title: Innovative approaches to clinical development and trial design.
abstract: Pharmaceutical innovation is increasingly risky, costly and at times inefficient, which has led to a decline in industry productivity. Despite the increased investment in R&D by the industry, the number of new molecular entities achieving marketing authorization is not increasing. Novel approaches to clinical development and trial design could have a key role in overcoming some of these challenges by improving efficiency and reducing attrition rates. The effectiveness of clinical development can be improved by adopting a more integrated model that increases flexibility and maximizes the use of accumulated knowledge. Central to this model of drug development are novel tools, including modelling and simulation, Bayesian methodologies, and adaptive designs, such as seamless adaptive designs and sample-size re-estimation methods. Applications of these methodologies to early- and late-stage drug development are described with some specific examples, along with advantages, challenges, and barriers to implementation. Because they are so flexible, these new trial designs require significant statistical analyses, simulations and logistical considerations to verify their operating characteristics, and therefore tend to require more time for the planning and protocol development phase. Greater awareness of the distinct advantages of innovative designs by regulators and sponsors are crucial to increasing the adoption of these modern tools.
authors: Novartis Pharma AG, One Health Plaza, East Hanover, NJ 07936-1080, USA. john.orloff@novartis.com
authors: John J
authors: JJ
authors: Orloff
authors: Donald
authors: D
authors: Stanski
mesh_terms: D001499:Bayes Theorem; D002986:Clinical Trials as Topic / Q000706:statistics & numerical data*; D006801:Humans; D015233:Models, Statistical; D010601:Pharmacology, Clinical / Q000706:statistics & numerical data / Q000639:trends*; D012107:Research Design / Q000706:statistics & numerical data / Q000639:trends*; D018401:Sample Size