Yale University-Mayo Clinic CERSI

Center of Excellence in Regulatory Science and Innovation

The Yale-Mayo CERSI conducts high-quality, high-impact collaborative research to support several areas of focus in the FDA strategic plan for regulatory science. Research topic areas include: adoption/de-adoption of FDA-approved medical products, postmarket surveillance, development and application of novel analytics, and patient-centered regulatory decision-making.

For comments or questions pertaining to our CERSI research projects, contact the Yale-Mayo Clinic CERSI at CERSI@yale.edu.

Current Projects

Generic drugs are approved based on bioequivalence to the brand name agents. However, there are sometimes concerns among patients and clinicians that generic and brand name drugs are not equivalent and have differing effects. Using a large administrative claims data source that includes information on privately insured and Medicare Advantage enrollees of all ages, we will characterize patterns of use of generic and brand-name L-thyroxine products and then compare the effectiveness and safety of generic and brand-name L-thyroxine among both new users and recent switchers.

Generic drugs are approved based on bioequivalence to the brand-name agents. However, there are sometimes concerns among patients and clinicians that generic and brand-name drugs are not equivalent and have differing effects. Building on our ongoing research, we will test different methods to compare the effectiveness and safety of generic and brand-name drugs using a large administrative claims data source that includes information on privately insured and Medicare Advantage enrollees of all ages. Further, we will create packages that will ease the implementation of these methods for future research. Collaborators from the University of Washington are involved in this project.

Overdose, or the syndrome where a drug causes loss of consciousness/coma, is the leading cause of accidental death in the U.S. It is clear that medications- not just illegal drugs- are increasingly involved in overdoses. As such, the FDA has pledged to re-examine the role of medications, particularly opioids and benzodiazepines, in the dramatic increase in overdoses. One of the main challenges in this work is that while we may know who has experienced an overdose, it has been very difficult to assess what medications they may have had access to or what they were taking. The primary reason for this difficulty is that there are many different sources of data on medication receipt and it is challenging to link these datasets. In this project, we will overcome those challenges, linking a variety of datasets that will generate a more accurate assessment of which medications at which doses put patients at risk for- or protect them from- overdose. Collaborators from the University of Connecticut are involved in this project.
In 2012, the FDA approved a Risk Evaluation and Mitigation Strategy (REMS) to provide prescriber education to help reduce adverse outcomes resulting from misuse and abuse of extended-release (ER) opioid analgesics. Recent studies, one conducted by FDA using the Medicare database, and one conducted by FDA using the Sentinel database, focused on inappropriate prescribing of ER opioid analgesics that require prior opioid tolerance to patients who do not appear (based on prescription dispensing records) to be opioid-tolerant. Those studies suggest a high incidence of potentially unsafe prescribing behavior for ER opioid analgesics to opioid non-tolerant patients, but recommend further validation in other datasets. The objective of this new study is twofold: (1) examine ER opioid analgesic prescribing patterns in the OptumLabs claims database of commercially insured and Medicare Advantage patients using the Willy and LaRochelle approach, and (2) provide further insight to understand the context of prescribing behavior using clinical data from Electronic Health Records (cdEHR) including data extracted from raw provider notes using advanced Natural Language Processing (NLP) techniques. Collaborators from OptumLabs are involved in this project.
Medical devices play an important role in advancing patient care and reducing morbidity and mortality. All devices must receive FDA approval before they can be marketed. Once medical devices are marketed, it is necessary and important to monitor their safety and effectiveness in real-world clinical practice. Safety concerns may emerge when these devices are used in significantly more patients than were studied before marketing and when longer duration of follow-up is available. FDA therefore requires post-market surveillance of medical devices to ascertain if devices perform as intended and detect any unexpected or serious adverse effects. While the FDA currently employs multiple post-market surveillance strategies, there is opportunity to strengthen this important area given its central role in FDA regulation and, therefore, it is an FDA regulatory science priority. An important component of post-market surveillance is obtaining health data from medical records and insurance claims; these data should also include longitudinal patient-reported outcomes since the goal of these devices is to help people live better and longer.

A novel sync-for-science mobile application has been developed that unobtrusively enables patients to provide their own outcomes (through short questionnaires and through synchronizing data from mobile health trackers) to the FDA after they have received a procedure that utilizes medical devices. In addition, with user permission, this application draws data from the electronic medical record to complement patient-reported data. In this project, we will conduct a pilot study testing this mobile health application to enable the FDA to conduct post-market surveillance of two procedures that use medical devices: the multiple devices (including sutures and stapler) used to perform bariatric surgeries (either sleeve gastrectomy or gastric bypass) in patients seeking weight loss and an ablation catheter when used in patients with atrial fibrillation seeking a return to sinus rhythm. Patients will be enrolled before receiving each of the devices and then will be asked to report specific symptoms related to their need for the procedure and those that may be expected at baseline (enrollment, which is pre-procedure), and 1, 4, and 8 weeks post-procedure. Additionally, patients will be asked 2-3 short questions every 3-4 days for the first 30 days post-procedure related to post-procedure symptoms. We will also test if these patients’ electronic health record data from multiple health systems where they receive care can be synchronized into a research-ready database. Patients will also be provided with syncable devices to provide additional insights into their health and health outcomes. Finally, we will test the feasibility of obtaining medication data from pharmacies or the current needs to create a functional system that can integrate pharmacy data into the mobile application. Integration of these multiple data sources (patient-reported outcomes, wearable/mobile device data, electronic health record data, and pharmacy data) have the potential to ultimately enable a more robust and thorough post-marketing surveillance strategy by leveraging the potential of digital health technologies. Non-Federal entities involved in this project include Me2Health (the developers of the Hugo mHealth application), Johnson & Johnson (collaborator- provides input on project and funds to Me2Health for development of Hugo mHealth application) and AliveCor (donated Kardia Mobile devices for this project).

ClinicalTrials.gov Identifier: NCT03436082

Non-Federal Entity Collaborators: Karla Childers, MSJ, Paul Coplan, ScD, MBA, and Stephen Johnston, MSc (Johnson and Johnson)
The FDA has long relied on electronic healthcare data (e.g., data from claims and EHRs) to examine the safety of drugs in the post-market setting as part of its pharmacoepidemiology contracts and Sentinel Initiative. The passing of the 21st Century Cures Act and the proposed commitments included in the reauthorization of the Prescription Drug User Fee Act require FDA to give further attention and issue guidance on this topic. Recently, linking multiple types of electronic healthcare data is getting more attention, due to its ability to improve the measurement of exposures, outcomes and confounders.

This project seeks to understand how linking laboratory data to insurance claims can help examine a drug’s performance after approval. We will conduct a case study looking at renal function and the performance of oral anticoagulant drugs in patients with atrial fibrillation (AF). The 30 million patients with AF are at nearly a five-fold risk of stroke. Lifelong oral anticoagulation is recommended in most patients with AF to prevent stroke. However, treatment decisions can be complicated by the presence of chronic kidney disease (CKD), as poor renal function increases the risks of both stroke and bleeding ( a major complication of oral anticoagulation treatment), and may change the risk-benefit ratio of different treatment options. This project proposes to answer three important questions pertaining to the impact of renal function on oral anticoagulation treatment in patients with AF. First, in patients with severe-to-no renal impairment, we will assess the comparative effectiveness and safety of different oral anticoagulant drugs across the range of renal function. Second, in patients on dialysis who have substantial risks of both stroke and bleeding, we will compare different potential treatment options, including warfarin, non-vitamin K antagonist oral anticoagulants (NOACs), and no treatment. Third, we will use novel analytic methods to identify patient characteristics that contribute to the heterogeneity in treatment effects.

We will answer these questions by leveraging the power of a large observational database, OptumLabs Data Warehouse, which contains over 160 million privately insured and Medicare Advantage enrollees of all ages, races, and from 50 states and the USRDS data. The proposed work could provide important new evidence on the safety and effectiveness of oral anticoagulants in relation to renal function and will help physicians and patients make a choice among different treatment options.

Non-Federal Entity Collaborators: Brahmajee Nallamothu, MD, MPH, and Rajiv Saran, MD, MS, MBBS - Co-Investigators (University of Michigan)
Atrial fibrillation (AF) is the most common abnormal heart rhythm in humans and is a leading cause of stroke. Over the last two decades, catheter ablation has emerged as an effective modality for treating some patients with AF and its use has been rapidly increasing, especially with the introduction of new technology that allows more effective treatment. However, the “real-world” incidence of short- and intermediate- term complications following AF ablation is not well-characterized in the modern era. Specifically, the development of atrioesophageal fistula – an abnormal connection between the heart and the esophagus (food pipe) – is a rare but deadly complication of catheter ablation of AF. It is widely believed that the diagnosis of atrioesophageal fistula is often missed and/or underreported, and that the true incidence of atrioesophageal fistula in the “real -world” is higher than the limited study data suggest. This research proposal aims to understand the incidence of short- and intermediate-term complications of AF ablation, with an emphasis on atrioesophageal fistula.

Non-Federal Entity Collaborators: James Hummel, MD- Co-Investigator (University of Wisconsin School of Medicine)
When the heart muscle is severely and/or suddenly weakened, it is unable to deliver blood, oxygen, and nutrients to the body, a condition referred to as cardiogenic shock. There are many causes of cardiogenic shock, with the most common being a heart attack. However, a clinically meaningful classification system for cardiogenic shock has yet to be developed and we treat all patients who have an abnormally low blood pressure or oxygen requirement as having cardiogenic shock. It is highly likely, though, that there are distinct subgroups of patients experiencing cardiogenic shock that represent distinct combinations of risk factors and cardiac status. Because all patients with cardiogenic shock are lumped together, many of the clinical trials that have been conducted to investigate the impact of various interventions have failed to show benefit. This may derive from the fact that there is a mixture of different types of patients or different types of cardiogenic shock, some of which may respond quite favorably to an intervention while others may not have a favorable response. By refining our categorization of cardiogenic shock, we hope to be able to provide physicians and patients better prognostic information and strategies to improve clinical outcomes.

This project proposes to advance our understanding of cardiogenic shock with the ultimate aim of enabling patients and providers to estimate risk and develop optimal, individualized treatment plans. Specifically, we will use the NCDR CathPCI and ACTION-GWTG registries, two national registries of patients with acute myocardial infarction (ACTION-GWTG) and patients undergoing stent procedures (CathPCI). Given the substantial morbidity and mortality associated with cardiogenic shock, the proposed work will enable us to advance our understanding of this condition, develop better treatment approaches, and will enhance regulatory science by improving the safety and effectiveness of mechanical circulatory support devices through helping target them to patients who will benefit. Collaborators from Texas A&M University are involved in this project.

Non-Federal Entity Collaborators: Jeptha Curtis, MD, Frederick Masoudi, MD, MSPH, and John Messenger, MD- Co-Investigators (American College of Cardiology)

Since its inception in 1976, the Center for Devices and Radiological Health (CDRH) at the FDA has been dedicated to the protection and promotion of public health. While the number of devices approved for adults continues to rise, little change has occurred in the number of devices developed for children. Over the years, stakeholders have raised concerns about a lack in the availability of devices designed and tested for children. To encourage the development of devices for underserved populations, Congress passed the Safe Medical Devices Act of 1990, and in 2007 Congress passed the Pediatric Medical Device Safety and Innovation Act (PMDSIA). Despite these actions, minimal improvement has been seen over the last 30 years in the number of devices developed for children. Pediatric device development is hindered by a number of factors including challenges in consent and enrollment in clinical trials, variations in anatomy and pathophysiology, and small, heterogeneous and geographically disparate populations. Creating a marketplace that supports development of technologies which serve the complexities of children may accelerate medical technology innovation for all Americans.

The goal of this project is to survey members of industry to better inform the growth of a marketplace that supports the development of devices for pediatric populations that are approved or cleared and labeled for use in pediatrics. Previous initiatives led by the FDA have identified some of the key challenges and barriers to market; however, a streamlined and targeted approach to address these challenges has not been outlined. This project seeks to prioritize the barriers to market that will inform regulatory decision-making and promote innovation.

Non-Federal Entity Collaborators: Andrew Lo, PhD- Co-Investigator (Massachusetts Institute of Technology)

Heart failure (HF) is a highly prevalent disease that also carries high morbidity and mortality. Improvements in mortality and healthcare utilization, including hospitalizations, remains the gold standard outcome for HF drug approvals. However, it is difficult to improve mortality as the only endpoint due to the variation in the age groups and comorbidities of the population and ineffectiveness to alter all-cause mortality. Considering these issues, there is a need for exploration of complimentary endpoints. The FDA recognizes the importance of developing patient-centric endpoints that are relevant to patients beyond mortality and hospitalizations. Patients with HF have substantially reduced functional capacity and quality of life (QoL) and it is imperative to explore interventions that impact endpoints that directly measure how a patient feels or functions on a daily basis.

Recently, new mobile health technologies have emerged as clinical tools and offer an opportunity to overcome the challenges in measuring functional capacity and recording symptoms. These technologies capture and integrate data from disparate sources reflecting patients’ functional status and symptomatology and have the potential of serving as surrogate endpoints for new HF therapy approvals. BodyGuardian Heart (FDA 510(k) cleared) is a mobile health technology capable of connecting to wireless scales and blood pressure monitors and Wavelet is a wrist-based wearable sensor that captures heart rate, respiration rate, and accelerometer data. A novel mobile health platform, Sentinel-HF (built and developed by Biofourmis) using an advanced analytics engine (BiovitalsTM), is capable of monitoring a patient’s physiology through its connection with wearable biosensors, functional capacity, and assessment of QoL through validated PROMs.

The goal of this project is to test the feasibility of obtaining quantifiable and reliable measures of functional capacity and QoL using these novel mobile platforms in HF patients. This study will not only advance the science but also inform the FDA how these measures can be used as alternative trial endpoints. Acute Decompensated Heart Failure (ADHF) patients will be recruited post-discharge from National Heart Centre and National University Hospital in Singapore. Patients will be monitored at home using Bluetooth connected wearable biosensors for a period of 60 days. Patients will also use the smartphone application to 1) perform a weekly 6MWT, and 2) report their symptoms and quality of life using QoL questionnaires.

Non-Federal Entity Collaborators: Kuldeep Singh Rajput, Maulik Majmudar, MD, and Carolyn Lam, MBBS, PhD, MS (Biofourmis)
Cardiovascular disease is the number one cause of death for women in the world. In recent years, approximately 1 in every 4 deaths in the United States results from heart disease, with similar rates among men and women. Heart failure patient-reported outcomes (PROs), like the Kansas City Cardiomyopathy Questionnaire (KCCQ), have been shown to correlate with the New York Heart Association classification system and to predict hospitalization and death. Instruments like the KCCQ are regularly used as endpoints in clinical studies and patient care for their utility. The differences in presentation and symptoms of the disease in female and male patients are well documented. However, because the instrument was developed and validated on a majority male population (69% male in the original study), there are large differences in scores between male and female patients with the same level of disease severity. Regulatory decisions being made upon these results may not fully reflect all patients adequately.

This work will seek to understand from a qualitative perspective differences in patient scores between those who identify as male and female. This study will further validate the usage of KCCQ as a clinical endpoint and provide an example to industrial sponsors of how to account for gender differences in a patient-reported outcome. An improved understanding of the KCCQ to address both male and female patients will advance clinical study design and analyses of heart failure trials. Furthermore, this work will also address improved health communication by initiating the work to make KCCQ clear and applicable to female patients, improving both patient care and regulatory decisions.

Related Projects

The ability to access population-scale data is essential for many emerging areas of biomedical research. Precision medicine, which focuses on identifying the optimal treatment pathway for very refined patient phenotypes, or those with specific genetic variation, require large sample sizes to identify differences in patient outcomes. Similarly, other biomedical research areas that have a limited number of events, such as drug development and pharmacovigilance surveillance, or projects that rely on high dimensional data, have an intrinsic need for very large sample sizes. Often, individual researchers and institutions are unable to identify a sufficient number of participants within local patient populations. However, data sharing and integration between clinical research data management systems (CDMs) and electronic health record (EHR) systems, which would allow systems to coordinate and collaborate to conduct research of this type, remains a challenging issue. To address this problem, the medical informatics community has made significant advances through the development of data and semantic interoperability standards to encourage multi-institutional collaborations and enable researchers to rapidly identify relevant patient cohorts. In this project, we will validate the accuracy and efficiency of these systems for drug safety surveillance, by implementing a universal CDM mapping approach and comparing it to gold standard data from the clinical data warehouse.