Pulmonary inflammation disorders represent a major healthcare burden, and novel
anti-inflammatory agents are critically needed for the treatment of patients unresponsive to current
therapies. In vivo animal models play a key role in the preclinical assessment of novel anti-inflammatory compounds. The implementation of streamlined in vivo experimental designs that are time-and cost-efficient, while keeping animal usage low, is a key consideration for
drug optimization programs. The
Sephadex rat model of
pulmonary inflammation captures many pathophysiologic characteristics of clinical
asthma and
allergy, such as eosinophilic infiltration andinterstitial
edema. Using the in vivo
Sephadex model, we compared two different study designs that were implemented to screen and select two novel candidate drugs for a
drug discovery project. The traditional one-start design, which utilizes few dose-testing groups with many animals per group, was used to select the first candidate
drug. Due to tight timelines, the selection process for the second candidate
drug had to be optimized, leading to the development of the novel two-start design, an approach whereby dose ranges are optimized in two experimental phases. Here we show that both study designs were comparable in their generation of robust median effective dose values for selected candidate drugs, as represented by similar confidence interval ratios. However, implementation of the two-start design resulted in approximately 50% fewer animals and 50% less time taken to assess the efficacy of an equal number of compounds compared with the one-start design. These results demonstrate that the two-start design is a more efficient experimental approach, and its widespread implementation in
drug optimization programs will impact upon the selection process for candidate drugs with regards to time, cost, and animal usage.