Removing the FDA's Boxed Hepatotoxicity Warning and Liver Function Testing Requirement for Ambrisentan.

Importance: Endothelin receptor antagonists are first-line therapy for pulmonary arterial hypertension (PAH). The first 2 agents approved in the class, bosentan and ambrisentan, initially carried boxed warnings for hepatotoxicity and required monthly liver function tests (LFTs) as part of a risk evaluation and mitigation strategy (REMS); however, in 2011, as further safety data emerged on ambrisentan, the boxed hepatotoxicity warning and LFT requirements were removed. Objective: To analyze changes in the use of and LFT monitoring for ambrisentan and bosentan after changes to the ambrisentan labeling and REMS. Design, Setting, and Participants: This serial cross-sectional study used data from 3 longitudinal health care insurance claims databases-Medicaid, Optum's deidentified Clinformatics Data Mart, and Merative Marketscan-to perform an interrupted time series analysis of prescription fills and LFTs for patients taking ambrisentan and bosentan. Participants were patients filling prescriptions for ambrisentan and bosentan from July 1, 2007, to December 31, 2018. Data analysis was performed from April 2021 to August 2023. Exposure: Removal of the boxed warning for hepatotoxicity and the REMS LFT monitoring requirements on ambrisentan in March 2011. Main Outcomes and Measures: The primary outcomes were use of ambrisentan (ie, individuals with at least 1 dispensing per 1 000 000 individuals enrolled in the 3 datasets) vs bosentan and LFT monitoring (ie, proportion of initiators with at least 1 ordered test) before initiation and before the first refill. Results: A total of 10 261 patients received a prescription for ambrisentan during the study period (7442 women [72.5%]; mean [SD] age, 52.6 [17.6] years), and 11 159 patients received a prescription for bosentan (7931 women [71.1%]; mean [SD] age, 47.7 [23.7] years). Removal of the ambrisentan boxed hepatotoxicity warning and LFT monitoring requirement was associated with an immediate increase in the use of ambrisentan (1.50 patients per million enrollees; 95% CI, 1.08 to 1.92 patients per million enrollees) but no significant change in the use of bosentan. There were reductions in recorded LFTs before drug initiation (13.1% absolute decrease; 95% CI, -18.2% to -8.0%) and before the first refill (26.4% absolute decrease; 95% CI, -34.4% to -18.5%) of ambrisentan but not bosentan. Conclusions and Relevance: In this serial cross-sectional study of ambrisentan, labeling changes and removal of the REMS-related LFT requirement were associated with shifts in prescribing and testing behavior for ambrisentan but not bosentan. Further clinician education may be needed to maximize the benefits of REMS programs and labeling warnings designed to ensure the safe administration of high-risk medications.

Trends in Use and Evidence of Adherence to Risk Evaluation and Mitigation Strategy Pregnancy Testing Requirements for Thalidomide, Lenalidomide, and Pomalidomide in the USA, 2000-2020.

INTRODUCTION: Lenalidomide, pomalidomide, and thalidomide are effective treatments for multiple myeloma but are teratogenic. To mitigate this risk, the US Food and Drug Administration (FDA) required risk evaluation and mitigation strategy (REMS) programs for these drugs, which include pregnancy testing among women of childbearing potential-twice before initiation, weekly in the first month on treatment, and every 2-4 weeks thereafter. OBJECTIVE: We evaluated dispensing trends of lenalidomide, pomalidomide, and thalidomide and assessed adherence to REMS pregnancy testing requirements among at-risk patients taking these drugs. METHODS: Using three US health insurance claims databases (Optum Clinformatics® [2004-2020], Merative Marketscan [2003-2019], and Medicaid [2000-2018]), we assessed monthly use of the drugs, patient characteristics and treatment persistence among drug initiators, and claims-based evidence for adherence to pregnancy testing requirements among initiators with child-bearing potential. RESULTS: Lenalidomide was the most prescribed agent following its approval in 2006 and through the end of the study period. A total of 48,311 lenalidomide (mean age = 59 years [standard deviation (SD) = 16]), 17,550 thalidomide (mean age = 65 years [SD = 12]), and 6560 pomalidomide initiators (mean age = 65 years [SD = 11]) were identified; 45% of initiators of each drug were women. Among initiators under follow-up on day 90, 70% were still on therapy. Initiators of childbearing potential comprised 3% (N = 1,920) of all initiators; among this cohort, 12% had evidence in claims data of two pregnancy tests before initiation, and 9% with at least 33 days of follow-up of four tests during the first month of treatment. By contrast, 52% who received a refill had claims-based evidence of a pregnancy test within 7 days of dispensing. CONCLUSION: Although most patients who initiated lenalidomide, pomalidomide, and thalidomide were not of child-bearing potential, further investigation into actual non-adherence to pregnancy testing is needed.

Sociodemographic Characteristics of Adverse Event Reporting in the USA: An Ecologic Study.

INTRODUCTION: The Food and Drug Administration Adverse Event Reporting System (FAERS) is a vital source of new drug safety information, but whether adverse event (AE) information collected from these systems adequately captures experiences of the overall United States (US) population is unknown. OBJECTIVE: To examine determinants of consumer AE reporting in the USA. METHODS: Five-year AE reporting rate per 100,000 residents per US county were calculated, mapped, and quartiled for AE reports received directly from consumers between 2011 and 2015. Associations between county-level sociodemographic factors obtained from County Health Rankings and AE reporting rates were evaluated using negative binomial regression. RESULTS: Reporting rates were variable across US counties with > 17.6 reports versus ≤ 5.5 reports/100,000 residents in the highest and lowest reporting quartile, respectively. Controlling for drug utilization, counties with higher reporting rates had higher proportions of individuals age ≥ 65 years (e.g., 2.4% reporting increase per 1% increase in individuals age > 65, incidence rate ratio (IRR): 1.024, 95% confidence interval (CI): 1.017-1.030), higher proportions of females (IRR: 1.027, 95% CI 1.012-1.043), uninsured (IRR: 1.009, 95% CI 1.005-1.013), higher median log household incomes (IRR: 1.897, 95% CI 1.644-2.189) and more mental health providers per 100,000 residents (IRR: 1.003, 95% CI 1.001-1.004). Lower reporting was observed in counties with higher proportions of individuals age ≤ 18 years (IRR: 0.966, 95% CI 0.959-0.974), American Indian or Alaska Native individuals (IRR: 0.991, 95% CI 0.986-0.996), individuals not proficient in English (IRR: 0.978, 95% CI 0.965-0.991), and individuals residing in rural areas within a county (IRR: 0.998, 95% CI 0.997-0.998). CONCLUSIONS: Observed variations in consumer AE reporting may be related to sociodemographic factors and healthcare access. Because these factors may also correspond to AE susceptibility, voluntary AE reporting systems may be suboptimal for capturing emerging drug safety concerns among more vulnerable populations.

How Do Risk Evaluation and Mitigation Strategies Impact Clinical Practice? A National Survey of Physicians.

The US Food and Drug Administration can require risk evaluation and mitigation strategy (REMS) programs for prescription drugs to ensure the benefits of use outweigh the risks. We conducted a national survey of physicians' experiences prescribing eight REMS-covered drugs: (1) ambrisentan; (2) bosentan; (3) clozapine; (4) isotretinoin; (5-7) the multiple myeloma (MM) drugs lenalidomide, pomalidomide, thalidomide; and (8) sodium oxybate. Between May 2022 and January 2023, we surveyed 5,331 physician prescribers of these drugs, and 1,295 (24%) returned surveys (range: 149 for bosentan to 226 for MM drugs). Although 765 (68%) respondents thought the certification process provided useful drug information, 757 (67%) wanted materials to include benefit data and 944 (84%) non-REMS-related risk data. A majority (704, 63%) thought the safe use requirements facilitated discussion with patients, but a similar number (637, 57%) attributed delayed medication access to these requirements. In multivariable modeling, MM drug and isotretinoin respondents were less likely than sodium oxybate respondents to agree that the certification process provided useful drug information (MM drug: odds ratio (OR) = 0.37, 95% confidence interval (CI) = 0.25-0.55; isotretinoin: OR = 0.39, 95% CI = 0.25-0.61), and isotretinoin, clozapine, and bosetan respondents were more likely than sodium oxybate respondents to agree that the safe use requirements often delayed medication access (isotretinoin: OR = 5.83, 95% CI = 3.70-9.19; clozapine: OR = 1.65, 95% CI = 1.08-2.54; bosentan: OR = 1.78, 95% CI = 1.12-2.85). Most physicians believe REMS programs convey useful drug safety information and facilitate discussion with patients but also seek information on benefits and non-REMS-related risks and better integration of REMS processes into clinical workflows.

Trends in Incident Prescriptions for Behavioral Health Medications in the US, 2018-2022.

Importance: The COVID-19 pandemic reportedly increased behavioral health needs and impacted treatment access. Objective: To assess changes in incident prescriptions dispensed for medications commonly used to treat depression, anxiety, attention-deficit/hyperactivity disorder (ADHD), and opioid use disorder (OUD), before and during the COVID-19 pandemic. Design, Setting, and Participants: This was a cross-sectional study using comprehensive, population-level, nationally projected data from IQVIA National Prescription Audit on incident prescriptions (prescriptions dispensed to patients with no prior dispensing from the same drug class in the previous 12 months) dispensed for antidepressants, benzodiazepines, Schedule II (C-II) stimulants, nonstimulant medications for ADHD, and buprenorphine-containing medication for OUD (MOUD), from US outpatient pharmacies. Data were analyzed from April 2018 to March 2022. Exposure: Incident prescriptions by drug class (by prescriber specialty, patient age, and sex) and drug. Main Outcomes and Measures: Interrupted time-series analysis to compare changes in trends in the monthly incident prescriptions dispensed by drug class and percentage changes in aggregate incident prescriptions dispensed between April 2018 and March 2022. Results: Incident prescriptions dispensed for the 5 drug classes changed from 51 500 321 before the COVID-19 pandemic to 54 000 169 during the pandemic. The largest unadjusted percentage increase in incident prescriptions by prescriber specialty was among nurse practitioners across all drug classes ranging from 7% (from 1 811 376 to 1 944 852; benzodiazepines) to 78% (from 157 578 to 280 925; buprenorphine MOUD), whereas for patient age and sex, the largest increases were within C-II stimulants and nonstimulant ADHD drugs among patients aged 20 to 39 years (30% [from 1 887 017 to 2 455 706] and 81% [from 255 053 to 461 017], respectively) and female patients (25% [from 2 352 095 to 2 942 604] and 59% [from 395 678 to 630 678], respectively). Trends for C-II stimulants and nonstimulant ADHD drugs (slope change: 4007 prescriptions per month; 95% CI, 1592-6422 and 1120 prescriptions per month; 95% CI, 706-1533, respectively) significantly changed during the pandemic, exceeding prepandemic trends after an initial drop at the onset of the pandemic (level changes: -50 044 prescriptions; 95% CI, -80 202 to -19 886 and -12 876 prescriptions; 95% CI, -17 756 to -7996, respectively). Although buprenorphine MOUD dropped significantly (level change: -2915 prescriptions; 95% CI, -5513 to -318), trends did not significantly change for buprenorphine MOUD, antidepressants, or benzodiazepines. Conclusions and Relevance: Incident use of many behavioral health medications remained relatively stable during the COVID-19 pandemic in the US, whereas ADHD medications, notably C-II stimulants, sharply increased. Additional research is needed to differentiate increases due to unmet need vs overprescribing, highlighting the need for further ADHD guideline development to define treatment appropriateness.

Six Years of the US Food and Drug Administration's Postmarket Active Risk Identification and Analysis System in the Sentinel Initiative: Implications for Real World Evidence Generation.

Congress mandated the creation of a postmarket Active Risk Identification and Analysis (ARIA) system containing data on 100 million individuals for monitoring risks associated with drug and biologic products using data from disparate sources to complement the US Food and Drug Administration's (FDA's) existing postmarket capabilities. We report on the first 6 years of ARIA utilization in the Sentinel System (2016-2021). The FDA has used the ARIA system to evaluate 133 safety concerns; 54 of these evaluations have closed with regulatory determinations, whereas the rest remain in progress. If the ARIA system and the FDA's Adverse Event Reporting System are deemed insufficient to address a safety concern, then the FDA may issue a postmarket requirement to a product's manufacturer. One hundred ninety-seven ARIA insufficiency determinations have been made. The most common situation for which ARIA was found to be insufficient is the evaluation of adverse pregnancy and fetal outcomes following in utero drug exposure, followed by neoplasms and death. ARIA was most likely to be sufficient for thromboembolic events, which have high positive predictive value in claims data alone and do not require supplemental clinical data. The lessons learned from this experience illustrate the continued challenges using administrative claims data, especially to define novel clinical outcomes. This analysis can help to identify where more granular clinical data are needed to fill gaps to improve the use of real-world data for drug safety analyses and provide insights into what is needed to efficiently generate high-quality real-world evidence for efficacy.

Assessment of the Impact of Mandated Postmarketing Pediatric-Focused Safety Reviews on Safety-Related Regulatory Actions 2013-2019.

The US Food and Drug Administration's (FDA's) routine postmarketing drug safety monitoring may lead to safety-related labeling changes for identified risks. Additionally, the Best Pharmaceuticals for Children Act (BPCA) and Pediatric Research Equity Act (PREA) require the FDA to conduct postmarket pediatric-focused safety reviews of adverse events. The purpose of these pediatric reviews is to identify risks associated with drug or biological products 18 months after the FDA approves a pediatric labeling change pursuant to studies conducted under the BPCA or PREA. These reviews are presented to the FDA Pediatric Advisory Committee (PAC) or publicly posted on FDA's website. The aim of this study was to evaluate the impact of pediatric reviews prompted by BPCA/PREA from October 1, 2013, to September 30, 2019. The impact was quantified by the number of new safety signals identified and the subsequent safety-related labeling changes resulting from pediatric reviews relative to safety-related labeling changes triggered by other data sources. Among 163 products with at least one pediatric review completed, a new safety signal that resulted in a safety-related labeling change was found for 5 of these products (representing 3 active ingredients); none described risks specific to the pediatric population. Between October 2013 and September 2021, there were 585 safety-related labeling changes implemented for products with at least one completed pediatric review. Less than 1% of 585 safety-related labeling changes were the result of a mandated pediatric review. Our study suggests that mandated pediatric reviews conducted 18 months after a pediatric labeling change provided minimal value over other postmarket safety surveillance activities.

The Food and Drug Administration's (FDA's) Drug Safety Surveillance During the COVID-19 Pandemic.

INTRODUCTION: On 4 February, 2020, the Secretary of the Department of Health and Human Services declared a public health emergency related to coronavirus disease 2019 (COVID-19), and on 27 March, 2020 declared circumstances existed to justify the authorization of the emergency use of drug and biological products (hereafter, "drugs") for COVID-19. At the outset of the pandemic with uncertainty relating to the virus, many drugs were being used to treat or prevent COVID-19, resulting in the US Food and Drug Administration's (FDA's) need to initiate heightened surveillance across these drugs. OBJECTIVE: We aimed to describe the FDA's approach to monitoring the safety of drugs to treat or prevent COVID-19 across multiple data sources and the subsequent actions taken by the FDA to protect public health. METHODS: The FDA conducted surveillance of adverse event and medication error data using the FDA Adverse Event Reporting System, biomedical literature, FDA-American College of Medical Toxicology COVID-19 Toxicology Investigators Consortium Pharmacovigilance Project Sub-registry, and the American Association of Poison Control Centers National Poison Data System. RESULTS: From 4 February, 2020, through 31 January, 2022, we identified 22,944 unique adverse event cases worldwide and 1052 unique medication error cases domestically with drugs to treat or prevent COVID-19. These were from the FDA Adverse Event Reporting System (22,219), biomedical literature (1107), FDA-American College of Medical Toxicology COVID-19 Toxicology Investigator's Consortium Sub-registry (638), and the National Poison Data System (32), resulting in the detection of several important safety issues. CONCLUSIONS: Safety surveillance using near real-time data was critical during the COVID-19 pandemic because the FDA monitored an unprecedented number of drugs to treat or prevent COVID-19. Additionally, the pandemic prompted the FDA to accelerate innovation, forging new collaborations and leveraging data sources to conduct safety surveillance to respond to the pandemic.

The US Food and Drug Administration Sentinel System: a national resource for a learning health system.

The US Food and Drug Administration (FDA) created the Sentinel System in response to a requirement in the FDA Amendments Act of 2007 that the agency establish a system for monitoring risks associated with drug and biologic products using data from disparate sources. The Sentinel System has completed hundreds of analyses, including many that have directly informed regulatory decisions. The Sentinel System also was designed to support a national infrastructure for a learning health system. Sentinel governance and guiding principles were designed to facilitate Sentinel's role as a national resource. The Sentinel System infrastructure now supports multiple non-FDA projects for stakeholders ranging from regulated industry to other federal agencies, international regulators, and academics. The Sentinel System is a working example of a learning health system that is expanding with the potential to create a global learning health system that can support medical product safety assessments and other research.

"Artificial Intelligence" for Pharmacovigilance: Ready for Prime Time?

There is great interest in the application of 'artificial intelligence' (AI) to pharmacovigilance (PV). Although US FDA is broadly exploring the use of AI for PV, we focus on the application of AI to the processing and evaluation of Individual Case Safety Reports (ICSRs) submitted to the FDA Adverse Event Reporting System (FAERS). We describe a general framework for considering the readiness of AI for PV, followed by some examples of the application of AI to ICSR processing and evaluation in industry and FDA. We conclude that AI can usefully be applied to some aspects of ICSR processing and evaluation, but the performance of current AI algorithms requires a 'human-in-the-loop' to ensure good quality. We identify outstanding scientific and policy issues to be addressed before the full potential of AI can be exploited for ICSR processing and evaluation, including approaches to quality assurance of 'human-in-the-loop' AI systems, large-scale, publicly available training datasets, a well-defined and computable 'cognitive framework', a formal sociotechnical framework for applying AI to PV, and development of best practices for applying AI to PV. Practical experience with stepwise implementation of AI for ICSR processing and evaluation will likely provide important lessons that will inform the necessary policy and regulatory framework to facilitate widespread adoption and provide a foundation for further development of AI approaches to other aspects of PV.

Sources of Evidence Triggering and Supporting Safety-Related Labeling Changes: A 10-Year Longitudinal Assessment of 22 New Molecular Entities Approved in 2008 by the US Food and Drug Administration.

INTRODUCTION: New safety issues concerning US FDA-approved drugs are commonly communicated through safety-related labeling changes. Therefore, to optimize and refine postmarket safety surveillance strategies, it is important to comprehensively characterize the sources of data giving rise to safety-related labeling changes. OBJECTIVES: Our objective was to characterize the sources of data triggering and supporting the identification of new safety risks of FDA-approved drugs communicated through safety-related labeling changes. METHODS: We conducted a retrospective study with a 10-year observation period using FDA's internal electronic data repositories for all prescription new molecular entities (NME) approved in 2008. We collected and analyzed information on new safety issues, the section of the full prescribing information updated, initiators (FDA, drug manufacturer), and triggering and supporting sources of evidence. RESULTS: Among 22 NMEs approved in 2008, 189 new safety issues for 18 NMEs were identified. Compared to drug manufacturer, FDA initiated safety-related labeling changes in nine of the ten changes to the Boxed Warnings, 28 of the 52 changes to the Warnings and Precautions, and 43 of the 134 changes to the Adverse Reactions sections of the full prescribing information. The most frequent triggering sources of evidence included the drug manufacturer safety database (32.3%) and FDA Adverse Event Reporting System (FAERS) safety reports (15.3%) for all relevant sections of the full prescribing information, and class-labeling changes (17.5%) for Boxed Warnings and the Warnings and Precautions sections. The most frequent triggering source of evidence was FAERS safety reports (69%) in the first year after drug approval and the drug manufacturer safety database in subsequent years. CONCLUSIONS: Our findings emphasize the continued importance of safety reports from FAERS and drug manufacturer safety databases and a comprehensive drug safety surveillance program throughout a drug's lifecycle.

The Use of Real-World Data to Assess the Impact of Safety-Related Regulatory Interventions.

The regulation of medicines seeks to ensure the efficacy, safety, and quality of prescription and non-prescription medicines. Given that the conditions under which a medicine's benefits outweigh its risks are complex, it is essential that communications about the safe and effective use of medicines be clear and actionable. Assessing the impact of interventions to improve the safe and effective use of medicines is a developing area, and one in which real-world data are playing an increasingly important role. Although real-world data are commonly used to assess the impact of regulatory interventions, there are several areas where their use could be improved. Specific areas for improvement include assessing regulatory interventions across a wider range of medicines, rather than concentrating on a relatively few therapeutic areas; assessing more clinically relevant outcomes rather than relying on measures such as changes in the number of prescriptions, which may not always correlate with the desired impact; assessing the potential unintended or negative consequences of regulatory interventions; applying methods to address potential confounders; assessing long-term, rather than just short-term, impacts of an intervention; increasing the use of comparator groups, when feasible; and evaluating the impact of regulatory interventions from multiple dimensions, rather than from a single dimension. Expanded use of real-world data could inform some of these efforts, although data sources beyond administrative claims data will likely be necessary to achieve all these goals.

Patient-Reported Opioid Analgesic Use After Discharge from Surgical Procedures: A Systematic Review.

OBJECTIVE: This systematic review synthesizes evidence on patient-reported outpatient opioid analgesic use after surgery. METHODS: We searched PubMed (February 2019) and Web of Science and Embase (June 2019) for U.S. studies describing patient-reported outpatient opioid analgesic use. Two reviewers extracted data on opioid analgesic use, standardized the data on use , and performed independent quality appraisals based on the Cochrane Risk of Bias Tool and an adapted Newcastle-Ottawa scale. RESULTS: Ninety-six studies met the eligibility criteria; 56 had sufficient information to standardize use in oxycodone 5-mg tablets. Patient-reported opioid analgesic use varied widely by procedure type; knee and hip arthroplasty had the highest postoperative opioid use, and use after many procedures was reported as <5 tablets. In studies that examined excess tablets, 25-98% of the total tablets prescribed were reported to be excess, with most studies reporting that 50-70% of tablets went unused. Factors commonly associated with higher opioid analgesic use included preoperative opioid analgesic use, higher inpatient opioid analgesic use, higher postoperative pain scores, and chronic medical conditions, among others. Estimates also varied across studies because of heterogeneity in study design, including length of follow-up and inclusion/exclusion criteria. CONCLUSION: Self-reported postsurgery outpatient opioid analgesic use varies widely both across procedures and within a given procedure type. Contributors to within-procedure variation included patient characteristics, prior opioid use, intraoperative and perioperative factors, and differences in the timing of opioid use data collection. We provide recommendations to help minimize variation caused by study design factors and maximize interpretability of forthcoming studies for use in clinical guidelines and decision-making.

Broadening the reach of the FDA Sentinel system: A roadmap for integrating electronic health record data in a causal analysis framework.

The Sentinel System is a major component of the United States Food and Drug Administration's (FDA) approach to active medical product safety surveillance. While Sentinel has historically relied on large quantities of health insurance claims data, leveraging longitudinal electronic health records (EHRs) that contain more detailed clinical information, as structured and unstructured features, may address some of the current gaps in capabilities. We identify key challenges when using EHR data to investigate medical product safety in a scalable and accelerated way, outline potential solutions, and describe the Sentinel Innovation Center's initiatives to put solutions into practice by expanding and strengthening the existing system with a query-ready, large-scale data infrastructure of linked EHR and claims data. We describe our initiatives in four strategic priority areas: (1) data infrastructure, (2) feature engineering, (3) causal inference, and (4) detection analytics, with the goal of incorporating emerging data science innovations to maximize the utility of EHR data for medical product safety surveillance.

Trend changes of national zolpidem users and exposure cases after FDA drug safety communications.

PURPOSE: To evaluate the impact of FDA's 2013 zolpidem Drug Safety Communications (DSCs), which recommended lowering the initial dose to mitigate drowsiness, on national estimates of zolpidem users and zolpidem exposure cases. METHODS: We analyzed trend changes of national zolpidem users from the IQVIA Total Patient Tracker (TPT) and zolpidem exposure cases reported to the National Poison Data System (NPDS), 2009-2018. To control for time varying confounding, the adjusted trends were analyzed using simple and controlled interrupted time series (ITS). We also adjusted for seasonal changes. Three sedating antidepressants were used together as a control. RESULTS: The national estimates of high-dose zolpidem users in TPT decreased significantly in the month immediately post-DSC; the absolute level decrease was -12.51 (95% CI: -14.12, -10.89) per 10 000 U.S. population relative to sedating antidepressants. The trend continuously decreased post-DSC, resulting in a 59% overall decrease by the end of the study period. There was a larger decrease in high-dose zolpidem use in females than in males. There was a level decrease of zolpidem exposure cases in the NPDS immediately post-DSC, -0.37 absolute decline (95% CI, -0.53, -0.20) per 10 000 national zolpidem users; or -1.33 absolute decline (95% CI, -1.54, -1.13) per 1000 total NPDS exposure cases relative to sedating antidepressants. Similar patterns were observed for cases reporting drowsiness. The results from the single ITS and controlled ITS were similar. CONCLUSIONS: Zolpidem users and exposure cases decreased significantly post-DSC, suggesting practitioners and patients became aware of and responded to the zolpidem DSCs.

The Impact of Variability in Patient Exposure During Premarket Clinical Development on Postmarket Safety Outcomes.

We characterized the size of the premarket safety population for 278 small-molecule new molecular entities (NMEs) and 61 new therapeutic biologics (NTBs) approved by the US Food and Drug Administration (FDA) between October 1, 2002, and December 31, 2014, evaluating the relationship of premarket safety population size to regulatory characteristics and postmarket safety outcomes. The median size of the safety population was 1,044, and was lower for NTBs than NMEs (median: 920 vs. 1,138, P = 0.04), orphan products than nonorphan products (393 vs. 1,606, P < 0.001), and for products with fast-track designation (617 vs. 1,455, P < 0.001), priority review (630 vs. 1,735, P < 0.001), and accelerated approval (475 vs. 1,164, P < 0.001), than products without that designation. The median number of postmarket safety label updates and issues added to the label were higher with larger premarket exposure among nonorphan products, but not among orphan products. Products with accelerated approval using a surrogate end point had a higher median number of safety issues added to the label than those with full approval, but this did not vary with the size of the safety population; fast-track and priority review were not associated with the number of safety issues added to the label. A smaller safety population size was associated with a longer time to first safety outcome for nonorphan products but not orphan products. For orphan and nonorphan products combined, smaller premarket safety population size is not associated with the number or timing of postmarket safety outcomes, regardless of expedited program participation.

A COVID-19-ready public health surveillance system: The Food and Drug Administration's Sentinel System.

The US Food and Drug Administration's Sentinel System was established in 2009 to use routinely collected electronic health data for improving the national capability to assess post-market medical product safety. Over more than a decade, Sentinel has become an integral part of FDA's surveillance capabilities and has been used to conduct analyses that have contributed to regulatory decisions. FDA's role in the COVID-19 pandemic response has necessitated an expansion and enhancement of Sentinel. Here we describe how the Sentinel System has supported FDA's response to the COVID-19 pandemic. We highlight new capabilities developed, key data generated to date, and lessons learned, particularly with respect to working with inpatient electronic health record data. Early in the pandemic, Sentinel developed a multi-pronged approach to support FDA's anticipated data and analytic needs. It incorporated new data sources, created a rapidly refreshed database, developed protocols to assess the natural history of COVID-19, validated a diagnosis-code based algorithm for identifying patients with COVID-19 in administrative claims data, and coordinated with other national and international initiatives. Sentinel is poised to answer important questions about the natural history of COVID-19 and is positioned to use this information to study the use, safety, and potentially the effectiveness of medical products used for COVID-19 prevention and treatment.