Table 1.

Key features, strengths, limitations, and applications of novel trial designs in multiple sclerosis.

Design	Key features	Strengths	Limitations	Appropriate applications
Adaptive trials	• Various possible types and designs; ultimate advantage/focus being the inclusion of defined points/criteria for modification of the trial design to achieve greater efficiency	• Savings for time, cost, sample size, patient exposure.	• Greater statistical and logistical requirements.	• Broad; depends on goal and type of trial utilized The full table in Supplemental Materials outlines these in depth
Platform multi-arm multi-stage	• Multiple therapies evaluated on a single-disease group, divided into arms, against a single control group. • Predefined interim analyses determine whether a treatment will proceed to next stage analysis or discontinued. • Additional therapies can be added at predefined time points.	• Built-in progression from Phases 2 to 3 if interim outcomes are met. • Opportunity to increase the control group rather than experimental arms (potential to limit cost). • Opportunity to test new hypotheses/arms during recruitment, while still controlling family-wise errors. • Shorter time and cost requirements compared to individual Phase 2/3 trials for different agents.	• Inherent operational and design challenges. • Complicated design/statistical issues depending on arm retention/additions, with implications for funding and logistics. • Underlying assumption is that all treatments work equally well under the null hypothesis (i.e. no one is better than any other). • Greater upfront cost. • Rely on valid, reliable intermediate outcomes that accurately predict the primary outcome.	• For use when multiple promising treatments for Phase 2/3 studies are available, with no strong belief that one treatment will be more effective than another. • Requires availability of adequate funding, and number of patients for enrollment. • Requires suitable intermediate outcome measure/s which correlates with the primary outcome measure (when the platform is designed for early phase adaptive trials).
Futility designs	• Phase 1/2 screening trial design for treatments of interest. • The null hypothesis is that the treatment of interest will increase the number of treatment successes by a minimal clinically significant amount.	• Optimizes early phase trial times. • Requires minimal sample sizes, utilizing historic controls as the trial’s control arm and to generate the likely outcome without treatment effect, and the clinically significant effect.	• Requires accurate predictions of likely natural disease progress without effective treatment, and agreement that the proposed treatment success rate is indeed clinically significant. • Risk of bias from unblinded treatment and reliance on historic controls. • Positive trial result does not support treatment efficacy but only indicates non-futility.	• For use in Phase 1 and 2 studies screening translational treatments of interest rapidly. • Particularly suitable for repurposed drugs.
Pragmatic cluster randomized	• Randomization, or control of exposure, to new treatment/s to clusters of patients rather than individuals. • Utilization of established registries to monitor outcomes.	• Benefit of limiting three major unquantifiable errors in large-scale interventions, time-dependent confounding, the Hawthorne effect, and regression-to-the-mean. • Significant cost-saving by utilizing registries for monitoring outcomes.	• Sample size estimations and statistics are complicated and need to consider the number of clusters, calendar-time, inter-cluster correlations, observations per cluster, and ultimate detail of the design. • Greater potential for underlying variability of quality of data collection, and missing data fields.	• Suitable for large-scale projects, such as national or healthcare-wide interventions, assessment of clinical pathways, or initiation of electronic records.

Note: Refer to full table in Supplemental Material for details of the different trial designs within each heading.