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Pulmonary & Critical Care Medicine Research

Research performed within the U-M Medical School Department of Internal Medicine Division of Pulmonary & Critical Care Medicine has greatly impacted our understanding of basic lung biology, disease pathogenesis and targeted therapeutics. 

NIH grant funding for research within the Division exceeds 13 million dollars annually. Our investigative portfolio is comprehensive, with specific areas of emphasis including pulmonary inflammation, lung injury and repair, fibrotic lung disorders, host defense, lung transplantation, and lung cancer.

New major areas of modern biology have emerged, including genetics/genomics, metagenomics, proteomics, metabolomics, stem cell biology, computational biology, and the microbiome. Researchers in the division participate in large multidisciplinary and multicenter disease-specific programs and networks in interstitial lung disease (IPFnet, COMET, LTRC), COPD (SPIROMICS, COPD gene, LTRC), and Acute Lung Injury (SCOR, SCCOR, ARDSnet).

Emerging fields of patient-oriented research have been added or expanded, including health services research and sleep. Active areas of health services research include long-term functional outcomes in survivors of critical illness, nosocomial infection, delirium in the ICU, health care utilization and health care policy.

Areas of Research
  • Cancer
  • Chronic Obstructive Pulmonary Disease
  • Critical Care
  • Fibrotic Lung Disease
  • Health Services, Outcomes & Policy Program
  • Lung Injury & Repair Reseach
  • Lung Transplantation & Stem Cell Biology Program
  • Multidisciplinary Intensive Care Research Workgroup (MICReW)
  • Microbiome Program
  • Pulmonary Immunity
  • Severe Asthma
    • Featured News & Stories See all news breaking new ground in COPD transparent lungs
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    Breaking New Ground in COPD: Latest Treatments and Advances in Management
    Join us for a free virtual panel discussion, Breaking New Ground in COPD: Latest Treatments and Advances in Management, on Tuesday, January 14, 2025.
         Lindsay and Andrew Admon
    Points of Blue
    Lindsay Admon, MD, MSc, and Andrew Admon, MD, MPH, MS: Helping students discover their passions
    Drs. Lindsay and Andew Admon met as students at University of Michigan Medical School and are now helping prepare future physicians for careers in medicine as faculty members.
         2024 Faculty and Staff Awards
    Medical School News
    Sixteen individuals, and members of Comprehensive Stroke Program, honored with Faculty and Staff Awards
    Sixteen faculty and staff, and members of the Comprehensive Stroke Program, were honored Dec. 4 at the annual Faculty and Staff Awards ceremony at the Jack Roth Stadium Club in Michigan Stadium. The awards acknowledge and celebrate those who demonstrate exceptional accomplishment in the areas of teaching, research, clinical care, community service, technology, leadership, teamwork and administration
         Dr. Bob Dickson receives the Toew's award
    Department News
    Dr. Bob Dickson is named the Galen B. Toews MD Legacy Professor in Pulmonary and Critical Care Medicine
    Dickson joined the faculty of the Division of Pulmonary and Critical Care Medicine in 2015 and was promoted to Associate Professor in 2020. He is the program director for the Pulmonary T32 program. Dickson also holds an appointment in the Department of Microbiology and Immunology and serves as deputy director of the Weil Institute for Critical Care Research and Innovation.
         Clarivate’s Highly Cited Researchers 2024
    Department News
    Internal Medicine Faculty Named to Clarivate’s Highly Cited Researchers List
    Nine faculty members from the Department of Internal Medicine named to Clarivate’s Highly Cited Researchers 2024 List.
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    Health Lab
    Racial differences in medical testing could introduce bias to AI models
    Black patients are less likely than white patients to receive certain medical tests that doctors use to diagnose severe disease, impacting artificial intelligence data. But researchers have found a way to correct the bias in these data sets.