The Instincts Behind a Career in Treatment-Resistant Depression: A Conversation With Maurizio Fava, MD

“Psychopharm Today” is a video-podcast series, created collaboratively with the American Society of Clinical Psychopharmacology (ASCP), in which members converse about the latest hot topics in psychopharmacology.

In this episode of “Psychopharm Today,” host Michael E. Henry, MD, and guest Maurizio Fava, MD, reflected on the clinical observations that led Fava to become an early investigator of treatment-resistant depression, the placebo response, and ketamine, and offered guidance for psychiatrists at every career stage navigating the growing role of artificial intelligence (AI) in the field.

Fava explained that his interest in treatment-resistant depression grew organically out of clinical practice rather than a deliberate research strategy. After joining Massachusetts General Hospital and signaling his interest in treating depression, he began receiving an increasing number of complex referrals—patients who had already cycled through several unsuccessful treatments rather than straightforward cases responsive to first-line antidepressants. Recognizing this as a distinct and underserved clinical population, he developed the Massachusetts General Hospital (MGH) Staging Method, a framework for classifying degrees of treatment resistance.¹

He described his broader pattern of discovery as tied to moments of mental rest rather than active problem-solving, citing beach walks as a recurring source of insight. One such moment centered on the observation that placebo response in psychiatric trials tends to concentrate in the first half of a study, independent of the trial's total duration. This insight led Fava, working with biostatistician David Schoenfeld, to design a trial methodology that re-randomizes patients following an initial placebo response—the sequential parallel comparison design (SPCD). The approach was formally introduced in 2003, and has since been applied in more than 40 multicenter trials, meaningfully reducing placebo response rates.²

Fava attributed his sustained productivity across multiple research domains—treatment-resistant depression, placebo response, and more recently ketamine—to collaboration, framing clinical research as a "team sport" shaped by his childhood experience with team athletics. He credited strong collaborators as essential to achieving results beyond what any individual researcher could accomplish alone.

On mentorship, Fava encouraged medical students to pursue psychiatry, pointing to an era of rapid advancement in pharmacology, neuromodulation devices, and psychotherapy driven by neuroscience and genetics, along with a substantial US psychiatrist shortage that ensures strong career prospects. He said his greatest professional satisfaction comes from contributing, even incrementally, to the development of new treatments.

Discussing AI, Fava urged early-career psychiatrists to treat it as a tool to be controlled rather than a force that controls the profession. His central concern is that AI could be misused as a standalone treatment solution, citing cases where reliance on chatbots for care led to fatal outcomes, and warning against patients delegating their health entirely to AI. For mid-career psychiatrists less familiar with the technology, he recommended learning from younger colleagues already fluent in AI tools, predicting that some use of AI will soon be unavoidable in psychiatric practice.

Dr Henry is a psychiatrist at Mass General Brigham Hospital and medical director of the Dauten Family Center for Bipolar Treatment Innovation.

Dr Fava is psychiatrist-in-chief of the Department of Psychiatry at Massachusetts General Brigham Academic Medical Center.

References

1. Fava M. Diagnosis and definition of treatment-resistant depression. Biol Psychiatry. 2003;53(8):649-659.

2. Fava M, Evins AE, Dorer DJ, Schoenfeld DA. The problem of the placebo response in clinical trials for psychiatric disorders: culprits, possible remedies, and a novel study design approach. Psychother Psychosom. 2003;72(3):115-127.