Quantitative Structure-Activity Relationship Models to Predict Cardiac Adverse Effects.

IntroductionThe most commonly reported adverse event, based on frequency of Medical Dictionary for Regulatory Activities (MedDRA) preferred terms (PTs), in the US FDA Adverse Event Reporting System (FAERS) database is “drug ineffective” (DI). This study aimed to describe the DI reports and provide data to support recommendations on how to best evaluate these reports.MethodsWe characterized all FAERS reports coded with the MedDRA PT “drug ineffective” received between 1 September 2012 and 31 August 2016 using all other FAERS reports as a comparator. Additionally, we conducted a manual evaluation to identify informative data elements in the report narratives.ResultsDuring the study period, 247,513 (6.4% of all FAERS reports) DI reports were entered in FAERS. Compared with non-DI reports, DI reports were more likely to be reported by consumers (69.8 vs. 48.1%) and less likely to report a serious outcome (26.2 vs. 56.3%). Most DI reports (88%) were from the USA. Manual evaluation of 552 sample US reports identified 43 reports (7.8%) deemed “useful”; a higher proportion of “useful” reports provided a batch or lot number (39.5 vs. 17.2%) and were coded with additional PTs beyond “drug ineffective” (83.7 vs. 59.2%), the most frequent of which were “product quality issue” (23.3%) and “product substitution issue” (18.6%).ConclusionsDI was the most frequently reported adverse event in the FAERS database; however, the yield from these reports in terms of usefulness from a pharmacovigilance perspective was low. Efficient strategies are needed to identify which DI reports are more likely to contain useful information.

ABSTRACTBackgroundThere remains a gap in understanding lapatinib's real-world safety, particularly in rare adverse events (AEs). Thus, this study aims to evaluate lapatinib’s safety by (1) performing data mining of the FDA Adverse Event Reporting System (FAERS); and (2) detecting and analysing safety signals associated with lapatinib that may require monitoring.MethodsFAERS data from March 2007 to July 2024 were analysed via OpenVigil (version 2.1). AEs were categorised into preferred terms (PTs) and system organ classes (SOCs) using the Medical Dictionary for Regulatory Activities. We used descriptive analysis to analyse report characteristics and four signal detection algorithms to quantify risk signals, including Proportional Reporting Ratio (PRR), Reporting Odds Ratio (ROR), Multi-item Gamma Poisson Shrinker (MGPS), and Bayesian Confidence Propagation Neural Network (BCPNN). Top novel strong suspected AEs were further assessed using a case-by-case analysis. The Naranjo algorithm was utilised to determine the potential relation between the suspected AEs and lapatinib.ResultsFrom 25,506,744 retrieved reports, 18,407 PTs identified lapatinib as the primary suspect, resulting in 10,959 signals analysed. AEs were predominantly females (77.9%) and individuals aged 18–64 (45.38%). Lapatinib-induced AEs affected 16 systems, with 155 lapatinib-related PTs; 115 of these were significantly disproportionate, including 57 new PTs. While gastrointestinal and dermatological disorders were the most common, the latter was more strongly associated with lapatinib, with diarrhoea being the only strong gastrointestinal signal. Notably, cardiac events were less reported, and the top new AEs based on signal strength, such as hypocapnia, lip ulceration, and hepatic infection, were mostly found to be ‘possibly’ related to lapatinib based on the case-by-case evaluation, warranting further clinical assessments. Initial or prolonged hospitalisation, death, and life-threatening events were the most common AEs outcomes reported, accounting for 28.79%, 13.79%, and 3.06%, respectively.ConclusionThis study provides valuable insights into lapatinib-induced toxicity in real-world settings.

Potassium citrate is widely used as oral alkali therapy for the prevention of recurrent nephrolithiasis. Despite its long-standing clinical use, systematically collected real-world safety data remain limited. We performed a pharmacovigilance analysis to characterize adverse event reports associated with potassium citrate using the U.S. Food and Drug Administration Adverse Event Reporting System (FAERS). FAERS reports submitted between 2014 and 2025 listing potassium citrate as the primary suspect drug were analyzed. Duplicate records were removed, and adverse events were coded using the Medical Dictionary for Regulatory Activities (MedDRA) at both the system organ class and standardized event term levels (preferred terms, PTs). Disproportionality analyses were conducted using reporting odds ratio, proportional reporting ratio, bayesian confidence propagation neural network, and multi-item gamma poisson shrinker methods. A total of 408 unique reports were included. Most reports involved adults and were physician-reported from the United States. Disproportionality analysis identified potential safety issues (signals), defined as drug event associations reported more frequently than expected in FAERS and therefore warranting further evaluation, although not establishing causality. The strongest associations involved product-related issues, laboratory investigations, and gastrointestinal disorders. When these potential safety issues were described using standardized MedDRA event terms most reflected formulation- and administration-related problems, including tablet residue in stool, abnormal solubility, swallowing difficulty, throat irritation, and foreign body sensations. Reports of rash were infrequent. This first FAERS-based analysis of potassium citrate highlights that most reported adverse events are related to formulation and administration characteristics rather than drug toxicity. These findings support the overall tolerability of potassium citrate while underscoring the importance of adherence, patient education, and formulation-specific considerations in clinical practice. As a spontaneous reporting system, FAERS is valuable for hypothesis generation, label expansion, and post-marketing surveillance, but it is not suitable for estimating the incidence or absolute risk of adverse events.

Objective To gain an improved comprehension of inclisiran safety in real-world settings by data mining from FAERS. Methods Data were gathered between 1 December 2020 and 31 December 2023. The Medical Dictionary for Regulatory Activities (MedDRA) corresponding preferred term (PT) and system organ class (SOC) were used to categorize adverse medication reactions in AE reports (AERs). By using reported odds ratio (ROR) method, positive signals were identified. Results There were 2,652 reports of inclisiran, and 150 of those AEs had significant disproportionality. Among the 44 PTs with moderate clinical priority, 35 PTs were discovered on the medicine label, including 12 IMEs and 2 DMEs. Of note, 9 PTs were unanticipated AEs that were not discovered in the medication label or reported clinical studies, such as movement disorder (ROR: 3.05; 95%CI: 1.73,5.37), aphonia (ROR: 3.77; 95%CI: 1.79,7.91), and pulmonary congestion (ROR: 3.47; 95%CI: 1.44,8.34). Inclisiran was found to be related to 12 serious AEs. The median TTO of 1896 cases was 13.5 (IQR 0-100) days. Conclusion We identified not only known AEs, but also new AE signals such as movement disorder. However, signals does not reveal actual risk, prospective clinical trials are still required to verify their causal connection.

Objective: To investigate and analyze the post-marketing adverse event (AE) data of multiple sclerosis (MS) therapeutic drug dalfampridine using the US Food and Drug Administration Adverse Event Reporting System (FAERS) for its clinical safety application. Methods: Use OpenVigil2.1 platform to obtain AE data of dalfampridine from FAERS from February 2010 to September 2022. Match "adverse drug reaction" with preferred term (PT) and system organ class (SOC) according to the Medical Dictionary for Regulatory Activities (MedDRA), then merge the same PT and delete non-AE PT. Positive signals were identified by the reporting odds ratio (ROR), proportional reporting ratio (PRR), and Bayesian confidence propagation neural network (BCPNN) methods. When AE signals met the criteria of those three methods, they were identified as positive signals. Results: A total of 44,092 dalfampridine-related AE reports were obtained, and 335 AE signals were identified, including 11,889 AE reports. AEs were more common in females and in the 45-65 age group, which is consistent with the epidemiological characteristics of MS. The 335 AE signals involved 21 SOCs, including investigations, infections and infestations, eye disorders, etc. Among the top 20 PTs in signal strength, 10 were associated with abnormal lymphocyte percentage and count, and 5 were associated with abnormal urine tests, some of which were not described in the instruction, such as spinal cord injury cauda equina, haemoglobin urine present, urinary sediment abnormal and so on. The most frequently reported AE signals were urinary tract infection, dizziness, condition aggravated. In addition, 23 AE signals with death outcomes were identified, with an incidence of less than 0.1%. Conclusion: Data mining of FAERS was conducted to analyze the AEs of dalfampridine, and new AE signals were found. This study provides a reference for the safe use of dalfampridine in the treatment of MS.

Evaluation of Natural Language Processing (NLP) systems to annotate drug product labeling with MedDRA terminology

Multisociety (AATS, ACCF, SCAI, and STS) Expert Consensus Statement: Operator and Institutional Requirements for Transcatheter Valve Repair and Replacement, Part 1: Transcatheter Aortic Valve Replacement

BackgroundThere have been debates about the association between the administration of glucocorticoids and the development of acute pancreatitis, since many anecdotal cases of this adverse event were affected either by concomitant diseases (such as systemic lupus erythematosus, SLE) that may develop acute pancreatitis without glucocorticoid treatment or by co-administered drugs with high risk for the event. The aim of the present study was to explore whether disproportionally elevated signals of developing acute pancreatitis may be detected in patients receiving glucocorticoids as compared those receiving other drugs.MethodsWe retrieved spontaneously reported cases of acute pancreatitis and clinically related adverse events (target events) from the US Food and Drug Administration Adverse Event Reporting System (FAERS) using 18 preferred terms (PTs). Target drugs studied were cortisol, cortisone, prednisolone, methylprednisolone, triamcinolone, dexamethasone, and betamethasone. After cleaning the data, we calculated reporting odds ratios (RORs) and 95% confidence intervals (CIs) of acute pancreatitis in patients who received one of the glucocorticoids. RORs were calculated for each glucocorticoid using all reported cases irrespective of reporters’ judgement about the contribution of the target drugs to events [i.e., primary suspected medication (PS), secondary suspected medication (SS), concomitant medication (C) and interacting (I)] and using cases with higher certainty of contribution (PS and SS), separately. When the lower limit of 95% CI of a ROR signal exceeded 1.0, the signal was considered statistically significant.ResultsThe RORs (95% CIs) calculated using all reported cases (PS, SS, C, and I) for cortisol (1.68; 1.43–1.98), prednisolone (1.33; 1.19–1.47), methylprednisolone (1.77; 1.55–2.02) were significant, whereas those for other target drugs were insignificant. Using the cases in which target drugs were considered to contribute the events with higher certainty (PS or SS), RORs for prednisolone (1.31; 1.10–1.55), methylprednisolone (1.62; 1.30–2.01), and dexamethasone (1.27; 1.10–1.47) were considered significant, whereas those for others were insignificant. Regarding the performance of PTs for detecting signals (RORs) associated with acute pancreatitis from FAERS database, “pancreatitis acute” gave RORs with higher significance than others, whereas more specific PTs, “haemorrhagic necrotic pancreatitis”, “ischaemic pancreatitis”, “pancreatic necrosis” and “pancreatitis necrotising”, gave RORs with greater magnitude.ConclusionThe present study demonstrated that the overrepresentation of signals for acute pancreatitis may be detected for prednisolone, methylprednisolone, and some others in the FAERS database.(372 words)

It’s well known that sex is a risk factor for the occurrence of adverse events (AEs), most of which have found sex differences. Real-world data studies on the sex differences of fall-risk-increasing drugs (FRIDs) are few and far between, with most small-scale retrospective studies based on FRID classes. To establish a list of FRIDs and describe their sex differences, we used preferred terms from the Medical Dictionary for Regulatory Activities to search for AEs in the FDA Adverse Event Reporting System (FAERS), and then perform disproportionality analyses and female/male ratio analyses. During January 2004 to March 2023, 101,746 fall-related AEs were reported in FAERS from patients aged 50 to 100, with 68,492 (67.3%) females and 32,547 (32.0%) males. We found 261 signals for females while 284 for males. For females, the top 3 signals with the highest reporting odds ratio (ROR) were anethole trithione, clopenthixol, nikethamide (ROR: 388.88, 212.10, 113.94), while the top 3 signals with the highest lower limit of information component (IC025) were nikethamide, anethole trithione, benzbromarone (IC025: 3.91, 3.15, 2.49). For males, the top 3 signals with the highest ROR were fluprednidene acetate, potassium hydroxide, ketazolam (ROR: 216.86, 108.43, 108.43), while the top 3 signals with the highest IC025 were clomethiazole, piribedil, melperone (IC025: 3.31, 3.24, 2.99). Moreover, among the 119 shared signals found between males and females, 33 were positively correlated with falls in females and 38 with falls in males. Signals showing significant sex differences were mainly concentrated on agents of the immune, nervous, musculo-skeletal, and cardiovascular systems. We offered a series of FRIDs and suggested their sex differences in falls through the FAERS. In the future, it is essential to balance the inclusion of women and men, and analyse sex-stratified for FRIDs.

Background Beta-lactam antibiotics are among the most commonly prescribed antimicrobials worldwide, but they are also a frequent cause of drug-induced hypersensitivity reactions, ranging from mild rashes to life-threatening anaphylaxis. While clinical trial data provide initial safety signals, rare and delayed adverse events often emerge post-marketing. This study aimed to analyze post-marketing reports of hypersensitivity reactions associated with beta-lactam antibiotics using the U.S. FDA Adverse Event Reporting System (FAERS) database.Forest Plot: Hypersensitivity Signals of Beta-Lactam Antibiotics (FAERS, 2010–2023) This forest plot displays the reporting odds ratios (RORs) with 95% confidence intervals for hypersensitivity-related adverse events associated with beta-lactam antibiotics. Notable signals include: Cefazolin–associated anaphylaxis (ROR 3.89) Angioedema with amoxicillin-clavulanate (ROR 2.97) Urticaria with ceftriaxone (ROR 2.12) All events exceeding an ROR of 1 with lower CI >1 are considered statistically significant safety signals, reinforcing the need for careful antibiotic selection, particularly in sensitized patients. Methods A retrospective pharmacovigilance analysis was conducted using FAERS data from January 2010 to December 2023. Reports involving penicillins, cephalosporins, carbapenems, and monobactams were extracted using generic and brand names. Hypersensitivity-related Preferred Terms (PTs) were identified via the MedDRA hierarchy, including anaphylactic reaction, angioedema, urticaria, erythema multiforme, and DRESS syndrome. Disproportionality was assessed using Reporting Odds Ratio (ROR) and Proportional Reporting Ratio (PRR), with statistical significance defined as ROR 95% CI >1 and ≥3 cases. Results A total of 14,728 hypersensitivity-related adverse event reports were associated with beta-lactam antibiotics. Among them, amoxicillin accounted for the highest number of reports (n = 4,615), followed by ceftriaxone (n = 2,763) and piperacillin-tazobactam (n = 1,980). Disproportionality analysis showed the strongest signal for anaphylaxis with cefazolin (ROR: 3.89, 95% CI: 3.22–4.68) and angioedema with amoxicillin-clavulanate (ROR: 2.97, 95% CI: 2.45–3.61). Cephalosporins were more frequently associated with skin-related hypersensitivity (e.g., urticaria, erythema), whereas carbapenems were linked to a lower but consistent signal for severe reactions. Conclusion This large-scale post-marketing analysis using FAERS data highlights distinct hypersensitivity risk profiles among beta-lactam subclasses. The findings reinforce the need for careful history-taking and individualized antibiotic selection, especially in patients with prior allergy history. Real-world data from spontaneous reporting systems like FAERS remain crucial in identifying emerging safety signals. Disclosures All Authors: No reported disclosures

ObjectiveThis study aimed to investigate the entire adverse events (AEs) spectrum and to identify some new or rare AEs associated with empagliflozin based on the FAERS database.MethodsA retrospective analysis was conducted on AE reports extracted from the FAERS, spanning from the first quarter of 2004 to that of 2023. Disproportionality analysis methods, including the ROR, PRR, BCPNN, and MGPS, were employed to quantify signals of AEs associated with empagliflozin. Additionally, demographic characteristics and time to onset were further elucidated.ResultsThe results showed a total of 20,734 AE reports related to empagliflozin, identifying 322 significant preferred terms (PTs) covering 27 System Organ Classes (SOCs). Empagliflozin was significantly associated with pre-specified AEs compared to other novel antidiabetic medications. Beyond common AEs, unexpected significant AEs such as pancreatitis, gastroenteritis, cerebral infarction, and cardiac operations were identified. The median onset time for empagliflozin-related AEs was 28 days (interquartile range (IQR) 4–154 days), with the majority of AE cases (n = 2,112, 10.19%) occurring within the first month following initiation of empagliflozin therapy.ConclusionThe clinically observed AEs, along with potential new AE signals associated with empagliflozin were identified based on the FAERS database, which could provide valuable evidence for clinical monitoring, risk identification, and further safety studies of identification.

Triptorelin, a gonadotropin-releasing hormone(GnRH) agonist, is approved by the US Food and Drug Administration(FDA) for treating advanced prostate cancer, endometriosis, and central precocious puberty(CPP) in children aged ≥ 2 years. This study aimed to characterize the real-world adverse event(AE) profile associated with triptorelin using data from the FDA Adverse Event Reporting System(FAERS). We conducted a retrospective pharmacovigilance study utilizing FAERS reports from the first quarter of 2004 to the third quarter of 2024 (2004Q1–2024Q3). Disproportionality analysis employing four distinct algorithms (Reporting Odds Ratio [ROR], Proportional Reporting Ratio [PRR], Bayesian Confidence Propagation Neural Network [BCPNN], and Multi-item Gamma Poisson Shrinker [MGPS]) was performed to identify potential statistical signals of triptorelin-associated AEs. Among 18,541,994 eligible FAERS reports, 4018 primary suspect reports involving triptorelin were identified. Disproportionality analysis revealed 102 statistically significant Preferred Terms(PTs). Unexpected statistical signals warranting further investigation included defiant behavior and Alzheimer’s dementia. The median time-to-onset (TTO) of AEs was 132 days (interquartile range[IQR] 36–361 days). AE reporting exhibited a bimodal distribution, with the highest proportions occurring within the first month (22.59%) and after more than one year (25.07%) following administration. Distinct statistical signal profiles were observed between genders. Analysis of FAERS data elicited statistical signals for both expected and unexpected AEs associated with triptorelin. These findings highlight potential safety signals, particularly defiant behavior and Alzheimer’s dementia, which meet the European Medicines Agency (EMA) 2024 criteria for safety signals requiring further investigation. Continuous pharmacovigilance monitoring is recommended. It is crucial to emphasize that these findings represent statistical associations identified through disproportionality analysis; they require clinical validation and do not establish causality.Supplementary InformationThe online version contains supplementary material available at 10.1038/s41598-025-16734-7.

A phenomenon of 'masking' or 'cloaking' in pharmacovigilance data mining has been described, which can potentially cause signals of disproportionate reporting (SDRs) to be missed, particularly in pharmaceutical company databases. Masking has been predicted theoretically, observed anecdotally or studied to a limited extent in both pharmaceutical company and health authority databases, but no previous publication systematically assesses its occurrence in a large health authority database. To explore the nature, extent and possible consequences of masking in the US FDA Adverse Event Reporting System (AERS) database by applying various experimental unmasking protocols to a set of drugs and events representing realistic pharmacovigilance analysis conditions. This study employed AERS data from 2001 through 2005. For a set of 63 Medical Dictionary for Regulatory Activities (MedDRA®) Preferred Terms (PTs), disproportionality analysis was carried out with respect to all drugs included in the AERS database, using a previously described urn-model-based algorithm. We specifically sought masking in which drug removal induced an increase in the statistical representation of a drug-event combination (DEC) that resulted in the emergence of a new SDR. We performed a series of unmasking experiments selecting drugs for removal using rational statistical decision rules based on the requirement of a reporting ratio (RR) >1, top-ranked statistical unexpectedness (SU) and relatedness as reflected in the WHO Anatomical Therapeutic Chemical level 4 (ATC4) grouping. In order to assess the possible extent of residual masking we performed two supplemental purely empirical analyses on a limited subset of data. This entailed testing every drug and drug group to determine which was most influential in uncovering masked SDRs. We assessed the strength of external evidence for a causal association for a small number of masked SDRs involving a subset of 29 drugs for which level of evidence adjudication was available from a previous study. The original disproportionality analysis identified 8719 SDRs for the 63 PTs. The SU-based unmasking protocols generated variable numbers of masked SDRs ranging from 38 to 156, representing a 0.43-1.8% increase over the number of baseline SDRs. A significant number of baseline SDRs were also lost in the course of our experiments. The trend in the number of gained SDRs per report removed was inversely related to the number of lost SDRs per protocol. Both the number and nature of the reports removed influenced the number of gained SDRs observed. The purely empirical protocols unmasked up to ten times as many SDRs. None of the masked SDRs had strong external evidence supporting a causal association. Most involved associations for which there was no external supporting evidence or were in the original product label. For two masked SDRs, there was external evidence of a possible causal association. We documented masking in the FDA AERS database. Attempts at unmasking SDRs using practically implementable protocols produced only small changes in the output of SDRs in our analysis. This is undoubtedly related to the large size and diversity of the database, but the complex interdependencies between drugs and events in authentic spontaneous reporting system (SRS) databases, and the impact of measures of statistical variability that are typically used in real-world disproportionality analysis, may be additional factors that constrain the discovery of masked SDRs and which may also operate in pharmaceutical company databases. Empirical determination of the most influential drugs may uncover significantly more SDRs than protocols based on predetermined statistical selection rules but are impractical except possibly for evaluating specific events. Routine global exercises to elicit masking, especially in large health authority databases are not justified based on results available to date. Exercises to elicit unmasking should be driven by prior knowledge or obvious data imbalances.

Atezolizumab has been widely used for the immunotherapy of various cancers. This study aims to analyze the adverse events (AEs) associated with Atezolizumab post-marketing using the FDA Adverse Event Reporting System (FAERS). We conducted a retrospective analysis of the FAERS database, focusing on reports associated with atezolizumab from the first quarter of 2016 to the third quarter of 2024. The ADRs were stratified by demographics, event types, and reported outcomes. We performed a disproportionality analysis using the reporting odds ratio (ROR), the proportional reporting ratio (PRR), the Bayesian confidence propagation neural network (BCPNN), and the empirical Bayesian geometric mean (EBGM) to assess the statistical association between atezolizumab use and specific AEs. Among the 18,310,937 non-duplicated reports collected from the FAERS database, 21,162 reports identified Atezolizumab as the “primary suspect (PS),” leading to the identification of 52,348 atezolizumab-induced AEs. The majority of AE reports (59.66%) occurred within the first 360 days of treatment, with most cases reported between 30 and 180 days of administration. A total of 494 Preferred Terms (PTs) were identified as significant across all four disproportionality-based pharmacovigilance signal assessment algorithms. The three system organ classes (SOCs) with the highest signal frequencies in AE reports were Gastrointestinal System Disorders (11.54%), Infectious and Invasive Disorders (10.12%), and Benign, Malignant, and Undetermined Tumors (including cystic and polypoid) (9.92%). The top five PTs with the strongest risk signals based on frequency screening were death, disease progression, pyrexia, anemia, and infectious pneumonia. Additionally, unexpected significant AEs were identified, including homicidal ideation, encephalitis, pancreatitis, disseminated intravascular coagulation, and Guillain- Barré syndrome. Atezolizumab treatment may be associated with a range of AEs. Further studies and continued pharmacovigilance efforts are essential to better understand the long-term safety of atezolizumab and to improve patient management strategies.

Capmatinib was approved by the US Food and Drug Administration (FDA) in 2020 for the treatment of non-small cell lung cancer with MET exon 14 mutation (METex14). Real-world studies on the safety of Capmatinib are still lacking. The aim of this study was to explore the significant adverse drug reactions (ADRs) associated with Capmatinib through the FDA Adverse Event Reporting System (FAERS) database. We employed the reported odds ratio (ROR), proportional reporting ratio (PRR), Bayesian confidence propagation neural network (BCPNN), and the Empirical Bayes Geometric Mean (EBGM) as primary algorithms for the disproportionality analysis. Adverse events (AEs) were classified as adverse drug reactions (ADRs) solely upon fulfillment of criteria across all four algorithms. In our study, there were 1767 cases explicitly attributed to Capmatinib. A total of 38 ADRs in preferred terms (PTs) level in 14 system-organ categories (SOCs) were identified after filtering. Notably, unexpected SOC "Ear and labyrinth disorders" and PTs "hypoacusis" and "deafness" were identified, without being specified in the drug label. Our study identified unexpected ADRs associated with Capmatinib, with a focus on ototoxicity-related events, underscoring the need for enhanced clinical monitoring and further investigation into the underlying mechanisms.