Emulated Clinical Trials from Longitudinal Real-World Data Efficiently Identify Candidates for Neurological Disease Modification: Examples from Parkinson’s Disease

Abstract

Real-world healthcare data hold the potential to identify therapeutic solutions for progressive diseases by efficiently pinpointing safe and efficacious repurposing drug candidates. This approach circumvents key clinical development challenges, particularly relevant for neurological diseases, concordant with the vision of the 21st Century Cures Act. However, to-date, these data have been utilized mainly for confirmatory purposes rather than as drug discovery engines. Here, we demonstrate the usefulness of real-world data in identifying drug repurposing candidates for disease-modifying effects, specifically candidate marketed drugs that exhibit beneficial effects on Parkinson's disease (PD) progression. We performed an observational study in cohorts of ascertained PD patients extracted from two large medical databases, Explorys SuperMart (N=88,867) and IBM MarketScan Research Databases (N=106,395); and applied two conceptually different, well-established causal inference methods to estimate the effect of hundreds of drugs on delaying dementia onset as a proxy for slowing PD progression. Using this approach, we identified two drugs that manifested significant beneficial effects on PD progression in both datasets: rasagiline, narrowly indicated for PD motor symptoms; and zolpidem, a psycholeptic. Each confers its effects through distinct mechanisms, which we explored via a comparison of estimated effects within the drug classification ontology. We conclude that analysis of observational healthcare data, emulating otherwise costly, large, and lengthy clinical trials, can highlight promising repurposing candidates for common, late-onset progressive diseases for which disease-modifying therapeutic solutions are scarce.

Framework for identifying drug repurposing candidates from observational healthcare data

“…We focus here on the methodological aspects of our framework and the means to validate its results. A discussion of the identified drug candidates for PD and their clinical validity appears in Laifenfeld et al 19 To the best of our knowledge, our study is the first to demonstrate systematic emulation of RCTs in observational data for screening drug repurposing candidates.…”

“…These 4 trials involved 4 distinct drugs: rasagiline, zolpidem, azithromycin, and valsartan. 19 Rasagiline, which was shown to be significantly associated with a lower rate of dementia onset, is currently narrowly indicated for treating PD motor symptoms. Deeper analysis of rasagiline and zolpidem’s effects and discussion of their potential mechanisms of action appear in ref.…”

“…Deeper analysis of rasagiline and zolpidem’s effects and discussion of their potential mechanisms of action appear in ref. 19 .…”

“…In the current study, we tested only individual active ingredients, corresponding to specific molecules. Laifenfeld et al 19 further inspected and analyzed two of the ingredients identified by our framework as beneficial for PD patients, namely rasagiline and zolpidem, and proposed plausible mechanistic explanations for the observed effects. Focusing on individual drugs may overlook significant effects shared by multiple similar molecules whose independent analysis lacks statistical power.…”

“…Emulated RCTs comparing the target drug to all its encompassing hierarchical ATC controls may suggest mechanist explanations for the estimated effect or serve as sensitivity analysis. 19 In the second setting, the alternative treatment is a drug randomly selected for each patient from his/her list of prescribed drugs; additional criteria can be applied to limit this random drug set. See Discussion for the rationale behind these settings.…”