Background and objectives: In clinical trials, the safety of drugs is summarized by the incidence of adverse events, while post-marketing reporting systems use disproportionate reporting of adverse drug reactions. Here, we propose a method to evaluate the novelty of a safety profile of a drug in a new class (in clinical trials), against that of those already on the market (using pharmacovigilance data).
Methods: Through Bayesian disproportionality analyses of the US Food and Drug Administration Adverse Event Reporting System (FAERS) data, we identified and ranked Preferred Terms for a pool of 30 antipsychotics. Adverse event rates in randomized, double-blind, placebo-controlled schizophrenia clinical trials were summarized by their class specificity. One study (N = 245) of the trace amine-associated receptor 1 (TAAR1) agonist ulotaront (SEP-363856) was compared with five studies of dopamine D2 receptor-based antipsychotics lurasidone (N = 1041), quetiapine (N = 119), olanzapine (N = 122), and placebo (N = 504).
Results: In clinical trials of antipsychotics, cumulative rates for adverse events at and above a threshold of disproportional reporting (Empirical Bayes Geometric Mean 50 > 3 in FAERS) were 52%, 42%, and 60% for lurasidone, quetiapine, and olanzapine, respectively, indicating that over half of the adverse events reported in clinical trials of an atypical antipsychotic are class-specific risks. In contrast, in the clinical trial of ulotaront, the cumulative rate was 23%, indicating a lower rate of antipsychotic class-specific risk.
Conclusions: These results demonstrate a novel approach to summarize adverse events in clinical trials, where the cumulative burden of class-specific risks describes the emerging safety profile of a new drug in clinical development, relative to reactions anticipated for drugs in an established pharmacological class. CLINICALTRIALS.
Gov identifiers: NCT0296938, NCT00088634, NCT00549718, NCT00615433, NCT00790192.
© 2021. The Author(s).