Pharmaceutical Domain Research Articles

Discovering New Horizons: A Systematic Review on Artificial Intelligence Applications in Drug Discovery and Development.

The intersection of AI and the pharmaceutical domain represents a fundamental transformation offering novel possibilities to accelerate the drug design and development timeline by enhancing precision in therapeutic modalities. We focused on the amalgamation of these two domains in a strategic view of bringing out the potential and précised drug candidates by overcoming the challenges triggered by traditional formulation methods. Our aim is to thoroughly analyze the diverse applications of AI from its significant contribution to target identification and authentication of its influence on clinical trial optimization. Functioning as an intellectual guide, this systematic review directs readers through the undiscovered area where the zones of artificial intelligence and pharmaceutical sciences collaborate. By acquiring the required information from various studies and methodologies, our systematic review endeavors not only to present a retrospective analysis of AI’s influence but also to provide a forward-thinking perspective on its transformative possibilities.

Integration of Samarium Vanadate/Halloysite Nanotubes: Electrochemical Determination of Furaltadone Using Flexible Electrode

In this study, a composite comprising a rare‐earth metal, samarium vanadate (SmVO4, SmV), anchored to halloysite nanotube (HNT) making SmV/HNT nanocomposite is synthesized for the sensitive electrochemical determination of furaltadone (FLD) through differential pulse voltammetry analysis based on the synergistic effect of SmV/HNT (the catalytic activity and chemical stability of SmV, which was further boosted by the improved surface area and conductance of HNT). Further, in the microscopic studies, it is revealed that SmV exhibits a tetragonal zircon‐type crystalline structure, with I41/amd (141) space group, whereas HNT comprises a multiphase kaolin composition as a gibbsite‐like octahedral sheet with multivalency, and the morphological irregularities of the individual constituents are rectified in the composite. The SmV/HNT composite is spray‐coated on polyethylene terephthalate sheet, which delivered a promising trace level limit of detection (0.009 μm) over a wide working range (0.05–194.4 μm) for FLD. Furthermore, real sample analysis is performed using human serum, and pharmaceutical tablet and the results reveal exceptional repeatability and sensitivity, indicating the real‐time application of SmV/HNT in the pharmaceutical domain.

Novel Drug Delivery Systems: An Important Direction for Drug Innovation Research and Development.

The escalating demand for enhanced therapeutic efficacy and reduced adverse effects in the pharmaceutical domain has catalyzed a new frontier of innovation and research in the field of pharmacy: novel drug delivery systems. These systems are designed to address the limitations of conventional drug administration, such as abbreviated half-life, inadequate targeting, low solubility, and bioavailability. As the disciplines of pharmacy, materials science, and biomedicine continue to advance and converge, the development of efficient and safe drug delivery systems, including biopharmaceutical formulations, has garnered significant attention both domestically and internationally. This article presents an overview of the latest advancements in drug delivery systems, categorized into four primary areas: carrier-based and coupling-based targeted drug delivery systems, intelligent drug delivery systems, and drug delivery devices, based on their main objectives and methodologies. Additionally, it critically analyzes the technological bottlenecks, current research challenges, and future trends in the application of novel drug delivery systems.

Managerial ability, intellectual property rights, R&D: does firm age play a role?

PurposeThe interplay between individual and collective creativity and its translation into innovation is a critical yet complex challenge in the ever-evolving innovation landscape. This study delves into the intricate relationship between managerial ability, intellectual property rights (IPRs) and research and development (R&D) investments contextualized within the dynamics of leverage, firm life stages and tangibility for pharmaceutical firms in the Asia-Pacific region. By exploring how micro-level factors influence macro-level innovation processes, this study aims to contribute to the broader understanding of creativity and innovation, a theme at the heart of addressing contemporary global challenges.Design/methodology/approachEconometric methodologies were used to analyse a data set comprising 2,660 firm-year observations spanning the decade from 2011 to 2020.FindingsA key finding was that companies with lower managerial prowess strategically leverage R&D intensity to signal their value to the market and accrue reputational currency. The research unearths a significant positive relationship between managerial ability, IPRs and R&D investment. In environments characterized by strong managerial acumen and robust IPR safeguards, firms exhibit a heightened propensity to allocate resources to R&D endeavours. This underscores the role of intellectual leadership and legal protections in shaping R&D strategies within the pharmaceutical domain. Incorporating firm life stages as a moderating factor reveals that firm maturity fundamentally influences the interplay between managerial ability, IPRs and R&D expenditure.Originality/valueThese findings’ implications resonate profoundly within policy-making circles and pharmaceutical firms’ day-to-day operational strategies, underscoring the pivotal role of intellectual capital and legal safeguards in shaping the future of innovation in the Asia-Pacific pharmaceutical sector.

Comparison of in vitro membrane permeabilities of diverse environmental chemicals with in silico predictions

The parallel artificial membrane permeability assay (PAMPA) is widely used for estimating biomembrane permeabilities of experimental drugs in pharmaceutical research. However, there are few reports of studies using PAMPA to measure membrane permeabilities of chemicals of environmental concern (CECs) outside the pharmaceutical domain, many of which differ substantially from drugs in their physicochemical properties. We applied PAMPA methods simulating gastrointestinal (PAMPA-GIT) and blood-brain barrier (PAMPA-BBB) membranes under consistent conditions to 51 CECs, including some pharmaceuticals. A backward stepwise multivariate linear regression was implemented to explore the correlation between the differences of measured permeabilities from PAMPA-GIT and PAMPA-BBB and Abraham solute descriptors. In addition, a previously reported in silico model was evaluated by comparing predicted and measured permeability results. PAMPA-GIT and PAMPA-BBB experimental permeability results agreed relatively well. The backward stepwise multivariate linear regression identified excess molar refraction and polarizability to be significant at the 0.10 level in predicting the differences between PAMPA-GIT and PAMPA-BBB. The in silico model performed well – with predicted permeability of most compounds within two-fold of experimentally measured values. We found that CECs pose experimental challenges to the PAMPA method in terms of having lower solubility and lower stability compared to most drugs.

A Quantitative ABCD Analysis of Factors Driving Share Price Volatility in the Indian Pharmaceutical Sector

Purpose: This research employs an innovative ABCD (Advantages, Benefits, Constraints, and Disadvantages) analysis framework to intricately explore and evaluate the diverse factors influencing share price volatility in the Indian Pharmaceutical Sector. Delving into both individual and systemic characteristics, the study quantitatively assesses the effectiveness of various elements impacting share prices. Each component related to share price movements is meticulously assigned a score or weightage, providing a nuanced understanding of their respective contributions. Design: The researcher utilized focused group interviews to collect participants’ viewpoints on the factors influencing share price dynamics in the Indian pharmaceutical industry. Opinions were obtained through designated measurements, and the collected data underwent subsequent quantitative analysis. Findings: In the specific context of the present study, which focuses on the quantitative ABCD analysis of factors driving share price fluctuations in the Indian pharma industry, the research findings underscore the notable impact of advantageous factors on volatility. The outcome of the ABCD analysis substantiates the effectiveness of the concepts/ideas related to Factors Driving Share Price Volatility in the Indian Pharmaceutical Sector. Originality: This research introduces a novel application of the ABCD analytical paradigm to investigate factors influencing variations in the pricing dynamics of shares in the Indian pharmaceutical industry. While ABCD analysis is prevalent in diverse areas, this study pioneers a unique exploration within the pharmaceutical domain. By identifying and evaluating the crucial elements influencing share prices, this work contributes to the originality of studies in the field, presenting a distinctive approach to understanding the dynamics of the Indian pharmaceutical market. Type of Paper: Empirical Analysis.

Recent Advances in the Total Synthesis of Spirotryprostatin Alkaloids.

Spirotryprostatin alkaloids, a class of alkaloids with a unique spirocyclic indoledionepiperazine structure, were first extracted from the fermentation broth of Aspergillus fumigatus and have garnered significant attention in the fields of biology and pharmacology. The investigation into the pharmacological potential of this class of alkaloids has unveiled promising applications in drug discovery and development. Notably, certain spirotryprostatin alkaloids have demonstrated remarkable anti-cancer activity, positioning them as potential candidates for anti-tumor drug development. In recent years, organic synthetic chemists have dedicated efforts to devise efficient and viable strategies for the total synthesis of spirotryprostatin alkaloids, aiming to meet the demands within the pharmaceutical domain. The construction of the spiro-C atom within the spirotryprostatin scaffold and the chirality control at the spiro atomic center emerge as pivotal aspects in the synthesis of these compounds. This review categorically delineates the synthesis of spirotryprostatin alkaloids based on the formation mechanism of the spiro-C atom.

Climatic zoning of yerba mate and climate change projections: a CMIP6 approach.

Yerba mate (Ilex paraguariensis) is renowned for its nutritional and pharmaceutical attributes. A staple in South American (SA) culture, it serves as the foundation for several traditional beverages. Significantly, the pharmaceutical domain has secured numerous patents associated with this plant's distinctive properties. This research delves into the climatic influence on yerba mate by leveraging the CMIP6 model projections to assess potential shifts brought about by climate change. Given its economic and socio-cultural significance, comprehending how climate change might sway yerba mate's production and distribution is pivotal. The CMIP6 model offers insights into future conditions, pinpointing areas that are either conducive or adverse for yerba mate cultivation. Our findings will be instrumental in crafting adaptive and mitigative strategies, thereby directing sustainable production planning for yerba mate. The core objective of this study was to highlight zones optimal for Ilex paraguariensis cultivation across its major producers: Brazil, Argentina, Paraguay, and Uruguay, under CMIP6's climate change forecasts. Our investigation encompassed major producing zones spanning the North, Northeast, Midwest, Southeast, and South of Brazil, along with the aforementioned countries. A conducive environment for this crop's growth features air temperatures between 21 to 25°C and a minimum precipitation of 1200mm per cycle. We sourced the current climate data from the WorldClim version 2 platform. Meanwhile, projections for future climatic parameters were derived from WorldClim 2.1, utilizing the IPSL-CM6A-LR model with a refined 30-s spatial resolution. We took into account four distinct socio-economic pathways over varying timelines: 2021-2040, 2041-2060, 2061-2081, and 2081-2100. Geographic information system data aided in the spatial interpolation across Brazil, applying the Kriging technique. The outcomes revealed a majority of the examined areas as non-conducive for yerba mate cultivation, with a scanty 12.25% (1.5 million km2) deemed favorable. Predominantly, these propitious regions lie in southern Brazil and Uruguay, the present-day primary producers of yerba mate. Alarming was the discovery that forthcoming climatic scenarios predominantly forecast detrimental shifts, characterized by escalating average air temperatures and diminishing rainfall. These trends portend a decline in suitable cultivation regions for yerba mate.

Potential of Artificial Intelligence to Accelerate Drug Development for Rare Diseases.

The growth in breadth and depth of artificial intelligence (AI) applications has been fast, running hand in hand with the increasing amount of digital data available. Here, we comment on the application of AI in the field of drug development, with a strong focus on the specific achievements and challenges posed by rare diseases. Data paucity and high costs make drug development for rare diseases especially hard. AI can enable otherwise inaccessible approaches based on the large-scale integration of heterogeneous datasets and knowledge bases, guided by expert biological understanding. Obstacles still exist for the routine use of AI in the usually conservative pharmaceutical domain, which can easily become disillusioned. It is crucial to acknowledge that AI is a powerful, supportive tool that can assist but not replace human expertise in the various phases and aspects of drug discovery and development.

Characteristic and taste test of aromatherapy candle from essential oil of Cananga odorata

Kenanga or ylang-ylang (Cananga odorata) is renowned in the pharmaceutical domain for its essential oil, which boasts therapeutic properties. This study aims to investigate the feasibility of utilizing C. odorata essential oil in the production of aromatherapy candles. It focuses on examining the oil’s characteristics, candle properties, and consumer preferences. The oil extraction employed the enfleurage method, while purification was achieved using a rotary evaporator. We adhered to the SNI 06-3949-1995 standards for analyzing the essential oil and the resultant candle characteristics. Consumer preferences were evaluated through surveys conducted with 30 panelists. The study’s results revealed an oil yield of 48.5%, consistent with the established standards. Optimally, the formula with 25% essential oil concentration demonstrated superior performance in aromatherapy candles, exhibiting a burn time of 8 hours, 30 minutes, and 30 seconds, and a melting point ranging from 51°C to 53°C. This concentration also elicited positive responses from participants in terms of the candles' appearance, aroma (both before and after burning), and therapeutic impact. Notably, the candles with a 25% essential oil concentration were most effective in rapidly delivering therapeutic benefits, predominantly inducing relaxation. The study concludes that ylang-ylang essential oil is highly promising for aromatherapy candle production, with the 25% concentration formula demonstrating optimal results in terms of standard compliance, burn time, and user satisfaction.

DIGITAL TOOLS FOR ENGLISH LANGUAGE LEARNING IN PHARMACY EDUCATION PROGRAMS

In response to the increasing demand for effective English language communication skills in the pharmaceutical domain, this study explores the integration of digital tools within pharmacy education programs. The globalized nature of the pharmaceutical industry necessitates a thorough examination of innovative strategies to enhance language proficiency among students. Utilizing a mixed-methods approach, the research combines quantitative assessments and qualitative analyses to investigate the impact of various digital tools on language learning outcomes, student engagement, and the practical application of acquired skills.The quantitative component involves evaluating language proficiency levels through surveys and assessments, providing a quantitative measure of the effectiveness of digital tools. Concurrently, qualitative analyses, including interviews and focus group discussions, aim to uncover insights into learner experiences, preferences, and the challenges associated with integrating digital tools into language learning curricula within pharmacy education programs. The study's significance lies in its potential to inform educators, curriculum developers, and policymakers about the benefits of leveraging digital tools for English language learning in pharmacy education. By tailoring strategies to enhance communication skills, the research seeks to prepare future pharmacy professionals to navigate the diverse linguistic landscape of the pharmaceutical industry. The findings contribute to the ongoing discourse on innovative teaching methodologies, providing actionable insights for stakeholders committed to fostering language proficiency and effective communication in pharmacy education programs.

CRISPR-Cas9 gene editing in pharmaceuticals : Current applications and future prospects

CRISPR-Cas9 gene editing has emerged as a transformative tool in pharmaceuticals, revolutionizing the understanding and treatment of genetic diseases. This review explores the current landscape and future potential of CRISPRCas9 technology in the pharmaceutical domain. Examining its fundamentals, including the CRISPR-Cas9 system and mechanisms, reveals unparalleled precision in disease modeling, drug discovery and targeted therapies. Challenges like offtarget effects and regulatory complexities are addressed alongside advancements in CRISPR technology beyond Cas9, offering enhanced precision and expanded therapeutic horizons. The significance of CRISPR-Cas9 in shaping the future of pharmaceuticals is evident in its potential applications for rare diseases, complex disorders and its integration with other pharmaceutical approaches, promising groundbreaking therapies. Ethical considerations and regulatory frameworks necessitate responsible innovation while predicting a profound impact on personalized medicine. The future of CRISPR-Cas9 in pharmaceuticals lies in refining delivery methods, addressing ethical concerns and exploring synergies with emerging technologies. This article underscores the ongoing evolution and immense potential of CRISPR-Cas9 in revolutionizing healthcare and therapeutics.

Applications of artificial intelligence and machine learning in pharmaceutical domain: A comprehensive review

Artificial Intelligence (AI) is transforming the medical sector by enhancing diagnosis accuracy, improving treatment outcomes, optimizing healthcare workflows and advancing medical research. Its ability to analyze complex data and assist healthcare professionals has the potential to revolutionize patient care and drive innovation in the field of medicine. Its ability to analyze the amounts of data, identify patterns and make predictions has significantly advanced these fields, leading to improved healthcare outcomes and fostering new avenues for medical research and development. In this review, various applications of AI techniques in healthcare, such as drug design, disease diagnosis, personalized treatment, gene editing and medical education. AI plays a crucial role in disease diagnosis by analyzing medical images, genomic data and patient records, were discussed. AI is transforming medical education by providing personalized and interactive learning experiences. AI algorithms can efficiently analyze large genomic datasets, identifying potential target genes and predicting the outcomes of genetic modifications.

A Curated Graphene Quantum Dot-Porphyrin-Based Photosensitizer for Effective Singlet Oxygen Generation through Energy Transfer.

Porphyrin-based photosensitizers are proven generators of reactive oxygen species (ROS), such as singlet oxygen, and used as anti-cancer therapeutic agents. However, most of these compounds suffer from potential drawbacks due to limited photostability, hydrophobicity, aggregation propensity, and low cellular uptake. Ultrasmall fluorescent graphene quantum dots (GQDs) have emerged as the next-generation carriers for drugs and have gained reputation in the pharmaceutical domain. Considering the various limiting factors in porphyrin-based ROS generation and cellular internalization, here, we have developed a method to generate tetrakis(m-nitrophenyl) porphyrin (TNPP)-GQD exciplexes. This allows resonance energy transfer (RET) from GQDs to TNPP. The calculated overlap integrals for GQD-TNPP and AGQD-TNPP (1.001 × 1018 and 1.257 × 1017 M-1 cm-1 nm4, respectively) assured 95 and 71% energy transfer. The optimum donor-acceptor distances in these couples are 59.82 and 62.65 Å, respectively, which yielded the rate constant of RET as 4.09 and 0.56 ns-1, respectively. The efficient RET helped in subsequent generation of singlet oxygen. The singlet oxygen quantum yields (SOQY) of around 0.435 and 0.464 for GQD-TNPP and AGQD-TNPP, respectively, are comparable to those of different porphyrin derivatives where the SOQY ranges from 0.55 to 0.70 when used with Triton X-100. The data show that non-conjugated amine- and amide-functionalized GQDs (AGQDs) are better candidates in this case because of the special properties of the amine groups. The systems could be excited at 450 nm for FRET, which favors biological usage.

PharmKE: Knowledge Extraction Platform for Pharmaceutical Texts Using Transfer Learning

Even though named entity recognition (NER) has seen tremendous development in recent years, some domain-specific use-cases still require tagging of unique entities, which is not well handled by pre-trained models. Solutions based on enhancing pre-trained models or creating new ones are efficient, but creating reliable labeled training for them to learn on is still challenging. In this paper, we introduce PharmKE, a text analysis platform tailored to the pharmaceutical industry that uses deep learning at several stages to perform an in-depth semantic analysis of relevant publications. The proposed methodology is used to produce reliably labeled datasets leveraging cutting-edge transfer learning, which are later used to train models for specific entity labeling tasks. By building models for the well-known text-processing libraries spaCy and AllenNLP, this technique is used to find Pharmaceutical Organizations and Drugs in texts from the pharmaceutical domain. The PharmKE platform also incorporates the NER findings to resolve co-references of entities and examine the semantic linkages in each phrase, creating a foundation for further text analysis tasks, such as fact extraction and question answering. Additionally, the knowledge graph created by DBpedia Spotlight for a specific pharmaceutical text is expanded using the identified entities. The obtained results with the proposed methodology result in about a 96% F1-score on the NER tasks, which is up to 2% better than those of the fine-tuned BERT and BioBERT models developed using the same dataset. The ultimate benefits of the platform are that pharmaceutical domain specialists may more easily identify the knowledge extracted from the input texts thanks to the platform’s visualization of the model findings. Likewise, the proposed techniques can be integrated into mobile and pervasive systems to give patients more relevant and comprehensive information from scanned medication guides. Similarly, it can provide preliminary insights to patients and even medical personnel on whether a drug from a different vendor is compatible with the patient’s prescription medication.

Combining machine learning with a pharmaceutical technology roadmap to analyze technological innovation opportunities

Technology roadmaps (TRM) with flexible architectural structures and development processes can effectively mitigate innovation dilemmas in pharmaceutical technology innovation opportunity analysis, such as long innovation cycles and inefficient translation. However, pharmaceutical technology innovation has become complicated and increasingly diverse. The current TRMs do not adapt well to this new reality. In response, this study proposes a systematic and specific framework to develop a pharmaceutical technology roadmap. Compared with standardized TRM, this TRM proposes three improvements. The first extension is the designing of the layers. The second extension is the selecting of the data source. The last extension is the processing of data sources. To validate the proposed framework, a case study in the field of hyperuricemia drugs was conducted. Our analysis focuses on the construction of a pharmaceutical TRM framework and a review of technology topics from multiple data sources that can supply quantitative information to explore the current trends. The analyzed results can assist the research and development professionals to predict technological opportunities and support experts to make more reasonable decision-making for a particular pharmaceutical domain.

Unleashing Inflation: The Surge in Poland's Pharmaceutical Domain

Unleashing Inflation: The Surge in Poland's Pharmaceutical Domain

Reuterin 및 이의 구조적 특징과 생물학적 활성에 대한 고찰

Reuterin, one of the low-molecular organic compounds, contains an aldehyde and alcohol group with three carbons. It also possesses a certain degree of complexity in chemical structure because of the presence of aldehyde group. In an aqueous solution of reuterin, monomeric, hydrate, and dimeric forms coexist in equilibrium. Reuterin has diverse biological activities, including antibacterial, anticancer, antiinflammatory, and antifungal activities. Specifically, it displays stronger antibacterial activities and lower toxicities than the existing antimicrobial agents such as glutaraldehyde. Due to the beneficial biological attributes, reuterin can be a potential candidate for novel functional compounds in the food and pharmaceutical industry. Preparation methods for reuterin include biochemical conversion and chemical synthesis. Biochemical conversion approach employs bioconversion using glycerol and Lactobacillus reuteri and chemical synthesis utilizes acrolein or 1,2,4-butanetriol as a starting material. However, despite its exceptional biological activities, the mechanism of action is obscure. Collectively, reuterin has substantial potential as a functional compound in food and pharmaceutical domain.

Dietary and nutraceutical-based therapeutic approaches to combat the pathogenesis of Huntington’s disease

• The structures, bioactivities and mechanisms of phytoconstituents for the management of Huntington’s disease were mentioned. • Clinical trials conducted on some phytoconstituents and vitamins against Huntington’s disease were included. • Other medicinal properties of phytoconstituents in concern were mentioned in the form of figure. • Pathophysiological mechanisms implicated in Huntington’s disease were elaborated. Among several neurodegenerative diseases, Huntington disease has posed a major threat across the world, particularly in the aged population. The disease is caused due to expansion of cytosine-adenine-guanine repeats which further triggers the formation of a mutant huntingtin protein responsible for neuronal death. Numerous pathophysiologic mechanisms have been implicated in Huntington’s disease. Striatum and cortex represent the most affected parts of the brain. Even though a wide range of medicines are available but they possess serious side effects. Therefore, the emergence of nutraceuticals derived from natural sources has received great attention in the pharmaceutical domain. Nutraceuticals are health-promoting supplements and enhance immunity in human beings. Currently, oxidative stress is the leading factor for chronic diseases that occur due to low intake of antioxidants. Herbal nutraceuticals are said to be enriched with a massive number of antioxidants. Therefore, this article throws light on various herbal nutraceuticals and their noteworthy effects on Huntington’s disease.

The Development of Healthcare Jobs in the COVID-Pandemic-A New Economic Market.

BackgroundThe COVID-19 pandemic commenced in China and has caused the death of numerous people globally. Despite the adverse effects, the outbreak has created room for job opportunities in healthcare, particularly the pharmaceutical domain. The main goal of this study is to examine how the current pandemic has triggered job creation in the healthcare domain and created a new economic market.MethodsThe study used the Preferred Reporting Items for Systematic and Meta-analyses for Scoping Review (PRISMA-ScR) to structure the manuscript and the subheadings to use. The source used to gather data is the PubMed database.ResultsThe study exclusively included fourteen articles, five of which focused on the pharmaceutical sector, three focused on vaccine sales, three on vaccination centers, and three on testing centers.ConclusionThe COVID-19 pandemic has created job opportunities in the healthcare sector. Most jobs are in the pharmaceutical sector, vaccination, and testing centers. However, more comprehensive research on the topic is necessary to gather conclusive outcomes on whether these jobs will be relevant after the pandemic.