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Over the past two years, scientists' efforts to develop vaccines and antiviral treatments against the COVID-19 pandemic have failed due to the lack of a proven therapy and the inefficacy of currently available vaccines against the virus' mutant forms. Therefore, the COVID-19 pandemic has forced scientists to develop highly reliable diagnostic and therapeutic procedures to quickly prevent the infection's spread. Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/CRISPRassociated protein (Cas) system is an RNA-directed adaptive immune system used as a gene-editing technology. Recent CRISPR application studies have shown that CRISPR effectors may limit the replication of double-stranded DNA or single-stranded RNA (ssRNA) viruses in mammalians. Because SARS-COV-2 contains a single-stranded, positive-sense RNA genome and structure, CRISPR-Cas systems are suitable for therapeutic use. Similarly, many clinical studies have investigated the CRISPRCas systems' potential for diagnosing SARS-COV-2 and have proven their effectiveness. CRISPR-Cas systems' success in quickly diagnosing SARS-COV-2 serves as a model for applying CRISPR-Cas systems to treat the Covid-19 pandemic. This review aims to investigate the uses of CRISPR-Cas-based gene-editing systems (CRISPR-Cas9, CRISPR-Cas12, CRISPR-Cas13) when treating patients during the COVID-19 pandemic, to analyze related articles, and to examine this novel technology's limits and possibilities. [ABSTRACT FROM AUTHOR]

Background: More sensitive and less burdensome efficacy end points are urgently needed to improve the effectiveness of clinical drug development for Alzheimer disease (AD). Although conventional end points lack sensitivity, digital technologies hold promise for amplifying the detection of treatment signals and capturing cognitive anomalies at earlier disease stages. Using digital technologies and combining several test modalities allow for the collection of richer information about cognitive and functional status, which is not ascertainable via conventional paper-and-pencil tests. Objective: This study aimed to assess the psychometric properties, operational feasibility, and patient acceptance of 10 promising technologies that are to be used as efficacy end points to measure cognition in future clinical drug trials. Methods: The Method for Evaluating Digital Endpoints in Alzheimer Disease study is an exploratory, cross-sectional, noninterventional study that will evaluate 10 digital technologies' ability to accurately classify participants into 4 cohorts according to the severity of cognitive impairment and dementia. Moreover, this study will assess the psychometric properties of each of the tested digital technologies, including the acceptable range to assess ceiling and floor effects, concurrent validity to correlate digital outcome measures to traditional paper-and-pencil tests in AD, reliability to compare test and retest, and responsiveness to evaluate the sensitivity to change in a mild cognitive challenge model. This study included 50 eligible male and female participants (aged between 60 and 80 years), of whom 13 (26%) were amyloid-negative, cognitively healthy participants (controls); 12 (24%) were amyloid-positive, cognitively healthy participants (presymptomatic); 13 (26%) had mild cognitive impairment (predementia); and 12 (24%) had mild AD (mild dementia). This study involved 4 in-clinic visits. During the initial visit, all participants completed all conventional paper-and-pencil assessments. During the following 3 visits, the participants underwent a series of novel digital assessments. Results: Participant recruitment and data collection began in June 2020 and continued until June 2021. Hence, the data collection occurred during the COVID-19 pandemic (SARS-CoV-2 virus pandemic). Data were successfully collected from all digital technologies to evaluate statistical and operational performance and patient acceptance. This paper reports the baseline demographics and characteristics of the population studied as well as the study's progress during the pandemic. Conclusions: This study was designed to generate feasibility insights and validation data to help advance novel digital technologies in clinical drug development. The learnings from this study will help guide future methods for assessing novel digital technologies and inform clinical drug trials in early AD, aiming to enhance clinical end point strategies with digital technologies. International Registered Report Identifier (IRRID): DERR1-10.2196/35442 [ABSTRACT FROM AUTHOR]

Simple Summary: Accurate identification of potential targets for drugs to interact with can accelerate drug development. The identification of drug–target interactions can provide insights into hidden drug efficacy. This paper presents a prediction model based on feature similarity fusion that can identify crucial features of drugs and targets to help predict drug–target interactions. The key to drug discovery is the identification of a target and a corresponding drug compound. Effective identification of drug–target interactions facilitates the development of drug discovery. In this paper, drug similarity and target similarity are considered, and graphical representations are used to extract internal structural information and intermolecular interaction information about drugs and targets. First, drug similarity and target similarity are fused using the similarity network fusion (SNF) method. Then, the graph isomorphic network (GIN) is used to extract the features with information about the internal structure of drug molecules. For target proteins, feature extraction is carried out using TextCNN to efficiently capture the features of target protein sequences. Three different divisions (CVD, CVP, CVT) are used on the standard dataset, and experiments are carried out separately to validate the performance of the model for drug–target interaction prediction. The experimental results show that our method achieves better results on AUC and AUPR. The docking results also show the superiority of the proposed model in predicting drug–target interactions. [ABSTRACT FROM AUTHOR]

Acquired immunodeficiency syndrome (AIDS) caused by human immunodeficiency virus (HIV) infection is a serious public problem threatening global health. At present, although "cocktail therapy" has achieved significant clinical effects, HIV still cannot be completely eradicated. Furthermore, long-term antiviral treatment has caused problems such as toxic side effects, the emergence of drug-resistant viruses, and poor patient compliance. Therefore, it is highly necessary to continue to search for high-efficient, low-toxic anti-HIV drugs with new mechanisms. Natural products have the merits of diverse scaffolds, biological activities, and low toxicity that are deemed the important sources of drug discovery. Thus, finding lead compounds from natural products followed by structure optimization has become one of the important ways of modern drug discovery. Nowadays, many natural products have been found, such as berberine, gnidimacrin, betulone, and kuwanon-L, which exert effective anti-HIV activity through immune regulation, inhibition of related functional enzymes in HIV replication, and anti-oxidation. This paper reviewed these natural products, their related chemical structure optimization, and their anti-HIV mechanisms. [ABSTRACT FROM AUTHOR]

Over the past decade there have been significant developments in the field of Cystic Fibrosis Transmembrane Regulator modulator drugs. Following treatment in patients with cystic fibrosis with common gating mutations using the potentiator drug ivacaftor, successive development of corrector drugs used in combination has led to highly effective modulator therapy being available to more than 85% of the cystic fibrosis population over 12 years of age in the form of elexacaftor/tezacaftor/ivacaftor. In this article, we review the evidence from clinical trials and mounting real-world observational and registry data that demonstrates the impact highly effective modulators have on both pulmonary and extra-pulmonary manifestations of cystic fibrosis. As clinical trials progress to younger patient groups, we discuss the challenges to demonstrating drug efficacy in early life, and also consider practicalities of drug development in an ever-shrinking modulator-naïve population. Drug–drug interactions are an important consideration in people with cystic fibrosis, where polypharmacy is commonplace, but also as the modulated population look to remain healthier for longer, we identify trials that aim to address treatment burden too. Inequity of care, through drug cost or ineligibility for modulators by genotype, is widening without apparent strategies to address this; however, we present evidence of hopeful early-stage drug development for non-modulatable genes and summarise the current state of gene-therapy development. [ABSTRACT FROM AUTHOR]

In biomarker enrichment study designs that start with an all-comer population, simultaneous evaluation of the entire and the marker-selected populations can be more desirable than pre-specifying the testing order, when the degree of marker predictiveness is uncertain. While there has been substantial research on this approach, our goal is to provide a complete overview and guidance in all aspects of this approach, including the interim analysis potentially using different endpoints, combination tests with associated multiplicity control, and the final treatment effect estimation. Regulatory/operational aspects and actual cases demonstrating the potential advantage of this approach are also described. [ABSTRACT FROM AUTHOR]

Quinoline is a preferred scaffold that emerges as a prominent assembly motif for the creation of novel pharmacological molecules among heterocyclic compounds. An important family of chemicals includes quinoline and its derivatives that have been studied for various biological activities. Due to its wide range of bioactivity, quinoline, which is made up of benzene fused with N-heterocyclic pyridine, has drawn a lot of interest as a key template in drug creation. In order to demonstrate the quinoline motifs' significant efficacies for upcoming drug development, this review intends to provide the most current developments in chemistry, their medicinal potential, and their pharmacological applications. As a result, these compounds have been produced by several scientific groups as intentional structures, and their biological functions have been examined. The current study offers succinct information on quinoline's natural sources, as well as details on newly marketed medications that include quinoline. The pharmacological effects of quinoline derivatives, such as their anticonvulsant, antibacterial, antiviral, anti-protozoal, antimalarial, anticancer, antiinflammatory, and anthelmintic properties, are also discussed in this study. [ABSTRACT FROM AUTHOR]

The destiny look at entails delivering drug/bioactive based totally on a unmarried nanoplatform poly lactic-co-glycolic acid (PLGA) for superior efficacy, synergistic effect, and reduced toxicity. Diverse NP formulations were allotted in drug development in an try to growth performance, protection and tolerability of integrated tablets. In this context, NP formulations that increase solubility, control release, and/or affect the in vivo disposition of drugs, had been evolved to enhance the pharmacokinetic and pharmacodynamic homes of encapsulated drugs. The nanoparticles have been formulated further to then characterized for percent yield, encapsulation performance, surface morphology, particle dimension, drug distribution studies, drug polymer interaction research and in vitro drug launch profiles. The goal of this effort is to put together and compare Poly (D, L-Lactideco-glycolide) (PLGA) Nanoparticles (NPs) of Castalin, an anticancer agent loaded by solvent displacement method by stabilizer (poly vinyl alcohol). The set NPs were characterized by FT-IR, DSC, drug loading, entrapment efficiency, particle size, and surface morphology by Atomic force microscopy (AFM), X-ray diffraction and in-vitro studies. FT-IR and DSC research indicated that there was no interplay between the drug and polymer. The morphological studies executed by using AFM showed uniform and spherical fashioned discrete particles without aggregation and easy in surface morphology with a nano length varies of 144 nm. The enormous quantity of news on PLGA NPs used as drug delivery systems during cancer management effects to see the potential of PLGA NPs used as drug delivery systems in the course of most cancer therapeutics and encourages similarly translational research. [ABSTRACT FROM AUTHOR]

Schizophrenia is a complex disorder of varied etiology, manifesting symptoms that can differ between patients and change throughout an individual's lifespan. Antipsychotic drugs have evolved through first (e.g., haloperidol), second (olanzapine and clozapine) and a possible third (aripiprazole) generation of drugs in an attempt to improve efficacy and tolerability, with minimal side-effects. Despite robust scientific efforts over the past 70 years, there remains a need to develop drugs with greater efficacy, particularly in relation to the negative and cognitive symptoms of schizophrenia, addressing treatment resistance, with a lower side-effects profile compared to existing antipsychotic drugs. Identifying and investigating novel therapeutic targets remains an important component of future antipsychotic drug discovery; however, mounting evidence demonstrates neurobiological, neuroanatomical and functional heterogeneity in cohorts of individuals with schizophrenia. This presents an opportunity to refresh the approach to drug trials to a more targeted strategy. By increasing understanding of the basic science and pharmacological mechanisms underlying the potential antipsychotic efficacy of novel therapeutics prior to clinical trials, new drugs may be appropriately directed to a target population of schizophrenia subjects based on the drug mechanisms and correlating biological sub-groupings of patient characteristics. Improving the lives of sub-populations of people with schizophrenia that share common biological characteristics and are likely to be responsive to a particular compound may be more achievable than aiming to treat the complexities of schizophrenia as a homogenous disorder. This approach to clinical trials in antipsychotic research is discussed in the present review. [ABSTRACT FROM AUTHOR]

The morbidity and mortality of hepatic fibrosis caused by various etiologies are high worldwide, and the trend is increasing annually. At present, there is no effective method to cure hepatic fibrosis except liver transplantation, and its serious complications threaten the health of patients and cause serious medical burdens. Additionally, there is no specific drug for the treatment of hepatic fibrosis, and many drugs with anti-hepatic fibrosis effects are in the research and development stage. Recently, remarkable progress has been made in the research and development of anti-hepatic fibrosis drugs targeting different targets. We searched websites such as PubMed, ScienceDirect, and Home-ClinicalTrials.gov and found approximately 120 drugs with anti-fibrosis properties, some of which are in phase Ⅱ or Ⅲ clinical trials. Additionally, although these drugs are effective against hepatic fibrosis in animal models, most clinical trials have shown poor results, mainly because animal models do not capture the complexity of human hepatic fibrosis. Besides, the effect of natural products on hepatic fibrosis has not been widely recognized at home and abroad. Furthermore, drugs targeting a single anti-hepatic fibrosis target are prone to adverse reactions. Therefore, currently, the treatment of hepatic fibrosis requires a combination of drugs that target multiple targets. Ten new drugs with potential for development against hepatic fibrosis were selected and highlighted in this mini-review, which provides a reference for clinical drug use. [ABSTRACT FROM AUTHOR]

Drug repurposing has broad importance in planetary health for therapeutics innovation in infectious diseases as well as common or rare chronic human diseases. Drug repurposing has also proved important to develop interventions against the COVID-19 pandemic. We propose a new approach for drug repurposing involving two-stage prediction and machine learning. First, diseases are clustered by gene expression on the premise that similar patterns of altered gene expression imply critical pathways shared in different disease conditions. Next, drug efficacy is assessed by the reversibility of abnormal gene expression, and results are clustered to identify repurposing targets. To cluster similar diseases, gene expression data from 262 cases of 31 diseases and 268 controls were analyzed by Uniform Manifold Approximation and Projection for Dimension Reduction followed by k-means to optimize the number of clusters. For evaluation, we examined disease-specific gene expression data for inclusion, body myositis, polymyositis, and dermatomyositis (DM), and used LINCS L1000 characteristic direction signatures search engine (L1000CDS2) to obtain lists of small-molecule compounds that reversed the expression patterns of these specifically altered genes as candidates for drug repurposing. Finally, the functions of affected genes were analyzed by Gene Set Enrichment Analysis to examine consistency with expected drug efficacy. Consequently, we found disease-specific gene expression, and importantly, identified 20 drugs such as BMS-387032, phorbol-12-myristate-13-acetate, mitoxantrone, alvocidib, and vorinostat as candidates for repurposing. These were previously noted to be effective against two of the three diseases, and have a high probability of being effective against the other. That is, inclusion body myositis and DM. The two-stage prediction approach to drug repurposing presented here offers innovation to inform future drug discovery and clinical trials in a variety of human diseases. [ABSTRACT FROM AUTHOR]

Coccidioidomycosis is a fungal disease endemic to the southwestern United States, Mexico, and Central and South America. Prevalence rates are increasing steadily, and new endemic areas of Coccidioides are emerging. Standard treatment is often administered for months to decades, and intolerance to medications and treatment failures are common. No new treatments for coccidioidomycosis have been approved in the United States in nearly 40 years. On 5 August 2020, the US Food and Drug Administration convened experts in coccidioidomycosis from academia, industry, patient groups, and other government agencies to discuss the disease landscape and strategies to facilitate product development for treatment of coccidioidomycosis. This article summarizes the key topics concerning drug development for coccidioidomycosis presented by speakers and panelists during the workshop, such as unmet need, trial designs, endpoints, incentives, research and development support, and collaborations to facilitate antifungal drug development. [ABSTRACT FROM AUTHOR]

Population of the world run into several health-related emergencies among mankind and humans as it creates a challenge for the evolution of novel drug discoveries. One such can be the emergence of multidrug-resistant (MDR) strains in both hospital and community settings, which have been due to an inappropriate use and inadequate control of antibiotics that has led to the foremost human health concerns with a high impact on the global economy. So far, there has been application of two strategies for the development of anti-infective agents either by classical antibiotics that have been derived for their synthetic analogs with increased efficacy or screening natural compounds along with the synthetic compound libraries for the antimicrobial activities. However, need for newer treatment options for infectious diseases has led research to develop new generation of antimicrobial activity to further lessen the spread of antibiotic resistance. Currently, the principles aim to find novel mode of actions or products to target the specific sites and virulence factors in pathogens by a series of better understanding of physiology and molecular aspects of the microbial resistance, mechanism of infection process, and gene-pathogenicity relationship. The design various novel strategies tends to provide us a path for the development of various antimicrobial therapies that intends to have a broader and wider antimicrobial spectrum that helps to combat MDR strains worldwide. The development of antimicrobial peptides, metabolites derived from plants, microbes, phage-based antimicrobial agents, use of metal nanoparticles, and role of CRISPR have led to an exceptional strategies in designing and developing the next-generation antimicrobials. These novel strategies might help to combat the seriousness of the infection rates and control the health crisis system. [ABSTRACT FROM AUTHOR]

Topical and transdermal drug delivery is an effective, safe, and preferred route of drug administration. As such, skin permeability is one of the critical parameters that should be taken into consideration in the process of drug discovery and development. The ex vivo human skin model is considered as the best surrogate to evaluate in vivo skin permeability. This investigation adopted a novel two-QSAR scheme by collectively incorporating machine learning-based hierarchical support vector regression (HSVR) and classical partial least square (PLS) to predict the skin permeability coefficient and to uncover the intrinsic permeation mechanism, respectively, based on ex vivo excised human skin permeability data compiled from the literature. The derived HSVR model functioned better than PLS as represented by the predictive performance in the training set, test set, and outlier set in addition to various statistical estimations. HSVR also delivered consistent performance upon the application of a mock test, which purposely mimicked the real challenges. PLS, contrarily, uncovered the interpretable relevance between selected descriptors and skin permeability. Thus, the synergy between interpretable PLS and predictive HSVR models can be of great use for facilitating drug discovery and development by predicting skin permeability. [ABSTRACT FROM AUTHOR]

Simple Summary: The biopharmaceutical industry increasingly focuses on the development of new anticancer drugs for effective cancer therapy. Despite these efforts, the success rate is low, and thereby, greater efficacy and better safety properties are required. The high failure rate in drug discovery may be due to limitations of preclinical cancer models that inappropriately recapitulate human cancer biology. To date, patient-derived cancer organoids (PDCOs) have emerged as a model system to recapitulate human cancer biology. In this review, we discuss the advantages and applications of PDCO as a model to investigate anticancer drug efficacy and precision medicine. We also describe the challenges that must be overcome so that PDCOs can substantially represent human cancer biology. The cancer burden is rapidly increasing in most countries, and thus, new anticancer drugs for effective cancer therapy must be developed. Cancer model systems that recapitulate the biological processes of human cancers are one of the cores of the drug development process. PDCO has emerged as a unique model that preserves the genetic, physiological, and histologic characteristics of original cancer, including inter- and intratumoral heterogeneities. Due to these advantages, the PCDO model is increasingly investigated for anticancer drug screening and efficacy testing, preclinical patient stratification, and precision medicine for selecting the most effective anticancer therapy for patients. Here, we review the prospects and limitations of PDCO compared to the conventional cancer models. With advances in culture success rates, co-culture systems with the tumor microenvironment, organoid-on-a-chip technology, and automation technology, PDCO will become the most promising model to develop anticancer drugs and precision medicine. [ABSTRACT FROM AUTHOR]

Background: The immune system matures throughout childhood; therefore, evidence about the safety and efficacy of vaccines for the prevention of COVID-19 in the paediatric population is important. Efficacy and safety have not been established for COVID-19 vaccines in a large part of the paediatric population at the time of the initial approval for use in adults. This study aims to provide an overview of planned and ongoing paediatric clinical trials investigating the safety and/or efficacy of COVID-19. Methods: We identified all paediatric clinical trials investigating the safety and/or efficacy of COVID-19 vaccines in clinicaltrials.gov and clinicaltrialregister.eu, as well as all clinical trials planned in agreed PIPs (Paediatric Investigational Plans) as of 11 June 2021. Information about the study design, the paediatric age groups that they included, and the primary and secondary safety and efficacy outcomes were collected, together with expected timelines for the studies. Results: 21 clinical trials were identified through the clinical trial registries and 19 clinical trials were specified in 6 agreed PIPs, 5 of these trials were also in the trial registers. All PIPs stipulated development of the COVID-19 vaccines for the full paediatric population, with a deferral. The earliest expected completion date of a PIPs is March 2024. The majority (14/21) of registered trials are randomised double-blinded studies. All investigated safety, 20 have a surrogate efficacy outcome (immunogenicity), of these 7 also measure clinical efficacy (COVID-19 infections). 18 studies were initiated, of these, all but one is still ongoing and one in adolescents has been finalised. Conclusion: Even though several trials have been planned in agreed PIPs, the registered paediatric clinical trials identified are most often not part of a PIP. [ABSTRACT FROM AUTHOR]

N-acetylcysteine (NAC) is considered as the body's major antioxidant molecules with diverse biological properties. In this review, the pharmacokinetics, safety and efficacy report on both the preclinical and clinical summary of NAC is discussed. Both in vitro and in vivo preclinical studies along with the clinical data have shown that NAC has enormous biological properties. NAC is used in the treatment of acetaminophen poisoning, diabetic nephropathy, Alzheimer's disease, schizophrenia, and ulcerative colitis, etc. Numerous analytical techniques, for instance, UPLC, LC-MS, HPLC, RP-IPC are primarily employed for the estimation of NAC in different single and fixed-dose combinations. The molecular docking studies on NAC demonstrate the binding within Sudlow's site-I hydrogen bonds and formation of NAC and BSA complexes. Various hydrophobic and hydrophilic amino acids generally exist in making contact with NAC as NAC-BSA complexes. Docking studies of NAC with the active site of the urease exposed an O-coordinated bond through nickel 3002 and a hydrogen bond through His-138. NAC and its analogs also made the allosteric pockets that helped to describe almost all favorable pose for the chaperone in a complex through the protein. Thus, we intended to highlight the several health benefits of this antioxidant compound and applications in pharmaceutical product development. [ABSTRACT FROM AUTHOR]

Race and ethnicity can contribute to differences in drug exposure and/or response. Here, we report that about 10% of the new molecular entities (NMEs) approved between 2014 and 2019 by the US Food and Drug Administration's Center for Drug Evaluation and Research showed differences in exposure and/or response based on race/ethnicity or pharmacogenetic factors known to vary in frequency across global populations. Fewer NMEs (10%) reported differences in the labeling in 2014 to 2019 when compared to about 21% of NMEs approved between 2008 and 2013 that had differences in pharmacokinetics, safety, response, and/or pharmacogenetics. Understanding the underlying mechanisms that lead to such differences and adequate enrollment of racial and ethnic subgroups is essential to obtain sufficient information on exposure and response. Though drug development is global, when heterogeneous populations are not adequately enrolled, the risk‐benefit assessments can remain incomplete for certain subgroups. Consequently, this can result in regional differences in drug approval, population‐specific prescribing recommendations, or need for additional postmarketing studies to address concerns related to exposure, response, or lack of representation that lead to gaps in information. [ABSTRACT FROM AUTHOR]

This article discusses current literature on the use of 3,4‐methylenedioxymethamphetamine (MDMA)‐assisted psychotherapy in the treatment of posttraumatic stress disorder (PTSD). MDMA, the intended active ingredient in illicit Ecstasy or Molly products, is a psychedelic that causes an elevated mood, feeling of bonding, and increased energy. In MDMA‐assisted psychotherapy, patients are subjected to 2 or 3 multihour sessions of therapy with a team of psychiatrists. The dosing of MDMA is used to allow the therapist to probe the underlying trauma without causing emotional distress. The use of MDMA‐assisted psychotherapy treatment reduced patient's Clinician‐Administered PTSD Scale (CAPS) scores from baseline more than control psychotherapy (–22.03; 95%CI, –38.53 to –5.52) but with high statistical heterogeneity. MDMA‐assisted psychotherapy enhanced the achievement of clinically significant reductions in CAPS scores (relative risk, 3.65; 95%CI, 2.39‐5.57) and CAPS score reductions sufficient to no longer meet the definition of PTSD (relative risk, 2.10; 95%CI, 1.37‐3.21) with no detected statistical heterogeneity. While therapy was generally safe and well tolerated, bruxism, anxiety, jitteriness, headache, and nausea are commonly reported. While MDMA‐assisted psychotherapy has been shown to be an effective therapy for patients with PTSD with a reasonable safety profile, use of unregulated MDMA or use in the absence of a strongly controlled psychotherapeutic environment has considerable risks. [ABSTRACT FROM AUTHOR]

Vildagliptin, a DPP-4 inhibitor has been available for the management of type 2 diabetes mellitus for more than a decade. The extensive clinical data support from several vildagliptin clinical trials and real-world studies provided the clinicians with an effective treatment option for lowering blood glucose, which neither causes weight gain nor increased the risk of hypoglycemia and cardiovascular events. This article reviews the development journey of vildagliptin from the proof-of-concept of DPP-4 inhibition from its earlystages in the 1990s to the present, being an extensively studied, well-established DPP-4 inhibitor. The article highlights the clinical effectiveness, safety, and tolerability studies of vildagliptin, which proved vildagliptin as an effective and safe option in the armamentarium of type 2 diabetes mellitus management in this era of evidence-based medical practice. This vildagliptin journey, from proof-of-concept to a very well-established molecule gives a lesson that a novel concept takes time and requires focused efforts, persistence, and long-term perseverance for bringing it into clinical practice. [ABSTRACT FROM AUTHOR]

The development of pediatric-specific dose forms is particularly difficult due to a variety of factors relating to pediatric population differences from adult populations. The buccal dosage form is considered a good alternative to oral dosage form if the latter cannot be used in pediatric patients. Both oral and buccal dosage formulations uphold great application qualities for pediatric patients. This review sheds light on both oral and buccal, as they are the most convenient dosage forms for pediatrics. The use of adult drugs to treat children is a legislation concern, as it may result in incorrect dose, safety, and efficacy. The Best Pharmaceuticals for Children Act (BPCA) and the Pediatric Research Equity Act (PREA) are two key pieces of legislation that encourage and regulate pediatric medication research. Both contribute to a well-balanced approach to emphasizing critical safety and efficacy warnings for the of medications within pediatric populations. These contributions are what enable companies to continue making significant investments in pediatric drug developments. Despite the importance of investigating medicines for children, there is still a demand for pediatric-specific formulations and dosage forms. Many formulations and dosage forms can be designed, among which the buccal drug delivery seems a good modality for pediatric-friendly dosage forms. The main issues associated with these pediatric dosage forms development, particularly clinical and physiological factors, are discussed in this review. In addition, formulation developments and regulatory expectations are highlighted. In turn, suggestions are made to potentially improve future pediatric formulation development. [ABSTRACT FROM AUTHOR]

Sepsis involves life-threatening organ dysfunction caused by a dysregulated host response to infection. Despite three decades of efforts and multiple clinical trials, no treatment, except antibiotics and supportive care, has been approved for this devastating syndrome. Simultaneously, numerous preclinical studies have shown the effectiveness of oncology-indicated drugs in ameliorating sepsis. Here we focus on cataloging these efforts with both oncology-approved and under-development drugs that have been repositioned to treat bacterial-induced sepsis models. In this context, we also envision the exciting prospect for further standard and oncology drug combination testing that could ultimately improve clinical outcomes in sepsis. [ABSTRACT FROM AUTHOR]

Several challenges are associated with rare disease drug development in neurology. In this article, we summarize the US Food and Drug Administration's experience with clinical drug development for rare neurological diseases and discuss clinical pharmacology's critical contributions to drug development for rare diseases. We used publicly available information to identify and screen drug products approved for rare neurological indications between 1983 and 2019. We highlighted cases in which clinical pharmacology contributed to the evidence of drug efficacy, dose selection for pivotal clinical trials, dose optimization based on intrinsic and extrinsic factors, pharmacokinetic bridging for formulations, and efficacy bridging across different racial groups. Fifty‐one approved drug products were identified since the introduction of the Orphan Drug Act in 1983. Interestingly, the number of approvals in the last few years increased significantly, probably due to advances in genomic research and targeted drug modalities. Evaluation of dose selection in patient populations showed that in 52% of cases, the sponsors did not evaluate efficacy for more than one or two dose levels throughout the development program. Clinical pharmacology studies to evaluate the effect of intrinsic or extrinsic factors were adequately characterized in most of the applications. With the expansion of model informed drug development applications, (e.g., quantitative systems pharmacology and deep learning neural network models), the role and impact of clinical pharmacology is expected to grow exponentially in the next decade and enhance the development of novel treatment modalities for neurological rare diseases. [ABSTRACT FROM AUTHOR]

• Using three methods and different conformations of DIP to predict its cocrystals behavior. • Analyzed the differences between predicted cocrystals behavior and experimental results using different conformations. • When predicting cocrystal behavior using MC and MEP methods, it is necessary to consider the molecular conformation, as different conformations can significantly affect the prediction results. Drug development necessitates substantial investments in both human and material resources. In the advanced stages of development, significant solubility challenges frequently emerge, critically influencing a drug's applicability and efficacy. Crystal engineering, particularly through the application of cocrystal technology, presents a novel strategy to address these solubility issues without compromising the drug's effectiveness. However, the success rate of cocrystals formation remains relatively low. This article evaluates the impact of widely used virtual cocrystal screening methods on prediction outcomes, especially in the context of conformational diversity. The study describes the effects of eight dipyridamole (DIP) conformations and 130 cocrystal formers (CCFs) using molecular complementarity and molecular electrostatic potential methods, while the hydrogen bond propensity method did not account for conformations variations. Findings indicate that different DIP conformations lead to variable prediction outcomes in virtual cocrystal screening. Thus, it is crucial consider the conformational states of APIs and CCFs in virtual screenings to enhance prediction accuracy. By comparing virtual screening results with experimental results, this study demonstrated that incorporating conformational considerations can improve cocrystal success rates, minimize experimental workload, and contribute to energy-conservation and emission-reduction. Additionally, this research provides the true positives and true negatives data of DIP's cocrystal, laying the groundwork for further studies. [Display omitted] [ABSTRACT FROM AUTHOR]

The 5-Hydroxytryptamine (5HT)-2A receptor, a key target in psychoactive drug development, presents significant challenges in the design of selective compounds. Here, we describe the construction, evaluation and validation of two machine learning (ML) models for the classification of bioactivity mechanisms against the (5HT)-2A receptor. Employing neural networks and XGBoost models, we achieved an overall accuracy of around 87 %, which was further enhanced through molecular modelling (MM) (e.g. molecular dynamics simulations) and binding free energy analysis. This ML-MM integration provided insights into the mechanisms of direct modulators and prodrugs. A significant outcome of the current study is the development of a 'binding free energy fingerprint' specific to (5HT)-2A modulators, offering a novel metric for evaluating drug efficacy against this target. Our study demonstrates the prospective of employing a successful workflow combining AI with structural biology, offering a powerful tool for advancing psychoactive drug discovery. [Display omitted] • Developed machine learning models to classify bioactivity mechanisms for the 5HT-2A receptor. • Used datasets from BindingDB and ChEMBL, achieving 87 % accuracy with XGBoost and neural networks. • Combined AI models with molecular dynamics and MM-PBSA analysis for deeper insight into receptor-ligand interactions. • Introduced a 'binding free energy fingerprint' for evaluating modulators, aiding in 5HT-2A drug discovery. [ABSTRACT FROM AUTHOR]

The incidence of skin trauma is high and the repair process is complex, often leading to poor healing and other issues, which can result in significant economic and social burdens. Traditional Chinese medicine (TCM) is a valuable resource with proven effectiveness and safety in wound repair, widely utilized in clinical practice. A systematic analysis of wound healing with a focus on TCM research progress holds both academic and clinical importance. This article reviews the research progress of TCM in promoting wound healing, and provides basic data for the development of innovative drugs that promote wound healing. This article provides a review of the literature from the past decade and conducts a thorough analysis of various databases that contain reports on the use of TCM for wound repair. The data for this systematic research was gathered from electronic databases including CNKI, SciFinder, and PubMed. The study explores and summarizes the research findings and patterns by creating relevant charts. This study reviewed the mechanism of wound healing, experimental TCM methods to promote wound healing, the theory and mode of action of TCM to promote wound healing, the active ingredients of TCM that promote wound healing, the efficacy of TCM formulae to promote wound healing, and the potential toxicity of TCM and its antidotes. This study enriched the theory of TCM in promoting wound healing. Skin wound healing is a complex process that can be influenced by various internal and external factors. This article offers a theoretical foundation for exploring and utilizing TCM resources that enhance wound repair. By analyzing a range of TCM that promote wound healing, the article highlights the clinical importance and future potential of these medicines in promoting wound healing. [Display omitted] • The complex process of wound healing was reviewed. • The experimental methods of TCM promoting wound healing were reviewed. • The mechanism of TCM promoting wound healing was reviewed. • The active components of TCM for wound healing were reviewed. • This article reviews the research progress of TCM formulae in promoting wound healing. [ABSTRACT FROM AUTHOR]

Traditionally, the Morus mesozygia tree leaf has been used to manage maladies such as peptic ulcer, hyperglycemia, dermatitis, rheumatism, stomach-ache, arthritis, cough, malignancies, and malaria in parts of Africa. The study aimed to evaluate the potential of ethanol leaf extract of Morus mesozygia (EEMm) to induce toxicity by employing both acute and sub-acute oral toxicity experimental models. The extract's cytotoxicity was studied using brine shrimps (Artemia salina) lethality assay (BSLA), while in the acute toxicity test, male and female mice were administered a single oral dose of EEMm (2000 mg/kg). Male and female Wistar rats received repeated doses of 100 or 500 mg/kg EEMm orally for 28 days in the sub-acute toxicity experiment. The phytochemical analysis of EEMm was done using the HPLC. The BSLA revealed a moderate cytotoxic potential of the extract, with an LC 50 of 567.13 ± 0.27 μg/mL. All the animals survived the acute toxicity test, with no significant changes in the relative organ weights, suggesting that LD 50 is greater than 2000 mg/kg. The animal weights did not vary significantly in the sub-acute toxicity test neither were the alterations in biochemical and hematological tests pronounced, although the histoarchitectures of the kidney, liver and spleen indicated slight anomalies in the evaluated animals. The HPLC analysis revealed the presence of quercetin, ferulic acid, rutin, caffeic acid, morin and gallic acid. Ethanol leaf extract of Morus mesozygia demonstrated a safe toxicity profile in rodents, supporting its broad folkloric use in African ethnomedicine. [Display omitted] [ABSTRACT FROM AUTHOR]

High-throughput drug screening (HTDS) has significantly reduced the time and cost of new drug development. Nonetheless, contact-dependent cell-cell communication (CDCCC) may impact the chemosensitivity of tumour cells. There is a pressing need for low-cost single-cell HTDS platforms, alongside a deep comprehension of the mechanisms by which CDCCC affects drug efficacy, to fully unveil the efficacy of anticancer drugs. In this study, we develop a microfluidic chip for single-cell HTDS and evaluate the molecular mechanisms impacted by CDCCC using quantitative mass spectrometry-based proteomics. The chip achieves high-quality drug mixing and single-cell capture, with single-cell drug screening results on the chip showing consistency with those on the 96-well plates under varying concentration gradients. Through quantitative proteomic analysis, we deduce that the absence of CDCCC in single tumour cells can enhance their chemoresistance potential, but simultaneously subject them to stronger proliferation inhibition. Additionally, pathway enrichment analysis suggests that CDCCC could impact several signalling pathways in tumour single cells that regulate vital biological processes such as tumour proliferation, adhesion, and invasion. These results offer valuable insights into the potential connection between CDCCC and the chemosensitivity of tumour cells. This research paves the way for the development of single-cell HTDC platforms and holds the promise of advancing tumour personalized treatment strategies. [Display omitted] • Proposing a single-cell high-throughput combined drug screening microfluidic chip. • Lack of CDCCC might enhance chemoresistance potential of tumour single cells. • CDCCC affects several signalling pathways that regulate key processes in tumours. [ABSTRACT FROM AUTHOR]

Accumulating clinical studies have consistently demonstrated that the microbes in the human body closely interact with the human host, actively participating in the regulation of drug effectiveness. Identifying the associations between microbes and drugs can facilitate the development of drug discovery, and microbes have become a new target in antimicrobial drug development. However, the discovery of microbe-drug associations relies on clinical or biological experiments, which are not only time-consuming but also financially burdensome. Thus, the utilization of computational methods to predict microbe-drug associations holds promise for reducing costs and enhancing the efficiency of biological experiments. Here, we introduce a new computational method, called HKFGCN (Heterogeneous information Kernel Fusion Graph Convolution Network), to predict the microbe-drug associations. Instead of extracting feature from a single network in previous studies, HKFGCN separately extracts topological information features from different networks, and further refines them by generating Gaussian kernel features. HKFGCN consists of three main steps. Firstly, we constructed two similarity networks and a microbe-drug association network based on numerous biological data. Second, we employed two types of encoders to extract features from these networks. Next, Gaussian kernel features were obtained from the drug and microbe features at each layer. Finally, we reconstructed the bipartite microbe-drug graph based on the learned representations. Experimental results demonstrate the excellent performance of the HKFGCN model across different datasets using the cross-validation scheme. Additionally, we conduced case studies on human immunodeficiency virus, and the results were corroborated by existing literatures. The prediction model's code is available at https://github.com/roll-of-bubble/HKFGCN. [Display omitted] [ABSTRACT FROM AUTHOR]

The herb pair of Chuanxiong Rhizome (Ligusticum chuanxiong Hort. , Chuanxiong in Chinese, CX) and Paeoniae Radix Rubra (Paeonia lactiflora Pall. Or Paeonia veitchii Lynch, Chishao in Chinese, CS) is a famous blood activating and stasis resolving pair that is often found in traditional Chinese medicine (TCM) formulas for the treatment of acute lung injury (ALI). However, the relationship of CX-CS herb pair to ALI and its underlying mechanisms are unclear. The study explored the effect and mechanisms of CX-CS herb pair in LPS induced ALI by network pharmacology and molecular docking combined with preclinical evaluation. The related targets of the active compounds of CX-CS herb pair in regulating ALI were screened by network pharmacology. PPI was constructed and the potential pathways were investigated by GO and KEGG. The contribution of each active ingredient of CX-CS herb pair to ALI were calculated by network-based efficacy. The interactions between potential targets and active ingredients were evaluated by molecular docking. LPS stimulated RAW264.7 cells and mice model experiments were adopted to verify the effect of CX-CS herb pair on ALI. A total of 25 compounds and 193 targets were identified in the CX-CS herb pair, of which 19 compounds and 64 targets were associated with ALI, and six compounds including baicalin, ellagic acid, baicalein, beta-sitosterol, paeoniflorin and ferulic acid accounted for 93.12% of the total combination index for ALI prevention. The CX-CS herbal pair against ALI was associated with PI3K/AKT and MAPK signaling pathways by GO and KEGG analysis. The screened active compounds showed good affinity for TNF, MAPK, and AKT by molecular docking. In vitro and in vivo tests showed that CX combined with CS synergistically inhibited LPS-induced ALI at 1:3, suppressed the release of TNF-α, IL-1β and IL-6, inhibited the accumulation of ROS, as well as regulated the content of SOD, MDA and GSH. Meanwhile, the herb pair was effective in inhibiting the expression of p38, ERK, IκBα, p65, caspase 3, PARP, and up-regulating the levels of AKT and Bcl-2/Bax. Our study confirmed the synergistic effect of CX-CS herb pair on the prevention of ALI by inhibiting inflammation, oxidative stress, and apoptosis through MAPK/NF-κB and PI3K/AKT signaling pathways. [Display omitted] [ABSTRACT FROM AUTHOR]

The development of innovative antifungal agents is essential. Some fungicidal agents are no longer effective due to resistance development, various side effects, and high toxicity. Therefore, the synthesis and development of some new antifungal agents are necessary. 1,2,4-Triazole is one of the most essential pharmacophore systems between five-membered heterocycles. The structure-activity relationship (SAR) of this nitrogen-containing heterocyclic compound showed potential antifungal activity. The 1,2,4-triazole core is present as the nucleus in a variety of antifungal drug categories. The most potent and broad activity of triazoles have confirmed them as pharmacologically significant moieties. The goal of this review is to highlight recent developments in the synthesis and SAR study of 1,2,4-triazole as a potential fungicidal compound. In this study, we provide the results of a biological activity evaluation using various structures and figures. Literature investigation showed that 1, 2, 4-triazole derivatives reveal the extensive span of antifungal activity. This review will assist researchers in the development of new potential antifungal drug candidates with high effectiveness and selectivity. [ABSTRACT FROM AUTHOR]

Around 20% of the American population have chronic pain and estimates in other Western countries report similar numbers. This represents a major challenge for global health care systems. Additional problems for the treatment of chronic and persistent pain are the comparably low efficacy of existing therapies, the failure to translate effects observed in preclinical pain models to human patients and related setbacks in clinical trials from previous attempts to develop novel analgesics. Drug repurposing offers an alternative approach to identify novel analgesics as it can bypass various steps of classical drug development. In recent years, several approved drugs were attributed analgesic properties. Here, we review available data and discuss recent findings suggesting that the approved drugs minocycline, fingolimod, pioglitazone, nilotinib, telmisartan, and others, which were originally developed for the treatment of different pathologies, can have analgesic, antihyperalgesic, or neuroprotective effects in preclinical and clinical models of inflammatory or neuropathic pain. For our analysis, we subdivide the drugs into substances that can target neuroinflammation or substances that can act on peripheral sensory neurons, and highlight the proposed mechanisms. Finally, we discuss the merits and challenges of drug repurposing for the development of novel analgesics. [ABSTRACT FROM AUTHOR]

Molnupiravir (Lagevrio®) is an orally-administered antiviral prodrug that inhibits replication of RNA viruses through viral error induction. It is being developed by Merck and Ridgeback Biotherapeutics for the prevention and treatment of Coronavirus disease 2019 (COVID-19). Molnupiravir received its first approval on 4 November 2021 in the UK for the treatment of mild to moderate COVID-19 in adults with a positive severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) diagnostic test and who have at least one risk factor for developing severe illness. Molnupiravir is filed for approval and has emergency use authorization for the treatment of COVID-19 in several countries, including the USA, Japan and those in the EU. This article summarizes the milestones in the development of molnupiravir leading to this first approval for COVID-19. [ABSTRACT FROM AUTHOR]

Background: Drug–drug interactions (DDIs) are the reactions between drugs. They are compartmentalized into three types: synergistic, antagonistic and no reaction. As a rapidly developing technology, predicting DDIs-associated events is getting more and more attention and application in drug development and disease diagnosis fields. In this work, we study not only whether the two drugs interact, but also specific interaction types. And we propose a learning-based method using convolution neural networks to learn feature representations and predict DDIs. Results: In this paper, we proposed a novel algorithm using a CNN architecture, named CNN-DDI, to predict drug–drug interactions. First, we extract feature interactions from drug categories, targets, pathways and enzymes as feature vectors and employ the Jaccard similarity as the measurement of drugs similarity. Then, based on the representation of features, we build a new convolution neural network as the DDIs' predictor. Conclusion: The experimental results indicate that drug categories is effective as a new feature type applied to CNN-DDI method. And using multiple features is more informative and more effective than single feature. It can be concluded that CNN-DDI has more superiority than other existing algorithms on task of predicting DDIs. [ABSTRACT FROM AUTHOR]

Artemisinin and its derivatives (ARTs), due to their potent antimalarial activities, are widely used as frontline antimalarials across the world. Although the large-scale deployment of ARTs has significantly contributed to a substantial decline in malaria deaths, the global malaria burden is still high. New antimalarial treatments need to be developed to manage the growing artemisinin resistance. Understanding the status of ART development is crucial for developing strategies for new alternatives and identifying opportunities to develop ART-based treatments. This study sampled ART clinical trials from the past two decades to gain an overview of the global ART-development landscape. A total of 768 trials were collected to analyze the disease focuses, activity trends, development status, geographic distribution, and combination treatment profiles of ART trials. The findings highlighted the constant focus of ARTs on malaria, the evolving combination research focus, the distinctions between ART development preferences across global regions, the urgent demands for treatments for artemisinin-resistant malaria, and the unavoidable need to consider ART combinations in the development of new antimalarials. [ABSTRACT FROM AUTHOR]

Cancer is one of the primary causes of mortality globally, and the discovery of new anticancer drugs is the most important need in recent times. Natural products have been recognized as effective in fight against various diseases including cancer for over 50 years. Plants and microbes are the primary and potential sources of natural compounds to fight against cancer. Moreover, researches in the field of plant-based natural compounds have moved towards advanced and molecular level understandings from the last few decades, leading to the development of potent anticancer agents. Also, plants have been accepted as abundant and prosperous sources for the development of novel therapeutic agents for the management and prevention of different cancer types. The high toxicity of some cancer chemotherapy drugs, as well as their unfavorable side effects and drugs resistance, drives up the demand for natural compounds as new anticancer drugs. In this detailed evidence-based mechanistic review, facts and information about various medicinal plants, their bioactive compounds with their potent anticancer activities against different cancers have been gathered, with further approach to represent the molecular mechanism behind the anticancer activity of these plants. This review will be beneficial for investigators/scientists globally involved in the development of natural, safe, effective, and economical therapeutic agents/drugs against various cancers. This might be an important contribution in the field of drug discovery, where drugs can be used alone or in combination to increase the efficacy of newly synthesized drugs. [ABSTRACT FROM AUTHOR]

Combination therapy has, to some extent, been successful in limiting the emergence of drug-resistant tuberculosis. Drug combinations achieve this advantage by simultaneously acting on different targets and metabolic pathways. Additionally, drug combination therapies are shown to shorten the duration of therapy for tuberculosis. As new drugs are being developed, to overcome the challenge of finding new and effective drug combinations, systems biology commonly uses approaches that analyse mycobacterial cellular processes. These approaches identify the regulatory networks, metabolic pathways, and signaling programs associated with M. tuberculosis infection and survival. Different preclinical models that assess anti-tuberculosis drug activity are available, but the combination of models that is most predictive of clinical treatment efficacy remains unclear. In this structured literature review, we appraise the options to accelerate the TB drug development pipeline through the evaluation of preclinical testing assays of drug combinations. [ABSTRACT FROM AUTHOR]

Motivation Accumulated clinical studies show that microbes living in humans interact closely with human hosts, and get involved in modulating drug efficacy and drug toxicity. Microbes have become novel targets for the development of antibacterial agents. Therefore, screening of microbe–drug associations can benefit greatly drug research and development. With the increase of microbial genomic and pharmacological datasets, we are greatly motivated to develop an effective computational method to identify new microbe–drug associations. Results In this article, we proposed a novel method, Graph2MDA, to predict microbe–drug associations by using variational graph autoencoder (VGAE). We constructed multi-modal attributed graphs based on multiple features of microbes and drugs, such as molecular structures, microbe genetic sequences and function annotations. Taking as input the multi-modal attribute graphs, VGAE was trained to learn the informative and interpretable latent representations of each node and the whole graph, and then a deep neural network classifier was used to predict microbe–drug associations. The hyperparameter analysis and model ablation studies showed the sensitivity and robustness of our model. We evaluated our method on three independent datasets and the experimental results showed that our proposed method outperformed six existing state-of-the-art methods. We also explored the meaning of the learned latent representations of drugs and found that the drugs show obvious clustering patterns that are significantly consistent with drug ATC classification. Moreover, we conducted case studies on two microbes and two drugs and found 75–95% predicted associations have been reported in PubMed literature. Our extensive performance evaluations validated the effectiveness of our proposed method. Availability and implementation Source codes and preprocessed data are available at https://github.com/moen-hyb/Graph2MDA. Supplementary information Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]

Toxoplasma gondii is a worldwide food-borne parasite that can infect almost all warm-blooded animals, including humans. To date, there are no effective drugs to prevent or eradicate T. gondii infection. Recent studies have shown that probiotics could influence the relationship between the microbiota and parasites in the host. Koumiss has been used to treat many diseases based on its probiotic diversity. Therefore, we explored the effect of koumiss on T. gondii infection via its effect on the host intestinal microbiota. BALB/c mice were infected with T. gondii and treated with PBS, koumiss and mares' milk. Brain cysts were counted, and long-term changes in the microbiota and the effect of koumiss on gut microbiota were investigated with high-throughput sequencing technology. The results suggested that koumiss treatment significantly decreased the cyst counts in the brain (P < 0.05). Moreover, T. gondii infection changed the microbiota composition, and koumiss treatment increased the relative abundance of Lachnospiraceae and Akkermansia muciniphila, which were associated with preventing T. gondii infection. Moreover, koumiss could inhibit or ameliorate T. gondii infection by increasing the abundance of certain bacteria that control unique metabolic pathways. The study not only established a close interaction among the host, intracellular pathogens and intestinal microbiota but also provided a novel focus for drug development to prevent and eradicate T. gondii infection. [ABSTRACT FROM AUTHOR]

Phase 2 and 3 development failure is one of the key factors for high drug development cost. Robust prediction of a candidate drug's efficacy and safety profile could potentially improve the success rate of the drug development. Therefore, systematic evaluation of the prediction is important for learning and continuous improvement of the prediction. In this article, we proposed a set of unified criteria that allow to evaluate the predictions across different endpoints, indications and development stages: standardized bias (SB), standardized mean squared errors (SMSE), and credibility of prediction. We applied the SB and SMSE to the predicted treatment effects for 54 comparisons in 5 compounds in immunology and diabetes. [ABSTRACT FROM AUTHOR]

Most clinically used drugs are metabolized in the body via oxidation, reduction, or hydrolysis reactions, which are considered phase I reactions. Cytochrome P450 (P450) enzymes, which primarily catalyze oxidation reactions, contribute to the metabolism of over 50% of clinically used drugs. In the last few decades, the function and regulation of P450s have been extensively studied, whereas the characterization of non-P450 phase I enzymes is still incomplete. Recent studies suggest that approximately 30% of drug metabolism is carried out by non-P450 enzymes. This review summarizes current knowledge of non-P450 phase I enzymes, focusing on their roles in controlling drug efficacy and adverse reactions as an important aspect of drug development. [ABSTRACT FROM AUTHOR]

Type 2 diabetes mellitus (T2DM) is an epidemic with an ever-increasing global prevalence. Current treatment strategies, although plentiful and somewhat effective, often fail to achieve desired glycaemic goals in many people, leading ultimately to disease complications. The lack of sustained efficacy of clinically-approved drugs has led to a heightened interest in the development of novel alternative efficacious antidiabetic therapies. One potential option in this regard is the peptide apelin, an adipokine that acts as an endogenous ligand of the APJ receptor. Apelin exists in various molecular isoforms and was initially studied for its cardiovascular benefits, however recent research suggests that it also plays a key role in glycaemic control. As such, apelin peptides have been shown to improve insulin sensitivity, glucose tolerance and lower circulating blood glucose. Nevertheless, native apelin has a short biological half-life that limits its therapeutic potential. More recently, analogues of apelin, particularly apelin-13, have been developed that possess a significantly extended biological half-life. These analogues may represent a promising target for future development of therapies for metabolic disease including diabetes and obesity. [ABSTRACT FROM AUTHOR]

The article presents the discussion on research news briefs. Topics include Zhang being identified the genes involved in turning the bisexual primordial flower into either a male or female flower; and promoting closure more efficiently and future drug development able for harnessing the allosteric effect in improving efficacy.

Pathogenesis of neonatal candidiasis (NC) is distinct from systemic candidiasis in adults and older pediatric patients due to the significant incidence of central nervous system involvement in neonates. Thus, although adequate and well-controlled trials in NC are often unfeasible due to difficulty enrolling patients, extrapolation of efficacy from antifungal drug trials in adults is generally not appropriate. However, treatment of NC is an area of great unmet need. We describe a regulatory review approach that combined the assessment of limited clinical efficacy, pharmacokinetics, and safety data from neonates and young infants along with microbiology outcomes and pharmacokinetic data from relevant nonclinical models of candidemia/invasive candidiasis to inform the use of micafungin in pediatric patients younger than 4 months, while communicating areas of remaining uncertainty in labeling. [ABSTRACT FROM AUTHOR]