A Patient Centered Research Road Map to Inform the Clinical Practice of Bipolar Disorder-View Recording

Video Transcription

Video Summary

The symposium discussed a patient-centered research roadmap to inform clinical practice for bipolar disorder, led by Dr. Mark Fry, a psychiatrist at Mayo Clinic, and Dr. Philip Wong, the Director of the Learning Health Systems Center at Brigham and Women's Hospital. The symposium's goal was to introduce the concept of learning health systems and networks, which enable patient-centered, meaningful research by utilizing large-scale data sets and molecular medicine. Dr. Wong emphasized the necessity for learning health systems due to the inadequacies in current mental health treatments, including detection, intervention, and the significant delay between onset and treatment. He detailed the structure of a deep learning health system, involving deeply phenotyped discovery cohorts, motivated clinician testing cohorts, and broader implementation cohorts. These systems aim to fast-track transformative research into practice using real-world data, machine learning, and advanced causal inference methods. The learning health system concept can revolutionize how treatments and preventive interventions are optimized and personalized. Furthermore, Dr. Fry illustrated how this approach is being applied to bipolar disorder through the BD Squared initiative, which seeks to optimize care and discover new targets through a combination of clinical data, genomics, and integrated learning health networks. Both presenters highlighted the importance of moving beyond traditional research methods to leverage a comprehensive, system-wide integration of clinical and biological data to improve patient outcomes in bipolar disorder treatment.

Keywords

patient-centered research

bipolar disorder

clinical practice

learning health systems

Dr. Mark Fry

Dr. Philip Wong

molecular medicine

mental health treatments

deep learning health system

real-world data

machine learning

BD Squared initiative

genomics