Despite the use of optimized, evidence-based therapy, many individuals with major depressive disorder (MDD) experience treatment resistance, defined as the “failure to respond to two or more antidepressant regimens despite adequate dose and duration and treatment adherence” by the US Food and Drug Administration (FDA) and European Medicines Agency (EMA).
Of individuals with MDD, treatment-resistant depression (TRD) is estimated to affect ~30% in clinical trials and up to 55% in real-world practice. As we mentioned in a prior blog post about treatment-resistant mental health conditions, people with TRD experience greater depression-related burden, including higher health care utilization, more intense treatments, greater impairment in psychosocial function, higher workplace disability and absenteeism, and poorer quality of life. This treatment gap highlights the need for faster-acting and more durable therapeutic mechanisms.
Current state of depression pharmacotherapy
Since the 1980s, pharmacotherapy for depression has been dominated by traditional antidepressants developed around the monoamine hypothesis. Today, this consists primarily of selective serotonin reuptake inhibitors (SSRIs) and serotonin/noradrenaline reuptake inhibitors (SNRIs). Although many participants benefit from these therapies, responses are inconsistent, and multiple attempts are required to find the most effective medication or combination of medications.
First-line monotherapy yields remission rates of only 30% to 40% within 12 weeks of initiation, and only 67% of individuals reach remission after four treatment steps. Treatment trials are typically long (4 to 12 weeks per trial at optimal doses with demonstrated adherence), so finding an effective medication or combination of medications often requires several sequential attempts, prolonging relief from depressive symptoms, increasing health care use, and contributing to treatment dropout rates.
The clinical toll of “waiting”
A key reason for long trial durations is the delayed onset of action of conventional antidepressants as well as the absence of reliable early “go/no-go” decision criteria. The variability in participant response often forces clinician judgment about when to switch or augment therapies and leaves many participants exposed to extended, suboptimal treatment periods.
Those extended, partially effective exposures matter clinically. Residual somatic symptoms (e.g., fatigue, psychomotor slowing, reduced motivation, sleep and appetite changes, sexual dysfunction) even after remission worsen functioning and increase the risk of relapse. Prolonged cycles of subthreshold benefit may also encourage biological adaptations, such as altered BDNF/glutamate signaling and maladaptive synaptic remodeling. These could plausibly contribute to entrenched, treatment‑refractory trajectories and response/remission ceilings.
Leveraging biomarkers and AI for personalized depression treatment
The journey toward personalizing depression treatment is evolving, with emerging biomarkers and predictive tools showing promise for identifying potential non-responders and the most effective treatment. However, these innovations are not yet fully ready for reliable clinical application.
The limitations of highly screened populations in randomized clinical trials hinder a more complete understanding of the underlying mechanisms of disease. Instead, larger, more inclusive datasets would enhance our ability to discern what puts people at risk of TRD, build biomarker libraries, and implement predictive algorithms.
Despite these challenges, risk factors for TRD have emerged from recent work. These include lower socioeconomic status, early-onset depression, and comorbid psychiatric disorders, such as anxiety or OCD. In addition, cerebral blood flow abnormalities in specific brain regions could act as biomarkers for TRD.
Due to the complexity and diversity of depression, the use of multiple biomarkers spanning neurological, sociodeterminants of health, inflammation, and more is likely needed to guide treatment choices or identify those most at risk of treatment resistance. However, implementing a multi-factorial analog algorithm is nearly impossible for busy clinicians. This is where large language models (LLMs) and machine learning make a difference.
Recent advancements in LLMs are transforming psychiatric care. These models excel at diagnostic assessment, risk stratification, and clinical decision support. By analyzing vast datasets, LLMs can predict how participants might respond to specific therapies, enabling more personalized and efficient treatment plans that minimize the “trial-and-error” participants experience today.
Mechanistically diverse, integrated approaches to TRD
As we enhance our ability to tailor treatments to individuals, novel interventions like glutamate modulators and psychedelics offer promising avenues to address depression's complexity. After all, less than 10% of central nervous system activity involves monoaminergic neurotransmitter systems.
Glutamate modulators, such as ketamine, have positively impacted the approach to TRD. Ketamine is FDA-approved in nasal spray form and as an intravenous infusion for use under supervision. Its rapid-acting effects occur within hours and can last beyond a week. Its mechanism involves NMDA receptor antagonism, leading to increased glutamate release and activation of AMPA receptors. This cascade enhances BDNF expression and synaptic plasticity, contributing to its antidepressant effects. Ketamine's effectiveness in TRD, with response rates reaching 59% and remission rates of 30% with repeated dosing, substantially exceeds the limited efficacy of traditional monoamine antidepressants in treatment-resistant populations, spurring research into other glutamatergic modulators for individuals with TRD.
Psychedelics like psilocybin and LSD are also gaining renewed interest for their ability to induce rapid and sustained changes in mood and perception, helping to reset the brain’s “narrative.” Psilocybin, in particular, has shown remarkable efficacy in psychedelic-assisted therapy, with a recent phase 3 study demonstrating that two doses administered three weeks apart significantly reduced symptoms in TRD. For some participants, the effects lasted at least through week 26 of the trial. The results are expected to support submission to the FDA, putting the product on the path to becoming the first approved psychedelic.
Because these therapies could address the underlying cause of depression rather than only providing symptomatic relief, they are of particular interest in TRD. We also covered how they are being explored as rapid-acting, effective therapies in other mental health conditions in another of our blog posts.
Looking ahead: Toward scalable, participant-centered care models
I'm optimistic about the future of TRD management as we move closer to integrating these breakthroughs into everyday practice, offering tangible benefits to participants. The ongoing focus on rapid onset and durability is crucial to lasting relief, and the move toward personalization will allow us to select and combine the best-fit modalities for each participant. Future work also involves refining supervision requirements and scaling protocols for therapies like psychedelics, so they become accessible to more participants.
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About the Author
Pieter Strauss, MD, MBChB, FRCPC, is a fellowship-trained psychiatrist and clinical trials investigator with decades of experience in clinical psychiatry, leadership, and wellness-focused care. He currently serves as a Principal Investigator at Okanagan Clinical Trials, a Headlands Research site.
Dr. Strauss completed his medical degree and psychiatry residency at the University of the Free State in South Africa and is a Fellow of the Royal College of Physicians of Canada. His career includes long-standing community psychiatry practice, hospital-based care, and executive leadership as former Chief of the Department of Psychiatry at Abbotsford Regional Hospital. His research experience includes participation in Phase 3 clinical trials in psychiatry and neurology, with investigational therapies such as olanzapine, risperidone, and donepezil. He is trained in Good Clinical Practice and Health Canada Division 5 requirements and brings a participant-centered, ethically grounded approach to clinical research.