INTRODUCTION:The integration of artificial intelligence (AI) into pharmacovigilance (PV) has advanced rapidly in recent years. AI tools have the potential to transform signal management by enabling faster and more accurate signal management and decision-making. However, the regulatory landscape governing these technologies remains complex. AREAS COVERED:This article presents available AI tools for signal management, provides an overview of the regulatory landscape of these tools, and explores stakeholder perspectives on the challenges and opportunities posed by AI regulations. On 23 July 2024, we conducted a Google search of the top 2,000 results using the query 'AI pharmacovigilance service provider.' Two searches were performed in Ovid MEDLINE to identify articles published between 1 January 2022, and 23 July 2024, using ad hoc queries. EXPERT OPINION:AI tools are now available to support all critical activities in signal management. However, regulatory discrepancies and variations persist across different regions. The findings underscore the urgent need for ongoing international collaboration to harmonize regulatory frameworks and ensure the safe and ethical implementation of AI in PV. As AI technologies continue to evolve, addressing these regulatory and operational challenges will be essential to fully realize their potential in enhancing drug safety and improving healthcare outcomes worldwide.

Background The use of certain chemotherapy agents is associated with the development of a condition called “chemotherapy-associated neutropenic enterocolitis” (CANE). Objective To determine the risk of CANE associated with the use of each antineoplastic agent. Methods The FDA FAERS database of spontaneous adverse reactions was searched for the occurrence of the MedDRA preferred term “neutropenic colitis.” Results The search resulted in 1134 records of patients (535 [47.3%] females, 479 [42.2%] males, sex not specified in 120 [10.6%]) with neutropenic colitis receiving immunosuppressive chemotherapy. The mean age of patients was 47 (SD 22). 22 antineoplastic agents were found to have a strong association (reported odds ratio [ROR] > 100) with the occurrence of CANE; 9 had ROR < 2. Conclusion Drug databases have several limitations in providing updated information about newly approved pharmaceutical adverse events. Signal detection is a diagnostic method recognized as practical in pharmacovigilance. It may be utilized in the FDA's adverse event reporting database and has demonstrated a reasonable predictive performance in signaling adverse events. Our study emphasized the substantial knowledge gap between what we know about the potential risk of CANE caused by antineoplastic agents and the reports of the FDA on their new approved products.

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.

INTRODUCTION:Statistical signal detection is a crucial tool for rapidly identifying potential risks associated with pharmaceutical products. The unprecedented environment created by the coronavirus disease 2019 (COVID-19) pandemic for vaccine surveillance predisposes commonly applied signal detection methodologies to a statistical issue called the masking effect, in which signals for a vaccine of interest are hidden by the presence of other reported vaccines. This masking effect may in turn limit or delay our understanding of the risks associated with new and established vaccines. OBJECTIVE:The aim is to investigate the problem of masking in the context of COVID-19 vaccine signal detection, assessing its impact, extent, and root causes. METHODS:Based on data underlying the Vaccine Adverse Event Reporting System, three commonly applied statistical signal detection methodologies, and a more advanced regression-based methodology, we investigate the temporal evolution of signals corresponding to five largely recognized adverse events and two potentially new adverse events. RESULTS:The results demonstrate that signals of adverse events related to COVID-19 vaccines may be undetected or delayed due to masking when generated by methodologies currently utilized by pharmacovigilance organizations, and that a class of advanced methodologies can partially alleviate the problem. The results indicate that while masking is rare relative to all possible statistical associations, it is much more likely to occur in COVID-19 vaccine signaling, and that its extent, direction, impact, and roots are not static, but rather changing in accordance with the changing nature of data. CONCLUSIONS:Masking is an addressable problem that merits careful consideration, especially in situations such as COVID-19 vaccine safety surveillance and other emergency use authorization products.

ABSTRACT Introduction Studies in patients with immune-mediated inflammatory diseases (IMIDs) have inconsistently suggested that anti-TNFα therapy may be associated with excessive weight gain. Areas covered We performed a nested case/non-case analysis to investigate the anti-TNF-α inhibitor-associated body-changes in the US Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) database. The risk was expressed as a measure of disproportionality using the reporting odds ratio (ROR) while adjusting for sex, drugs known to cause weight gain and reporter type. We also performed a time-to-onset (TTO) analysis of body weight-related events. Results Infliximab was the most commonly involved TNF-α inhibitor in body weight-related changes, reaching an aROR of 1.42 (95%CI:1. 26; 1.59). An increased risk was especially found in patients affected by rheumatic disorders, both in the adult and pediatric population. The median TTO after the start of anti- TNFα therapy was about 6–7 months for both children and adults. Conclusions Given the potential effect of these agents on the excess weight gain in IMIDs patients, continuous attention for this side effect with appropriate counseling regarding lifestyle modifications are warranted, especially in those at high risk for obesity.

Background: Hypoglycemia is a rare adverse effect of tramadol that is described in the medical literature and package insert. Objective: The purpose of this study was to review reports of tramadol and hypoglycemia in the Food and Drug Administration Adverse Event Reporting System (FAERS) database to determine a potential association. Methods: Disproportionality analysis with Bayesian correction was used to compare tramadol and hypoglycemia with other medications in FAERS. The results were considered significant if the fifth percentile of the Empirical Bayesian geometric mean distribution (EB05) >2. Logistic regression odds ratios was used to determine if age, diabetes medications, and renal insufficiency masked the disproportionality of hypoglycemia, with the fifth percentile of the logistic regression odds ratio (LR05) >2 indicating a potential signal. The Interaction Signal Score (INTSS) was computed to determine the influence of predisposing risk factors on the signal. Results: A total of 605 cases of tramadol-associated hypoglycemia were reported, but our results were not significant (EB05: 1.590). Tramadol-associated hypoglycemia was significant in patients who did not take diabetes medications (EB05: 2.256; LR05: 2.2104). Renal insufficiency was not found to increase the risk of tramadol-associated hypoglycemia (INTSS: 0.865). There was a significant signal for tramadol-associated hypoglycemia in patients aged 0 to 1 year (LR05: 3.0240) and 2 to 4 years (LR05: 2.6853). Conclusion and Relevance: Results of our analysis suggest a potential signal between hypoglycemia and tramadol use in patients not taking diabetes medications. Our results do not support a predisposition for tramadol-associated hypoglycemia in patients with renal insufficiency, increasing age, and/or diabetes as noted in the tramadol package insert.

PURPOSEThe potential link between serious or life-threatening bleeding and the use of direct oral anticoagulants (DOACs) was evaluated.METHODSQualitative and quantitative reviews of case reports of bleeding events involving dabigatran, rivaroxaban, apixaban, edoxaban, and warfarin through March 31, 2017, were performed. A disproportionality analysis was conducted for each DOAC using an empirical Bayesian approach based on the relative reporting rate. Subanalyses were performed to assess (1) bleeding events (including mortality and life-threatening events) associated with DOACs among all adverse-event reports and (2) warfarin-related bleeding events. These analyses were conducted based on clinical definitions from the Medical Dictionary for Regulatory Activities.RESULTSDuring the Food and Drug Administration Adverse Event Reporting System (FAERS) review period, 35 adverse-event terms (in any system organ class) with a disproportionality score (EB05) of >7.5 for DOACs were identified; this accounted for 40,109 adverse-event reports. Adverse events with the highest disproportionality scores included atrial thrombosis, increased factor X level, dysfunctional uterine bleeding, high-frequency ablation, pericardial hemorrhage, and internal hemorrhage. Adverse events with the highest EB05 (>5) included internal hemorrhage, hemorrhage, and exsanguination; events with the greatest number of patient experiences included hemorrhage (6,881 events), internal hemorrhage (2,569 events), and hematoma (1,995 events). Warfarin-related events (including death or life-threatening events) were also assessed. A total of 8,729 adverse events were associated with warfarin use. The most common of these included hemorrhage (6,225 events), hematoma (2,199 events), and internal hemorrhage (270 events).CONCLUSIONThe disproportionality analysis of the FAERS database suggests a quantitative signal between DOAC use and life-threatening or serious bleeding.

Background: To date, there is limited literature regarding the association between dipeptidyl peptidase-4 (DPP-4) inhibitors and pancreatic carcinoma. Objective: To describe the comparative incidence of DPP-4 inhibitors and pancreatic carcinoma as reportedly available in the Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) database. The goal was to provide health care practitioners a general understanding of the drug-disease occurrence. Methods: This is a case/noncase study utilizing Empirica Signal software to query FAERS from November 1968 to December 31, 2013. The software was used to calculate a disproportionality statistic—namely, the empirical Bayesian geometric mean (EBGM)—for reports of DPP-4 inhibitors–associated pancreatic carcinoma. The FDA considers an EBGM significant if the fifth percentile of the distribution is at least 2, defined as an EB05 ≥ 2. With use of a disproportionality analysis, DPP-4 inhibitors were compared with all agents listed in FAERS. Results: A total of 156 patients experienced pancreatic carcinoma while receiving DPP-4 inhibitor therapy. An EB05 of 10.3 was determined for sitagliptin, 7.1 for saxagliptin, 4.9 for linagliptin, and 1.4 for alogliptin, compared with all other agents included in FAERS. Although an EB05 > 2 was achieved in 2 other antihyperglycemic agents, the findings were not consistent within their medication classes. Conclusion: There appears to be a statistical association between DPP-4 inhibitor use and pancreatic carcinoma. Causality cannot be inferred from the data provided. Additional clinical studies are needed to further explore this statistical association.

Background: To date, there is limited literature regarding the association between dipeptidyl peptidase-4 (DPP-4) inhibitors and pancreatic carcinoma. Objective: To describe the comparative incidence of DPP-4 inhibitors and pancreatic carcinoma as reportedly available in the Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) database. The goal was to provide health care practitioners a general understanding of the drug-disease occurrence. Methods: This is a case/noncase study utilizing Empirica Signal software to query FAERS from November 1968 to December 31, 2013. The software was used to calculate a disproportionality statistic-namely, the empirical Bayesian geometric mean (EBGM)-for reports of DPP-4 inhibitors associated pancreatic carcinoma. The FDA considers an EBGM significant if the fifth percentile of the distribution is at least 2, defined as an EB05 >= 2. With use of a disproportionality analysis, DPP-4 inhibitors were compared with all agents listed in FAERS. Results: A total of 156 patients experienced pancreatic carcinoma while receiving DPP-4 inhibitor therapy. An EB05 of 10.3 was determined for sitagliptin, 7.1 for saxagliptin, 4.9 for linagliptin, and 1.4 for alogliptin, compared with all other agents included in FAERS. Although an EB05 > 2 was achieved in 2 other antihyperglycemic agents, the findings were not consistent within their medication classes. Conclusion: There appears to be a statistical association between DPP-4 inhibitor use and pancreatic carcinoma. Causality cannot be inferred from the data provided. Additional clinical studies are needed to further explore this statistical association.

STUDY OBJECTIVE:To review quantitatively and qualitatively the U.S. Food and Drug Administration (FDA) Adverse Event Reporting System (AERS) database to provide clinicians with a general understanding of the comparative occurrence of clinically meaningful adverse events associated with 15 antimicrobial new molecular entities approved by the FDA since 2006: anidulafungin, darunavir, maraviroc, raltegravir, doripenem, telavancin, ceftaroline, boceprevir, telaprevir, fidaxomicin, bedaquiline, dolutegravir, simeprevir, sofosbuvir, and dalbavancin. DESIGN:Retrospective analysis. DATA SOURCE:FDA AERS database. MEASUREMENTS AND MAIN RESULTS:Empirica Signal software was used to query the AERS database from November 1968 to December 2012. Using disproportionality analyses, we calculated a relative reporting ratio (RRR) estimate for reports of antimicrobial adverse events. The RRR estimate compares the occurrence of a specific adverse event with an index drug of interest to the occurrence of the same adverse event with similar agents or with all other FDA-approved prescription drugs. Common industry practice considers an RRR meaningful if the 5th percentile of the distribution is at least 2 (RRR05 of 2.0 or higher). Antimicrobials were compared with agents within their respective antimicrobial therapeutic class as well as with all agents in the AERS database. Seventeen adverse signals with an RRR05 of 2.0 or higher were identified from the database for six agents. Ten of the 17 signals were not included in the most up-to-date manufacturers' package inserts for four of the six agents: doripenem-associated hepatic dysfunction (RRR05 3.7) and hyperchloremia (RRR05 2.6); boceprevir-associated weight loss (RRR05 2.2); darunavir-associated premature labor (RRR05 3.1), sudden infant death syndrome (RRR05 2.9), ventricular hypertrophy (RRR05 2.7), acute coronary syndrome (RRR05 2.4), and congenital anomaly in offspring (RRR05 2.4); and raltegravir-associated congenital heart valve disorders (RRR05 2.5) and SIDS (RRR05 2.3). CONCLUSION:Clinically meaningful adverse event signals appeared to be associated with antimicrobial new molecular entities approved since 2006 including many not yet identified in package inserts. Although a disproportionality analysis suggests a quantitative signal for these associations, causality cannot be inferred from the data. Due to several key limitations in this type of analysis, investigative studies are needed to further explore these adverse event signals and the potential mechanisms by which they occur.

Study Objective To provide clinicians with an understanding of the comparative occurrence of tigecycline and pancreatitis, and to provide any clinically relevant characteristics that may be useful in identifying the patients at risk. Design Retrospective cohort study. Data Source Spontaneous reports in the United States Food and Drug Administration (FDA) Adverse Event Reporting System (AERS) database generated between January 1997 and December 2010. Patients Sixty-two patients who experienced pancreatitis while receiving tigecycline therapy. Measurements and Main Results Disproportionality analysis with Bayesian correction methodology was used to compare tigecycline with all other agents listed in the AERS. Disproportionality analysis uses an adverse event relative reporting ratio (RRR) to compare the occurrence of a specific adverse event with an index drug of interest to the occurrence of the same adverse event with similar agents or with all other FDA-approved prescription drugs. The value was considered meaningful if the 5th percentile of the distribution of the RRR (RRR05) was 2 or greater. Our review identified 62 potential cases of tigecyline-related pancreatitis. An RRR05 score of 10.4, 10.38, and 2.87 was determined for tigecycline-related pancreatitis compared with all other agents, systemic antibiotics, and select tetracyclines listed in the AERS, respectively. In addition, a sex-based RRR05 score was higher in women versus men (14.432 vs 3.125) when tigecycline was compared with all agents in the AERS. Conclusion Our analysis suggests a quantitative signal between tigecycline use and pancreatitis; however, given the limitations of our study, a cause-and-effect relationship cannot be inferred. Thus, additional rigorous scientific analyses are warranted to explore these findings.

STUDY OBJECTIVE:To provide clinicians with an understanding of the comparative occurrence of linezolid and blindness, and to provide any clinically relevant characteristics that may be useful in identifying the patients at risk.DESIGN:Retrospective cohort study.DATA SOURCE:Spontaneous reports in the United States Food and Drug Administration Adverse Event Reporting System (AERS) database generated between November 1, 1997, and December 21, 2008.PATIENTS:Twenty-nine patients who experienced blindness while receiving linezolid therapy.MEASUREMENTS AND MAIN RESULTS:Available information related to each case of linezolid-reported blindness in the AERS database was qualitatively and quantitatively reviewed. Optic nerve disorders, glaucoma, and treatment with linezolid for long durations were common characteristics in patients experiencing blindness. A limitation of AERS is the lack of a quantitative exposure estimate to put rare adverse events of the AERS, such as linezolid-related blindness, into perspective. To overcome this limitation, disproportionality analysis with Bayesian correction methodology was used. Disproportionality analysis uses an adverse event relative reporting ratio (RRR) to compare the occurrence of a specific adverse event with an index drug of interest to the occurrence of the same adverse event with similar agents or with all other FDA-approved prescription drugs. The disproportionality analysis was considered meaningful if the 5th percentile of the distribution of the RRR (RRR(05)) was 2 or greater. Among the 29 reported cases of linezolid use and blindness, an RRR(05) of 2.1 was determined for linezolid-related blindness compared with all other agents listed in the AERS. Also, RRR(05) values of 2.7 and 2.2 were found when linezolid was compared with all other systemic antibiotics and a select subgroup of antibiotics, respectively.CONCLUSION:Although disproportionality analyses suggested a quantitative signal for an association between linezolid use and blindness, causality cannot be inferred from the data. Thus, additional rigorous scientific analyses are warranted to explore these findings.

The increased focus on the safety of medical products, as well as the growing volume of available safety information, has created a need for objective quantitative approaches to supplement the medical review of individual case safety reports. Statistical algorithms can be used to identify trends and relationships in both clinical and postmarketing safety databases in support of safety signal detection. Powerful data visualization tools facilitate the medical review of the complex information generated by these methods. In addition, all these approaches need to be integrated into the daily practice of clinical safety and postmarketing pharmacovigilance.

This paper presents an approach which allows companies to deal with some of the major problems associated with adverse event data management in both an effective and efficient way. It is based upon discussions with representatives of severalpharmaceutical and device manufacturing companies. The approach integrates adverse event data management with other, related activities in: procedures, systems, and organization. It provides sharing of data, work flow management, and document management. The benefits of such an approach are speed, efficiency, and auditability.

After a brief introduction on the reasons for validating a clinical data system, this paper will provide a description of the organizational and technical environment in which validation at Organon International took place, followed by an overview of the actual audit that has been performed, and the project that was undertaken to arrive at a validated clinical data system. Organon's experiences and observations during these activities and plans for the future will be covered.