4.3 Article

Approval success rates of drug candidates based on target, action, modality, application, and their combinations

Journal

CTS-CLINICAL AND TRANSLATIONAL SCIENCE
Volume 14, Issue 3, Pages 1113-1122

Publisher

WILEY
DOI: 10.1111/cts.12980

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The study revealed that the approval success rate of drug candidates is influenced by drug features, with specific types of drugs having higher success rates in terms of drug action and drug modality. Stimulant in drug action, and drug application categories B, G, or J were statistically associated with higher approval success rates.
The current success rate of a drug candidate, from the beginning of the clinical trial to receiving marketing approval, is about 10%-20%, and it has not changed during the past few decades. Therefore, pharmaceutical companies are under pressure to select one compound, among many others, with a high probability of success. The differences in drug features affect their probabilities of approval success. In this study, we examined the approval success rates of drug candidates, developed in the United States, the European Union, or Japan, by focusing on four parameters (drug target, drug action, drug modality, and drug application) and their combinations, and identified factors that conditioned the outcome of the drug development process. We obtained a total success rate of 12.8%, after evaluating 3999 compounds. Moreover, after analyzing the combinations of these parameters, the approval success rates of drugs that corresponded to the following categories-a stimulant in drug action or an enzyme in drug target and biologics (excluding monoclonal antibody) in drug modality-were high (34.1% and 31.3%, respectively). Univariate and multivariate logistic regression analyses revealed that stimulant in drug action, and B (blood and blood forming organs), G (genito-urinary system and sex), and J (anti-infectives for systemic use) in drug application were statistically associated with high approval success rates. We found several parameters and their combinations that affected drug approval success rates. Our results could assist pharmaceutical companies in evaluating the probability of success of their drug candidates and, thus, in efficiently conducting the clinical development process.

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