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Yale University-Mayo Clinic CERSI

2021-2022 CERSI Scholars

Yale University

Guneet Janda

Doctorate of Medicine Candidate, Yale School of Medicine
Project Title: Characterizing the Approvals and Supporting Evidence of Qualified Infectious Disease Products from 2012-2020

Guneet Janda is a medical student at the Yale School of Medicine. His research interests include health policy and clinical trial design. Prior to medical school, he studied biochemistry and then engaged in structural biology research at the National Cancer Institute. He has also worked in the Center for Outcomes Research and Evaluation (CORE) while at Yale. His CERSI scholar project aims to characterize the evidence behind recent antimicrobials in the context of evolving antimicrobial resistance and changes in reimbursement.

Osman Moneer

Doctorate of Medicine Candidate, Yale School of Medicine
Project Title: Agreement of Treatment Effects from Observational Studies and Clinical Trials Evaluating Therapeutics for COVID-19: A Meta-Epidemiological Study

Osman Moneer is a medical student at Yale School of Medicine interested in health policy for medical technologies. Through the CERSI Scholars program, he is studying the agreement of treatment effects between observational studies and randomized controlled trials for COVID-19 therapeutics. His work seeks to inform future clinical and regulatory decision-making in the context of limited evidence.

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Sara Mullin, PhD, MS

Postdoctoral Fellow, Yale Center for Medical Informatics
Project Title: Identifying Opioid Misuse and Abuse Phenotypes and Subtypes in the Emergency Department

Dr. Mullin's research focuses on modeling information contained in electronic health record and health data repositories. She holds a PhD in Biomedical Informatics and an MS in Statistics. She is primarily interested in using machine and deep learning in conjunction with terminological and ontological information to pursue precision medicine with a focus on substance abuse and mental health outcomes, especially related to the use of opioids. She developed an interest in substance abuse and misuse policy while working as a statistician in a clinical psychology lab and through various drug-drug interaction and substance abuse and misuse prediction projects during her doctoral work.

Reshma Ramachandran, MD, MPP

National Clinician Scholars Program Fellow, Yale School of Medicine
Project Title: Assessment of FDA Approval of Drugs Not Meeting Pivotal Study Primary Endpoints

Reshma Ramachandran, MD, MPP is a health services researcher, family physician, and National Clinician Scholars Program fellow at the Yale School of Medicine. Her research focuses on the realignment of incentives for healthcare stakeholders including pharmaceutical companies, hospitals, and universities towards prioritizing equitable patient access to safe, effective health technologies. Through her CERSI Scholar project, Reshma hopes to determine the frequency of and the rationale for FDA approval of drugs and biologics not meeting pivotal study primary endpoints. Doing so may inform the need for additional confirmatory evidence to help inform decision-making around such therapies for clinicians and patients.

Xiaoting Shi

Doctoral Student, Department of Environmental Health Sciences, Yale School of Public Health
Project Title: Quantitative Bias Analysis Methods for Epidemiological Studies: A Systematic Review

Xiaoting Shi is a current PhD student in the Department of Environmental Health Sciences at Yale School of Public Health. Her research and training focus on synthesizing evidence and conducting meta-research (i.e., research on research) projects. In particular, she is interested in synthesizing and assessing evidence from the literature, evaluating current publication practices, and conducting research on regulatory science. Her current project, which is also an essential component of her doctoral dissertation work, aims to systematically identify, summarize, and compare all the quantitative bias analysis approaches that have been proposed in the existing literature for observational studies. The proposed study has the potential to guide researchers and regulators, who conduct observational studies or make decision on the basis of imperfect data, and therefore, help make optimal use of real-world data.

Mayo Clinic

Jamie Felzer, MD MPH

Clinical Fellow, Pulmonary & Critical Care, Mayo Clinic Rochester
Project Title: Disparities in Vaccine-Preventable Respiratory Illnesses by Race, Socioeconomic Status, and Rurality

Dr. Felzer is a second-year Pulmonary & Critical Care Fellow at Mayo Clinic where she is passionate about researching healthcare disparities and finding actionable ways to reduce these disparities. Her CERSI Scholars research project will evaluate factors of race, socioeconomic status, geographic region and marital status to see if they are associated with respiratory vaccine (COVID-19, influenza, pneumococcus) uptake for adults, including smokers, deemed high-risk for pneumococcal disease in southeastern Minnesota. Longitudinal vaccine data will be compared to COVID vaccination to evaluate if there are factors uniquely impacting COVID immunization. Previously, while obtaining her Master of Public Health at Emory University, Dr. Felzer evaluated disparities in cancer treatment and conducted pneumococcal vaccine research in collaboration with the Centers for Disease Control and Prevention. Dr. Felzer hopes that this research can lead to a successful career combining pulmonary medicine with translational action for reducing disparities in both access to healthcare and related clinical outcomes.

Delaney Liskey, BA

Postdoctoral Student, Regenerative Sciences, Mayo Clinic Graduate School of Biomedical Sciences
Project title: The Utility of OCT Papillary Retinal Nerve Fiber Layer Thickness in Differentiating Recurrent Optic Neuritis

Delaney is a first-year graduate student in the inaugural Regenerative Sciences PhD track, and formerly, a Post-Baccalaureate Research Education Program (PREP) student at the Mayo Clinic. She is interested in promoting regeneration in the central nervous system after degenerative injury, especially for conditions such as multiple sclerosis (MS). Specifically, she is interested in uncovering the cellular mechanisms that underlie vision restoration in this context. Her CERSI Scholars project aims to contribute to clinical trial design by establishing criteria thresholds for retinal swelling and consequent thinning in conditions that cause recurrent optic neuritis.

Vishal Shah, MD

Postdoctoral Fellow, Kern Knowledge Synthesis Center
Project Title: Laboratory Correlates of Infectivity for SARS-CoV-2

Vishal is a research fellow in the Knowledge Synthesis Unit at Mayo Clinic. After completing medical school at St. Louis University, he completed his Internal Medicine training at New York University and his Preventive Medicine fellowship at Mayo Clinic. His research interests include population health, vaccine preventable illness, and the translation from data to guideline development. His primary research currently focuses on improving the understanding and safety of occupationally acquired COVID-19 in the healthcare setting. Additionally, he is working to better understand the burden of chronic hepatitis B in the United States among Immigrants of African descent in the United States.

Andrew Tseng, MD

Cardiovascular Disease Fellow, School of Graduate Medical Education
Project Title: Ambulatory QT Monitoring during Antiarrhythmic Drug Loading Using an Artificial Intelligence-ECG Algorithm on a Mobile ECG Platform

Andrew Tseng is cardiovascular diseases fellow at the Mayo Clinic in Rochester, Minnesota. His research interests include the application of artificial intelligence and mobile device data in clinical cardiovascular care. Specifically, he has been interested in the application of artificial intelligence-enhanced interpretation of electrocardiograms on conditions such as prediction of atrial fibrillation, aortic stenosis, heart failure, etc. His CERSI Scholars project seeks to evaluate the use of artificial intelligence-enhanced interpretation of electrocardiograms obtained from mobile devices for antiarrhythmic drug loading.