Background Treatments are needed to address the growing prevalence of Alzheimer’s disease (AD). Clinical trials have failed to produce any AD drugs for Food and Drug Administration (FDA) approval since 2003, and the pharmaceutical development process is both time-consuming and costly. Drug repurposing provides an opportunity to accelerate this process by investigating the AD-related effects of agents approved for other indications. These drugs have known safety profiles, pharmacokinetic characterization, formulations, doses, and manufacturing processes. Methods We assessed repurposed AD therapies represented in Phase I, Phase II, and Phase III of the current AD pipeline as registered on ClinicalTrials.gov as of February 27, 2020. Results We identified 53 clinical trials involving 58 FDA-approved agents. Seventy-eight percent of the agents in trials had putative disease-modifying mechanisms of action. Of the repurposed drugs in the pipeline 20% are hematologic-oncologic agents, 18% are drugs derived from cardiovascular indications, 14% are agents with psychiatric uses, 12% are drug used to treat diabetes, 10% are neurologic agents, and the remaining 26% of drugs fall under other conditions. Intellectual property strategies utilized in these programs included using the same drug but altering doses, routes of administration, or formulations. Most repurposing trials were supported by Academic Medical Centers and were not funded through the biopharmaceutical industry. We compared our results to a European trial registry and found results similar to those derived from ClinicalTrials.gov. Conclusions Drug repurposing is a common approach to AD drug development and represents 39% of trials in the current AD pipeline. Therapies from many disease areas provide agents potentially useful in AD. Most of the repurposed agents are generic and a variety of intellectual property strategies have been adopted to enhance their economic value.

Introduction Undergraduate medical education has evolved necessarily with the increasing utilization of technology and the availability of ancillary resources developed for medical students. However, medical educational resources are expensive and there have been few studies validating these resources for their ability to significantly modify student exam performance. Methods A post-exam survey was devised to evaluate medical students for resource usage, student-perceived preparedness, and exam performance. Results Students who felt more prepared for exams performed better than students who felt less prepared (p = .017). Students who watched didactic lectures online and those who utilized peer-to-peer tutoring outperformed students who did not use these resources (p = .035, p = .008). Analyses of the data show that none of the purchased resources utilized significantly improved student exam performance. The majority of students used between six and eight resources for exam preparation. There may be a slightly negative association with the quantity of resources used and exam scores (p = .18). Discussion Contrary to traditional confidence studies that correlate overconfidence with underperformance, medical students who reported feeling more prepared for exams performed better than students who felt less prepared. Conclusion Medical students may have a more complete grasp of their knowledge base and deficits, which may enable a more accurate match between exam expectations and academic performance. This post-exam survey method can be customized and applied to evaluate resource utility as it pertains to specific undergraduate medical education curricula at individual institutions.

Introduction Despite the increase in Alzheimer's disease (AD) cases in the United States, no new treatments have been approved in the United States since 2003. The costs associated with drug development programs are high and serve as a significant deterrent to AD therapeutic investigations. In this study, we analyze the sponsorship data for AD clinical trials conducted since 2016 to assess the fiscal support for AD clinical trials. Methods We analyzed the funding sources of all AD trials over the past 5 years as reported on ClinicalTrials.gov. Results There were 136 trials being conducted for treatments in the US AD therapeutic pipeline on the index date of this study. Among non‐prevention trials, disease‐modifying therapies (DMT) in Phase 3 were almost entirely sponsored by the biopharmaceutical industry; Phase 2 DMT trials were split between the biopharmaceutical industry and funding from the National Institutes of Health (NIH) to academic medical centers (AMCs). The majority of prevention trials received sponsorship from public–private partnerships (PPP). Trials of symptomatic agents are equally likely to have biopharmaceutical or NIH/AMC sponsorship. Most trials with repurposed agents had NIH/AMC funding (89%). Since 2016, there has been consistent growth in the number of trials sponsored both in part and fully by NIH/AMC sources and in PPP, and there has been a reduction in biopharmaceutical company–sponsored trials. Discussion The number of trials supported by the biopharmaceutical industry has decreased over the past 5 years; trials supported from federal sources and PPP have increased. Repurposed compounds are mostly in Phase 2 trials and provide critical mechanistic information.

Background and Objectives Remdesivir is an antiviral drug used to treat coronavirus disease 2019 (COVID-19) with a relatively obscure cardiac effect profile. Previous studies have reported bradycardia associated with remdesivir, but few have examined its clinical characteristics. The objective of this study was to investigate remdesivir associated bradycardia and its associated clinical characteristics and outcomes. Methods This is a single-institution retrospective study that investigated bradycardia in 600 patients who received remdesivir for treatment of COVID-19. A total of 375 patients were included in the study after screening for other known causes of bradycardia (atrioventricular [AV] nodal blockers). All patients were analyzed for episodes of bradycardia from when remdesivir was initiated up to 5 days after completion, a time frame based on the drug’s putative elimination half-life. Univariate and multivariate statistical tests were conducted to analyze the data. Results The mean age of the sample was 56.63 ± 13.23 years. Of patients who met inclusion criteria, 49% were found to have bradycardia within 5 days of remdesivir administration. Compared to the cohort without a documented bradycardic episode, patients with bradycardia were significantly more likely to experience inpatient mortality (22% vs 12%, p = 0.01). The patients with bradycardia were found to have marginally higher serum D-dimer levels (5.2 vs 3.4 µg/mL, p = 0.05) and were more likely to undergo endotracheal intubation (28% vs 14%, p = 0.008). Male sex, hyperlipidemia, and bradycardia within 5 days of completing remdesivir were significant predictors of inpatient mortality. No significant differences in length of stay were found. Conclusions Bradycardia that occurs during or shortly after remdesivir treatment in COVID-19 patients may be associated with an increased rate of in-hospital mortality. However, COVID-19 and its cardiac complications cannot be excluded as potential contributors of bradycardia in the present study. Future studies are needed to further delineate the cardiac characteristics of COVID-19 and remdesivir. Supplementary Information The online version contains supplementary material available at 10.1007/s40261-022-01187-x.

Background:Retrospective chart review studies may be delayed by inability to export clean clinical data from an electronic medical record (EMR) or data repository. Macros are preprogrammed procedures that can be used in Microsoft Excel to help streamline the process of cleaning clinical datasets. Objectives: To demonstrate how macros may be useful for researchers at community hospitals and smaller academic health centers that lack informatics support. Methods: Using an intrinsic function of our institution's EMR, vital signs and lab results from 20 individual hospitalizations were exported to a spreadsheet. Two macros were developed to sort through these datasets and output them into a specified format. The speed of macroassisted data cleaning was compared to manual transcription. Results: Time spent on data cleaning was significantly reduced when using macro-assisted sorting compared to the manual approach for both vital signs (46.5 seconds versus 12.3 minutes per record, a 94% reduction; P < 0.001) and labs (13.7 seconds versus 2.6 minutes per record, a 91% reduction; P < 0.001). Conclusions:Macros offer a flexible and efficient tool for cleaning large sets of clinical data, particularly when an institution lacks informatics support or EMR functionality to export clinical data in an analysis-ready format.