While major strides have been made over the past two decades in basic neurosciences, the pace of translation into more effective treatments has eluded the field. Among the many factors contributing to this reality are the standard clinical trial methods that have barely changed, perhaps with the exception of increased use of electronic data acquisition and analysis.
Clinical trials in neuropsychiatric disorders continue to suffer from high failure rates even with biological targets that are well validated. Even in the hands of experienced investigators, the now commonplace problem of poor assay sensitivity, and attendant trial failure, have adversely affected pharmaceutical and device development. Signal detection in CNS trials is regularly beset by high placebo or non-specific response, intra-subject variability of endpoints, inter-subject and inter-site variability in multicenter trials, poor treatment adherence, and weak patient engagement and retention. The net effect of these challenges has been to simply increase the trial sample size in an attempt to control type II error. Yet, promising early clinical data often are not replicated in larger registration trials, and phase III failure rate in neuroscience randomized controlled trials remain among the highest in medicine. The apparent unsustainability of the current clinical development scenario has driven many large pharmaceutical companies entirely out of investment in neurosciences.
Quite apart from the business perspective, the fact that many early stage clinical trials misleadingly provide a signal (a type I error) raises the question whether volunteering for these trials is in the best interest of trial subjects, in particular, and for the patients with that particular disorder in general.
Better methods, from clinical study design through execution and evaluation, could help restore the integrity, feasibility, acceptability, efficiency and economic viability of clinical neuropsychiatric development. However, in order to use innovative approaches to address these challenges, buy-in and acceptance from the regulatory community will be important. For example, adaptive trials could offer a more efficient means of addressing experimental questions involving multiple uncertainties, although they are often infrequently used. In addition, understanding the utility of wearable and patient monitoring devices (and the data generated) in neuroscience clinical trials is needed. Given the current challenges in neuroscience clinical trials, this public workshop will bring together key stakeholders to discuss opportunities to improve the integrity, efficiency, and validity of clinical trials for nervous system disorders (focusing specifically on Phase II and Phase III trials).
Meeting objectives:
- Examine assay sensitivity challenges in clinical trials for nervous system disorders, including causes of type I error in early trials and poor signal detection and type II error in later stage trials.
- Explore opportunities to improve clinical trial methodology for nervous system disorders, including strategies for:
- Guiding the selection of patient populations, such as using endophenotyping to increase the yield of responders and using genomics, proteomics, and imaging biomarkers to “stage” nervous system disorders.
- Increasing patient engagement through all phases of the clinical trial (i.e., recruitment, screening, and post-trial) and improving adherence and retention.
- Using patient-centric technologies (e.g., wearables) and integrating such real-world, real-time data with traditional clinical data.
- Improving monitoring during clinical trials.
- Leveraging recent advances in diagnostics, biomarkers, and endpoints to develop more efficient clinical trials.
- Using novel trial designs (e.g., adaptive, enrichment, and platform design studies) for nervous system disorders, including associated regulatory challenges and opportunities.
As of March 2016, the Health and Medicine Division continues the consensus studies and convening activities previously undertaken by the Institute of Medicine (IOM).