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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. [ABSTRACT FROM AUTHOR]

Copyright of Chinese Journal of Intelligent Science & Technology is the property of Beijing Xintong Media Co., Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Shenyang Pharmaceutical University is the property of Shenyang Pharmaceutical University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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.

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.

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. Metabolomics greatly facilitates drug research and development from understanding disease mechanisms and identifying drug targets to predicting drug response and enabling personalized treatment. [Display omitted] [ABSTRACT FROM AUTHOR]

As clinical research and drug development in China continue to advance, greater attention has been paid to the value of clinical research guidelines. The first revision of the original E8 recommendations (R1), 'General Considerations for Clinical Research' was made by the International Council for Harmonization in October 2021. Our National Medical Products Administration has recently opted to implement the rules beginning from July 2023. In order to provide useful references for improved design and execution of drug clinical studies in China, this paper primarily interprets the fundamental background and revision of E8 (R1) from the perspective of clinical workers. It also analyzes and discusses the application of the current clinical study guidelines in China.

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.

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.

Heme oxygenase (HO-2) is an enzyme mainly involved in the physiologic turnover of heme and intracellular gas sensing, and it is very abundant in the brain, testes, kidneys and vessels. Since 1990, when HO-2 was discovered, the scientific community has underestimated the role of this protein in health and disease, as attested by the small amount of articles published and citations received. One of the reason that have contributed to the lack of interest in HO-2 was the difficulty in upregulating or inhibiting this enzyme. However, over the last 10 years, novel HO-2 agonists and antagonists have been synthesized, and the availability of these pharmacological tools should increase the appeal of HO-2 as drug target. In particular, these agonists and antagonists could help explain some controversial aspects, such as the neuroprotective versus neurotoxic roles of HO-2 in cerebrovascular diseases. Furthermore, the discovery of HO-2 genetic variants and their involvement in Parkinson's disease, in particular in males, opens new avenues for pharmacogenetic studies in gender medicine. [ABSTRACT FROM AUTHOR]

Currently, hormonal drugs are the mainstay for treating endometriosis or adenomyosis. Aside from staying within the "therapeutic window" and cutting off the hormonal support to the ectopic endometrium, none of these treatments were developed with a previously identified target. The current lack of innovation is humbling, especially considering that among >34,000 PubMed-indexed publications on endometriosis or adenomyosis, approximately 65% of them were published in the last 2 decades, many of them presumably with all the benefits of omics and molecular biology. One major reason for so many doomed research and development (R&D) projects on nonhormonal drugs is the failure to understand the natural history of the ectopic endometrium. Other reasons include, but are not limited to, the number of side effects that these nonhormonal drug candidates presented, which the developers were either unaware of or simply had ignored when pursuing a too narrowly minded development—a common cognitive trap known as invisible gorillas. Unless we have a clear global picture with a good grasp of the natural history of ectopic endometrium, "potholes" and "blind alleys" in drug R&D are difficult to avoid. This review shall explore some new concepts in the progression of ectopic endometrium and explain how these new perspectives offer insights for devising better therapeutic options, explain why some drug R&D projects for endometriosis or adenomyosis have failed, provide a critical analysis of some issues encountered in everyday practice, expose knowledge gaps in need of further research, and, finally, offer possible ways to circumvent hurdles and potholes and avoid cul-de-sacs in nonhormonal drug R&D. [ABSTRACT FROM AUTHOR]

Research and development (R&D) of nanodrugs is a long, complex and uncertain process. Since the 1960s, computing has been used as an auxiliary tool in the field of drug discovery. Many cases have proven the practicability and efficiency of computing in drug discovery. Over the past decade, computing, especially model prediction and molecular simulation, has been gradually applied to nanodrug R&D, providing substantive solutions to many problems. Computing has made important contributions to promoting data-driven decision-making and reducing failure rates and time costs in discovery and development of nanodrugs. However, there are still a few articles to examine, and it is necessary to summarize the development of the research direction. In the review, we summarize application of computing in various stages of nanodrug R&D, including physicochemical properties and biological activities prediction, pharmacokinetics analysis, toxicological assessment and other related applications. Moreover, current challenges and future perspectives of the computing methods are also discussed, with a view to help computing become a high-practicability and -efficiency auxiliary tool in nanodrugs discovery and development. [ABSTRACT FROM AUTHOR]

Hemophilia is the only rare hereditary hemorrhagic disorder included in the First Rare Diseases catalogue. However, rare bleeding diseases identified in the clinic are far more common than hemophilia. Most other rare hemorrhagic disorders have less effective treatment than hemophilia. Hemophilia has a history of successful drug development in rare hemorrhagic diseases, and the cycle between clinical research and drug development has been gradually realized. Drug research and pharmaceutical companies can refer to the drug research and development process in the field of hemophilia, learn from the experience of hemophilia drug research and develop treatments. The industry can increase drug development by strengthening basic research, focusing on the value of natural history research, the application of quantitative pharmacological tools and improving the efficiency of drug development to meet the urgent unmet medical needs of patients with rare hemorrhagic diseases.

Heme oxygenase (HO-2) is an enzyme mainly involved in the physiologic turnover of heme and intracellular gas sensing, and it is very abundant in the brain, testes, kidneys and vessels. Since 1990, when HO-2 was discovered, the scientific community has underestimated the role of this protein in health and disease, as attested by the small amount of articles published and citations received. One of the reason that have contributed to the lack of interest in HO-2 was the difficulty in upregulating or inhibiting this enzyme. However, over the last 10 years, novel HO-2 agonists and antagonists have been synthesized, and the availability of these pharmacological tools should increase the appeal of HO-2 as drug target. In particular, these agonists and antagonists could help explain some controversial aspects, such as the neuroprotective versus neurotoxic roles of HO-2 in cerebrovascular diseases. Furthermore, the discovery of HO-2 genetic variants and their involvement in Parkinson’s disease, in particular in males, opens new avenues for pharmacogenetic studies in gender medicine.

Introduction: This review aims to present briefly the new horizon opened to pharmacology by the deep learning (DL) technology, but also to underline the most important threats and limitations of this method. Material and Methods: We searched multiple databases for articles published before May 2021 according to the preferred reported item related to deep learning and drug research. Out of the 267 articles retrieved, we included 49 in the final review Results: DL and other different types of artificial intelligence have recently entered all spheres of science, taking an increasingly central position in the decision-making processes, also in pharmacology. Hence, there is a need for better understanding of these technologies. The basic differences between AI (artificial intelligence), DL and ML (machine learning) are explained. Additionally, the authors try to highlight the role of deep learning methods in drug research and development as well as in improving the safety of pharmacotherapy. Finally, future directions of DL in pharmacology were outlined as well as possible misuses of it. Conclusion: DL is a promising and powerful tool for comprehensive analysis of big data related to all fields of pharmacology, however it has to be used carefully. [ABSTRACT FROM AUTHOR]

Research and development (R&D) of nanodrugs is a long, complex and uncertain process. Since the 1960s, computing has been used as an auxiliary tool in the field of drug discovery. Many cases have proven the practicability and efficiency of computing in drug discovery. Over the past decade, computing, especially model prediction and molecular simulation, has been gradually applied to nanodrug R&D, providing substantive solutions to many problems. Computing has made important contributions to promoting data-driven decision-making and reducing failure rates and time costs in discovery and development of nanodrugs. However, there are still a few articles to examine, and it is necessary to summarize the development of the research direction. In the review, we summarize application of computing in various stages of nanodrug R&D, including physicochemical properties and biological activities prediction, pharmacokinetics analysis, toxicological assessment and other related applications. Moreover, current challenges and future perspectives of the computing methods are also discussed, with a view to help computing become a high-practicability and -efficiency auxiliary tool in nanodrugs discovery and development.

In mainland China, there remains a shortage of pediatric drugs. The Chinese government has recently launched policies and incentives to encourage pediatric drug development and clinical trials. However, data on the characteristics or development trends of these trials are limited. In this review, we extracted source data from the Chinese Clinical Trials Registry and Information Transparency Platform and systematically reviewed the pediatric clinical trials conducted in mainland China from 2009 to 2020, a comprehensive process evaluation of the pediatric drug clinical trials development in the past decade, providing data support to policy makers and industry stakeholders. We included 487 pediatric clinical trials. Over the past decade, the number of pediatric trials has increased, especially since 2016. The most common therapeutic areas were infectious diseases (n = 108, 22.2%), agents for preventive purpose (n = 99, 20.3%), and neurological and psychiatric diseases (n = 71, 14.6%). The number of clinical trials involving epilepsy (39, 10.1%), asthma (33, 8.5%), and influenza (24, 6.2%) were the highest. The distribution of leading institutions is unbalanced in mainland China, with most units in East China (34.0%) and few in Southwest China (6.9%). China has made progress in improving the research and development environment of pediatric drugs and increasing pediatric trials. However, a wide gap in pediatric drug development and clinical trials quality exists between China and the developed countries. The pharmaceutical industry in China has faced grim setbacks, including study duplication, lack of innovation, poor research design, and unbalanced resource allocation. Thus, we suggest that the Chinese government should adjust their policies to improve innovation and clinical design capacity, and optimize resource allocation between regions.

Regulatory agencies installed orphan drug regulations to stimulate research and development of new innovative treatments for life-threatening diseases with a low prevalence (rare diseases). We established a list of well-known food-related ingredients with clinical evidence for rare diseases in the open medical literature that obtained marketing authorization as an expensive "orphan drug", protected by intellectual property (IP) rights. We show that these ingredients are part of an established practice of medicinal compounding—a form of point of care manufacturing. We argue that these ingredients should be considered as "pharmaceutical commons", and that regulatory incentives for private companies and market protection mechanisms such as IP rights are not justified in this case. [ABSTRACT FROM AUTHOR]

Regulatory agencies installed orphan drug regulations to stimulate research and development of new innovative treatments for life-threatening diseases with a low prevalence (rare diseases). We established a list of well-known food-related ingredients with clinical evidence for rare diseases in the open medical literature that obtained marketing authorization as an expensive “orphan drug”, protected by intellectual property (IP) rights. We show that these ingredients are part of an established practice of medicinal compounding—a form of point of care manufacturing. We argue that these ingredients should be considered as “pharmaceutical commons”, and that regulatory incentives for private companies and market protection mechanisms such as IP rights are not justified in this case.

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.

Alzheimer's disease (AD) is a neurodegenerative disorder characterized by progressive and irreversible worsening of cognitive functions, inability to perform everyday activities, and mood disorders. As recently reported by [5], 132 drugs are under clinical development for AD and only 28 of them are in phase III; among these latter, nine are anti-amyloid agents, eight are compounds targeting neuropsychiatric symptoms, and only three are antioxidant/neurotransmitter-based therapies. Over the last few years, many drugs, initially authorized and marketed for the treatment of other diseases, have proven to be potentially effective for the treatment of AD. Decoding the synaptic dysfunction of bioactive human AD brain soluble A to inspire novel therapeutic avenues for Alzheimer's disease. [Extracted from the article]

Early clinical successes are driving enthusiasm for fecal microbiota transplantation (FMT), the transfer of healthy gut bacteria through whole stool, as emerging research is linking the microbiome to many different diseases. However, preliminary trials have yielded mixed results and suggest that heterogeneity in donor stool may play a role in patient response. Thus, clinical trials may fail because an ineffective donor was chosen rather than because FMT is not appropriate for the indication. Here, we describe a conceptual framework to guide rational donor selection to increase the likelihood that FMT clinical trials will succeed. We argue that the mechanism by which the microbiome is hypothesized to be associated with a given indication should inform how healthy donors are selected for FMT trials, categorizing these mechanisms into four disease models and presenting associated donor selection strategies. We next walk through examples based on previously published FMT trials and ongoing investigations to illustrate how donor selection might occur in practice. Finally, we show that typical FMT trials are not powered to discover individual taxa mediating patient responses, suggesting that clinicians should develop targeted hypotheses for retrospective analyses and design their clinical trials accordingly. Moving forward, developing and applying novel clinical trial design methodologies like rational donor selection will be necessary to ensure that FMT successfully translates into clinical impact. [ABSTRACT FROM AUTHOR]

There is strong epidemiological evidence that poor diet is associated with depression. The reverse has also been shown, namely that eating a healthy diet rich in fruit, vegetables, fish and lean meat, is associated with reduced risk of depression. To date, only one randomised controlled trial (RCT) has been conducted with elevated depression symptoms being an inclusion criterion, with results showing that a diet intervention can reduce clinical levels of depression. No such RCTs have been performed in young adults. Young adults with elevated levels of depression symptoms and who habitually consume a poor diet were randomly allocated to a brief 3-week diet intervention (Diet Group) or a habitual diet control group (Control Group). The primary and secondary outcome measures assessed at baseline and after the intervention included symptoms of depression (Centre for Epidemiological Studies Depression Scale; CESD-R; and Depression Anxiety and Stress Scale– 21 depression subscale; DASS-21-D), current mood (Profile of Mood States), self-efficacy (New General Self-Efficacy Scale) and memory (Hopkins Verbal Learning Test). Diet compliance was measured via self-report questionnaires and spectrophotometry. One-hundred-and-one individuals were enrolled in the study and randomly assigned to the Diet Group or the Control Group. Upon completion of the study, there was complete data for 38 individuals in each group. There was good compliance with the diet intervention recommendations assessed using self-report and spectrophotometry. The Diet group had significantly lower self-reported depression symptoms than the Control Group on the CESD-R (p = 0.007, Cohen’s d = 0.65) and DASS-21 depression subscale (p = 0.002, Cohen’s d = 0.75) controlling for baseline scores on these scales. Reduced DASS-21 depression subscale scores were maintained on follow up phone call 3 months later (p = .009). These results are the first to show that young adults with elevated depression symptoms can engage in and adhere to a diet intervention, and that this can reduce symptoms of depression. The findings provide justification for future research into the duration of these benefits, the impacts of varying diet composition, and their biological basis. [ABSTRACT FROM AUTHOR]

Head and neck squamous cell carcinoma (HNSCC) remains a morbid disease with poor prognosis and treatment that typically leaves patients with permanent damage to critical functions such as eating and talking. Currently only three targeted therapies are FDA approved for use in HNSCC, two of which are recently approved immunotherapies. In this work, we identify biological pathways involved with this disease that could potentially be targeted by current FDA approved cancer drugs and thereby expand the pool of potential therapies for use in HNSCC treatment. We analyzed 508 HNSCC patients with sequencing information from the Genomic Data Commons (GDC) database and assessed which biological pathways were significantly enriched for somatic mutations or copy number alterations. We then further classified pathways as either “light” or “dark” to the current reach of FDA-approved cancer drugs using the Cancer Targetome, a compendium of drug-target information. Light pathways are statistically enriched with somatic mutations (or copy number alterations) and contain one or more targets of current FDA-approved cancer drugs, while dark pathways are enriched with somatic mutations (or copy number alterations) but not currently targeted by FDA-approved cancer drugs. Our analyses indicated that approximately 35–38% of disease-specific pathways are in scope for repurposing of current cancer drugs. We further assess light and dark pathways for subgroups of patient tumor samples according to HPV status. The framework of light and dark pathways for HNSCC-enriched biological pathways allows us to better prioritize targeted therapies for further research in HNSCC based on the HNSCC genetic landscape and FDA-approved cancer drug information. We also highlight the importance in the identification of sub-pathways where targeting and cross targeting of other pathways may be most beneficial to predict positive or negative synergy with potential clinical significance. This framework is ideal for precision drug panel development, as well as identification of highly aberrant, untargeted candidates for future drug development. [ABSTRACT FROM AUTHOR]

Fundamental scientific advances can take decades to translate into improvements in human health. Shortening this interval would increase the rate at which scientific discoveries lead to successful treatment of human disease. One way to accomplish this would be to identify which advances in knowledge are most likely to translate into clinical research. Toward that end, we built a machine learning system that detects whether a paper is likely to be cited by a future clinical trial or guideline. Despite the noisiness of citation dynamics, as little as 2 years of postpublication data yield accurate predictions about a paper's eventual citation by a clinical article (accuracy = 84%, F1 score = 0.56; compared to 19% accuracy by chance). We found that distinct knowledge flow trajectories are linked to papers that either succeed or fail to influence clinical research. Translational progress in biomedicine can therefore be assessed and predicted in real time based on information conveyed by the scientific community's early reaction to a paper. [ABSTRACT FROM AUTHOR]

Introduction: Despite increased treatment availability, HIV-infected individuals continue to start antiretroviral therapy (ART) late in disease progression, increasing early mortality risk. Materials and methods: Nested prospective cohort study within a randomized clinical trial of adult patients initiating ART at clinics in urban Nairobi and rural Maseno, Kenya, between 2013–2014. We estimated mortality incidence rates following ART initiation and used Cox proportional hazards regression to identify predictors of mortality within 12 months of ART initiation. Analyses were stratified by clinic site to examine differences in mortality correlates and risk by location. Results: Among 811 participants initiated on ART, the mortality incidence rate within a year of initiating ART was 7.44 per 100 person-years (95% CI 5.71, 9.69). Among 207 Maseno and 612 Nairobi participants initiated on ART, the mortality incidence rates (per 100 person-years) were 12.78 (95% CI 8.49, 19.23) and 5.72 (95% CI 4.05, 8.09). Maseno had a 2.20-fold greater risk of mortality than Nairobi (95% CI 1.29, 3.76; P = 0.004). This association remained [adjusted hazard ratio (HR) = 2.09 (95% CI 1.17, 3.74); P = 0.013] when adjusting for age, gender, education, pre-treatment drug resistance (PDR), and CD4 count, but not when adjusting for BMI. In unadjusted analyses, other predictors (P<0.05) of mortality included male gender (HR = 1.74), age (HR = 1.04 for 1-year increase), fewer years of education (HR = 0.92 for 1-year increase), unemployment (HR = 1.89), low body mass index (BMI<18.5 m/kg2; HR = 4.99), CD4 count <100 (HR = 11.67) and 100–199 (HR = 3.40) vs. 200–350 cells/μL, and pre-treatment drug resistance (PDR; HR = 2.49). The increased mortality risk associated with older age, males, and greater education remained when adjusted for location, age, education and PDR, but not when adjusted for BMI and CD4 count. PDR remained associated with increased mortality risk when adjusted for location, age, gender, education, and BMI, but not when adjusted for CD4 count. CD4 and BMI associations with increased mortality risk persisted in multivariable analyses. Despite similar baseline CD4 counts across locations, mortality risk associated with low CD4 count, low BMI, and PDR was greater in Maseno than Nairobi in stratified analyses. Conclusions: High short-term post-ART mortality was observed, partially due to low CD4 count and BMI at presentation, especially in the rural setting. Male gender, older age, and markers of lower socioeconomic status were also associated with greater mortality risk. Engaging patients earlier in HIV infection remains critical. PDR may influence short-term mortality and further studies to optimize management will be important in settings with increasing PDR. [ABSTRACT FROM AUTHOR]

Background: Active management of third stage of labor is the most indispensable intervention to avert post-partum hemorrhage which is one of the typical causes of maternal morbidity and mortality. Therefore, the aim of the study was to assess practice and factors associated with active management of third stage of labor among obstetric care providers in referral hospitals. Methods: Institution based cross-sectional study design was conducted from April 1–30, 2018. Simple random sampling technique was used to select a total of 356 obstetric care providers. Data were collected using pretested, structured and self-administered questionnaires. Data were entered to Epi data version 3.1 statistical software and exported to SPSS 23 for analysis. Bivariate and multivariate logistic regression analyses were performed to identify associated factors. P value <0.05 with 95% confidence level were used to declare statistical significance. Result: This study revealed that practice of active management of third stage of labor was 61.2%. Age group of 20–30 years [AOR = 1.95 (95%CI;1.13–3.38)], Being male obstetric care provider [AOR = 1.74 (95%CI;1.03–2.94)], having work experience ≥2 years [AOR = 1.95(95%CI;1.13–3.38)], availability of oxytocin [AOR = 5.46 (95%CI; 2.41–12.3)], having exposure to manage third stage of labor [AOR = 2.91(95%CI; 1.55–5.48)], and having good knowledge [AOR = 2.67 (95%CI; 1.46–4.90)], were the factors associated with practice. Conclusion: This study showed that practice of active management of third stage of labor was high. Age group between 20–30 years, being a male obstetric care provider, having ≥2years work experience, availability of oxytocin, exposure to third stage management and having good knowledge were factors associated with practice. Therefore, all referral hospitals and concerned bodies need efforts to focus on providing training to increase health care provider’s knowledge so as to sustain good practice through appropriate interventions. [ABSTRACT FROM AUTHOR]

Background and objective: Trial registration is widely endorsed as it is considered not only to enhance transparency and quality of reporting but also to help safeguard against outcome reporting bias and probably spin, known as specific reporting that could distort the interpretation of results thus mislead readers. We planned to investigate the current registration status of recently published randomized controlled trials (RCTs) of acupuncture, outcome reporting bias in the prospectively registered trials, and the association between trial registration and presence of spin and methodological factors in acupuncture RCTs. Methods: Acupuncture RCTs published in English in recent 5 years (January 2013 to December 2017) were searched in PubMed, Cochrane Central Register of Controlled Trials, and EMBASE. Trial registration records identified in the publications and trial registries were classified into prospectively registered, retrospectively registered, or unregistered. Primary outcomes were identified and the direction of the results was judged as statistically significant (positive) or statistically nonsignificant (negative). We compared registered and published primary outcomes to assess outcome reporting bias and assessed whether discrepancies favored statistically significant outcomes. Frequency and strategies of spin in published reports with statistically nonsignificant results for primary outcomes were then identified. We also analyzed whether the trial registration status was associated with spin and quality of methodological factors. Results: Of the 322 included RCTs, 41.9% (n = 135) were prospectively registered. Among 64 studies that were prospectively registered and specified primary outcomes, 25 trials had the discrepancies between the registered and published primary outcomes and 60% of them (15 trials) favored the statistically significant findings. Among 169 studies that specified primary outcomes, trial registration status was not associated with the direction of results, i.e., statistically significant or not. Spin was identified in 56.4% out of 78 studies with statistically nonsignificant primary outcomes and claiming efficacy with no consideration of statistically nonsignificant primary outcomes was the most common strategy for spin. Trial registration status was not statistically different between studies with and without spin. Conclusion: While trial registration seemed to have improved over time, primary outcomes in registered records and publications were often inconsistent, tending to favor statistically significant findings and spin was common in studies with statistically nonsignificant primary outcomes. Journal editors and researchers in this field should be alerted to still prevalent reporting bias and spin. [ABSTRACT FROM AUTHOR]

Background: It remains unknown which is the optimal first-line treatment regimen for patients with advanced epidermal growth factor receptor (EGFR)-mutated non-small cell lung cancer (NSCLC). We performed a network meta-analysis to address this important issue. Methods: PubMed, Embase, Cochrane Library, Web of Science and major international scientific meetings were searched for relevant randomized controlled trials (RCTs). Progression-free survival (PFS) data was the primary outcome of interest, and overall survival (OS) and serious adverse events (SAEs) were the secondary outcomes of interests, reported as hazard ratio (HR) or odds ratio (OR) and 95% confidence intervals (CIs). Results: 25 RCTs with a total of 5005 patients randomized to receive seven treatments were included in the meta-analysis. Third-generation tyrosine kinase inhibitor (TKI) (osimertinib) and first-generation TKIs (F-TKIs) in combination with chemotherapy (F-TKIs+CT) were more effective than F-TKIs alone in terms of PFS (HR = 0.46, 95% CI: 0.22–0.93; P = 0.031 and HR = 0.62, 95% CI: 0.39–0.98; P = 0.041) and OS (HR = 0.63, 95% CI: 0.43–0.91; P = 0.014 and HR = 0.73, 95% CI: 0.57–0.92; P = 0.008). Second-generation TKIs (S-TKIs) showed significant OS advantage over F-TKIs (HR = 0.83, 95% CI: 0.70–0.99; P = 0.04). Based on treatment ranking in terms of PFS and OS, osimertinib had the highest probability of being the most effective treatment (89% and 86%) and with the best tolerability. F-TKIs+CT was ranked the second-most effective regimen, but with relatively high risk of SAEs. Conclusions: Osimertinib seemed to be the most preferable first-line treatment in advanced EGFR-mutated NSCLC. However, limitations of the study including a single RCT investigating osimertinib and immature OS data need to be considered. [ABSTRACT FROM AUTHOR]

Acinetobacter baumannii, has been developing resistance to even the last line of drugs. Antimicrobial peptides (AMPs) to which bacteria do not develop resistance easily may be the last hope. A few independent experimental studies have designed and studied the activity of AMPs on A. baumannii, however the number of such studies are still limited. With the goal of developing a rational approach to the screening of AMPs against A. baumannii, we carefully curated the drug activity data from 75 cationic AMPs, all measured with a similar protocol, and on the same ATCC 19606 strain. A quantitative model developed and validated with a part of the data. While the model may be used for predicting the activity of any designed AMPs, in this work, we perform an in silico screening for the entire database of naturally occurring AMPs, to provide a rational guidance in this urgently needed drug development. [ABSTRACT FROM AUTHOR]

Objective: We assessed the impact of intravenous (IV) infusion versus intramuscular (IM) oxytocin on postpartum blood loss and rates of postpartum hemorrhage (PPH) when administered during the third stage of labor. While oxytocin is recommended for prevention of PPH, few double-blind studies have compared outcomes by routes of administration. Methods: A double-blind, placebo-controlled randomized trial was conducted at a hospital in Argentina. Participants were assigned to receive 10 IU oxytocin via IV infusion or IM injection and a matching saline ampoule for the other route after vaginal birth. Blood loss was measured using a calibrated receptacle for a 1-hour minimum. Shock index (SI) was also calculated, based on vital signs measurements, and additional interventions were recorded. Primary outcomes included: the frequency of blood loss ≥500ml and mean blood loss. Results: 239 (IV infusion) and 241 (IM) women were enrolled with comparable baseline characteristics. Mean blood loss was 43ml less in the IV infusion group (p = 0.161). Rates of blood loss ≥500ml were similar (IV infusion = 21%; IM = 24%, p = 0.362). Women in the IV infusion group received significantly fewer additional uterotonics (5%), than women in the IM group (12%, p = 0.007). Women with PPH in the IM group experienced a larger increase in SI after delivery, which may have influenced recourse to additional interventions. Conclusions: The route of oxytocin administration for PPH prevention did not significantly impact measured blood loss after vaginal birth. However, differences were observed in recourse to additional uterotonics, favoring IV infusion over IM. In settings where IV lines are routinely placed, oxytocin infusion may be preferable to IM injection. [ABSTRACT FROM AUTHOR]

• Discussed the significance of in silico CYP450 prediction in drug discovery. • Introduced the major functions and usages of mainstream in silico CYP450 prediction online tools and software packages. • Summarized inhibitor, inducer and substrate information for 52 most frequently prescribed drugs for their interactions with CYP1A2, CYP2C9, CYP2C19, CYP2D6, and CYP3A4 sub-enzymes. • Assessed and compared the performance of four online tools and software package in inhibitor prediction for CYP1A2, CYP2C9, CYP2C19, CYP2D6, and CYP3A4 sub-enzymes. • Provided guidance on selecting suitable in silico tools to predict whether a compound is an inhibitor of a specific CYP450 sub-enzyme. 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. [ABSTRACT FROM AUTHOR]

Human parasitic nematodes are the causative agents of lymphatic filariasis (elephantiasis) and onchocerciasis (river blindness), diseases that are endemic to more than 80 countries and that consistently rank in the top ten for the highest number of years lived with disability. These filarial nematodes have evolved an obligate mutualistic association with an intracellular bacterium, Wolbachia, a symbiont that is essential for the successful development, reproduction, and survival of adult filarial worms. Elimination of the bacteria causes adult worms to die, making Wolbachia a primary target for developing new interventional tools to combat filariases. To further explore Wolbachia as a promising indirect macrofilaricidal drug target, the essential cellular processes that define the symbiotic Wolbachia-host interactions need to be identified. Genomic analyses revealed that while filarial nematodes encode all the enzymes necessary for glycolysis, Wolbachia does not encode the genes for three glycolytic enzymes: hexokinase, 6-phosphofructokinase, and pyruvate kinase. These enzymes are necessary for converting glucose into pyruvate. Wolbachia, however, has the full complement of genes required for gluconeogenesis starting with pyruvate, and for energy metabolism via the tricarboxylic acid cycle. Therefore, we hypothesized that Wolbachia might depend on host glycolysis to maintain a mutualistic association with their parasitic host. We did conditional experiments in vitro that confirmed that glycolysis and its end-product, pyruvate, sustain this symbiotic relationship. Analysis of alternative sources of pyruvate within the worm indicated that the filarial lactate dehydrogenase could also regulate the local intracellular concentration of pyruvate in proximity to Wolbachia and thus help control bacterial growth via molecular interactions with the bacteria. Lastly, we have shown that the parasite’s pyruvate kinase, the enzyme that performs the last step in glycolysis, could be a potential novel anti-filarial drug target. Establishing that glycolysis is an essential component of symbiosis in filarial worms could have a broader impact on research focused on other intracellular bacteria-host interactions where the role of glycolysis in supporting intracellular survival of bacteria has been reported. [ABSTRACT FROM AUTHOR]

Observational studies have demonstrated that de-escalation of antimicrobial therapy is independently associated with lower mortality. This most probably results from confounding by indication. Reaching clinical stability is associated with the decision to de-escalate and with survival. However, studies rarely adjust for this confounder. We quantified the potential confounding effect of clinical stability on the estimated impact of de-escalation on mortality in patients with community-acquired pneumonia. Data were used from the Community-Acquired Pneumonia immunization Trial in Adults (CAPiTA). The primary outcome was 30-day mortality. We performed Cox proportional-hazards regression with de-escalation as time-dependent variable and adjusted for baseline characteristics using propensity scores. The potential impact of unmeasured confounding was quantified through simulating a variable representing clinical stability on day three, using data on prevalence and associations with mortality from the literature. Of 1,536 included patients, 257 (16.7%) were de-escalated, 123 (8.0%) were escalated and in 1156 (75.3%) the antibiotic spectrum remained unchanged. Crude 30-day mortality was 3.5% (9/257) and 10.9% (107/986) in the de-escalation and continuation groups, respectively. The adjusted hazard ratio of de-escalation for 30-day mortality (compared to patients with unchanged coverage), without adjustment for clinical stability, was 0.39 (95%CI: 0.19–0.79). If 90% to 100% of de-escalated patients were clinically stable on day three, the fully adjusted hazard ratio would be 0.56 (95%CI: 0.27–1.12) to 1.04 (95%CI: 0.49–2.23), respectively. The simulated confounder was substantially stronger than any of the baseline confounders in our dataset. Quantification of effects of de-escalation on patient outcomes without proper adjustment for clinical stability results in strong negative bias. This study suggests the effect of de-escalation on mortality needs further well-designed prospective research to determine effect size more accurately. [ABSTRACT FROM AUTHOR]

Background: An earlier open label, prospective, non-randomized, non-comparative, multi-centric study conducted within public health facilities in Bihar, India (CTRI/2012/08/002891) measured the field effectiveness of three new treatment regimens for visceral leishmaniasis (VL): single dose AmBisome (SDA), and combination therapies of AmBisome and miltefosine (AmB+Milt) and miltefosine and paromomycin (Milt+PM) up to 6 months follow-up. The National Vector Borne Disease Control Program (NVBDCP) recommended an extended follow up at 12 months post-treatment of the original study cohort to quantify late relapses. Methods: The 1,761 patients enrolled in the original study with the three new regimens were contacted and traced between 10 and 36 months following completion of treatment to determine their health status and any occurrence of VL relapse. Results: Of 1,761 patients enrolled in the original study, 1,368 were traced at the extended follow-up visit: 711 (80.5%), 295 (83.2%) and 362 (71.5%) patients treated with SDA, AmB+Milt and Milt+PM respectively. Of those traced, a total of 75 patients were reported to have relapsed by the extended follow-up; 45 (6.3%) in the SDA, 25 (8.5%) in the AmB+Milt and 5 (1.4%) in the Milt+PM arms. Of the 75 relapse cases, 55 had already been identified in the 6-months follow-up and 20 were identified as new cases of relapse at extended follow-up; 7 in the SDA, 10 in the AmB+Milt and 3 in the Milt+PM arms. Conclusion: Extending follow-up beyond the standard 6 months identified additional relapses, suggesting that 12-month sentinel follow-up may be useful as a programmatic tool to better identify and quantify relapses. With limited drug options, there remains an urgent need to develop effective new chemical entities (NCEs) for VL. [ABSTRACT FROM AUTHOR]

Background: Commercial or industry funding is associated with outcomes that favour the study funder in published studies, across various areas of research. However, it is currently unclear whether there are differences between trials with and without industry involvement at the stage of trial registration. Objective: To determine whether industry involvement (industry sponsorship, funding, or collaboration) is associated with trial characteristics at the time of trial registration. Methods: We conducted a cross-sectional analysis of all interventional studies registered on the Australian New Zealand Clinical Trials Registry in 2017 and classified them by industry involvement. We analysed whether there were differences in study characteristics (including type of control, sample size, study phase, randomisation, registration timing, and purpose of study) by industry involvement. Results: Industry involvement was reported by 21% of the 1,433 included trials. Only 40% of trials with industry involvement used an active control compared to 58% of non-industry trials (OR = 0.49, 95%CI = 0.38 to 0.63, p < .001), and industry trials reported smaller sample sizes (Median(IQR)industry = 45(24–100), Median(IQR)non-industry = 70(35–160), Mean Difference = -153, 95% CI = -233 to -75, p < .001). Industry trials were more likely to be earlier phase trials (Χ2(df) = 71.46(4), p < .001). There was no difference in use of randomisation between industry (70%) and non-industry trials (73%) (OR = 0.88, 95%CI = 0.67–1.20, p = .38). Eighty-three percent of industry trials compared to 70% of non-industry trials were prospectively registered (OR = 2.02, 95%CI = 1.47–2.82, p < .001). Industry trials were more likely to assess treatment (85%), rather than prevention, education or diagnosis compared to non-industry trials (64%) (OR = 3.02, 95%CI = 2.17–4.32, p < .001). Conclusion: The current study gives insight into differences in trial characteristics by industry involvement at registration stage. There was a reduced use of active controls in trials with industry involvement which has previously been proposed as a mechanism behind more favourable results. Non-industry funders and sponsors are crucial to ensure research addresses not only treatments, but also prevention, diagnosis and education questions. [ABSTRACT FROM AUTHOR]

In pediatric burns the use of systemic antibiotic prophylaxis is a standard procedure in some burn centers, though its beneficial effect on the infectious complications is debated. The present meta-analysis aimed at determining whether systemic antibiotic prophylaxis prevents infectious complications in pediatric patients with burn injuries. We searched the PubMed, EMBASE, and Cochrane Library databases from inception to August 2019. We included 6 studies, in which event rates of infectious complications were reported in children with burn injuries receiving or not receiving systemic antibiotic prophylaxis. We found that the overall odds ratio (OR) of developing an infection (including local and systemic) was not different between the groups (OR = 1.35; 95% CI, 0.44, 4.18). The chances for systemic infectious complications alone were also not different between antibiotic-treated and non-treated patients (OR = 0.74; 95% CI, 0.38, 1.45). Based on the age, affected total body surface area, and country income level, we did not find any subgroup that benefited from the prophylaxis. Our findings provide quantitative evidence for the inefficacy of systemic antibiotic prophylaxis in preventing infections in pediatric burns. To validate our conclusion, multinational, randomized trials in a diverse population of children with burn injuries are warranted. [ABSTRACT FROM AUTHOR]

Novel manipulations of the well-established multivariate calibration models namely; partial least square regression (PLSR) and support vector regression (SVR) are introduced in the presented comparative study. Two preprocessing methods comprising first derivatization and orthogonal projection to latent structures (OPLS) are implemented prior to modeling with PLSR and SVR. Quantitative determination of pyridostigmine bromide (PR) in existence of its two associated substances; impurity a (IMP A) and impurity b (IMP B); was utilized as a case study for achieving comparison. A series consisting of 16 mixtures with numerous percentages of the studied compounds was applied for implementation of a 3 factor 4 level experimental design. Additionally, a series consisting of 9 mixtures was employed in an independent test to verify the predictive power of the suggested models. Significant improvement of predictive abilities of the two studied chemometric models was attained via implementation of OPLS processing method. The root mean square error of prediction RMSEP for the test set mixtures was employed as a key comparison tool. About PLSR model, RMSEP was found 0.5283 without preprocessing method, 1.1750 when first derivative data was used and 0.2890 when OPLS preprocessing method was applied. With regard to SVR model, RMSEP was found 0.2173 without preprocessing method, 0.3516 when first derivative data was used and 0.1819 when OPLS preprocessing method was applied. [ABSTRACT FROM AUTHOR]