Continuous medical and safety monitoring of subject data during a clinical trial is a critical part of evaluating the safety of trial participants and as such is governed by protocol procedures and regulatory guidelines to meet the trial\'s intended objectives. We present an open-source validated graphical tool (clinDataReview R package) which provides access to the trial data with drill-down to individual patient profiles. The tool incorporates functionalities that facilitate detection of error and data inconsistencies requiring follow-up. It supports regular medical monitoring and oversight as well as safety monitoring committees with interactive tables and listings alongside graphical visualizations of the primary safety data in reports. An implementation example is given where the tool is used to deliver validated outputs following FDA/EMA guidelines. As such, this tool enables a more efficient, interactive, and reproducible review of safety data collected during an ongoing clinical trial.

BACKGROUND: Preclinical Alzheimer\'s disease is increasingly studied in clinical trials. Although safety signals are routinely monitored in clinical trial populations with Alzheimer\'s disease, it can be challenging to identify new safety signals against background rates of age-related medical comorbidities.
OBJECTIVE: To report detailed safety data from a cognitively unimpaired older population with evidence of elevated cerebral amyloid levels on amyloid positron emission tomography in the placebo arm of a Phase 3 clinical trial.
METHODS: Phase 3, 4.5-year, multicenter, placebo-controlled trial.
METHODS: Placebo data from the Anti-Amyloid Treatment in Asymptomatic Alzheimer\'s Disease (A4) study.
METHODS: Enrolled participants were aged 65-85 years with a global Clinical Dementia Rating score of 0, a Mini-Mental State Examination score of 25-30, a Wechsler Memory Scale Logical Memory IIa (delayed recall) score of 6-18, and elevated brain amyloid levels on 18F-florbetapir positron emission tomography.
METHODS: Study participants who received placebo were followed up with post-baseline safety measures. Assessments included review of concomitant medication and adverse events, the Columbia Suicide Severity Rating Scale, electrocardiograms, and neuroimaging (brain magnetic resonance imaging).
RESULTS: In total, 591 study participants (mean age [standard deviation] 71.9 [5.0] years) were assigned to and received placebo in the A4 study, and were followed up to 240 weeks. Participants were primarily White (93.9%) and from the United States (86.8%); 60.4% were women. The most common serious adverse events (incidence rate per 100 person-years) were pneumonia (incidence rate=0.4; 95% confidence interval=0.2-0.7) and atrial fibrillation (incidence rate=0.4; 95% confidence interval=0.2-0.7). The most common treatment-emergent adverse events were upper respiratory tract infection (incidence rate=10.9; 95% confidence interval=9.4-12.5), fall (incidence rate=7.7; 95% confidence interval=6.6-9.0), and nasopharyngitis (incidence rate=5.8; 95% confidence interval=4.8-6.9). The most common ischemia-related findings on magnetic resonance imaging were subcortical infarction (incidence rate=1.4; 95% confidence interval=1.0-2.0) and acute ischemia (incidence rate=0.6; 95% confidence interval=0.3-1.0). Emergent amyloid-related imaging abnormalities with hemosiderin deposition occurred in 32.8% of participants who received placebo; the primary factor associated with these events during the post-baseline period was the number of microhemorrhages at baseline (odds ratio=349.9; 95% confidence interval=247.6-494.4; adjusted p<0.001).
CONCLUSIONS: Safety findings in the placebo-treated group from the A4 study provide a robust characterization of expected safety in a clinical trial population with preclinical Alzheimer\'s disease. These results may provide context in planning future studies and safety evaluations during ongoing blinded studies in preclinical Alzheimer\'s disease.

BACKGROUND: The reporting of adverse events (AEs) relating to medical devices is a long-standing area of concern, with suboptimal reporting due to a range of factors including a failure to recognize the association of AEs with medical devices, lack of knowledge of how to report AEs, and a general culture of nonreporting. The introduction of artificial intelligence as a medical device (AIaMD) requires a robust safety monitoring environment that recognizes both generic risks of a medical device and some of the increasingly recognized risks of AIaMD (such as algorithmic bias). There is an urgent need to understand the limitations of current AE reporting systems and explore potential mechanisms for how AEs could be detected, attributed, and reported with a view to improving the early detection of safety signals.
OBJECTIVE: The systematic review outlined in this protocol aims to yield insights into the frequency and severity of AEs while characterizing the events using existing regulatory guidance.
METHODS: Publicly accessible AE databases will be searched to identify AE reports for AIaMD. Scoping searches have identified 3 regulatory territories for which public access to AE reports is provided: the United States, the United Kingdom, and Australia. AEs will be included for analysis if an artificial intelligence (AI) medical device is involved. Software as a medical device without AI is not within the scope of this review. Data extraction will be conducted using a data extraction tool designed for this review and will be done independently by AUK and a second reviewer. Descriptive analysis will be conducted to identify the types of AEs being reported, and their frequency, for different types of AIaMD. AEs will be analyzed and characterized according to existing regulatory guidance.
RESULTS: Scoping searches are being conducted with screening to begin in April 2024. Data extraction and synthesis will commence in May 2024, with planned completion by August 2024. The review will highlight the types of AEs being reported for different types of AI medical devices and where the gaps are. It is anticipated that there will be particularly low rates of reporting for indirect harms associated with AIaMD.
CONCLUSIONS: To our knowledge, this will be the first systematic review of 3 different regulatory sources reporting AEs associated with AIaMD. The review will focus on real-world evidence, which brings certain limitations, compounded by the opacity of regulatory databases generally. The review will outline the characteristics and frequency of AEs reported for AIaMD and help regulators and policy makers to continue developing robust safety monitoring processes.
UNASSIGNED: PRR1-10.2196/48156.

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There is a need to transition from conventional (on-site) clinical trials (CTs) to trials conducted within the comfort of a patient\'s home or community (decentralized CT) through e-consent, remote data monitoring, and telemedicine consults. This shift in trial procedures will positively impact recruitment rates, compliance and participant retention, protocol deviations, and delays or missed visits. Home nursing in CTs (HNCTs) will be an important component of this decentralization effort. A few limitations may impact the implementation of HNCT in India. In this regard, the workstream conducted semi-structured qualitative interviews with experts from diverse domains of CT conduct (researchers from academia and industry, clinicians, investigators, nursing staff, patient research advocates, institutional ethics committee, or institutional review board members, legal experts, and trial participants) to collect their understanding, perspectives, and the ground realities about HNCTs in India. The current review puts forth the key areas that would facilitate the establishment of HNCTs in India and provides recommendations for the same.

Decarbonization of the energy system is a key aspect of the energy transition. Energy storage in the form of chemical bonds has long been viewed as an optimal scheme for energy conversion. With advances in systems engineering, hydrogen has the potential to become a low cost, low emission, energy carrier. However, hydrogen is difficult to contain, it exhibits a low flammability limit (>40000 ppm or 4%), low ignition energy (0.02 mJ), and it is a short-lived climate forcer. Beyond commercially available sensors to ensure safety through spot checks in enclosed environments, new sensors are necessary to support the development of low emission infrastructure for production, transmission, storage, and end use. Efficient scalable broad area hydrogen monitoring motivates lowering the detection limit below that (10 ppm) of best in class commercial technologies. In this perspective, we evaluate recent advances in hydrogen gas sensing to highlight technologies that may find broad utility in the hydrogen sector. It is clear in the near term that a sensor technology suite is required to meet the variable constraints (e.g., power, size/weight, connectivity, cost) that characterize the breadth of the application space, ranging from industrial complexes to remote pipelines. This perspective is not intended to be another standard hydrogen sensor review, but rather provide a critical evaluation of technologies with detection limits preferably below 1 ppm and low power requirements. Given projections for rapid market growth, promising techniques will also be amenable to rapid development in technical readiness for commercial deployment. As such, methods that do not meet these requirements will not be considered in depth.

Batteries play a crucial role as energy storage devices across various industries. However, achieving high performance often comes at the cost of safety. Continuous monitoring is essential to ensure the safety and reliability of batteries. This paper investigates the advancements in battery monitoring technology, focusing on fiber Bragg gratings (FBGs). By examining the factors contributing to battery degradation and the principles of FBGs, this study discusses key aspects of FBG sensing, including mounting locations, monitoring targets, and their correlation with optical signals. While current FBG battery sensing can achieve high measurement accuracies for temperature (0.1 °C), strain (0.1 με), pressure (0.14 bar), and refractive index (6 × 10-5 RIU), with corresponding sensitivities of 40 pm/°C, 2.2 pm/με, -0.3 pm/bar, and -18 nm/RIU, respectively, accurately assessing battery health in real time remains a challenge. Traditional methods struggle to provide real-time and precise evaluations by analyzing the microstructure of battery materials or physical phenomena during chemical reactions. Therefore, by summarizing the current state of FBG battery sensing research, it is evident that monitoring battery material properties (e.g., refractive index and gas properties) through FBGs offers a promising solution for real-time and accurate battery health assessment. This paper also delves into the obstacles of battery monitoring, such as standardizing the FBG encapsulation process, decoupling multiple parameters, and controlling costs. Ultimately, the paper highlights the potential of FBG monitoring technology in driving advancements in battery development.

BACKGROUND: The use of herbal medicines is on the rise throughout the world due to their perceived safety profile. However, incidences of herb-drug, herb-herb and herb-food interactions considering safety aspects have opened new arenas for discussion.
OBJECTIVE: The current study aims to provide comprehensive insights into the various types of herb interactions, the mechanisms involved, their assessment, and historical developments, keeping herbal safety at the central point of discussion.
METHODS: The authors undertook a focused/targeted literature review and collected data from various databases, including Science Direct, Wiley Online Library, Springer, PubMed, and Google Scholar. Conventional literature on herbal remedies, such as those by the WHO and other international or national organizations.
RESULTS: The article considered reviewing the regulations, interaction mechanisms, and detection of herb-herb, herb-drug and herb-food interactions in commonly used yet vital plants, including Glycyrrhiza glabra, Mentha piperita, Aloe barbadensis, Zingiber officinale, Gingko biloba, Withania somnifera, etc. The study found that healthcare professionals worry about patients not informing them about their herbal prescriptions (primarily used with conventional treatment), which can cause herb-drug/herb-food/herb-herb interactions. These interactions were caused by altered pharmacodynamic and pharmacokinetic processes, which might be explained using in-vivo, in-vitro, in-silico, pharmacogenomics, and pharmacogenetics. Nutrivigilance may be the greatest method to monitor herb-food interactions, but its adoption is limited worldwide.
CONCLUSIONS: This article can serve as a lead for clinicians, guiding them regarding herb-drug, herb-food, and herb-herb interactions induced by commonly consumed plant species. Patients may also be counseled to avoid conventional drugs, botanicals, and foods with a restricted therapeutic window.

Multisystem inflammatory syndrome in children (MIS-c) is an uncommon, but serious, inflammatory response that occurs after SARS-CoV-2 infection. As time went by, MIS-c was also reported as a potential adverse event following COVID-19 vaccination. A descriptive analysis was performed of Individual Case Safety Reports (ICSRs) associated with anti COVID-19 vaccines and related to the pediatric population from 2020 to 2022. The present pharmacovigilance study aimed to describe cases of MIS-c following COVID-19 vaccination, stratified by sex, reported in the Vaccine Adverse Events Reporting System (VAERS) and meeting the Brighton Collaboration criteria for case definition. We assessed all suspected cases through the case definition and classification of the Brighton Collaboration Group, and only definitive, probable, and possible cases were included in the analysis. The Reporting Odds Ratio (ROR) with 95% Confidence Interval (CI) was computed to assess if males have a lower/higher probability of reporting ICSRs with MIS-c compared with females. Overall, we found 79 cases of potentially reported MIS-c following vaccination. This study demonstrated that MIS-c following vaccination was more commonly reported for male subjects with a median age of 10 years (IQR 10.0-11.4), especially after the first dose of anti COVID-19 vaccines with a median time to onset of 27 days. Even so, the rate of occurrence of MIS-c following anti COVID-19 vaccines is lower (0.12/100,000 vaccinated subjects; 95% CI, 0.12-0.13). Overall, all ICSRs were serious and caused or prolonged hospitalization. Finally, disproportionality analysis showed that males had a higher reporting probability of MIS-c compared with females following immunization with mRNA COVID-19 vaccines. Since only a few years of marketing are available, further data from real-life contexts are needed.

Background and Objectives: Non-steroidal anti-inflammatory drugs (NSAIDs), which have anti-inflammatory and analgesic properties, are commonly used in the treatment of various, particularly frequent, as well as chronic, conditions in older patients. Due to common polypragmasia in these patients and a high risk of adverse drug reactions (ADRs) and drug interactions, pain management poses a therapeutic challenge. This study describes the importance of ADR reports in the identification of polypharmacy and the ensuing interactions. Materials and Methods: Both healthcare professionals (HPs) and non-healthcare professionals (non-HPs) reports collected in the EudraVigilance database of NSAIDs, including most commonly co-reported medications and reported reactions, were analysed and differences between HPs and non-HPs reports were identified. Results: In the analysed period and group, non-HPs reported more reactions but indicated fewer drugs as suspect or concomitant. The outcomes of our analysis indicate more HP engagement and more detailed reports of serious ADRs when compared to non-serious individual case safety reports (ICSRs) by non-HPs, which appeared more detailed. Such reactions as kidney failure and increased risk of bleeding are known adverse reactions to NSAIDs and common symptoms of their interactions, which were described in the available literature. They were much more frequently reported by HPs than by non-HPs. Non-HPs more frequently reported reactions that may have been considered less significant by HPs. Conclusions: The differences between healthcare professionals\' (HPs) and non-healthcare professionals\' (non-HPs) reports may result from the fact that the reports from patients and their caregivers require a professional medical diagnosis based on symptoms described by the patient or additional diagnostic tests. This means that when appropriately classified, medically verified, and statistically analysed, the data may provide new evidence for the risks of medication use or drug interactions.