An integrative approach using real-world data to identify alternative therapeutic uses of existing drugs

Trailblazing real-world-data to confront hepatocellular carcinoma - disinterring repurposable drugs by amalgamating avant-garde stratagems

Drug repurposing is preferred over de-novo drug discovery to unveil the therapeutic applications of existing drug candidates before investing considerable resources in unexplored novel chemical entities. This study demonstrated multifaceted stratagems to reconnoiter promising repurposable candidates against Hepatocellular Carcinoma (HCC) by amalgamating Real-World-Data (RWD) with bioinformatics algorithms corroborated with in-silico and in-vitro studies. At the outset, the RWD from the Food and Drug Administration Adverse Event Reporting System (FAERS) was explored to navigate signals to retrieve repurposable drugs that are inversely associated with HCC via Disproportionality Analysis. Further, transcriptomic analysis was used to capture the potential targets of HCC. Following this, the interactions between repurposable drugs and HCC targets were virtually demonstrated via molecular docking and Molecular Dynamics Simulations (MDS). Furthermore, additional cytotoxicity and gene expression experiments were conducted to corroborate the results. Overall, 64 drugs with Drug Event >5 were shortlisted as prospective repurposable drugs as per the RWD obtained from FAERS. The transcriptomic analysis highlighted significant upregulation of Cyclin A2 (CCNA2) in HCC, which activates Cyclin Dependent Kinase 2 (CDK2). Further, in-silico studies identified Losartan and Allopurinol, with docking scores of -7.11 and -6.219, respectively, as potential repurposable drugs. The selected drugs underwent further scrutiny through in-vitro studies. The treatment of HepG2 cells with Allopurinol resulted in significant downregulation of CCNA2/CDK2 expression with an elevation in reactive oxygen species levels, uncovering Allopurinol's anticancer mechanism through cellular apoptosis. This study suggests the importance of RWD in drug repurposing and the potential of Allopurinol as a repurposable drug against HCC.

Time-to-onset Analysis of Rhabdomyolysis due to Different Proton Pump Inhibitors Using a Pharmacovigilance Database

BACKGROUND/AIM

Recent research has increasingly demonstrated an association between proton pump inhibitors (PPIs) and serious adverse events. This study aimed to evaluate the association between PPI and rhabdomyolysis (RM), examining its time-to-onset profiles using the Japanese Adverse Drug Event Report (JADER) database.

PATIENTS AND METHODS

Data spanning from April 2004 to March 2022 were used. The association between PPIs and RM was evaluated using the reporting odds ratio (ROR), adjusted for sex and age. Subsequent analyses were conducted after excluding cases involving concomitant use of statins or fibrates. Furthermore, the onset time of RM and Weibull distribution parameters were calculated to evaluate the expression profile of RM, and the outcomes were examined.

RESULTS

RM was associated with the use of esomeprazole, omeprazole, and rabeprazole, even in the absence of concomitant statin or fibrate use. The median time to RM onset varied among PPIs, ranging from 6.5 to 127 d. The Weibull distribution parameters indicated that the hazard types of nearly all orally administered PPIs were classified as early failure or close to random failure. Regarding outcomes, cases of death were reported for all PPIs except vonoprazan.

CONCLUSION

The findings suggest the need for vigilant monitoring of RM during PPI administration, particularly in the early stages, considering the varying onset times.

Drug Repurposing Using FDA Adverse Event Reporting System (FAERS) Database

Drug repurposing is an emerging approach to reassigning existing pre-approved therapies for new indications. The FDA Adverse Event Reporting System (FAERS) is a large database of over 28 million adverse event reports submitted by medical providers, patients, and drug manufacturers and provides extensive drug safety signal data. In this review, four common drug repurposing strategies using FAERS are described, including inverse signal detection for a single disease, drug-drug interactions that mitigate a target ADE, identifying drug-ADE pairs with opposing gene perturbation signatures and identifying drug-drug pairs with congruent gene perturbation signatures. The purpose of this review is to provide an overview of these different approaches using existing successful applications in the literature. With the fast expansion of adverse drug event reports, FAERS-based drug repurposing represents a promising strategy for discovering new uses for existing therapies.

Association of Torsade de Pointes and QT Prolongation With Antifungal Triazoles: Analysis Using a Pharmacovigilance Database

BACKGROUND/AIM

Torsade de pointes (TdP)/QT prolongation (QTP) is one of the most life-threatening adverse effects of antifungal triazoles. The aim of the present study was to evaluate the association of antifungal triazoles with TdP/QTP by age group and the profile of the time of TdP/QTP onset by analyzing the spontaneous adverse event database for Japan.

PATIENTS AND METHODS

Data registered in the Japanese Adverse Drug Event Report database (JADER) from April 2004 to March 2022 were analyzed. The association between the administration of antifungal triazoles and TdP/QTP according to age was evaluated using an adjusted reporting odds ratio (aROR). In addition, the time-to-onset of TdP/QTP after antifungal triazole treatment was analyzed using the Weibull distribution according to the route of administration.

RESULTS

Antifungal triazole treatment was associated with TdP/QTP (aROR=1.77, 95% confidence interval=1.52-2.07). In the subgroup analyses by age group, antifungal triazole treatments in patients ≤29 years old and ≥50 (except ≥90) years old were associated with TdP/QTP. The medians (quartiles) of time-to-onset for intravenous and oral antifungal triazole treatment were 8 (6-12) and 23 (8-86) days, respectively. In addition, the shape parameter in the Weibull distribution analysis of oral triazole treatment revealed that the hazard exhibited an early failure profile.

CONCLUSION

TdP/QTP is associated with antifungal triazoles even in young patients, and patients should be monitored for the development of TdP/QTP, especially early after the initiation of treatment.

Repositioning of Benzodiazepine Drugs and Synergistic Effect with Ciprofloxacin Against ESKAPE Pathogens

Infectious diseases are among the leading causes of morbidity and mortality worldwide. Combating them becomes more complex when caused by the pathogens of the ESKAPE group, which are Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa and Enterobacter spp. The purpose of this study was to investigate the repositioning potential of the benzodiazepines clonazepam and diazepam individually and in combination with the antibacterial ciprofloxacin against ESKAPE. The minimum inhibitory concentration and minimum bactericidal concentration against seven American Type Culture Collection (ATCC) reference standard strains and 64 ESKAPE clinical isolates were determined. In addition, the interaction with ciprofloxacin was determined by the checkerboard method and fractional inhibitory concentration index (FICI) of clonazepam against 11 ESKAPE and diazepam against five ESKAPE. We also list the results found and their clinical significance. Benzodiazepines showed similar antibacterial activity against Gram-positive and Gram-negative. The checkerboard and FICI results showed a synergistic effect of these drugs when associated with ciprofloxacin against almost all tested isolates. Viewing the clinical cases studied, benzodiazepines have potential as treatment alternatives. The results allow us to conclude that clonazepam and diazepam, when in combination with ciprofloxacin, have promising activity against ESKAPE, therefore, assuming the position of candidates for repositioning.

Pharmacovigilance-based drug repurposing: searching for putative drugs with hypohidrosis or anhidrosis adverse events for use against hyperhidrosis

BACKGROUND

Drug repurposing refers to the application of existing drugs to new therapeutic indications. As phenotypic indicators of human drug response, drug side effects may provide direct signals and unique opportunities for drug repurposing.

OBJECTIVES

We aimed to identify drugs frequently associated with hypohidrosis or anhidrosis adverse reactions (that is, the opposite condition of hyperhidrosis) from the pharmacovigilance database, which could be potential candidates as anti-hyperhidrosis treatment agents.

METHODS

In this observational, retrospective, pharmacovigilance study, adverse event reports of hypohidrosis or anhidrosis in the US Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) were assessed between January 2004 and December 2021 using reporting odds ratio (ROR) estimates and categorized by the World Health Organization Anatomical Therapeutic Chemical (ATC) classification code. The onset time of drug-associated hypohidrosis or anhidrosis was also examined.

RESULTS

There were 540 reports of 192 drugs with suspected drug-associated hypohidrosis or anhidrosis in the FAERS database, of which 39 drugs were found to have statistically significant signals. Nervous system drugs were most frequently reported (187 cases, 55.82%), followed by alimentary tract and metabolism drugs (35 cases, 10.45%), genitourinary system and sex hormones (28 cases, 8.36%), and dermatologicals (22 cases, 6.57%). The top 3 drug subclasses were antiepileptics, drugs for urinary frequency and incontinence, and antidepressants. Taking disproportionality signals, pharmacological characteristics of drugs and appropriate onset time into consideration, the main putative drugs for hyperhidrosis were glycopyrronium, solifenacin, oxybutynin, and botulinum toxin type A. Other drugs, such as topiramate, zonisamide, agalsidase beta, finasteride, metformin, lamotrigine, citalopram, ciprofloxacin, bupropion, duloxetine, aripiprazole, prednisolone, and risperidone need more investigation.

CONCLUSIONS

Several candidate agents among hypohidrosis or anhidrosis-related drugs were identified that may be redirected for diminishing sweat production. There are affirmative data for some candidate drugs, and the remaining proposed candidate drugs without already known sweat reduction mechanisms of action should be further explored.

Drug repurposing using real-world data

The use of real-world data in drug repurposing has emerged due to well-established advantages of drug repurposing in supplementing de novo drug discovery and incentives in incorporating real-world evidence in regulatory approvals. We conducted a scoping review to characterize repurposing studies using real-world data and discuss their potential challenges and solutions. A total of 250 studies met the inclusion criteria, of which 36 were original studies on hypothesis generation, 101 on hypothesis validation, and seven on safety assessment. Key challenges that should be addressed for future progress in using real-world data for repurposing include isolated data sources with poor clinical granularity, false-positive signals from data mining, the sensitivity of hypothesis validation to bias and confounding, and the lack of clear regulatory guidance.

Drug repositioning prediction for psoriasis using the adverse event reporting database

Introduction

Inverse signals produced from disproportional analyses using spontaneous drug adverse event reports can be used for drug repositioning purposes. The purpose of this study is to predict drug candidates using a computational method that integrates reported drug adverse event data, disease-specific gene expression profiles, and drug-induced gene expression profiles.

Methods

Drug and adverse events from 2015 through 2020 were downloaded from the United States Food and Drug Administration Adverse Event Reporting System (FAERS). The reporting odds ratio (ROR), information component (IC) and empirical Bayes geometric mean (EBGM) were used to calculate the inverse signals. Psoriasis was selected as the target disease. Disease specific gene expression profiles were obtained by the meta-analysis of the Gene Expression Omnibus (GEO). The reverse gene expression scores were calculated using the Library of Integrated Network-based Cellular Signatures (LINCS) and their correlations with the inverse signals were obtained.

Results

Reversal genes and the candidate compounds were identified. Additionally, these correlations were validated using the relationship between the reverse gene expression scores and the half-maximal inhibitory concentration (IC50) values from the Chemical European Molecular Biology Laboratory (ChEMBL).

Conclusion

Inverse signals produced from a disproportional analysis can be used for drug repositioning and to predict drug candidates against psoriasis.

The potential antidepressant effect of antidiabetic agents: New insights from a pharmacovigilance study based on data from the reporting system databases FAERS and VigiBase

Background: Growing evidence supports a bidirectional association between diabetes and depression; promising but limited and conflicting data from human studies support the intriguing possibility that antidiabetic agents may be used to relieve effectively depressive symptoms in diabetic patients. We investigated the potential antidepressant effects of antidiabetic drugs in a high-scale population data from the two most important pharmacovigilance databases, i.e., the FDA Adverse Event Reporting System (FAERS) and the VigiBase. Material and methods: From the two primary cohorts of patients treated with antidepressants retrieved from FDA Adverse Event Reporting System and VigiBase we identified cases (depressed patients experiencing therapy failure) and non-cases (depressed patients experiencing any other adverse event). We then calculated the Reporting Odds Ratio (ROR), Proportional Reporting Ratio (PRR), Empirical Bayes Geometric Mean (EBGM), and Empirical Bayes Regression-Adjusted Mean (ERAM) for cases versus non-cases in relation with the concurrent exposure to at least one of the following antidiabetic agent: A10BA Biguanides; A10BB Sulfonylureas; A10BG Thiazolidinediones; A10BH DPP4-inhibitors; A10BJ GLP-1 analogues; A10BK SGLT2 inhibitors (i.e., those agents for which preliminary evidence from literature supports our pharmacological hypothesis). Results: For GLP-1 analogues, all the disproportionality scores showed values <1, i.e., statistically significant, in both analyses [from the FAERS: ROR confidence interval of 0.546 (0.450-0.662); PRR (p-value) of 0.596 (0.000); EBGM (CI) of 0.488 (0.407-0.582); ERAM (CI) of 0.480 (0.398-0.569) and VigiBase: ROR (CI) of 0.717 (0.559-0.921); PRR (p-value) of 0.745 (0.033); EBGM (CI) of 0.586 (0.464-0.733); ERAM of (CI): 0.515 (0.403-0.639)]. Alongside GLP-1 analogues, DPP-4 Inhibitors and Sulfonylureas showed the greatest potential protective effect. With regard to specific antidiabetic agents, liraglutide and gliclazide were associated with a statistically significant decrease in all disproportionality scores, in both analyses. Conclusion: The findings of this study provide encouraging results, albeit preliminary, supporting the need for further clinical research for investigating repurposing of antidiabetic drugs for neuropsychiatric disorders.

Use of real-world evidence in translational pharmacology research

Real-world evidence (RWE) refers to observational data gathered outside the formalism of randomized controlled trials, in real life situations, on marketed drugs. While clinical trials are the gold standards to demonstrate the efficacy and tolerability of a medicinal product, the generalizability of their results to actual use in real-life is limited by the biases induced by the very nature of clinical trials; indeed, the patients included in the trials may differ from actual users because of their concomitant diseases or treatments, or other factors excluding them from the trials. Clinical researchers and pharmaceutical industries have hence become increasingly interested in expanding and integrating RWE into clinical research, by capitalizing on the exponential growth in access to data from electronic health records, claims databases, electronic devices, software or mobile applications, registries embedded in clinical practice and social media. Meanwhile, applications of RWE may also be used for drug discovery and repurposing, for clinical developments and post-marketing studies. The aim of this review is to provide our opinion regarding the use of RWE in translational research, including non-clinical and clinical pharmacology research, at the different step of drugs development use.

Repurposing haloperidol for the treatment of rheumatoid arthritis: an integrative approach using data mining techniques

Introduction

Treatment of rheumatoid arthritis (RA) has advanced with the introduction of biological disease-modifying antirheumatic drugs. However, more than 20% of patients with RA still have moderate or severe disease activity. Hence, novel antirheumatic drugs are required. Recently, drug repurposing, a process of identifying new indications for existing drugs, has received great attention. Furthermore, a few reports have shown that antipsychotics are capable of affecting several cytokines that are also modulated by existing antirheumatic drugs. Therefore, we investigated the association between antipsychotics and RA by data mining using real-world data and bioinformatics databases.

Methods

Disproportionality and sequence symmetry analyses were employed to identify the associations between the investigational drugs and RA using the US Food and Drug Administration Adverse Event Reporting System (2004-2016) and JMDC administrative claims database (January 2005-April 2017; JMDC Inc., Tokyo, Japan), respectively. The reporting odds ratio (ROR) and information component (IC) were used in the disproportionality analysis to indicate a signal. The adjusted sequence ratio (SR) was used in the sequence symmetry analysis to indicate a signal. The bioinformatics analysis suite, BaseSpace Correlation Engine (Illumina, CA, USA) was employed to explore the molecular mechanisms associated with the potential candidates identified by the drug-repurposing approach.

Results

A potential inverse association between the antipsychotic haloperidol and RA, which exhibited significant inverse signals with ROR, IC, and adjusted SR, was found. Furthermore, the results suggested that haloperidol may exert antirheumatic effects by modulating various signaling pathways, including cytokine and chemokine signaling, major histocompatibility complex class-II antigen presentation, and Toll-like receptor cascade pathways.

Conclusion

Our drug-repurposing approach using data mining techniques identified haloperidol as a potential antirheumatic drug candidate.

An Analytical Review of Computational Drug Repurposing

Drug repurposing is a vital function in pharmaceutical fields and has gained popularity in recent years in both the pharmaceutical industry and research community. It refers to the process of discovering new uses and indications for existing or failed drugs. It is cost-effective and reliable in contrast to experimental drug discovery, which is a costly, time-consuming, and risky process and limited to a relatively small number of targets. Accordingly, a plethora of computational methodologies have been propounded to repurpose drugs on a large scale by utilizing available high throughput data. The available literature, however, lacks a contemporary and comprehensive analysis of the current computational drug repurposing methodologies. In this paper, we presented a systematic analysis of computational drug repurposing which consists of three main sections: Initially, we categorize the computational drug repurposing methods based on their technical approach and artificial intelligence perspective and discuss the strengths and weaknesses of various methods. Secondly, some general criteria are recommended to analyze our proposed categorization. In the third and final section, a qualitative comparison is made between each approach which is a guide to understanding their preference to one another. Further, this systematic analysis can help in the efficient selection and improvement of drug repurposing techniques based on the nature of computational methods implemented on biological resources.

Disproportionality analysis in VigiBase as a drug repositioning method for the discovery of potentially useful drugs in Alzheimer's disease

Drug repositioning aims to propose new indications for marketed drugs. Although several methods exist, the utility of pharmacovigilance databases for this purpose is unclear. We conducted a disproportionality analysis in the World Health Organization pharmacovigilance database VigiBase to identify potential anticholinesterase drug candidates for repositioning in Alzheimer's disease (AD).

METHODS

Disproportionality analysis is a validated method for detecting significant associations between drugs and adverse events (AEs) in pharmacovigilance databases. We applied this approach in VigiBase to establish the safety profile displayed by the anticholinesterase drugs used in AD and searched the database for drugs with similar safety profiles. The detected drugs with potential activity against acetylcholinesterase and butyrylcholinesterases (BuChEs) were then evaluated to confirm their anticholinesterase potential.

RESULTS

We identified 22 drugs with safety profiles similar to AD medicines. Among these drugs, 4 (clozapine, aripiprazole, sertraline and S-duloxetine) showed a human BuChE inhibition rate of over 70% at 10^-5  M. Their human BuChE half maximal inhibitory concentration values were compatible with clinical anticholinesterase action in humans at their normal doses. The most active human BuChE inhibitor in our study was S-duloxetine, with a half maximal inhibitory concentration of 1.2 μM. Combined with its ability to inhibit serotonin (5-HT) reuptake, the use of this drug could represent a novel multitarget directed ligand therapeutic strategy for AD.

CONCLUSION

We identified 4 drugs with repositioning potential in AD using drug safety profiles derived from a pharmacovigilance database. This method could be useful for future drug repositioning efforts.

Integrative analysis of clinical and bioinformatics databases to identify anticancer properties of digoxin

Cardiac glycosides, such as digoxin, inhibit Na⁺/K⁺-ATPases and cause secondary activation of Na⁺/Ca²⁺ exchangers. Preclinical investigations have suggested that digoxin may have anticancer properties. In order to clarify the functional mechanisms of digoxin in cancer, we performed an integrative analysis of clinical and bioinformatics databases. The US Food and Drug Administration Adverse Event Reporting System and the Japan Medical Data Center claims database were used as clinical databases to evaluate reporting odds ratios and adjusted sequence ratios, respectively. The BaseSpace Correlation Engine and Connectivity Map bioinformatics databases were used to investigate molecular pathways related to digoxin anticancer mechanisms. Clinical database analyses suggested an inverse association between digoxin and four cancers: gastric, colon, prostate and haematological malignancy. The bioinformatics database analysis suggested digoxin may exert an anticancer effect via peroxisome proliferator-activated receptor α and apoptotic caspase cascade pathways. Our integrative analysis revealed the possibility of digoxin as a drug repositioning candidate for cancers.