chromatography, nuclear magnetic resonance (NMR) spectroscopy, and RAMAN spectroscopy are some of the techniques used to isolate and characterize impurities in pharmaceuticals. Liquid Chromatography (LC)-Mass Spectroscopy (MS), GC-MS, LC-NMR, LC- NMR-MS, and LC-MS are the most frequently used hyphenated techniques for drug impurity profiling. This demonstrates the importance and range of drug impurity profiling in pharmaceutical research.

Side-scattering spectroscopy of biological aggregates

In this study, we introduce a novel optical setup tailored for measuring scattering spectra of small biological aggregates with minimal sample volumes. Calibration was achieved using Polystyrene beads (PS beads) based on Mie scattering principles, enabling accurate measurements of scattering intensities. Bovine serum albumin (BSA) served as a model for studying protein aggregation due to its predictable aggregation behaviour at elevated temperatures. Analysis of non-aggregated and aggregated BSA solutions revealed significant differences in particle size, underscoring the setup's capability to detect variations in aggregation states. Key findings demonstrate the system's efficacy in monitoring protein aggregation processes, which is critical for biochemical and pharmaceutical research. The precise calibration method and the use of BSA as a validation tool highlight the setup's sensitivity and accuracy in quantifying changes in particle concentration and size due to aggregation. This study provides a framework for analysing protein aggregation and offers insights into the aggregation's impact on scattering properties.

Unveiling novel eccentric neighborhood forgotten indices for graphs and gaph operations: A comprehensive exploration of boiling point prediction

<abstract><p>This paper marks a significant advancement in the field of chemoinformatics with the introduction of two novel topological indices: the forgotten eccentric neighborhood index (FENI) and the modified forgotten eccentric neighborhood index (MFENI). Uniquely developed for predicting the boiling points of various chemical substances, these indices offer groundbreaking tools in understanding and interpreting the thermal properties of compounds. The distinctiveness of our study lies in the in-depth exploration of the discriminative capabilities of FENI and MFENI. Unlike existing indices, they provide a nuanced capture of structural features essential for determining boiling points, a key factor in drug design and chemical analysis. Our comprehensive analyses demonstrate the superior predictive power of FENI and MFENI, highlighting their exceptional potential as innovative tools in the realms of chemoinformatics and pharmaceutical research. Furthermore, this study conducts an extensive investigation into their various properties. We present explicit results on the behavior of these indices in relation to diverse graph types and operations, including join, disjunction, composition and symmetric difference. These findings not only deepen our understanding of FENI and MFENI but also establish their practical versatility across a spectrum of chemical and pharmaceutical applications. Thus the introduction of FENI and MFENI represents a pivotal step forward in the predictive analysis of boiling points, setting a new standard in the field and opening avenues for future research advancements.</p></abstract>

Unraveling molecular mechanisms of β-glucuronidase inhibition by flavonoids from Centaurea scoparia: integrated in silico and in vitro insights

Investigating the detailed molecular mechanisms of β-glucuronidase inhibition is critical for pioneering new therapeutic solutions and driving progress in pharmaceutical research.

Advances and challenges in the origin and evolution of ovarian cancer organoids.

Despite advancements in cancer research, epithelial ovarian cancer remains a leading threat to women's health with a low five-year survival rate of 48%. Prognosis for advanced cases, especially International Federation of Gynecology and Obstetrics (FIGO) III-IV, is poor. Standard care includes surgical resection and platinum-based chemo, but 70-80% face recurrence and chemoresistance. In recent years, three- dimensional (3D) cancer models, especially patients-derived organoids (PDOs), have revolutionized cancer research for personalized treatment. By transcending the constraints of conventional models, organoids accurately recapitulate crucial morphological, histological, and genetic characteristics of diseases, particularly in the context of ovarian cancer. The extensive potential of ovarian cancer organoids is explored, spanning from foundational theories to cutting-edge applications. As potent preclinical models, organoids offer invaluable tools for predicting patient treatment responses and guiding the development of personalized therapeutic strategies. Furthermore, in the arena of drug evaluation, organoids demonstrate their unique versatility as platforms, enabling comprehensive testing of innovative drug combinations and novel candidates, thereby pioneering new avenues in pharmaceutical research. Notably, organoids mimic the dynamic progression of ovarian cancer, from inception to systemic dissemination, shedding light on intricate and subtle disease mechanisms, and providing crucial insights. Operating at an individualized level, organoids also unravel the complex mechanisms underlying drug resistance, presenting strategic opportunities for the development of effective treatment strategies. This review summarizes the emerging role of ovarian cancer organoids, meticulously cultivated cellular clusters within three-dimensional models, as a groundbreaking paradigm in research.

Unveiling sultam in drug discovery: spotlight on the underexplored scaffold.

Decades ago, the application of cyclic sulfonamide (sultam) and its derivatives primarily focused on their antibacterial properties. However, recent years have seen a shift in research attention towards exploring their potential as anticancer, anti-inflammatory, antidiabetic, and antiviral agents. Despite this broadening scope, only a few sultam drugs have made it to the commercial market, as much of the research on sultams remains in the discovery phase. This class of compounds holds significant promise and remains pertinent in pharmaceutical research. Due to sultam's relevance and growing importance in drug discovery, this review paper aims to consolidate and examine the biological activities of sultam derivatives ranging from 4 to 8-membered ring structures.

Solvation controlled excited-state dynamics in a donor-acceptor phenazine-imidazole derivative.

In the past few decades, significant efforts have been devoted to developing phenazine derivatives in various fields such as medicine, pesticides, dyes, and conductive materials owing to their highly Stokes-shifted fluorescence and distinctive photophysical properties. The modulation of the surrounding environment can effectively influence the luminescent behavior of phenazine derivatives, prompting us to investigate the solvent effect on the excited state dynamics. Herein, we present the solvent controlled excited state dynamics of a novel triphenylamine-based phenazine-imidazole molecule (TPAIP) through steady-state spectra and femtosecond transient absorption spectra. The fluorescence emission spectrum exhibited a redshift with increasing solvent polarity, indicating the existence of a charge transfer state. Furthermore, by tracking the femtosecond transient absorption spectra of TPAIP, we found that the nature of the relaxed S1 state was strongly influenced by the solvent polarity: intersystem crossing character appears in apolar solvent, whereas intramolecular charge transfer character occurs in polar solvent because of solvation. These findings provide significant theoretical insights into the impact of solvents on the excited state dynamics within phenazine derivatives. This understanding supports diverse applications ranging from advanced biological probe design to photocatalysis and pharmaceutical research.

Nanosponges- An emerging trend in drug delivery

Advancement in pharmaceutical research has led to the discovery of nanosized drug delivery systems that act as a mean to deliver drugs at the target site. The nanosized carriers are studied for the diagnosis (biomarkers), prevention (prophylactic therapy), and therapeutic treatment of the diseases. Nanosponges an offshoot of nanotechnology has gained upstream because of its unique structural properties. It is a tiny sponge made up of either organic or inorganic material with wide cavities between them. Gases, micromolecules, and macromolecules of both hydrophobic and hydrophilic in nature can be entrapped in the structure. Progress in the research had led to the development of four generations of nanosponges namely, plain nanosponges, modified nanosponges, stimuli activated nanosponges, and molecularly imprinted nanosponges. They offer advantages of the sustained-release profile, better bioavailability, and negligible toxicity. The present review provides brief information on the structural features, different generations, methods of preparation, and characterization techniques and application of nanosponge formulation.

Synthesis and elucidation of strained galactopyronose esters as selective cyclooxygenase-2 inhibitor: a comprehensive computational approach.

Cyclooxygenase-2 (COX-2) is critically implicated in various pathologies, including inflammation, cancer, disorders involving the nervous system, and multidrug resistance. In both academic and pharmaceutical research, the development of COX-2 selective drugs as anti-inflammatory and anti-tumor therapeutics is a key focus. Traditional nonsteroidal anti-inflammatory drugs (NSAIDs) have ulcerogenic, gastrointestinal adverse effects, and myocardial infarction risk, which resulted in their limited applications. In response to this challenge, we synthesized a series of glycoconjugates featuring six-membered sugar rings and acyl chains of varying lengths attached at the C-6 position. Using molecular docking techniques, we identified galactose esters with optimal acyl chain lengths that selectively and effectively bind to the active site of COX-2 over COX-1. These compounds exhibited enhanced binding affinity and superior inhibition constants (pK i) for COX-2, thereby offering selective inhibition with potentially reduced ulcerogenic risks, as COX-1 inhibition is thought to contribute to these side effects. The molecular docking study identified two potential compounds, G6 and G8, which were validated via MD simulation for the assessment of their stability and were compared to the complex of the standard drugs, aspirin and rofecoxib. In addition, compound structures were optimized using the DFT method under the B3LYP/6-31+g(d,p) basis set to study their physio-spectral properties, frontier molecular orbitals (HOMO-LUMO), and their energy gap that correlates to their reactivity and stability. ADMET, drug-likeness, and PASS analyses were also carried out to assess their drug-ability and toxicity profiling.

Repurposing of biologics and biopharmaceuticals.

The field of drug repurposing is gaining attention as a way to introduce pharmaceutical agents with established safety profiles to new patient populations. This approach involves finding new applications for existing drugs through observations or deliberate efforts to understand their mechanisms of action. Recent advancements in bioinformatics and pharmacology, along with the availability of extensive data repositories and analytical techniques, have fueled the demand for novel methodologies in pharmaceutical research and development. To facilitate systematic drug repurposing, various computational methodologies have emerged, combining experimental techniques and in silico approaches. These methods have revolutionized the field of drug discovery by enabling the efficient repurposing of screens. However, establishing an ideal drug repurposing pipeline requires the integration of molecular data accessibility, analytical proficiency, experimental design expertise, and a comprehensive understanding of clinical development processes. This chapter explores the key methodologies used in systematic drug repurposing and discusses the stakeholders involved in this field. It emphasizes the importance of strategic alliances to enhance the success of repurposing existing compounds for new indications. Additionally, the chapter highlights the current benefits, considerations, and challenges faced in the repurposing process, which is pursued by both biotechnology and pharmaceutical companies. Overall, drug repurposing holds great promise in expanding the use of existing drugs and bringing them to new patient populations. With the advancements in computational methodologies and the collaboration of various stakeholders, this approach has the potential to accelerate drug development and improve patient outcomes.