Home Insights Challenges and Innovations in Psychopharmacology Trials

Challenges and Innovations in Psychopharmacology Trials

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Introduction

Although psychopharmacology has seen substantial advancements over the past 70 years, adequate treatment for many mental health conditions is yet to be identified. This situation stems from a limited understanding of the underlying pathophysiology of these disorders, limited mechanisms of action being targeted and a lack of biological markers for patient stratification and personalised treatment. Most crucially, there are challenges in drug development that prevent new pharmacological agents from moving from phase 2 to phase 3 in randomized controlled trials. The following sections of this article will outline some of the challenges and potential solutions.

Recruitment, retention and site performance

Randomized controlled trials often have restrictive inclusion criteria, resulting in trial participants who do not represent the real-world population. To address this, it is crucial to broaden these criteria by including participants with certain comorbid disorders. This approach would enhance recruitment, make trials more clinically relevant, and better align with principles of diversity, equity, and inclusion. Additionally, to address this limited representation, standards can be implemented in phase 4 trials to test generalizability and utility of the newly approved medication across different patient subgroups and circumstances. Finally, to enhance retention, minimize data loss, and maintain sufficient statistical power, adopting strategies to mitigate early discontinuations is essential. For instance, implementing rescue strategies to provide alternative treatments for participants experiencing adverse effects may improve retention. Additionally, shortening the follow-up period or incorporating remote follow-up visits can reduce the burden on participants, potentially decreasing withdrawal rates.

Trials are usually conducted across multiple sites, leading to high heterogeneity and lower compliance with trial procedures. This issue is particularly evident when looking at patient ratings, which are performed by assessors to gather baseline data or treatment outcomes. To address this, it is crucial to train raters not only on rating procedures but also on eliciting valid data. Alternatively, employing centralized raters can ensure consistent ratings. Additionally, modern technologies such as language processing, speech analysis, and facial expression analysis can provide valuable insights, especially in conditions like schizophrenia, mania, and depression.

Placebo response

Major pharmaceutical companies have reduced their investment in developing medications for mental health disorders due to difficulties in signal detection caused by unexpectedly high placebo responses. Furthermore, clinicians and patients are increasingly reluctant to participate in placebo-controlled trials, which also suffer from high dropout rates. The elevated placebo response can be attributed to several factors, including expectations of improvement, invalid baseline assessments, and misjudgement of symptom severity at baseline. Indeed, in trials investigating antidepressants for the treatment of depressive disorders, more severe baseline symptoms are linked to a lower placebo response and a greater drug-placebo difference. Using self-rated or objective outcomes, instead of clinician-rated outcomes, has been associated with a lower placebo effect. Moreover, adopting a sequential parallel comparative design (SPCD) has been shown to enhance the detection of a drug’s efficacy by reducing inflated placebo response​.

Lack of trial adaptability

Non-adaptive trial designs fail to incorporate evidence generated during the early stages of the trial, adhering to a one-design-fits all approach that misses out on useful data produced by the trial itself. Various aspects of a trial can be adapted, including drug dose, randomisation, sample size and population characteristics. Adapting the drug dose has the advantage of minimizing exposure to ineffective or potentially unsafe doses, reducing trial duration, and decreasing costs. Employing an enrichment design targets populations that are more likely to respond positively to the treatment, significantly cutting costs and increasing the chances of trial success. However, this approach can compromise the inclusivity and representativeness of the trial population, thereby negatively impacting the generalizability of the results.

Conclusion

The development and approval of new pharmacological agents, particularly for mental health conditions, is a complex process. However, by broadening trial inclusion criteria, harnessing modern technologies, and adopting adaptive trial designs, we can enhance the success of progressing through phase 2 and phase 3 studies. These methodological innovations promise not only regulatory approval but also significantly improved outcomes for patients.