As the temporal, financial, and ethical cost of randomized clinical trials (RCTs) continues to rise, researchers and regulators in drug discovery and development face increasing pressure to make better use of existing data sources. This pressure is especially high in rare disease, where traditionally designed RCTs are often infeasible due to the inability to recruit enough patients or the unwillingness of patients or trial leaders to randomly assign anyone to placebo. Bayesian statistical methods have recently been recommended in such settings for their ability to combine disparate data sources, increasing overall study power. The use of these methods has received a boost in the United States thanks to a new willingness by regulators at the Food and Drug Administration to consider complex innovative trial designs. These designs allow trialists to change the nature of the trial (eg, stop early for success or futility, drop an underperforming trial arm, incorporate data on historical controls, etc) while it is still running. In this article, we review a broad collection of Bayesian techniques useful in rare disease research, indicating the benefits and risks associated with each. We begin with relatively innocuous methods for combining information from RCTs and proceed on through increasingly innovative approaches that borrow strength from increasingly heterogeneous and less carefully curated data sources. We also offer 2 examples from the very recent literature illustrating how clinical pharmacology principles can make important contributions to such designs, confirming the interdisciplinary nature of this work.

Using external controls based on real-world or natural history data (RWD/NHD) for drug evaluations in Duchenne muscular dystrophy (DMD) is appealing given the challenges of enrolling placebo-controlled trials, especially for multi-year trials. Comparisons to external controls, however, face risks of bias due to differences in outcomes between trial and RWD/NHD settings. To assess this bias empirically, we conducted a multi-institution study comparing mean 48-week changes in North Star Ambulatory Assessment (NSAA) total score between trial placebo arms and RWD/NHD sources, with and without adjustment for baseline prognostic factors. Analyses used data from three placebo arms (235 48-week intervals, N = 235 patients) and three RWD/NHD sources (348 intervals, N = 202 patients). Differences in mean ΔNSAA between placebo arms and RWD/NHD sources were small before adjustment (-1.2 units, 95% CI: [-2.0 -0.5]) and were attenuated and no longer statistically significant after adjustment (0.1 units (95% CI: [-0.6, 0.8]). Results were similar whether adjusting using multivariable regression or propensity score matching. This consistency in ΔNSAA between trial placebo arms and RWD/NHD sources accords with prior findings for the six-minute walk distance, provides a well-validated framework for baseline adjustment of prognostic factors, and supports the suitability of RWD/NHD external controls for drug evaluations in ambulatory DMD.

Centronuclear myopathies are severe rare congenital diseases. The clinical variability and genetic heterogeneity of these myopathies result in major challenges in clinical trial design. Alternative strategies to large placebo-controlled trials that have been used in other rare diseases (e.g., the use of surrogate markers or of historical controls) have limitations that Bayesian statistics may address. Here we present a Bayesian model that uses each patient\'s own natural history study data to predict progression in the absence of treatment. This prospective multicentre natural history evaluated 4-year follow-up data from 59 patients carrying mutations in the MTM1 or DNM2 genes.
Our approach focused on evaluation of forced expiratory volume in 1 s (FEV1) in 6- to 18-year-old children. A patient was defined as a responder if an improvement was observed after treatment and the predictive probability of such improvement in absence of intervention was less than 0.01. An FEV1 response was considered clinically relevant if it corresponded to an increase of more than 8%.
The key endpoint of a clinical trial using this model is the rate of response. The power of the study is based on the posterior probability that the rate of response observed is greater than the rate of response that would be observed in the absence of treatment predicted based on the individual patient\'s previous natural history. In order to appropriately control for Type 1 error, the threshold probability by which the difference in response rates exceeds zero was adapted to 91%, ensuring a 5% overall Type 1 error rate for the trial.
Bayesian statistical analysis of natural history data allowed us to reliably simulate the evolution of symptoms for individual patients over time and to probabilistically compare these simulated trajectories to actual observed post-treatment outcomes. The proposed model adequately predicted the natural evolution of patients over the duration of the study and will facilitate a sufficiently powerful trial design that can cope with the disease\'s rarity. Further research and ongoing dialog with regulatory authorities are needed to allow for more applications of Bayesian statistics in orphan disease research.

In a previous Phase 2 study, olesoxime had a favorable safety profile. Although the primary endpoint was not met, analyses suggested that olesoxime might help in the maintenance of motor function in patients with Types 2/3 SMA. This open-label extension study (OLEOS) further characterizes the safety, tolerability and efficacy of olesoxime over longer therapy durations. In OLEOS, no new safety risks were identified. Compared to matched natural history data, patients treated with olesoxime demonstrated small, non-significant changes in motor function over 52 weeks. Motor function scores were stable for 52 weeks but declined over the remainder of the study. The greatest decline in motor function was seen in patients ≤15 years old, and those with Type 2 SMA had faster motor function decline versus those with Type 3 SMA. Previous treatment with olesoxime in the Phase 2 study was not protective of motor function in OLEOS. Respiratory outcomes were stable in patients with Type 3 SMA >15 years old but declined in patients with Type 2 SMA and in patients with Type 3 SMA ≤15 years old. Overall, with no stabilization of functional measures observed over 130 weeks, OLEOS did not support significant benefit of olesoxime in patients with SMA.