Pharmaceutical Research Research Articles

Folate-Mediated Targeting and Controlled Release: PLGA-Encapsulated Mesoporous Silica Nanoparticles Delivering Capecitabine to Pancreatic Tumor.

The discovery of specifically tailored therapeutic delivery systems has sparked the interest of pharmaceutical researchers considering improved therapeutic effectiveness and fewer adverse effects. The current study concentrates on the design and characterization of PLGA (polylactic-co-glycolic acid) capped mesoporous silica nanoparticles (MSN)-based systems for drug delivery for pH-sensitive controlled drug release in order to achieve a targeted drug release inside the acidic tumor microenvironment. The physicochemical properties of the nanoformulations were analyzed using TEM, zeta potential, AFM, TGA, FTIR, and BET analyses in addition to DLS size. The final formed PLGA-FoA-MSN-CAP and pure MSN had sizes within the therapeutic ranges of 164.5 ± 1.8 and 110.7 ± 2.2, respectively. Morphological characterization (TEM and AFM) and elemental analysis (FTIR and XPS) confirmed the proper capping and tagging of PLGA and folic acid (FoA). The PLGA-coated FoA-MSN exhibited a pH-dependent controlled release of the CAP (capecitabine) drug, showing efficient release at pH 6.8. Furthermore, the in vitro MTT test on PANC1 and MIAPaCa-2 resulted in an IC50 value of 146.37 μg/ml and 105.90 μg/ml, respectively. Mitochondrial-mediated apoptosis was confirmed from the caspase-3 and annexin V/PI flow cytometry assay, which displayed a cell cycle arrest at the G1 phase. Overall, the results predicted that the designed nanoformulation is a potential therapeutic agent in treating pancreatic cancer.

Recent Approaches of Impurity Profiling in Pharmaceutical Analysis: A Concise Review

Purity profiling is the process of gathering and analyzing information to determine the biological safety of a specific impurity, hence highlighting its importance and range in pharmaceutical research. In the field of pharmaceuticals, impurity has no precise meaning. Identification, structural elucidation, and quantitative determination of impurities and degradation products in bulk medicinal materials and pharmaceutical formulations are all included in impurity profiling. Since unrecognized, possibly poisonous impurities are dangerous to health and should be found and determined by selective procedures in order to increase the safety of drug therapy, impurity profiling has become more significant in contemporary pharmaceutical analysis. Impurities are typically described using words like residual solvents, byproducts, transformation products, degradation products, interaction products, and related products. Impurity identification is carried out using different chromatographic methods in addition to passing the CGMP, QC, QA, and water activity tests, a pharmaceutical ingredient also needs to satisfy the requirements for a new impurity. It is important to separate and characterize impurities in order to collect and evaluate data that determines biological safety, which emphasizes the need for and promise of drug impurity profiling in pharmaceutical research. To separate and measure the pollutants, a range of instrumental analytical techniques have been consistently used. The detection and regulatory evaluation of organic impurities is a very challenging task because to the numerous sources of organic impurities, including microbiological contamination, API breakdown products, and traces of intermediates.

Synthesis, structure determination, molecular interaction, optical, thermal and anticancer activity studies, pharmacokinetic evaluation, and in-silico analysis of monocarbonyl curcumin derivative: An approach to drug discovery

Overseeing the diverse pharmacological traits of curcumin, a novel monocarbonyl based curcumin derivative (1-(4-ethylbenzoyl)-3, 5-bis ((E)-4-methoxybenzylidene) piperidin-4-one) [EMBP] was synthesized by Claisen-Schmidt condensation and Schotten-Baumann reaction procedures, and diffraction quality crystal was obtained by slow evaporation method. Geometrical parameters were calculated for the grown crystal by using the SCXRD technique. The non-covalent interactions like CH∙∙∙π, π∙∙∙π were visualized by Hirshfeld surfaces analysis. The contribution of various interactions towards the total Hirshfeld surface has been quantified by 2D fingerprint plot. The synthesized material is characterized for various optical and spectral properties through NMR, FT-Raman, FT-IR, UV–Vis, and PL spectra. The thermal stability and melting point of the material have been examined by TG/DTA analysis. The cytotoxic effect on the normal cell line HEK-293 was evaluated, and found that the compound is highly toxic. Anticancer activity on MCF-7 cell line of the compound was assessed and found to exhibit exceptional efficacy against cancerous cells. Results of molecular docking studies and evaluated ADMET properties clearly demonstrate that the synthesized material can be proposed as a promising medication for treating breast cancer but after an extensive biological and pharmaceutical research.

Abstract 1303: Harness the power of data to improve cancer care - Understanding the complex landscape of health policies and regulations

Abstract In the era of big data and artificial intelligence, biomedical research and healthcare have been presented with unprecedented opportunities for improving the understanding of cancer biology. In addition, the Open Science Initiative aims to shift the current paradigm of research practice towards broad sharing and public access to research findings as the norm. Big data in oncology usually includes a combination of genomic sequencing, proteomics, medical imaging, electronic health records, payor records, and other data sources from pharmaceutical research, wearables, and medical devices. While combining, linking, and analyzing data from different sources across research and healthcare enterprises is key to realizing the promise of big data and a health learning system, it poses tremendous challenges for researchers and implementers to understand the nuances of relevant policies, laws, and regulations while striving for broad, equitable, timely and responsible data sharing, as well as tackling issues in data quality, harmonization, interoperability, and security. Herein, we aim to shine a light on the ever-evolving landscape of data privacy regulations, laws, and policies that govern different touch points of a patient's journey where data are collected for research and healthcare purposes throughout the lifecycle that would impact data-sharing outcomes. We hope the illumination of a complex landscape of data governance framework to consider for many data sources will facilitate broad community engagement including data scientists and technologists, patients and advocacy groups, and policymakers to maximize open data and science while protecting patient privacy and confidentiality. Citation Format: Ying Huang, Heather Basehore, Emily S. Boja, Jaime M. Guidry Auvil. Harness the power of data to improve cancer care - Understanding the complex landscape of health policies and regulations [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1303.

Abstract 79: Enabling fast and convenient immune profiling of fresh and long-term stabilized human whole blood samples with CyTOF

Abstract Accurate phenotyping of immune cells in whole blood (WB) from patients with cancer is critical for making disease prognoses and monitoring clinical efficacy of immunotherapies. Fresh WB must be analyzed within 24 hours of collection to minimize changes in cellular composition. However, WB collection and cytometric analysis are often performed at different sites, which can result in sample processing delays. Several WB preservation reagents have been developed to address this challenge, including PROT1 (Smart Tube Inc.) and Cytodelics Whole Blood Cell Stabilizer (Cytodelics). However, not all antibody panels are compatible with these reagents. A CyTOF® panel was developed to be compatible with these commercial WB stabilizers and for use in pharmaceutical and clinical research. CyTOF flow cytometry uses metal-tagged antibodies to identify cellular and functional phenotypes. Advantages and features of CyTOF technology enable rapid design and application of 50-plus-marker panels and convenient workflows in which samples can be stained and acquired in a single tube. Compensation is not required since CyTOF flow cytometry has low signal spillover and no autofluorescence. Moreover, antibody cocktails and stained samples can be frozen for later use and acquisition. Thus, CyTOF technology overcomes major hurdles of fluorescence-based cytometry and provides a streamlined and flexible workflow in clinical research. The CyTOF panel contains 20 antibodies to identify over 30 immune cell populations. For easy customization, there are more than 30 additional open channels to analyze markers of interest. The panel works with fresh and stabilized WB samples and is amenable to different staining and acquisition workflows. To show the flexibility of sample staining and stabilization, WB from three healthy donors was assessed using two stabilization workflows. First, fresh WB samples were stained with the antibody panel, followed by PROT1 or Cytodelics stabilization and storage at -80 °C. The second workflow involved immediate stabilization/fixation of WB with PROT1 or Cytodelics and storage at -80 °C. Subsequently, the samples for the second workflow were thawed, surface stained, and acquired. To reduce technical variability from staining, the antibodies were pooled together and frozen at -80 °C as single-use aliquots. Furthermore, all samples were barcoded and acquired as a single tube to reduce variability from sample acquisition. The CyTOF panel developed for broad immune profiling is compatible with WB stabilizers, which overcomes traditional and logistical challenges with WB processing and acquisition. Furthermore, freezing antibody cocktails is a unique feature of CyTOF flow cytometry, ensuring batch-to-batch consistency in clinical research. Thus, CyTOF workflows enable swift and convenient analysis of WB samples. For Research Use Only. Not for use in diagnostic procedures. Citation Format: Michael Cohen, Shakir Hasan, Stephen Li, Christina Loh. Enabling fast and convenient immune profiling of fresh and long-term stabilized human whole blood samples with CyTOF [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 79.

Simulation of viscoelastic free-surface flows with the Particle Finite Element Method

Viscoelastic fluids are central in numerous applications from polymer manufacturing to the pharmaceutical industry and biological research. However, since analytical solutions are generally not available or too complex, it is common practice to study free-surface viscoelastic flows through numerical simulation techniques. This work proposes the use of the so-called particle finite element method (PFEM), a Lagrangian approach combining standard FEM techniques with a remeshing strategy. The PFEM is able to efficiently handle mesh distortion and to accurately track the free-surface evolution. Therefore, it is exploited in this work to deal with large displacements problems in the context of nonlinear viscoelasticity. An implementation of the Oldroyd-B constitutive model in the PFEM framework is here presented including details regarding how to deal with the transfer of the internal variables during remeshing events. Additionally, an innovative approach to impose unilateral Dirichlet boundary conditions ensuring optimal mass conservation is presented. The implementation is verified with two free-surface highly viscous benchmark flows: the impacting drop and the jet buckling problems. The results show perfect agreement with those obtained with other numerical techniques. The proposed framework opens the way for using PFEM in various applications, ranging from polymer extrusion to more sophisticated scenarios involving viscoelastic and viscoelasto-plastic constitutive laws.

Abstract 3333: Targeting the MDM2-p53 interaction: Time- and concentration-dependent studies in tumor and normal human bone marrow cells reveal strategies for an enhanced therapeutic index

Abstract Aim We aimed to design an MDM2-p53 antagonist with a differentiated tolerability profile that could be used to treat patients with wild-type TP53 malignancies. As part of an alliance between Newcastle University, Astex Pharmaceuticals, and Cancer Research Horizons, we discovered ASTX295, a potent inhibitor of the MDM2-p53 interaction that is currently under clinical investigation in patients with solid tumors (NCT03975387). We selected ASTX295 as a compound with a predicted short plasma half-life, which we hypothesised would help to mitigate the dose-limiting neutropenia and thrombocytopenia observed with earlier MDM2-p53 antagonists in clinical studies. To examine this hypothesis in vitro, we determined time- and concentration-dependent responses to ASTX295 treatment in healthy volunteer-derived human bone marrow cells, megakaryocytes, and in a panel of human tumor cell lines. Methods Samples containing bone marrow cells from healthy patients undergoing hip surgery were obtained under the ethical approval of the Newcastle Biobank (REC 12/NE/0395). Following Lymphoprep™ separation, cells were treated ex vivo with ASTX295 and seeded for Granulocyte-macrophage (GM) colony-forming assays in methylcellulose. Megakaryocytes were obtained from in vitro differentiation of CD34+ stem/progenitor cells. Human tumor cell lines (including MDM2-amplified SJSA-1) were treated with ASTX295 in vitro and seeded at low density for colony-forming assays. Exposures of 6, 12, or 24h were examined, and the data plotted to calculate LC50 values. Results The clonogenic survival of tumor cells was time-dependent, with LC50 values (mean ± SEM) in SJSA1 cells being 238 ± 46nM and 75 ± 7nM respectively (n = 3-4), following a 12h or 24h exposure to ASTX295. Time-dependent effects were also evident in five human bone marrow samples but with LC50 values of 1.9, >3, >10, >10, and >10uM being achieved at 12h, and 860 ± 268nM at 24h. Megakaryocytes showed similar time-dependent sensitivities in which daily treatment of 2 or 6h over three days did not induce apoptosis while significant cell death was observed when the treatment time was extended to 16-24h daily. In contrast, short, daily pulse treatment of 2-6h in cell lines (MV4-11, MOLM-13, SJSA-1) over three days was sufficient to induce cell death. Conclusions ASTX295 is a potent antagonist of the MDM2-p53 interaction. Collectively, our in vitro data suggest that a shorter exposure to ASTX295 (up to 12h), may help to spare healthy bone marrow cells whilst killing tumor cells. Hence, intermittent exposure to an MDM2-p53 antagonist could favourably modulate its therapeutic index. The predicted short plasma half-life of ASTX295 should provide flexibility in controlling the duration of exposure in vivo, potentially enabling a more bone-marrow sparing approach to MDM2-p53 antagonism to be utilised. Citation Format: Elaine Willmore, Maria Ahn, Suzanne Kyle, Yan Zhao, Huw Thomas, Kenneth S. Rankin, Luke Bevan, Lynsey Fazal, Keisha Hearn, Nicola Wilsher, Justyna Kucia-Tran, Nicola Ferrari, Nicola Wallis, Neil Thompson, John Lyons, Duncan Miller, Celine Cano, Martin E. Noble, Ian R. Hardcastle, Steven Howard, Gianni Chessari, John Lunec, David R. Newell, Steve R. Wedge. Targeting the MDM2-p53 interaction: Time- and concentration-dependent studies in tumor and normal human bone marrow cells reveal strategies for an enhanced therapeutic index [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3333.

Exploring Cyclodextrin-Based Nanosponges as Drug Delivery Systems: Understanding the Physicochemical Factors Influencing Drug Loading and Release Kinetics.

Cyclodextrin-based nanosponges (CDNSs) are complex macromolecular structures composed of individual cyclodextrins (CDs) and nanochannels created between cross-linked CD units and cross-linkers. Due to their unique structural and physicochemical properties, CDNSs can possess even more beneficial pharmaceutical features than single CDs. In this comprehensive review, various aspects related to CDNSs are summarized. Particular attention was paid to overviewing structural properties, methods of synthesis, and physicochemical analysis of CDNSs using various analytical methods, such as DLS, PXRD, TGA, DSC, FT-IR, NMR, and phase solubility studies. Also, due to the significant role of CDNSs in pharmaceutical research and industry, aspects such as drug loading, drug release studies, and kinetics profile evaluation of drug-CDNS complexes were carefully reviewed. The aim of this paper is to find the relationships between the physicochemical features and to identify crucial characteristics that are influential for using CDNSs as convenient drug delivery systems.

Synthesis, characterization and Antibacterial Evaluation of Novel Thiazolidine Derivatives

Background: Heterocyclic compounds, which incorporate atoms such as nitrogen and sulfur alongside carbon, play a crucial role in nature and organic chemistry. Thiazolidine derivatives, characterized by sulfur and nitrogen atoms with a carbonyl group at the -4 position, are particularly noteworthy for their stability and diverse biological activities. We synthesized novel thiazolidine derivatives and determined their antibacterial properties. the synthesis of novel thiazolidine compounds was perforemd using thioglycolic acid with hydrazides, generated from the combination of hydrazides with benzaldehyde. Methods: The esters, hydrazides, hydrazones, and thiazolidines, were synthesized and characterized using infrared spectroscopy, nuclear magnetic resonance, and melting point analysis. Assessment of anti-bacterial activity was carried out against Gram-positive and Gram-negative bacterial strain of Staphylococcus aureus, Acinetobacter baumannii, Aeromonas sobria, and Escherichia coli. . Results: We synthesized ethyl 2-acetate (benzo[d]thiazol-2-yloxy), followed by the formation of 2-(benzo[d]thiazol-2-yloxy)acetohydrazide (hydrazide) through the reaction of this acetate with hydrazine. 16 compounds were synthesized with rigorous validation at each stage through spectral analysis. Thiazolidine derivatives exhibited promising inhibitory effects against bacterial growth, indicating their potential as antibacterial agents.Compound SH8 exhibited moderate to strong inhibitory effects against all tested species, notably Aeromonas sobria and Staphylococcus aureus, at a concentration of 0.1 mg/ml. Conclusion: In conclusion, the synthesized compounds exhibited both structural integrity and potent antibacterial activity, suggesting avenues for further exploration in pharmaceutical research.

Phytochemistry of Medicinal Herbs Belongs to Asclepiadaceae Family for Therapeutic Applications: A Critical Review.

The world of pharmaceutical research has been increasingly turning its gaze toward the treasure trove of natural products in search of novel drugs and therapeutic agents. Amidst the vast array of medicinal plants that dot our planet, the Asclepiadaceae family unexplored species have piqued the interest of researchers. Both medicinal plants are indigenous to specific regions and have been integral to traditional medicine systems for centuries. This systematic review aims to provide a comprehensive summary of the current knowledge regarding the phytochemical profile of these plants and their potential implications in the pharmaceutical industry. These plants are rich in phytochemical constituents such as alkaloids, flavonoids, terpenoids, phenolic compounds, glycosides, and saponins. These constituents have been found to exhibit a range of pharmacological activities. They have antimicrobial properties, providing a defense against various microorganisms. They also show anti-inflammatory properties, helping to reduce inflammation in the body. In addition, these plants have antioxidant properties, which help protect cells from damage by harmful free radicals. They have shown anticancer activity, offering potential for cancer treatment. Their neuroprotective properties could be beneficial in treating neurological disorders. The analgesic properties of these plants could be harnessed for pain relief. Furthermore, they have antidiabetic properties, offering potential for diabetes management. The hope is that this review will stimulate further research into these fascinating plants and contribute to discovering new drugs from natural herbs.

Patent highlights August-September 2023.

A snapshot of noteworthy recent developments in the patent literature of relevance to pharmaceutical and medical research and development.

Artificial Intelligence in Biology

This article provides an in-depth analysis of the use of Artificial Intelligence (AI) in various aspects of biology, including healthcare, agriculture, and environmental monitoring. It highlights AI's ability to mimic human intelligence and analyze large datasets for predictions and tasks. The article also discusses its integration into Chinese medicine, where AI-guided diagnostic and therapeutic systems optimize clinical treatments and health management. AI is also used in disease management, analyzing data on diseases and pests, predicting their impact on ecosystems, and implementing preventative measures. The article also highlights the role of integrated information systems in environmental monitoring. Artificial intelligence (AI) has significant potential in healthcare research and chemical discoveries. Pharmaceutical companies are using AI to improve drug development by utilizing computational biology and machine learning systems to predict molecular behavior and the likelihood of finding a useful drug. This saves time and money on unnecessary tests. Clinical studies, electronic medical records, high-resolution medical images, and genomic profiles can be used as resources for drug development. Strong AI systems can analyze extensive data sets in pharmaceutical and medical research. This review focuses on integrating knowledge of cancer drugs, drug resistance, next-generation sequencing, genetic variants, and structural biology in cancer precision drug discovery.

Establishment of RWS guidance reflecting contributions of China to regulatory science

ABSTRACT China’s accession to the ICH has accelerated the advancement of its regulatory science. To foster innovation and improve the efficiency of pharmaceutical research and development, the China National Medical Products Administration (NMPA) encourages the use of real-world evidence (RWE) to support drug regulatory decision-making and has constructed a series of real-world study (RWS) related guidance, reflecting the contribution of the NMPA to the field of RWS in drug clinical development. Based on the four guidelines on RWE, real-world data (RWD), RWS design and protocol development, and communication with regulatory authorities, the guidance has been extended to more specific clinical applications, such as oncology, rare diseases, pediatric drugs, and traditional Chinese medicine. This paper reviews the core content and features of the series of RWS guidelines, presents their role in promoting drug development, and discusses challenges of using RWE in support of drug regulatory decision-making in China.

REVOLUTIONIZING DRUG DELIVERY INNOVATION: LEVERAGING AI-DRIVEN CHATBOTS FOR ENHANCED EFFICIENCY

This study aims to delineate the pivotal role of ChatGPT, an Artificial intelligence-driven (AI) language model, in revolutionizing drug delivery research within the pharmaceutical sciences domain. The investigation adopted a structured approach involving systematic literature exploration across databases such as PubMed, ScienceDirect, IEEE Xplore, and Google Scholar. A selection criterion emphasizing peer-reviewed articles, conference proceedings, patents, and seminal texts highlights the integration of AI-driven chatbots, specifically ChatGPT, into various facets of drug delivery research and development. ChatGPT exhibits multifaceted contributions to drug delivery innovation, streamlining drug formulation optimization, predictive modeling, regulatory compliance, and fostering patient-centric approaches. Real-world case studies have underscored its efficacy in expediting drug development timelines and enhancing research efficiency. This paper delves into the diverse applications of ChatGPT, showcasing its potential across drug delivery systems. It elucidates its capabilities in accelerating research phases, facilitating formulation development, predictive modeling for efficacy and safety, and simplifying regulatory compliance. This discussion outlines the transformative impact of ChatGPT in reshaping drug delivery methodologies. In conclusion, ChatGPT, an AI-driven chatbot, has emerged as a transformative tool in pharmaceutical research. Their integration expedites drug development pipelines, ensures effective drug delivery solutions, and augments healthcare advancements. Embracing AI tools such as ChatGPT has become pivotal in evolving drug delivery methodologies for global patient welfare.

Deepstacked-AVPs: predicting antiviral peptides using tri-segment evolutionary profile and word embedding based multi-perspective features with deep stacking model

BackgroundViral infections have been the main health issue in the last decade. Antiviral peptides (AVPs) are a subclass of antimicrobial peptides (AMPs) with substantial potential to protect the human body against various viral diseases. However, there has been significant production of antiviral vaccines and medications. Recently, the development of AVPs as an antiviral agent suggests an effective way to treat virus-affected cells. Recently, the involvement of intelligent machine learning techniques for developing peptide-based therapeutic agents is becoming an increasing interest due to its significant outcomes. The existing wet-laboratory-based drugs are expensive, time-consuming, and cannot effectively perform in screening and predicting the targeted motif of antiviral peptides.MethodsIn this paper, we proposed a novel computational model called Deepstacked-AVPs to discriminate AVPs accurately. The training sequences are numerically encoded using a novel Tri-segmentation-based position-specific scoring matrix (PSSM-TS) and word2vec-based semantic features. Composition/Transition/Distribution-Transition (CTDT) is also employed to represent the physiochemical properties based on structural features. Apart from these, the fused vector is formed using PSSM-TS features, semantic information, and CTDT descriptors to compensate for the limitations of single encoding methods. Information gain (IG) is applied to choose the optimal feature set. The selected features are trained using a stacked-ensemble classifier.ResultsThe proposed Deepstacked-AVPs model achieved a predictive accuracy of 96.60%%, an area under the curve (AUC) of 0.98, and a precision-recall (PR) value of 0.97 using training samples. In the case of the independent samples, our model obtained an accuracy of 95.15%, an AUC of 0.97, and a PR value of 0.97.ConclusionOur Deepstacked-AVPs model outperformed existing models with a ~ 4% and ~ 2% higher accuracy using training and independent samples, respectively. The reliability and efficacy of the proposed Deepstacked-AVPs model make it a valuable tool for scientists and may perform a beneficial role in pharmaceutical design and research academia.

Identification and In-Silico Profiling of Phytoconstituents in Leaves of Punica grantum L.

Punica granatum L. also called Pomegranate, a valuable fruit belonging to Punicaceae family. Pomegranate is not only nutrious but has remarkable medicinal properties. This study aimed to identify the phytochemical constituents present in Pomegranate leaves utilizing Gas Chromatography-Mass Spectrometry (GC-MS) technique, and to assess their medicinal potential using the PASS online software. The results of the analysis revealed the presence of several important phytochemicals, like Neophytadiene,Phytol,1,2 Benzene Dicarboxylic acid known for their medicinal properties such as Saccharopepsin inhibitor, Retinol dehydrogenase inhibitor, anti-inflammatory, anti-pyretic and anti-cancer. From the screened potent compounds, notably Phytol showed good activity which can be further evaluated for in-vivo drug evaluation. This study contributes to the understanding of the phytochemical composition and medicinal potential of Pomegranate leaves, highlighting its significance as a valuable natural resource for pharmaceutical research and development.

Challenges, Alternatives, and Paths to Sustainability for Health Information Exchange Efforts Using PROMETHEE Method

Electronic health information sharing and regional health information centres The practise of emergency medicine in the United States can have a significant impact. Regional Health Information Institutes are stakeholder networks that share local or regional information in a specific geographic area. Set up electronic data transfer. Safety of medical care and to improve efficiency across the country regional health information institutions are being created; Public health initiatives, biological surveillance and enhancing the reaction of catastrophe management; and identifying for research enormous databases of aggregate data. However, the economy Organizational issues and including geography to facilitate exchange With the Regional Health Information Organization (RHIO) model They identified challenges. Direct, institutional HIE and such as seller-mediated exchange versus alternative modes of exchange RHIOs vary. Due to political and economic reasons HIE is a difficult task. It is of many types Classified by optional activities; they are for alternatives in judgments The differences between Used to allocate. Under conventional criterion priority functions Using PROMETHEE Choice of health information exchange. This paper proposes that in the final option to check the effect of different optional functions Comparable results are presented. Seven economic and environmental criteria, Four health information and Five decision makers health information exchange problem Major Structures. with decision makers using a five-point Likert scale by personal communication Data was collected. Under the usual criterion function PROMETHEE's algorithm is implemented. The pharmaceutical industry and research, medical trials, healthcare fraud detection, neurological research, and electronic health records are alternatives. Evaluation Parameters are Transparent, Autonomy, Open Source, Anonymity and Decentralized. Health Information Exchange using PROMETHEE. Electronic Health Records, is got third rank, Clinical Research is got first rank, Medical Fraud Detection is got forth rank, Neuroscience Research is got fifth rank and Pharmaceutical Industry and Research is got second rank

Nanotheranostics: A Cutting-Edge Technology for Cancer Management.

Cancer is the second-leading cause of death in the 21st century, where early detection and appropriate therapeutic interventions are two components essential for effective cancer management. Despite the availability of several conventional diagnostics and therapeutic agents, cancer mortality rates are rising due to an increase in the frequency of recurrence and metastasis in cancer patients. Therefore, tremendous efforts have been expended to address this significant clinical issue and improve therapeutic efficacy. In this regard, nanotheranostic is a multipotential single platform for both cancer diagnosis and treatment through enhanced aqueous solubility and bioavailability of the encapsulated agent, stimulus responsiveness, tumor-specific targeting ability, precise tumor imaging, and real-time drug delivery. Nonetheless, the translational success of nanotheranostic platforms is still in its infancy and requires more extensive research in the context of tumor heterogeneity, safety profile, and regulatory issues, which pose one of the largest technological limitations. The present review summarizes different nanotheranostic platforms and nanotheranostic candidates in clinical trials (AGuIX® , NBTXR3, Ferumoxtran, MM-398, EndoTAG-1, etc.), along with disadvantages and challenges to improving cancer diagnosis and treatment. Overall, the concept, platform, and technical knowledge of nanotheranostics are really helpful to academic and pharmaceutical researchers.

The health-care utilization and economic burden in patients with genetic skeletal disorders

BackgroundMost genetic skeletal disorders (GSD) were complex, disabling and life-threatening without effective diagnostic and treatment methods. However, its impacts on health system have not been well studied. The study aimed to systematically evaluate the health-care utilization and economic burden in GSD patients.MethodsThe patients were derived from 2018 Nationwide Inpatient Sample and Nationwide Readmissions Database. GSD patients were extracted based on International Classification of Diseases-10th revision codes.ResultsA total of 25,945 (0.12%) records regarding GSD were extracted from all 21,400,282 records in NIS database. GSD patients were likely to have significantly longer length of stay (6.50 ± 0.08 vs. 4.63 ± 0.002, P < 0.001), higher total charges ($85,180.97 ± 1,239.47 vs. $49,884.26 ± 20.99, P < 0.001), suffering more procedure, diagnosis and transferring records in comparison to patients with common conditions. GSD patients had a significantly higher 30-day all-cause readmission rate based on Nationwide Readmissions Database.ConclusionsThe heavy health-care utilization and economic burden emphasized the urgency for policy leaders, scientific and pharmaceutical researchers, health care providers and employers to identify innovative ways and take effective measurements immediately, and eventually to help improve the care, management, and treatment of these devastating diseases.

Contribution to Pharmacy/pharmacist Education through Writing

The Education Award of the Pharmaceutical Society of Japan (PSJ) was conferred for "Contribution to pharmacy/pharmacist education through writing on organic chemistry." The award-winning activities were described in three parts section 1-3. Section 1 Importance of Research and Education in Organic Chemistry: In this section, it is explained that organic chemistry serves as the fundamental basis for a wide range of natural science disciplines studied in pharmaceutical departments. It emphasizes that having a solid foundation in organic chemistry is essential for pharmacists to understand pharmaceuticals. This knowledge contributes significantly in healthcare settings such as team-based medical care (interprofessional cooperation) with physicians and nurses, as well as in interactions with patients, providing a unique contribution that other professions cannot achieve. Section 2 Two Serial Articles Written on Organic Chemistry: This part mentions two serial articles that are beneficial for pharmacists and pharmaceutical researchers. These articles aimed to broaden specialized knowledge and provide practical information, contributing to pharmaceutical education and professional training for pharmacists. Section 3 Publication of New Organic Chemistry Textbooks: In this section, the introduction of textbooks and reference books in the field of organic chemistry for pharmaceutical education is highlighted. These educational materials were published to offer valuable information to pharmaceutical students and aspiring pharmacists, enhancing their expertise. These three writing activities significantly contributed to pharmaceutical education and the improvement of the professional work of pharmacists.