Abstract
Major depressive disorder (MDD) is a disabling condition affecting children, adolescents, and adults worldwide. A high proportion of patients do not respond to one or more pharmacological treatments and are said to have treatment-resistant or difficult-to-treat depression. Inadequate response to current treatments could be due to medication nonadherence, inter-individual variability in treatment response, misdiagnosis, diminished confidence in treatment after many trials, or lack of selectivity. Demonstrating an adequate response in the clinical trial setting is also challenging. Patients with depression may experience non-specific treatment effects when receiving placebo in clinical trials, which may contribute to inadequate response. Studies have attempted to reduce the placebo response rates using adaptive designs such as sequential parallel comparison design. Despite some of these innovations in study design, there remains an unmet need to develop more targeted therapeutics, possibly through precision psychiatry-based approaches to reduce the number of treatment failures and improve remission rates. Examples of precision psychiatry approaches include pharmacogenetic testing, neuroimaging, and machine learning. These approaches have identified neural circuit biotypes of MDD that may improve precision if they can be feasibly bridged to real-world clinical practice. Clinical biomarkers that can effectively predict response to treatment based on individual phenotypes are needed. This review examines why current treatment approaches for MDD often fail and discusses potential benefits and challenges of a more targeted approach, and suggested approaches for clinical studies, which may improve remission rates and reduce the risk of relapse, leading to better functioning in patients with depression.