BACKGROUND Social media has become a new source for obtaining real-world data on adverse drug reactions. Many studies have investigated the use of social media to detect early signals of adverse drug reactions. However, the trustworthiness of signals derived from social media is questionable. To confirm this, a confirmatory study with a positive control (eg, new black box warnings, labeling changes, or withdrawals) is required. OBJECTIVE This study aimed to evaluate the use of social media in detecting new black box warnings, labeling changes, or withdrawals in advance. METHODS This scoping review adhered to the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews checklist. A researcher searched PubMed and EMBASE in January 2021. Original studies analyzing black box warnings, labeling changes, or withdrawals from social media were selected, and the results of the studies were summarized. RESULTS A total of 14 studies were included in this scoping review. Most studies (8/14, 57.1%%) collected data from a single source, and 10 (71.4%) used specialized health care social networks and forums. The analytical methods used in these studies varied considerably. Three studies (21.4%) manually annotated posts, while 5 (35.7%) adopted machine learning algorithms. Nine studies (64.2%) concluded that social media could detect signals 3 months to 9 years before action from regulatory authorities. Most of these studies (8/9, 88.9%) were conducted on specialized health care social networks and forums. On the contrary, 5 (35.7%) studies yielded modest or negative results. Of these, 2 (40%) used generic social networking sites, 2 (40%) used specialized health care networks and forums, and 1 (20%) used both generic social networking sites and specialized health care social networks and forums. The most recently published study recommends not using social media for pharmacovigilance. Several challenges remain in using social media for pharmacovigilance regarding coverage, data quality, and analytic processing. CONCLUSIONS Social media, along with conventional pharmacovigilance measures, can be used to detect signals associated with new black box warnings, labeling changes, or withdrawals. Several challenges remain; however, social media will be useful for signal detection of frequently mentioned drugs in specialized health care social networks and forums. Further studies are required to advance natural language processing and mine real-world data on social media.
Due to the impermeable structure and barrier function of the blood–brain barrier (BBB), the delivery of therapeutic molecules into the CNS is extremely limited. Nanodelivery systems are regarded as the most effective and versatile carriers for the CNS, as they can transport cargo molecules across the BBB via various mechanisms. This review emphasizes the multi-functionalization strategies of nanodelivery systems and combinatorial approaches for the delivery of therapeutic drugs and genes into the CNS. The characteristics and functions of the BBB and underlying mechanisms of molecular translocation across the BBB are also described.
Efferocytosis of neutrophils/macrophages and differentiation of satellite cells/postnatal muscle stem cells play pivotal roles in skeletal muscle regeneration. The aim of this study is to provide a beneficial tactic on muscle regeneration using intramuscular delivery systems with nanoparticles containing CD146. Herein, we construct an injectable, in situ hydrogel system consisting of CD146, IGF-1, collagen I/III, and poloxamer 407, termed CIC gel. The thermoreversible phase transition of the CIC gel at body temperature results in the sustained-release of CD146 and IGF-1 after muscular subcutaneous administration. The secreted CD146 then binds to VEGFR2 on muscle surface and effectively induces efferocytosis of neutrophils and macrophages. Consequently, these combined molecules activate muscle regeneration via autophagy and suppress muscle inflammation and apoptosis. In this report, we provide an applicable concept of the myogenesis-activating protein formulation, broadening the thermoreversible hydrogel to the protein therapeutics for damaged muscle recovery.
Social media has become a new source for obtaining real-world data on adverse drug reactions. Many studies have investigated the use of social media to detect early signals of adverse drug reactions. However, the trustworthiness of signals derived from social media is questionable. To confirm this, a confirmatory study with a positive control (eg, new black box warnings, labeling changes, or withdrawals) is required.This study aimed to evaluate the use of social media in detecting new black box warnings, labeling changes, or withdrawals in advance.This scoping review adhered to the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews checklist. A researcher searched PubMed and EMBASE in January 2021. Original studies analyzing black box warnings, labeling changes, or withdrawals from social media were selected, and the results of the studies were summarized.A total of 14 studies were included in this scoping review. Most studies (8/14, 57.1%%) collected data from a single source, and 10 (71.4%) used specialized health care social networks and forums. The analytical methods used in these studies varied considerably. Three studies (21.4%) manually annotated posts, while 5 (35.7%) adopted machine learning algorithms. Nine studies (64.2%) concluded that social media could detect signals 3 months to 9 years before action from regulatory authorities. Most of these studies (8/9, 88.9%) were conducted on specialized health care social networks and forums. On the contrary, 5 (35.7%) studies yielded modest or negative results. Of these, 2 (40%) used generic social networking sites, 2 (40%) used specialized health care networks and forums, and 1 (20%) used both generic social networking sites and specialized health care social networks and forums. The most recently published study recommends not using social media for pharmacovigilance. Several challenges remain in using social media for pharmacovigilance regarding coverage, data quality, and analytic processing.Social media, along with conventional pharmacovigilance measures, can be used to detect signals associated with new black box warnings, labeling changes, or withdrawals. Several challenges remain; however, social media will be useful for signal detection of frequently mentioned drugs in specialized health care social networks and forums. Further studies are required to advance natural language processing and mine real-world data on social media.
In response to the coronavirus disease-19 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), global efforts are focused on the development of new therapeutic interventions. For the treatment of COVID-19, selective lung-localizing strategies hold tremendous potential, as SARS-CoV-2 invades the lung via ACE2 receptors and causes severe pneumonia. Similarly, recent reports have shown the association of COVID-19 with decreased 25-hydroxycholesterol (25-HC) and increased cytokine levels. This mechanism, which involves the activation of inflammatory NF-κB- and SREBP2-mediated inflammasome signaling pathways, is believed to play a crucial role in COVID-19 pathogenesis, inducing acute respiratory distress syndrome (ARDS) and sepsis. To resolve those clinical conditions observed in severe SARS-CoV-2 patients, we report 25-HC and didodecyldimethylammonium bromide (DDAB) nanovesicles (25-HC@DDAB) as a COVID-19 drug candidate for the restoration of intracellular cholesterol level and suppression of cytokine storm. Our data demonstrate that 25-HC@DDAB can selectively accumulate the lung tissues and effectively downregulate NF-κB and SREBP2 signaling pathways in COVID-19 patient-derived PBMCs, reducing inflammatory cytokine levels. Altogether, our findings suggest that 25-HC@DDAB is a promising candidate for the treatment of symptoms associated with severe COVID-19 patients, such as decreased cholesterol level and cytokine storm.
Recent studies on osteosarcoma regimens have mainly focused on modifying the combination of antineoplastic agents rather than enhancing the therapeutic efficacy of each component. Here, an albumin nanocluster (NC)-assisted methotrexate (MTX), doxorubicin (DOX), and cisplatin (MAP) regimen with improved antitumor efficacy is presented. Human serum albumin (HSA) is decorated with thiamine pyrophosphate (TPP) to increase the affinity to the bone tumor microenvironment (TME). MTX or DOX (hydrophobic MAP components) is adsorbed to HSA-TPP via hydrophobic interactions. MTX- or DOX-adsorbed HSA-TPP NCs exhibit 20.8- and 1.64-fold higher binding affinity to hydroxyapatite, respectively, than corresponding HSA NCs, suggesting improved targeting ability to the bone TME via TPP decoration. A modified MAP regimen consisting of MTX- or DOX-adsorbed HSA-TPP NCs and free cisplatin displays a higher synergistic anticancer effect in HOS/MNNG human osteosarcoma cells than conventional MAP. TPP-decorated NCs show 1.53-fold higher tumor accumulation than unmodified NCs in an orthotopic osteosarcoma mouse model, indicating increased bone tumor distribution. As a result, the modified regimen more significantly suppresses tumor growth in vivo than solution-based conventional MAP, suggesting that HSA-TPP NC-assisted MAP may be a promising strategy for osteosarcoma treatment.
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