Comprehensive applications of the artificial intelligence technology in new drug research and development.

Purpose: Target-based strategy is a prevalent means of drug research and development (R&D), since targets provide effector molecules of drug action and offer the foundation of pharmacological investigation. Recently, the artificial intelligence (AI) technology has been utilized in various stages of drug R&D, where AI-assisted experimental methods show higher efficiency than sole experimental ones. It is a critical need to give a comprehensive review of AI applications in drug R &D for biopharmaceutical field. Methods: Relevant literatures about AI-assisted drug R&D were collected from the public databases (Including Google Scholar, Web of Science, PubMed, IEEE Xplore Digital Library, Springer, and ScienceDirect) through a keyword searching strategy with the following terms [("Artificial Intelligence" OR "Knowledge Graph" OR "Machine Learning") AND ("Drug Target Identification" OR "New Drug Development")]. Results: In this review, we first introduced common strategies and novel trends of drug R&D, followed by characteristic description of AI algorithms widely used in drug R&D. Subsequently, we depicted detailed applications of AI algorithms in target identification, lead compound identification and optimization, drug repurposing, and drug analytical platform construction. Finally, we discussed the challenges and prospects of AI-assisted methods for drug discovery. Conclusion: Collectively, this review provides comprehensive overview of AI applications in drug R&D and presents future perspectives for biopharmaceutical field, which may promote the development of drug industry.

Discussion of the classification of pediatric drug clinical trials in children's hospitals in China.

Objectives: This study aimed to gain insights into pediatric clinical trials conducted in children's hospitals in China and provide valuable references for the development of children's hospitals and the research and development of pediatric drugs. Methods: A comprehensive search was performed on the Chinese Clinical Trial Registry (Chi CTR) and ChinaDrugTrials.org.cn to collect information on all clinical trials involving subjects under 18 years, including those conducted in children's hospitals. The retrieval period was extended until 31 December 2022. Results: A total of 459 pediatric clinical trials were collected, comprising 299 from Chi CTR and 160 from the Drug Clinical Trial Registration and Information Publicity Platform (Information Platform). Post-marketing drug studies and phase III clinical trials accounted for the majority of research stages. These trials covered a wide range of diseases/systems, with a particular focus on respiratory system disorders, tumors, endocrine disorders, and nutritional or metabolic diseases. Chemical drugs constituted the most extensively studied category, while traditional Chinese medicine/natural drugs received comparatively less attention. Clinical trial activities were primarily geographically focused on the eastern coastal regions of China, with multicenter trials being the most predominant. Ethics committee approval was obtained for 427 studies. Conclusion: The pediatric clinical trials conducted by children's hospitals in China have shown an overall upward trend; however, there is limited research focusing on traditional Chinese medicine, along with significant regional and institutional imbalances. Furthermore, there is still room for improvement regarding ethical review processes. It is recommended that children's hospitals enhance their scientific research capabilities while optimizing resource allocation to meet medical service demands effectively. Additionally, fostering more research-focused children's hospitals will contribute to the high-quality development of children's health in China.

(3D) Bioprinting-Next Dimension of the Pharmaceutical Sector.

To create a review of the published scientific literature on the benefits and potential perspectives of the use of 3D bio-nitrification in the field of pharmaceutics. This work was performed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines for reporting meta-analyses and systematic reviews. The scientific databases PubMed, Scopus, Google Scholar, and ScienceDirect were used to search and extract data using the following keywords: 3D bioprinting, drug research and development, personalized medicine, pharmaceutical companies, clinical trials, drug testing. The data points to several aspects of the application of bioprinting in pharmaceutics were reviewed. The main applications of bioprinting are in the development of new drug molecules as well as in the preparation of personalized drugs, but the greatest benefits are in terms of drug screening and testing. Growth in the field of 3D printing has facilitated pharmaceutical applications, enabling the development of personalized drug screening and drug delivery systems for individual patients. Bioprinting presents the opportunity to print drugs on demand according to the individual needs of the patient, making the shape, structure, and dosage suitable for each of the patient's physical conditions, i.e., print specific drugs for controlled release rates; print porous tablets to reduce swallowing difficulties; make transdermal microneedle patches to reduce patient pain; and so on. On the other hand, bioprinting can precisely control the distribution of cells and biomaterials to build organoids, or an Organ-on-a-Chip, for the testing of drugs on printed organs mimicking specified disease characteristics instead of animal testing and clinical trials. The development of bioprinting has the potential to offer customized drug screening platforms and drug delivery systems meeting a range of individualized needs, as well as prospects at different stages of drug development and patient therapy. The role of bioprinting in preclinical and clinical testing of drugs is also of significant importance in terms of shortening the time to launch a medicinal product on the market.

Laboratory based correlative cryo-soft X-ray tomography and cryo-fluorescence microscopy.

Cryo-soft X-ray tomography is the unique technology that can image whole intact cells in 3D under normal and pathological conditions without labelling or fixation, at high throughput and spatial resolution. The sample preparation is relatively straightforward; requiring just fast freezing of the specimen before transfer to the microscope for imaging. It is also possible to image chemically fixed samples where necessary. The technique can be correlated with cryo fluorescence microscopy to localize fluorescent proteins to organelles within the whole cell volume. Cryo-correlated light and soft X-ray tomography is particularly useful for the study of gross morphological changes brought about by disease or drugs. For example, viral fluorescent tags can be co-localized to sites of viral replication in the soft X-ray volume. In general this approach is extremely useful in the study of complex 3D organelle structure, nanoparticle uptake or in the detection of rare events in the context of whole cell structure. The main challenge of soft X-ray tomography is that the soft X-ray illumination required for imaging has heretofore only been available at a small number of synchrotron labs worldwide. Recently, a compact device with a footprint small enough to fit in a standard laboratory setting has been deployed ("the SXT-100") and is routinely imaging cryo prepared samples addressing a variety of disease and drug research applications. The SXT-100 facilitates greater access to this powerful technique and greatly increases the scope and throughput of potential research projects. Furthermore, the availability of cryo-soft X-ray tomography in the laboratory will accelerate the development of novel correlative and multimodal workflows by integration with light and electron microscope based approaches. It also allows for co-location of this powerful imaging modality at BSL3 labs or other facilities where safety or intellectual property considerations are paramount. Here we describe the compact SXT-100 microscope along with its novel integrated cryo-fluorescence imaging capability.

Computational model for drug research.

This special issue focuses on computational model for drug research regarding drug bioactivity prediction, drug-related interaction prediction, modelling for immunotherapy and modelling for treatment of a specific disease, as conveyed by the following six research and four review articles. Notably, these 10 papers described a wide variety of in-depth drug research from the computational perspective and may represent a snapshot of the wide research landscape.

Combating COVID-19 Crisis using Artificial Intelligence (AI) Based Approach: Systematic Review.

BACKGROUND: SARS-CoV-2, the unique coronavirus that causes COVID-19, has wreaked damage around the globe, with victims displaying a wide range of difficulties that have encouraged medical professionals to look for innovative technical solutions and therapeutic approaches. Artificial intelligence-based methods have contributed a significant part in tackling complicated issues, and some institutions have been quick to embrace and tailor these solutions in response to the COVID-19 pandemic's obstacles. Here, in this review article, we have covered a few DL techniques for COVID-19 detection and diagnosis, as well as ML techniques for COVID-19 identification, severity classification, vaccine and drug development, mortality rate prediction, contact tracing, risk assessment, and public distancing. This review illustrates the overall impact of AI/ML tools on tackling and managing the outbreak. PURPOSE: The focus of this research was to undertake a thorough evaluation of the literature on the part of Artificial Intelligence (AI) as a complete and efficient solution in the battle against the COVID-19 epidemic in the domains of detection and diagnostics of disease, mortality prediction and vaccine as well as drug development. METHODS: A comprehensive exploration of PubMed, Web of Science, and Science Direct was conducted using PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) regulations to find all possibly suitable papers conducted and made publicly available between December 1, 2019, and August 2023. COVID-19, along with AI-specific words, was used to create the query syntax. RESULTS: During the period covered by the search strategy, 961 articles were published and released online. Out of these, a total of 135 papers were chosen for additional investigation. Mortality rate prediction, early detection and diagnosis, vaccine as well as drug development, and lastly, incorporation of AI for supervising and controlling the COVID-19 pandemic were the four main topics focused entirely on AI applications used to tackle the COVID-19 crisis. Out of 135, 60 research papers focused on the detection and diagnosis of the COVID-19 pandemic. Next, 19 of the 135 studies applied a machine-learning approach for mortality rate prediction. Another 22 research publications emphasized the vaccine as well as drug development. Finally, the remaining studies were concentrated on controlling the COVID-19 pandemic by applying AI AI-based approach to it. CONCLUSION: We compiled papers from the available COVID-19 literature that used AI-based methodologies to impart insights into various COVID-19 topics in this comprehensive study. Our results suggest crucial characteristics, data types, and COVID-19 tools that can aid in medical and translational research facilitation.

Challenges in distinguishing functional proteins from polyproteins in databases: implications for drug discovery.

This opinion article addresses a major issue in molecular biology and drug discovery by highlighting the complications that arise from combining polyproteins and their functional products within the same database entry. This problem, exemplified by the discovery of novel inhibitors for the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) main protease, has an influence on our ability to retrieve precise data and hinders the development of targeted therapies. It also emphasizes the need for improved database practices and underscores their significance in advancing scientific research. Furthermore, it emphasizes the need of learning from the SARS-CoV-2 pandemic in order to improve global preparedness for future health crises.

Drug Repurposing in the Chemotherapy of Infectious Diseases.

Repurposing is a universal mechanism for innovation, from the evolution of feathers to the invention of Velcro tape. Repurposing is particularly attractive for drug development, given that it costs more than a billion dollars and takes longer than ten years to make a new drug from scratch. The COVID-19 pandemic has triggered a large number of drug repurposing activities. At the same time, it has highlighted potential pitfalls, in particular when concessions are made to the target product profile. Here, we discuss the pros and cons of drug repurposing for infectious diseases and analyze different ways of repurposing. We distinguish between opportunistic and rational approaches, i.e., just saving time and money by screening compounds that are already approved versus repurposing based on a particular target that is common to different pathogens. The latter can be further distinguished into divergent and convergent: points of attack that are divergent share common ancestry (e.g., prokaryotic targets in the apicoplast of malaria parasites), whereas those that are convergent arise from a shared lifestyle (e.g., the susceptibility of bacteria, parasites, and tumor cells to antifolates due to their high rate of DNA synthesis). We illustrate how such different scenarios can be capitalized on by using examples of drugs that have been repurposed to, from, or within the field of anti-infective chemotherapy.

[Current situation and development trend of digital traditional Chinese medicine pharmacy].

The 21st century is a highly information-driven era, and traditional Chinese medicine(TCM) pharmacy is also moving towards digitization and informatization. New technologies such as artificial intelligence and big data with information technology as the core are being integrated into various aspects of drug research, manufacturing, evaluation, and application, promoting interaction between these stages and improving the quality and efficiency of TCM preparations. This, in turn, provides better healthcare services to the general population. The deep integration of emerging technologies such as artificial intelligence, big data, and cloud computing with the TCM pharmaceutical industry will innovate TCM pharmaceutical technology, accelerate the research and industrialization process of TCM pharmacy, provide cutting-edge technological support to the global scientific community, boost the efficiency of the TCM industry, and promote economic and social development. Drawing from recent developments in TCM pharmacy in China, this paper discussed the current research status and future trends in digital TCM pharmacy, aiming to provide a reference for future research in this field.

Synthesis and Evaluation of Novel Substituted N-Aryl 1,4-Dihydropyridines as Antituberculostatic Agents.

BACKGROUND: Tuberculosis has been the main cause of mortality of infectious diseases worldwide, with strongly limited therapeutic options. With increasing resistance and missing suitable drugs in those cases, there is a strong need for novel antituberculostatic drugs. We developed novel N-aryl 1,4-dihydropyridines with various substitution patterns to evaluate them as antituberculostatic agents. METHODS: 1,4-Dihydropyridine derivatives were synthesized and purified by column chromatography or recrystallization. The mycobacterial growth inhibition was determined in a fluorescent mycobacterial growth assay. RESULTS: The compounds were prepared in a simple one-pot reaction under acidic conditions with structurally varied components. The substituent effects on the determined mycobacterial growth inhibitory properties are discussed. CONCLUSION: Lipophilic diester substituted derivatives show promising activities that were additionally affected by the aromatic substituent functions. Thus, we identified compounds with activities almost reaching that of the used antimycobacterial drug as control.

Key Contributions by the Swiss Tropical and Public Health Institute Towards New and Better Drugs for Tropical Diseases.

Thanks to its expertise in clinical research, epidemiology, infectious diseases, microbiology, parasitology, public health, translational research and tropical medicine, coupled with deeply rooted partnerships with institutions in low- and middle-income countries (LMICs), the Swiss Tropical and Public Health Institute (Swiss TPH) has been a key contributor in many drug research and development consortia involving academia, pharma and product development partnerships. Our know-how of the maintenance of parasites and their life-cycles in the laboratory, plus our strong ties to research centres and disease control programme managers in LMICs with access to field sites and laboratories, have enabled systems for drug efficacy testing in vitro and in vivo, clinical research, and modelling to support the experimental approaches. Thus, Swiss TPH has made fundamental contributions towards the development of new drugs - and the better use of old drugs - for neglected tropical diseases and infectious diseases of poverty, such as Buruli ulcer, Chagas disease, food-borne trematodiasis (e.g. clonorchiasis, fascioliasis and opisthorchiasis), human African trypanosomiasis, leishmaniasis, malaria, schistosomiasis, soil-transmitted helminthiasis and tuberculosis. In this article, we show case the success stories of molecules to which Swiss TPH has made a substantial contribution regarding their use as anti-infective compounds with the ultimate aim to improve people's health and well-being.

Psychedelic Drugs or Hallucinogens: Exploring Their Medicinal Potential.

Serotonergic hallucinogens also referred to as psychedelics, are psychoactive substances that profoundly alter perception, mood, and cognitive processes. These substances, historically intertwined with religious and cultural rituals, offer profound effects that extend beyond mere hallucinations to profoundly altered states of consciousness. Notable compounds like Lysergic acid diethylamide (LSD) and psilocybin, potent in their action on serotonin receptors, play pivotal roles in influencing brain functions. Despite societal misconceptions that have overshadowed their potential, contemporary research increasingly recognizes their therapeutic value. These substances have shown promise in treating neuropsychiatric disorders such as depression, post-traumatic stress disorder (PTSD), and anxiety, leveraging their influence on neuroplasticity. Furthermore, they exhibit therapeutic potential across various conditions, challenging conventional treatment methodologies. Compared to substances like alcohol, traditional psychedelics like LSD and psilocybin emerge as relatively safer substances. The modern revival of scientific interest in psychedelics necessitates a renewed perspective, viewing them not just as recreational entities but as potent therapeutic tools. Harnessing their actual value mandates rigorous scientific investigations and a receptive societal discourse. A re-evaluation of their classification following international criteria is necessary in light of this increasing understanding. Hallucinogens or psychedelic drugs, if used correctly, can potentially be potential treatments for mental illness, signalling a paradigm shift from traditional techniques. To dispel myths and use their therapeutic advantages, embracing this potential necessitates thorough scientific investigation together with an open societal discourse.

Novel pyrazolothienopyridinones as potential GABAA receptor modulators.

The synthesis of novel pyrazolothienopyridinone derivatives as potential GABAA receptor modulators was performed and is herein described. A crucial step of the synthesis involving handling unstable aminothiophenes was managed via two different synthetic strategies delivering a set of 8 target compounds. Supplementary Information: The online version contains supplementary material available at 10.1007/s00706-023-03063-6.

Metabolomics in drug research and development: The recent advances in technologies and applications.

Emerging evidence has demonstrated the vital role of metabolism in various diseases or disorders. Metabolomics provides a comprehensive understanding of metabolism in biological systems. With advanced analytical techniques, metabolomics exhibits unprecedented significant value in basic drug research, including understanding disease mechanisms, identifying drug targets, and elucidating the mode of action of drugs. More importantly, metabolomics greatly accelerates the drug development process by predicting pharmacokinetics, pharmacodynamics, and drug response. In addition, metabolomics facilitates the exploration of drug repurposing and drug-drug interactions, as well as the development of personalized treatment strategies. Here, we briefly review the recent advances in technologies in metabolomics and update our knowledge of the applications of metabolomics in drug research and development.

Thiadiazole and Thiazole Derivatives as Potential Antimicrobial Agents.

BACKGROUND: This review summarizes data on heterocyclic systems with thiadiazole and thiazole fragments in molecules as promising antimicrobial agents. INTRODUCTION: Thiadiazole and thiazole backbones are the most favored and well-known heterocycles, a common and essential feature of various drugs. These scaffolds occupy a central position and are the main structural components of numerous drugs with a wide spectrum of action. These include antimicrobial, antituberculous, anti-inflammatory, analgesic, antiepileptic, antiviral, and anticancer agents. METHOD: The research is based on bibliosemantic and analytical methods using bibliographic and abstract databases, as well as databases of chemical compounds. RESULT: This review reports on thiadiazole and thiazole derivatives, which have important pharmacological properties. We are reviewing the structural modifications of various thiadiazole and thiazole derivatives, more specifically, the antimicrobial activity reported over the last years, as we have taken this as our main research area. 80 compounds were illustrated, and various derivatives containing hydrazone bridged thiazole and pyrrole rings, 2-pyridine and 4-pyridine substituted thiazole derivatives, compounds containing di-, tri- and tetrathiazole moieties, Spiro-substituted 4-thiazolidinone-imidazoline-pyridines were analyzed. Derivatives of 5-heteroarylidene-2,4-thiazolidinediones, fluoroquinolone-thiadiazole hybrids, and others. CONCLUSION: 1,3,4-thiadiazoles and thiazoles are valuable resource for researchers engaged in rational drug design and development in this area.

ETCM v2.0: An update with comprehensive resource and rich annotations for traditional Chinese medicine.

Existing traditional Chinese medicine (TCM)-related databases are still insufficient in data standardization, integrity and precision, and need to be updated urgently. Herein, an Encyclopedia of Traditional Chinese Medicine version 2.0 (ETCM v2.0, http://www.tcmip.cn/ETCM2/front/#/) was constructed as the latest curated database hosting 48,442 TCM formulas recorded by ancient Chinese medical books, 9872 Chinese patent drugs, 2079 Chinese medicinal materials and 38,298 ingredients. To facilitate the mechanistic research and new drug discovery, we improved the target identification method based on a two-dimensional ligand similarity search module, which provides the confirmed and/or potential targets of each ingredient, as well as their binding activities. Importantly, five TCM formulas/Chinese patent drugs/herbs/ingredients with the highest Jaccard similarity scores to the submitted drugs are offered in ETCM v2.0, which may be of significance to identify prescriptions/herbs/ingredients with similar clinical efficacy, to summarize the rules of prescription use, and to find alternative drugs for endangered Chinese medicinal materials. Moreover, ETCM v2.0 provides an enhanced JavaScript-based network visualization tool for creating, modifying and exploring multi-scale biological networks. ETCM v2.0 may be a major data warehouse for the quality marker identification of TCMs, the TCM-derived drug discovery and repurposing, and the pharmacological mechanism investigation of TCMs against various human diseases.

Research Progress on Small-molecule Inhibitors of Protein Arginine Methyltransferase 5 (PRMT5) for Treating Cancer.

BACKGROUND: The protein arginine methyltransferase family includes nine members, with PRMT5 being the major type II arginine methyltransferase. PRMT5 is upregulated in a variety of tumors and promotes tumorigenesis and tumor cell proliferation and metastasis, making it a potential tumor therapy target. Recently, PRMT5 inhibitor research and development have become hotspots in the tumor therapy field. METHODS: We classified and summarized PRMT5 inhibitors according to different binding mechanisms. We mainly analyzed the structure, biological activity, and binding interactions of PRMT5 inhibitors with the PRMT5 enzyme. RESULTS: At present, many PRMT5 inhibitors with various mechanisms of action have been reported, including substrate-competitive inhibitors, SAM-competitive inhibitors, dual substrate-/SAMcompetitive inhibitors, allosteric inhibitors, PRMT5 degraders, MTA-cooperative PRMT5 inhibitors and PPI inhibitors. CONCLUSION: These inhibitors are beneficial to the treatment of tumors. Some drugs are being used in clinical trials. PRMT5 inhibitors have broad application prospects in tumor therapy.

Comparison and summary of in silico prediction tools for CYP450-mediated drug metabolism.

The cytochrome P450 (CYP450) enzyme system is responsible for the metabolism of more than two-thirds of xenobiotics. This review summarizes reports of a series of in silico tools for CYP450 enzyme-drug interaction predictions, including the prediction of sites of metabolism (SOM) of a drug and the identification of inhibitor/substrates for CYP subtypes. We also evaluated four prediction tools to identify CYP inhibitors utilizing 52 of the most frequently prescribed drugs. ADMET Predictor and CYPlebrity demonstrated the best performance. We hope that this review provides guidance for choosing appropriate enzyme prediction tools from a variety of in silico platforms to meet individual needs. Such predictions are useful for medicinal chemists to prioritize their designed compounds for further drug discovery.

[Application and development of systems biology in computer-aided drug design].

With the advances in medicine, people have deeply understood the complex pathogenesis of diseases. Revealing the mechanism of action and therapeutic effect of drugs from an overall perspective has become the top priority of drug design. However, the traditional drug design methods cannot meet the current needs. In recent years, with the rapid development of systems biology, a variety of new technologies including metabolomics, genomics, and proteomics have been used in drug research and development. As a bridge between traditional pharmaceutical theory and modern science, computer-aided drug design(CADD) can shorten the drug development cycle and improve the success rate of drug design. The application of systems biology and CADD provides a methodological basis and direction for revealing the mechanism and action of drugs from an overall perspective. This paper introduces the research and application of systems biology in CADD from different perspectives and proposes the development direction, providing reference for promoting the application.