Anesthesiology, Perioperative and Pain Medicine
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Mo Esfahanian, MD, D. ABA, FAAP
Clinical Assistant Professor, Anesthesiology, Perioperative and Pain Medicine
Current Research and Scholarly InterestsMy current interests include investigating the role of regional anesthesia to enhance postoperative recovery in pediatrics, including the suprazygomatic maxillary nerve block for cleft palate surgery, and the external oblique intercostal plane block for first stage microtia repair.
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Titilola Falasinnu
Assistant Professor of Medicine (Immunology and Rheumatology) and, by courtesy, of Anesthesiology, Perioperative and Pain Medicine (Adult Pain)
BioI am primarily a lupus researcher and identify as a pain scientist and methodologist in this field. Systemic lupus erythematosus (SLE) disproportionately affects women and racial minorities and is the fifth most common cause of death among 15- to 24-year-old Black and Hispanic women in the U.S., highlighting its significant public health impact. More than half of patients with SLE experience chronic pain, often secondary to SLE itself or overlapping conditions (e.g., migraines, low back pain, fibromyalgia), contributing significantly to disability and impaired quality of life. Chronic pain is not merely a symptom but a disease in its own right—one that deserves the same rigorous study and clinical attention as comorbidities like kidney disease and cardiovascular disease in rheumatology. The enormous global burden of chronic pain underscores the urgent need for a clear, standardized definition of pain as a disease, particularly in autoimmune rheumatic diseases where pain can arise from inflammatory, nociplastic, and biopsychosocial mechanisms. Without recognizing pain as a distinct disease entity, its mechanisms remain poorly understood, and effective treatment strategies remain underdeveloped.
I am a co-Principal Investigator of the Pain Intelligence Lab, where our mission is to advance the study of pain as a disease in rheumatology through two primary objectives. First, we develop and validate computational methods that enable clinicians and researchers to leverage electronic health records, administrative claims, and disease registries to study chronic pain as a distinct disease entity in rheumatology. By applying machine learning, natural language processing, and real-world data analysis, we seek to enhance pain phenotyping, classify distinct pain subtypes, and develop predictive models for treatment response. Second, we use a biopsychosocial framework to examine the predictive power of biomarkers and psychosocial measures in rheumatologic pain. By integrating biological, psychological, and social determinants of pain, we aim to conduct rigorous, patient-oriented research that translates targeted assessments into mechanistically informed, personalized treatment approaches for optimized clinical care. Ultimately, my long term career goal is to bridge the gap between research and clinical practice, ensuring that pain management in autoimmune rheumatic diseases is precise, equitable, and optimized for improved patient outcomes.
