Remdesivir Discontinuation Decisions Based on Thresholds of Aminotransferase in an Observational Registry.

BACKGROUND: Remdesivir is an antiviral approved by the US Food and Drug Administration (FDA) for treatment of coronavirus disease 2019 (COVID-19), and aminotransferase elevation is commonly reported. Thresholds to be considered for discontinuation due to alanine aminotransferase (ALT) elevation differ between the FDA and European Medicines Agency (EMA). The primary objective was to describe aminotransferase thresholds being used in real-world practice for discontinuation of remdesivir in patients with COVID-19, and compare them with labeled recommendations. METHODS: This study used a descriptive design based on an ongoing national registry of adverse events, the FDA ACMT COVID-19 ToxIC (FACT) pharmacovigilance project, with 17 participating health systems in the USA. Cases were identified retrospectively for an 18-month period (23 November 2020-18 May 2022). Classification of discontinuation as premature and due to aminotransferases was based on chart documentation by the treating team. RESULTS: Of 1026 cases in the FACT registry, 116 cases were included with supplemental data forms completed for aminotransferase elevation with remdesivir, defined a priori for inclusion as ALT doubling or increasing by ≥ 50 U/L. ALT was elevated prior to remdesivir in 47% and increased above baseline during dosing by a median of 92 U/L [interquartile range (IQR) 51-164, max 8350]. Remdesivir was discontinued early in 37 (31.9%) patients due to elevated aminotransferases. The ALT threshold for premature discontinuation was median 200 U/L (IQR 145-396, range 92-5743). Among patients with premature discontinuation of remdesivir for aminotransferase elevation, only 21.6% met FDA criteria to consider discontinuation, and 40.5% met prior EMA criteria to consider discontinuation. CONCLUSION: In this descriptive study of real-world practice in the USA, clinicians are overall making more conservative treatment decisions than are recommended for consideration in approved drug labeling of discontinuation, with wide variation in the aminotransferase thresholds being used.

Intranasal Naloxone Repeat Dosing Strategies and Fentanyl Overdose: A Simulation-Based Randomized Clinical Trial.

Importance: Questions have emerged as to whether standard intranasal naloxone dosing recommendations (ie, 1 dose with readministration every 2-3 minutes if needed) are adequate in the era of illicitly manufactured fentanyl and its derivatives (hereinafter, fentanyl). Objective: To compare naloxone plasma concentrations between different intranasal naloxone repeat dosing strategies and to estimate their effect on fentanyl overdose. Design, Setting, and Participants: This unblinded crossover randomized clinical trial was conducted with healthy participants in a clinical pharmacology unit (Spaulding Clinical Research, West Bend, Wisconsin) in March 2021. Inclusion criteria included age 18 to 55 years, nonsmoking status, and negative test results for the presence of alcohol or drugs of abuse. Data analysis was performed from October 2021 to May 2023. Intervention: Naloxone administered as 1 dose (4 mg/0.1 mL) at 0, 2.5, 5, and 7.5 minutes (test), 2 doses at 0 and 2.5 minutes (test), and 1 dose at 0 and 2.5 minutes (reference). Main Outcomes and Measures: The primary outcome was the first prespecified time with higher naloxone plasma concentration. The secondary outcome was estimated brain hypoxia time following simulated fentanyl overdoses using a physiologic pharmacokinetic-pharmacodynamic model. Naloxone concentrations were compared using paired tests at 3 prespecified times across the 3 groups, and simulation results were summarized using descriptive statistics. Results: This study included 21 participants, and 18 (86%) completed the trial. The median participant age was 34 years (IQR, 27-50 years), and slightly more than half of participants were men (11 [52%]). Compared with 1 naloxone dose at 0 and 2.5 minutes, 1 dose at 0, 2.5, 5, and 7.5 minutes significantly increased naloxone plasma concentration at 10 minutes (7.95 vs 4.42 ng/mL; geometric mean ratio, 1.95 [1-sided 97.8% CI, 1.28-∞]), whereas 2 doses at 0 and 2.5 minutes significantly increased the plasma concentration at 4.5 minutes (2.24 vs 1.23 ng/mL; geometric mean ratio, 1.98 [1-sided 97.8% CI, 1.03-∞]). No drug-related serious adverse events were reported. The median brain hypoxia time after a simulated fentanyl 2.97-mg intravenous bolus was 4.5 minutes (IQR, 2.1-∞ minutes) with 1 naloxone dose at 0 and 2.5 minutes, 4.5 minutes (IQR, 2.1-∞ minutes) with 1 naloxone dose at 0, 2.5, 5, and 7.5 minutes, and 3.7 minutes (IQR, 1.5-∞ minutes) with 2 naloxone doses at 0 and 2.5 minutes. Conclusions and Relevance: In this clinical trial with healthy participants, compared with 1 intranasal naloxone dose administered at 0 and 2.5 minutes, 1 dose at 0, 2.5, 5, and 7.5 minutes significantly increased naloxone plasma concentration at 10 minutes, whereas 2 doses at 0 and 2.5 minutes significantly increased naloxone plasma concentration at 4.5 minutes. Additional research is needed to determine optimal naloxone dosing in the community setting. Trial Registration: ClinicalTrials.gov Identifier: NCT04764630.

Adverse Events in Pregnant Patients Treated with Coronavirus Disease 2019 Therapeutics.

BACKGROUND: Pregnant patients are at high risk of maternal and fetal complications from Coronavirus Disease 2019 (COVID-19) infections. The COVID-19 pandemic prompted a surge in the development and repurposing of therapies for the SARS-CoV-2 virus. Evidence is sparse on the efficacy and safety of these therapies in pregnant patients. Our objective was to describe adverse events (AEs) to COVID-19 therapeutics in pregnant patients. METHODS: This was a case series of AEs reported to the FDA ACMT COVID-19 ToxIC (FACT) Pharmacovigilance Project between November 23, 2020, and June 28, 2022. FACT is an ongoing toxicosurveillance project at 17 sites to proactively identify and report AEs associated with COVID-19 therapeutics. Abstracted information includes demographics, case narratives, exposure details, clinical information, pregnancy details, treatments, and outcomes. RESULTS: Forty-six COVID-19-positive pregnant patients who developed AEs following COVID-19 therapeutics were reported to the FACT Pharmacovigilance Project over 19 months. The most reported medications were remdesivir in 22 patients (47.8%) and casirivimab/imdevimab in 8 patients (17.4%). Four patients (8.7%) had life-threatening clinical manifestation, and 16 patients (34.8%) required intervention to prevent permanent damage. The most common maternal and fetal events were elevated serum alanine aminotransferase (26.1%) and non-reassuring fetal heart patterns (20.0%), respectively. CONCLUSIONS: This case series reports AEs of elevated serum alanine aminotransferase, maternal bradycardia, maternal hypothermia, non-reassuring fetal heart patterns, and emergent or unplanned cesarean sections following administration of several COVID-19 therapeutics. This study was not designed to definitely identify causation, and further study is needed to evaluate the causal role of these therapeutics in AEs affecting pregnant COVID-19 patients.

Rewiring Drug Research and Development through Human Data-Driven Discovery (HD3).

In an era of unparalleled technical advancement, the pharmaceutical industry is struggling to transform data into increased research and development efficiency, and, as a corollary, new drugs for patients. Here, we briefly review some of the commonly discussed issues around this counterintuitive innovation crisis. Looking at both industry- and science-related factors, we posit that traditional preclinical research is front-loading the development pipeline with data and drug candidates that are unlikely to succeed in patients. Applying a first principles analysis, we highlight the critical culprits and provide suggestions as to how these issues can be rectified through the pursuit of a Human Data-driven Discovery (HD3) paradigm. Consistent with other examples of disruptive innovation, we propose that new levels of success are not dependent on new inventions, but rather on the strategic integration of existing data and technology assets. In support of these suggestions, we highlight the power of HD3, through recently published proof-of-concept applications in the areas of drug safety analysis and prediction, drug repositioning, the rational design of combination therapies and the global response to the COVID-19 pandemic. We conclude that innovators must play a key role in expediting the path to a largely human-focused, systems-based approach to drug discovery and research.

Identification of Bradycardia Following Remdesivir Administration Through the US Food and Drug Administration American College of Medical Toxicology COVID-19 Toxic Pharmacovigilance Project.

Importance: The rapid spread and mortality associated with COVID-19 emphasized a need for surveillance system development to identify adverse events (AEs) to emerging therapeutics. Bradycardia is a remdesivir infusion-associated AE listed in the US Food and Drug Administration-approved prescribing information. Objective: To evaluate the magnitude and duration of bradycardic events following remdesivir administration. Design, Setting, and Participants: A multicenter cohort study of patients with recorded heart rate less than 60 beats per minute within 24 hours after administration of a remdesivir dose was conducted between November 23, 2020, and October 31, 2021. Participants included patients hospitalized with COVID-19 at 15 medical centers across the US. Patients excluded had AEs unrelated to bradycardia, AEs in addition to bradycardia, or first onset of bradycardia after 5 remdesivir doses. Exposures: Remdesivir administration. Main Outcomes and Measures: Linear mixed-effect models for the minimum HR before starting remdesivir and within 24 hours of each dose included doses as fixed effects. Baseline covariates were age (≥65 years vs <65 years), sex (male vs female), cardiovascular disease history (yes vs no), and concomitant use of bradycardia-associated medications. The interactions between variables and doses were considered fixed-effects covariates to adjust models. Results: A total of 188 patients were included in the primary analysis and 181 in the secondary analysis. The cohort included 108 men (57.4%); 75 individuals (39.9%) were non-Hispanic White and mean (SD) age was 61.3 (15.4) years. Minimum HR after doses 1 to 5 was lower than before remdesivir. Mean minimum HR was lowest after dose 4, decreasing by -15.2 beats per minute (95% CI, -17.4 to -13.1; P < .001) compared with before remdesivir administration. Mean (SD) minimum HR was 55.6 (10.2) beats per minute across all 5 doses. Of 181 patients included in time-to-event analysis, 91 had their first episode of bradycardia within 23.4 hours (95% CI, 20.1-31.5 hours) and 91 had their lowest HR within 60.7 hours (95% CI, 54.0-68.3 hours). Median time to first bradycardia after starting remdesivir was shorter for patients aged 65 years or older vs those younger than 65 years (18.7 hours; 95% CI, 16.8-23.7 hours vs 31.5 hours; 95% CI, 22.7-39.3 hours; P = .04). Median time to lowest HR was shorter for men vs women (54.2 hours; 95% CI, 47.3-62.0 hours vs 71.0 hours; 95% CI, 59.5-79.6 hours; P = .02). Conclusions and Relevance: In this cohort study, bradycardia occurred during remdesivir infusion and persisted. Given the widespread use of remdesivir, practitioners should be aware of this safety signal.

Effect of Paroxetine or Quetiapine Combined With Oxycodone vs Oxycodone Alone on Ventilation During Hypercapnia: A Randomized Clinical Trial.

Importance: Opioids can cause severe respiratory depression by suppressing feedback mechanisms that increase ventilation in response to hypercapnia. Following the addition of boxed warnings to benzodiazepine and opioid products about increased respiratory depression risk with simultaneous use, the US Food and Drug Administration evaluated whether other drugs that might be used in place of benzodiazepines may cause similar effects. Objective: To study whether combining paroxetine or quetiapine with oxycodone, compared with oxycodone alone, decreases the ventilatory response to hypercapnia. Design, Setting, and Participants: Randomized, double-blind, crossover clinical trial at a clinical pharmacology unit (West Bend, Wisconsin) with 25 healthy participants from January 2021 through May 25, 2021. Interventions: Oxycodone 10 mg on days 1 and 5 and the following in a randomized order for 5 days: paroxetine 40 mg daily, quetiapine twice daily (increasing daily doses from 100 mg to 400 mg), or placebo. Main Outcomes and Measures: Ventilation at end-tidal carbon dioxide of 55 mm Hg (hypercapnic ventilation) using rebreathing methodology assessed for paroxetine or quetiapine with oxycodone, compared with placebo and oxycodone, on days 1 and 5 (primary) and for paroxetine or quetiapine alone compared with placebo on day 4 (secondary). Results: Among 25 participants (median age, 35 years [IQR, 30-40 years]; 11 female [44%]), 19 (76%) completed the trial. The mean hypercapnic ventilation was significantly decreased with paroxetine plus oxycodone vs placebo plus oxycodone on day 1 (29.2 vs 34.1 L/min; mean difference [MD], -4.9 L/min [1-sided 97.5% CI, -∞ to -0.6]; P = .01) and day 5 (25.1 vs 35.3 L/min; MD, -10.2 L/min [1-sided 97.5% CI, -∞ to -6.3]; P < .001) but was not significantly decreased with quetiapine plus oxycodone vs placebo plus oxycodone on day 1 (33.0 vs 34.1 L/min; MD, -1.2 L/min [1-sided 97.5% CI, -∞ to 2.8]; P = .28) or on day 5 (34.7 vs 35.3 L/min; MD, -0.6 L/min [1-sided 97.5% CI, -∞ to 3.2]; P = .37). As a secondary outcome, mean hypercapnic ventilation was significantly decreased on day 4 with paroxetine alone vs placebo (32.4 vs 41.7 L/min; MD, -9.3 L/min [1-sided 97.5% CI, -∞ to -3.9]; P < .001), but not with quetiapine alone vs placebo (42.8 vs 41.7 L/min; MD, 1.1 L/min [1-sided 97.5% CI, -∞ to 6.4]; P = .67). No drug-related serious adverse events were reported. Conclusions and Relevance: In this preliminary study involving healthy participants, paroxetine combined with oxycodone, compared with oxycodone alone, significantly decreased the ventilatory response to hypercapnia on days 1 and 5, whereas quetiapine combined with oxycodone did not cause such an effect. Additional investigation is needed to characterize the effects after longer-term treatment and to determine the clinical relevance of these findings. Trial Registration: ClinicalTrials.gov Identifier: NCT04310579.

Ivermectin associated adverse events in the treatment and prevention of COVID-19 reported to the FACT pharmacovigilance project.

BACKGROUND: In August 2021, the Centers for Disease Control and Prevention (CDC) released a health alert following the rapid increase in ivermectin prescriptions and reports of severe illness associated with use of products containing ivermectin for the prevention or treatment of COVID-19 infections. The United States Food and Drug Administration (FDA) and the CDC have explicitly discouraged the use of ivermectin in the prevention or treatment of COVID-19 outside of clinical trials. The study aims to describe the adverse events (AEs) related to ivermectin use for the prevention or treatment of COVID-19. METHODS: This is a prospective case series of adverse events related to therapeutics used in the prevention or treatment of COVID-19 submitted to the FDA ACMT COVID-19 ToxIC (FACT) Pharmacovigilance Project sub-registry between October 2020 and December 2021. This is an ongoing toxico-surveillance system at 15 major academic medical centers in 12 states. Data collected included sociodemographics, exposure related information including dose, frequency, route, duration, and reason for taking ivermectin as well as a clinical description of the adverse event and the outcome. RESULTS: A total of 40 patients who developed AEs following ivermectin use were reported to FACT over 15 months. Self-medication with veterinary formulations were reported in 18/40 patients Thirty-three patients presented to emergency departments and nineteen patients were admitted to the hospital. Patients reported using ivermectin for prevention (24/40), treatment of symptoms (19/40), and for treatment of documented COVID-19 (8/40). Neurological toxicity was the most frequent finding. Fifteen patients had minor symptoms while 25 developed severe toxicity. CONCLUSIONS: Ivermectin use for the attempted treatment of COVID-19 has potential adverse health effects primarily related to neurological function. This is especially true when patients are self-treating with this medication and when they are using formulations intended for non-human use.

Acute Hyperkinetic Movement Disorders as a Multifactorial Pharmacodynamic Drug Interaction Between Methylphenidate and Risperidone in Children and Adolescents.

PURPOSE/BACKGROUND: Acute hyperkinetic movement disorders have been reported with the concomitant use of attention-deficit/hyperactivity disorder (ADHD) stimulants and antipsychotics in children and adolescents. We analyzed postmarketing reports of suspected acute hyperkinetic movement disorder associated with concomitant use of ADHD stimulants and antipsychotics. METHODS/PROCEDURES: We searched for postmarketing reports of acute hyperkinetic movement disorders associated with concomitant use of ADHD stimulants-antipsychotics in the US Food and Drug Administration Adverse Event Reporting System through December 6, 2019. PubMed and EMBASE were also searched for acute hyperkinetic movement reports with the concomitant use of ADHD stimulants-antipsychotics through January 13, 2020. FINDINGS/RESULTS: We identified 36 cases resulting in acute hyperkinetic movement disorder associated with the concomitant use of ADHD stimulants-antipsychotics, 19 of which were also identified in the medical literature. From an ADHD stimulant perspective, methylphenidate products accounted for the largest number of cases (n = 23 [64%]), followed by amphetamine products (n = 9 [25%]) and atomoxetine (n = 4 [11%]). From an antipsychotic perspective, all 36 cases were reported with second-generation antipsychotics, particularly risperidone (n = 20 [56%]). Most of the cases were reported in boys (n = 31 [86%]) aged 6 to 12 years (n = 27 [75%]). Approximately 53% of the cases reported a time to onset within 24 hours of the drug change. Acute dystonic reactions (n = 27 [75%]) were the most frequently reported movement disorder. IMPLICATIONS/CONCLUSIONS: As outlined in changes to the US prescribing information for all methylphenidate and risperidone products, health care professionals should be aware that changes to this combination may be associated with a pharmacodynamic drug-drug interaction resulting in acute hyperkinetic movement disorder.

Retrospective analysis of clinical trial safety data for pembrolizumab reveals the effect of co-occurring infections on immune-related adverse events.

Biologics targeting PD-1, PD-L1, and CTLA-4 immune checkpoint proteins have been used in a variety of tumor types including small and non-small cell lung cancers, melanoma, and renal cell carcinoma. Their anti-tumor activity is achieved through amplifying components of the patient's own immune system to target immune response evading cancer cells. However, this unique mechanism of action causes a range of immune related adverse events, irAEs, that affect multiple physiological systems in the body. These irAEs, depending on severity, often cause suspension or discontinuation of therapy and, in rare cases, may lead to fatal outcomes. In this study we focused on pembrolizumab, a PD-1 inhibitor currently approved for multiple types of cancer. We analyzed over ten thousand adverse event reports from Keynote clinical trials of pembrolizumab for various cancer indications with or without co-occurring infections, and observed a statistically significant 80% increase in the risk of developing an irAE in subjects with infections.

New science, drug regulation, and emergent public health issues: The work of FDA's division of applied regulatory science.

The U.S. Food and Drug Administration (FDA) Division of Applied Regulatory Science (DARS) moves new science into the drug review process and addresses emergent regulatory and public health questions for the Agency. By forming interdisciplinary teams, DARS conducts mission-critical research to provide answers to scientific questions and solutions to regulatory challenges. Staffed by experts across the translational research spectrum, DARS forms synergies by pulling together scientists and experts from diverse backgrounds to collaborate in tackling some of the most complex challenges facing FDA. This includes (but is not limited to) assessing the systemic absorption of sunscreens, evaluating whether certain drugs can convert to carcinogens in people, studying drug interactions with opioids, optimizing opioid antagonist dosing in community settings, removing barriers to biosimilar and generic drug development, and advancing therapeutic development for rare diseases. FDA tasks DARS with wide ranging issues that encompass regulatory science; DARS, in turn, helps the Agency solve these challenges. The impact of DARS research is felt by patients, the pharmaceutical industry, and fellow regulators. This article reviews applied research projects and initiatives led by DARS and conducts a deeper dive into select examples illustrating the impactful work of the Division.

Myocarditis occurrence with cancer immunotherapy across indications in clinical trial and post-marketing data.

Antibodies targeting the PD-1, PD-L1, and CTLA-4 immune checkpoint axis have been used in a variety of tumor types. They achieve anti-tumor activity through activating the patient's own immune system to target immune response evading cancer cells. However, this unique mechanism of action may cause immune-related adverse events, irAEs. One of these irAEs is myocarditis which is associated with an alarming mortality rate. In this study we presented clinical cases of myocarditis from safety trial datasets submitted to the U.S. Food and Drug Administration, FDA. Additionally, we analyzed over fourteen million FDA Adverse Event Reporting System, FAERS, submissions. The statistical analysis of the FAERS data provided evidence of significantly increased reporting of myocarditis in patients administered immune checkpoint inhibitors alone, in combination with another immune checkpoint inhibitor, the kinase inhibitor axitinib, or chemotherapy, for all cancer types, when compared to patients administered chemotherapy. All combination therapies led to further increased reporting odds ratios of myocarditis. We further analyzed the occurrence of myocarditis by stratifying the reports into sub-cohorts based on specific cancer types and treatment/control groups in major cancer immunotherapy efficacy trials and confirmed the observed trend for each cohort.

Target Adverse Event Profiles for Predictive Safety in the Postmarket Setting.

We improved a previous pharmacological target adverse-event (TAE) profile model to predict adverse events (AEs) on US Food and Drug Administration (FDA) drug labels at the time of approval. The new model uses more drugs and features for learning as well as a new algorithm. Comparator drugs sharing similar target activities to a drug of interest were evaluated by aggregating AEs from the FDA Adverse Event Reporting System (FAERS), FDA drug labels, and medical literature. An ensemble machine learning model was used to evaluate FAERS case count, disproportionality scores, percent of comparator drug labels with a specific AE, and percent of comparator drugs with the reports of the event in the literature. Overall classifier performance was F1 of 0.71, area under the precision-recall curve of 0.78, and area under the receiver operating characteristic curve of 0.87. TAE analysis continues to show promise as a method to predict adverse events at the time of approval.

Predicting potential adverse events using safety data from marketed drugs.

BACKGROUND: While clinical trials are considered the gold standard for detecting adverse events, often these trials are not sufficiently powered to detect difficult to observe adverse events. We developed a preliminary approach to predict 135 adverse events using post-market safety data from marketed drugs. Adverse event information available from FDA product labels and scientific literature for drugs that have the same activity at one or more of the same targets, structural and target similarities, and the duration of post market experience were used as features for a classifier algorithm. The proposed method was studied using 54 drugs and a probabilistic approach of performance evaluation using bootstrapping with 10,000 iterations. RESULTS: Out of 135 adverse events, 53 had high probability of having high positive predictive value. Cross validation showed that 32% of the model-predicted safety label changes occurred within four to nine years of approval (median: six years). CONCLUSIONS: This approach predicts 53 serious adverse events with high positive predictive values where well-characterized target-event relationships exist. Adverse events with well-defined target-event associations were better predicted compared to adverse events that may be idiosyncratic or related to secondary target effects that were poorly captured. Further enhancement of this model with additional features, such as target prediction and drug binding data, may increase accuracy.

Evaluating kratom alkaloids using PHASE.

Kratom is a botanical substance that is marketed and promoted in the US for pharmaceutical opioid indications despite having no US Food and Drug Administration approved uses. Kratom contains over forty alkaloids including two partial agonists at the mu opioid receptor, mitragynine and 7-hydroxymitragynine, that have been subjected to the FDA's scientific and medical evaluation. However, pharmacological and toxicological data for the remaining alkaloids are limited. Therefore, we applied the Public Health Assessment via Structural Evaluation (PHASE) protocol to generate in silico binding profiles for 25 kratom alkaloids to facilitate the risk evaluation of kratom. PHASE demonstrates that kratom alkaloids share structural features with controlled opioids, indicates that several alkaloids bind to the opioid, adrenergic, and serotonin receptors, and suggests that mitragynine and 7-hydroxymitragynine are the strongest binders at the mu opioid receptor. Subsequently, the in silico binding profiles of a subset of the alkaloids were experimentally verified at the opioid, adrenergic, and serotonin receptors using radioligand binding assays. The verified binding profiles demonstrate the ability of PHASE to identify potential safety signals and provide a tool for prioritizing experimental evaluation of high-risk compounds.

Target-Adverse Event Profiles to Augment Pharmacovigilance: A Pilot Study With Six New Molecular Entities.

Clinical trials can fail to detect rare adverse events (AEs). We assessed the ability of pharmacological target adverse-event (TAE) profiles to predict AEs on US Food and Drug Administration (FDA) drug labels at least 4 years after approval. TAE profiles were generated by aggregating AEs from the FDA adverse event reporting system (FAERS) reports and the FDA drug labels for drugs that hit a common target. A genetic algorithm (GA) was used to choose the adverse event (AE) case count (N), disproportionality score in FAERS (proportional reporting ratio (PRR)), and percent of comparator drug labels with an AE to maximize F-measure. With FAERS data alone, precision, recall, and specificity were 0.57, 0.78, and 0.61, respectively. After including FDA drug label data, precision, recall, and specificity improved to 0.67, 0.81, and 0.71, respectively. Eighteen of 23 (78%) postmarket label changes were identified correctly. TAE analysis shows promise as a method to predict AEs at the time of drug approval.

Association Between Serotonin Syndrome and Second-Generation Antipsychotics via Pharmacological Target-Adverse Event Analysis.

Case reports suggest an association between second-generation antipsychotics (SGAs) and serotonin syndrome (SS). The US Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) was analyzed to generate hypotheses about how SGAs may interact with pharmacological targets associated with SS. FAERS was integrated with additional sources to link information about adverse events with drugs and targets. Using Proportional Reporting Ratios, we identified signals that were further investigated with the literature to evaluate mechanistic hypotheses formed from the integrated FAERS data. Analysis revealed common pharmacological targets perturbed in both SGA and SS cases, indicating that SGAs may induce SS. The literature also supported 5-HT2A antagonism and 5-HT1A agonism as common mechanisms that may explain the SGA-SS association. Additionally, integrated FAERS data mining and case studies suggest that interactions between SGAs and other serotonergic agents may increase the risk for SS. Computational analysis can provide additional insights into the mechanisms underlying the relationship between SGAs and SS.

Translating New Science Into the Drug Review Process: The US FDA's Division of Applied Regulatory Science.

In 2011, the US Food and drug Administration (FDA) developed a strategic plan for regulatory science that focuses on developing new tools, standards, and approaches to assess the safety, efficacy, quality, and performance of FDA-regulated products. In line with this, the Division of Applied Regulatory Science was created to move new science into the Center for Drug Evaluation and Research (CDER) review process and close the gap between scientific innovation and drug review. The Division, located in the Office of Clinical Pharmacology, is unique in that it performs mission-critical applied research and review across the translational research spectrum including in vitro and in vivo laboratory research, in silico computational modeling and informatics, and integrated clinical research covering clinical pharmacology, experimental medicine, and postmarket analyses. The Division collaborates with Offices throughout CDER, across the FDA, other government agencies, academia, and industry. The Division is able to rapidly form interdisciplinary teams of pharmacologists, biologists, chemists, computational scientists, and clinicians to respond to challenging regulatory questions for specific review issues and for longer-range projects requiring the development of predictive models, tools, and biomarkers to speed the development and regulatory evaluation of safe and effective drugs. This article reviews the Division's recent work and future directions, highlighting development and validation of biomarkers; novel humanized animal models; translational predictive safety combining in vitro, in silico, and in vivo clinical biomarkers; chemical and biomedical informatics tools for safety predictions; novel approaches to speed the development of complex generic drugs, biosimilars, and antibiotics; and precision medicine.

Linking MedDRA(®)-Coded Clinical Phenotypes to Biological Mechanisms by the Ontology of Adverse Events: A Pilot Study on Tyrosine Kinase Inhibitors.

INTRODUCTION: A translational bioinformatics challenge exists in connecting population and individual clinical phenotypes in various formats to biological mechanisms. The Medical Dictionary for Regulatory Activities (MedDRA(®)) is the default dictionary for adverse event (AE) reporting in the US Food and Drug Administration Adverse Event Reporting System (FAERS). The ontology of adverse events (OAE) represents AEs as pathological processes occurring after drug exposures. OBJECTIVES: The aim of this work was to establish a semantic framework to link biological mechanisms to phenotypes of AEs by combining OAE with MedDRA(®) in FAERS data analysis. We investigated the AEs associated with tyrosine kinase inhibitors (TKIs) and monoclonal antibodies (mAbs) targeting tyrosine kinases. The five selected TKIs/mAbs (i.e., dasatinib, imatinib, lapatinib, cetuximab, and trastuzumab) are known to induce impaired ventricular function (non-QT) cardiotoxicity. RESULTS: Statistical analysis of FAERS data identified 1053 distinct MedDRA(®) terms significantly associated with TKIs/mAbs, where 884 did not have corresponding OAE terms. We manually annotated these terms, added them to OAE by the standard OAE development strategy, and mapped them to MedDRA(®). The data integration to provide insights into molecular mechanisms of drug-associated AEs was performed by including linkages in OAE for all related AE terms to MedDRA(®) and the existing ontologies, including the human phenotype ontology (HP), Uber anatomy ontology (UBERON), and gene ontology (GO). Sixteen AEs were shared by all five TKIs/mAbs, and each of 17 cardiotoxicity AEs was associated with at least one TKI/mAb. As an example, we analyzed "cardiac failure" using the relations established in OAE with other ontologies and demonstrated that one of the biological processes associated with cardiac failure maps to the genes associated with heart contraction. CONCLUSION: By expanding the existing OAE ontological design, our TKI use case demonstrated that the combination of OAE and MedDRA(®) provides a semantic framework to link clinical phenotypes of adverse drug events to biological mechanisms.

Use of data mining at the Food and Drug Administration.

OBJECTIVES: This article summarizes past and current data mining activities at the United States Food and Drug Administration (FDA). TARGET AUDIENCE: We address data miners in all sectors, anyone interested in the safety of products regulated by the FDA (predominantly medical products, food, veterinary products and nutrition, and tobacco products), and those interested in FDA activities. SCOPE: Topics include routine and developmental data mining activities, short descriptions of mined FDA data, advantages and challenges of data mining at the FDA, and future directions of data mining at the FDA.