Pharmacovigilance in patients with diabetes: A data-driven analysis identifying specific RAS antagonists with adverse pulmonary safety profiles that have implications for COVID-19 morbidity and mortality

In-silico approaches to assessing multiple high-level drug-drug and drug-disease adverse drug effects

INTRODUCTION

Pharmacovigilance plays a pivotal role in monitoring adverse events (AEs) related to chemical substances in human/animal populations. With increasing spontaneous-reporting systems, researchers turned to in-silico approaches to efficiently analyze drug safety profiles. Here, we review in-silico methods employed for assessing multiple drug-drug/drug-disease AEs covered by comparative analyses and visualization strategies.

AREAS COVERED

Disproportionality, involving multi-stage statistical methodologies and data processing, identifies safety signals among drug-AE pairs. By stratifying data based on disease indications/demographics, researchers address confounders and assess drug safety. Comparative analyses, including clustering techniques and visualization techniques, assess drug similarities, patterns, and trends, calculate correlations, and identify distinct toxicities. Furthermore, we conducted a thorough Scopus search on 'pharmacovigilance,' yielding 5,836 publications spanning 2003 to 2023.

EXPERT OPINION

Pharmacovigilance relies on diverse data sources, presenting challenges in the integration of in-silico approaches and requiring compliance with regulations and AI adoption. Systematic use of statistical analyses enables identifications of potential risks with drugs. Frequentist and Bayesian methods are used in disproportionalities, each with its strengths and weaknesses. Integration of pharmacogenomics with pharmacovigilance enables personalized medicine, with AI further enhancing patient engagement. This multidisciplinary approach holds promise, improving drug efficacy and safety, and should be a core mission of One-Health studies.

Understanding the effects of COVID-19 on patients with diabetic nephropathy: a systematic review

Background

Diabetic nephropathy is one of the consequences of diabetes mellitus that causes a continuous decline in the eGFR. After the COVID-19 pandemic, studies have shown that patients with diabetic nephropathy who had contracted COVID-19 have higher rates of morbidity and disease progression. The aim of this study was to systematically review the literature to determine and understand the effects and complications of SARS-CoV-2 on patients with diabetic nephropathy.

Materials and methods

The authors' research protocol encompassed the study selection process, search strategy, inclusion/exclusion criteria, and a data extraction plan. A systematic review was conducted by a team of five reviewers, with an additional reviewer assigned to address any discrepancies. To ensure comprehensive coverage, the authors employed multiple search engines including PubMed, ResearchGate, ScienceDirect, SDL, Ovid, and Google Scholar.

Results

A total of 14 articles meeting the inclusion criteria revealed that COVID-19 directly affects the kidneys by utilizing ACE2 receptors for cell entry, which is significant because ACE2 receptors are widely expressed in the kidney.

Conclusion

COVID-19 affects kidney health, especially in individuals with diabetic nephropathy. The mechanisms include direct viral infection and immune-mediated injury. Early recognition and management are vital for improving the outcomes.

A retrospective study of adverse drug events in anticoagulant administration with relevance to COVID-19

Initial studies in COVID-19 patients reported lower mortality rates associated with the use of the drug heparin, a widely used anticoagulant. The objective of this analysis was to determine whether there are adverse events associated with the administration of anticoagulants, and specifically how this might apply in patients known to have COVID-19. Data for this study were obtained from the Food and Drug Administration's Adverse Event Reporting System (FAERS) public database and from the NIH's clinical trials website. Proportional Reporting Ratios (PRR) with lower 95% confidence intervals (lower CI) and empirical Bayes geometric mean (EBGM) scores with lower 95% confidence limits were calculated for data from the FAERS database where the adverse events studied mimicked COVID-19 symptoms.

Data-driven methodology for discovery and response to pulmonary symptomology in hypertension through statistical learning and data mining: Application to COVID-19 related pharmacovigilance

Background: Potential therapy and confounding factors including typical co-administered medications, patient's disease states, disease prevalence, patient demographics, medical histories, and reasons for prescribing a drug often are incomplete, conflicting, missing, or uncharacterized in spontaneous adverse drug event (ADE) reporting systems. These missing or incomplete features can affect and limit the application of quantitative methods in pharmacovigilance for meta-analyses of data during randomized clinical trials.

Methods: Data from patients with hypertension were retrieved and integrated from the FDA Adverse Event Reporting System. 134 antihypertensive drugs out of 1151 drugs were filtered and then evaluated using the Empirical Bayes Geometric Mean (EBGM) of the posterior distribution to build ADE-drug profiles with an emphasis on the pulmonary ADEs (pADE). Afterward, the Graphical Least Absolute Shrinkage and Selection Operator (GLASSO) captured drug associations based on pADEs by correcting hidden factors and confounder misclassification. Selected drugs were then compared using the Friedman test in drug classes and clusters obtained from GLASSO.

Results: Following multiple filtering stages to exclude insignificant and noise-driven reports, we found that drugs from antihypertensives agents, urologicals, and antithrombotic agents (macitentan, bosentan, epoprostenol, selexipag, sildenafil, tadalafil, and beraprost) form a similar class with a significantly higher incidence of pADEs. Macitentan and bosentan were associates with 64% and 56% of pADEs, respectively. Because these two medications are prescribed in diseases affecting pulmonary function and may be likely to emerge among the highest reported pADEs, in fact, they serve to validate the methods utilized here. Conversely, doxazosin and rilmenidine were found to have the least pADEs in selected drugs from hypertension patients. Nifedipine and candesartan were also found by signal detection methods to form a drug cluster, shown by several studies an effective combination of these drugs on lowering blood pressure and appeared an improved side effect profile in comparison with single-agent monotherapy.

Conclusions: We consider pADE profiles in multiple long-standing groups of therapeutics including antihypertensive agents, antithrombotic agents, beta-blocking agents, calcium channel blockers, or agents acting on the renin-angiotensin system, in patients with hypertension associated with high-risk for COVID-19. We found that several individual drugs have significant differences between their drug classes and compared to other drug classes. For instance, macitentan and bosentan from endothelin receptor antagonists show major concern while doxazosin and rilmenidine exhibited the least pADEs compared to the outcomes of other drugs. Using techniques in this study, we assessed and confirmed the hypothesis that drugs from the same drug class could have very different pADE profiles affecting outcomes in acute respiratory illness.

Funding: GJW and MJD accepted funding from BioNexus KC for funding on this project, but BioNexus KC had no direct role in this article.

Immune response variables and viral mutations impact on COVID-19 reinfection and relapse

The possibility of human reinfection with SARS-CoV-2, the coronavirus responsible for COVID-19, has not previously been thoroughly investigated. Although it is generally believed that virus-specific antibodies protect against COVID-19 pathogenesis, their duration of function and temporal activity remain unknown. Contrary to media reports that people retain protective antibody responses for a few months, science does not exclude reinfection and disease relapse shortly after initiating all immune responses during the primary onset of COVID-19. Despite production of antiviral antibodies, activated CD4+/CD8+ lymphocytes, and long-lived memory B cells, susceptibility to reinfection in humans for extended periods cannot be precluded due to repeated exposures to coronavirus or potential reactivation of the virus due to incomplete virus clearance. However, the mechanism of reinfection remains unknown. The biological characteristics of SARS-CoV-2, such as emergence of multiple mutations in the virus RNA molecules, transmissibility, rates of infection, reactivation and reinfection, can all affect the trajectory of the virus spread. Innate and adaptive immune response variables, differences in underlying diseases, and comorbidities, particularly in high risk individuals, can influence the dynamics of the virus infection. In this article, immune parameters and viral mutations pertaining to reinfection and disease relapse are reviewed and scientific gaps are discussed.

Global Trends in Cancer Nanotechnology: A Qualitative Scientific Mapping Using Content-Based and Bibliometric Features for Machine Learning Text Classification

This study presents a new way to investigate comprehensive trends in cancer nanotechnology research in different countries, institutions, and journals providing critical insights to prevention, diagnosis, and therapy. This paper applied the qualitative method of bibliometric analysis on cancer nanotechnology using the PubMed database during the years 2000-2021. Inspired by hybrid medical models and content-based and bibliometric features for machine learning models, our results show cancer nanotechnology studies have expanded exponentially since 2010. The highest production of articles in cancer nanotechnology is mainly from US institutions, with several countries, notably the USA, China, the UK, India, and Iran as concentrated focal points as centers of cancer nanotechnology research, especially in the last five years. The analysis shows the greatest overlap between nanotechnology and DNA, RNA, iron oxide or mesoporous silica, breast cancer, and cancer diagnosis and cancer treatment. Moreover, more than 50% of the information related to the keywords, authors, institutions, journals, and countries are considerably investigated in the form of publications from the top 100 journals. This study has the potential to provide past and current lines of research that can unmask comprehensive trends in cancer nanotechnology, key research topics, or the most productive countries and authors in the field.

Diabetic Nephropathy and COVID-19: The Potential Role of Immune Actors

Nowadays, type II diabetes mellitus, more specifically ensuing diabetic nephropathy, and severe COVID-19 disease are known to be closely associated. The exact mechanisms behind this association are less known. An implication for the angiotensin-converting enzyme 2 remains controversial. Some researchers have started looking into other potential actors, such as neuropilin-1, mitochondrial glutathione, vitamin D, and DPP4. In particular, neuropilin-1 seems to play an important role in the underlying mechanism linking COVID-19 and diabetic nephropathy. We suggest, based on the findings in this review, that its up-regulation in the diabetic kidney facilitates viral entry in this tissue, and that the engagement of both processes leads to a depletion of neuropilin-1, which was demonstrated to be strongly associated with the pathogenesis of DN. More studies are needed to confirm this hypothesis, and research should be directed towards elucidating the potential roles of all these suggested actors and eventually discovering new therapeutic strategies that could reduce the burden of COVID-19 in patients with diabetic nephropathy.

Pulmonary adverse drug event data in hypertension with implications on COVID-19 morbidity

Hypertension is a recognized comorbidity for COVID-19. The association of antihypertensive medications with outcomes in patients with hypertension is not fully described. However, angiotensin-converting enzyme 2 (ACE2), responsible for host entry of the novel coronavirus (SARS-CoV-2) leading to COVID-19, is postulated to be upregulated in patients taking angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin II receptor blockers (ARBs). Here, we evaluated the occurrence of pulmonary adverse drug events (ADEs) in patients with hypertension receiving ACEIs/ARBs to determine if disparities exist between individual drugs within the respective classes using data from the FDA Spontaneous Reporting Systems. For this purpose, we proposed the proportional reporting ratio to provide a statistical summary for the commonality of an ADE for a specific drug as compared to the entire database for drugs in the same or other classes. In addition, a statistical procedure, multiple logistic regression analysis, was employed to correct hidden confounders when causative covariates are underreported or untrusted to correct analyses of drug-ADE combinations. To date, analyses have been focused on drug classes rather than individual drugs which may have different ADE profiles depending on the underlying diseases present. A retrospective analysis of thirteen pulmonary ADEs showed significant differences associated with quinapril and trandolapril, compared to other ACEIs and ARBs. Specifically, quinapril and trandolapril were found to have a statistically significantly higher incidence of pulmonary ADEs compared with other ACEIs as well as ARBs (P < 0.0001) for group comparison (i.e., ACEIs vs. ARBs vs. quinapril vs. trandolapril) and (P ≤ 0.0007) for pairwise comparison (i.e., ACEIs vs. quinapril, ACEIs vs. trandolapril, ARBs vs. quinapril, or ARBs vs. trandolapril). This study suggests that specific members of the ACEI antihypertensive class (quinapril and trandolapril) have a significantly higher cluster of pulmonary ADEs.