About Our Research

Anesthesiology has been undergoing major changes globally, expanding roles beyond the operating room in offering high-quality personalized services in peri-operative health, pain management, critical care, and other medical disciplines. Research has been a major factor underlining these changes and will continue to be an essential force driving the evolution of the specialty.
Stanford Anesthesia research includes a wide spectrum of programs in basic, translational, clinical, health service, and medical education areas. Project fields range from subcellular mechanisms of anesthesia, pain, and opioid addiction, tissue/organ injury, novel anesthesia agents, techniques and devices, treatment effectiveness, epidemiology, patient safety, health economics, and other areas. Interdisciplinary collaborations are increasingly a feature. Our department has been among the top five NIH funded anesthesia departments since 2011, with current external research grants and contracts totaling $17 million annually.

Stanford Anesthesia pays special attention to research training for the next generation of anesthesiologists and has established a research-training continuum bridging between medical student and faculty stages. We place special emphasis on supporting the residency-fellowship-junior faculty period. A key part of this support is the Fellowship in Anesthesia Research and Medicine (FARM) program and our two NIH supported T32 training grants.

Research Programs

Basic Science

Visit our basic science page to learn more about our ongoing research. 

Clinical and Translational Science

Visit our clinical and translational science page to learn more about our ongoing research. 

Data Science

Visit our data science page to learn more about our ongoing research. 

Anesthesia T32 Research fellowship

Visit our research fellowship to learn more about our NIH funded opportunities for residents and postdoctoral fellows. 

News Spotlight

Dr. Mudumbai Secures Wellcome Leap Award

March, 2024

Dr. Mudumbai's proposal, "Leveraging Artificial Intelligence and Multi-Omic Data to Predict Opioid Addiction," has been accepted by the Wellcome Leap program, echoing DARPA's innovation-driven projects. Their project aims to develop advanced predictive models to assess the risk of opioid use disorder integrating AI with EHR, genomic, and microbiomic data. The overarching goal is to inform better clinical decision-making and resource allocation from the start of opioid prescribing, especially for high-risk groups like veterans.

Congratulations to Dr. Mudumbai!

Dr. Anderson Awarded an R18 Proposal

December, 2023

This new R18 proposal funded by NIBIB will study focused ultrasound to treat acute pain by blocking peripheral nerves. The team will determine parameters for noninvasive focused ultrasound-induced peripheral nerve blockade and develop a focused ultrasound prototype device for use in humans.

Congratulations to Dr. Anderson!

Dr. Aghaeepour Receives an R01 Award

November, 2023

Dr. Aghaeepour has received a Notice of Award (NOA) for their latest R01 project titled:

  • 'Multiomics and Artificial Intelligence for Predictive Models and Biomarker Discovery in Preterm Infants.'

This project is a collaborative effort, with Nima Aghaeepour serving as a key co-principal Investigator (MPI), alongside Mohan Pammi from Texas Children's as the Principal Investigator. 

Congratulations to Dr. Aghaeepour!

Anesthesia Team, led by Dr. Simons, Receives NIH Funding to Validate a Signature of Pain Persistence or Recovery

November, 2023

The discovery of robust markers of the recovery vs. persistence of pain and disability is essential to develop more resourceful and patient-specific treatment strategies and to conceive novel approaches that benefit refractory patients. Given that chronic pain is a biopsychosocial process, the discovery, and validation of a prognostic and robust signature for pain recovery vs. persistence requires measurements across multiple dimensions in the same patient cohort in combination with a suitable ‘big data’ computational analysis pipeline for the extraction of reliable and cross-validated results from a multilayered and complex dataset. The SPRINT (Signature of Pain Recovery in Teens) brings together a team of scientists and clinicians from Stanford University (Nima Aghaeepour, Martin Angst, Brice Gaudilliere, Laura Simons), University of Toronto/Hospital for Sick Children, and Cincinnati Children’s Hospital Medical Center. With an initial signature derived in the discovery (R61) phase that implicated neuroimaging, immune, quantitative sensory, and psychological markers using machine learning approaches from our large and complex data set, we now launch into the R33/Validation Phase to validate the signature derived in the R61 study. This signature will be useful for a range of adolescent-based clinical trials in which identification of the highest risk individuals is necessary hopefully providing a clinically actionable intervention algorithm.