Overcoming blinding confounds in psychedelic randomized controlled trials using biomarker driven causal mediation analysis

Introduction

Psychedelic-assisted therapies have attracted substantial scientific, public and commercial interest for a range of psychiatric disorders, including major depressive disorder, post-traumatic stress disorder and other mood and anxiety conditions. Despite promising results from early Phase 2 and Phase 3 trials for agents such as psilocybin, MDMA and ketamine/esketamine, effect-size estimates from randomized controlled trials (RCTs) are likely confounded by de-blinding: the distinctive psychoactive effects of these drugs tend to reveal treatment allocation to participants and study personnel, producing expectancy and placebo-related responses that may inflate measured clinical benefits. Muthukumaraswamy proposes an alternative validation strategy: use causal mediation analysis (CMA) driven by objectively measured biological mediators to link treatment exposure to clinical outcome. The paper introduces the Neyman–Rubin potential outcomes framework and Directed Acyclic Graphs (DAGs) to illustrate how blinding failures generate back-door confounding, then outlines the assumptions and methodology of CMA. It argues that response biomarkers measured during or soon after the intervention, analysed within a causal mediation framework, could provide mechanistic evidence of treatment effects even when traditional blinding is compromised, and contends that psychedelic therapies should not be approved as routine medicines until causal pathways linking treatment to outcome are established.