Its important to take a strategic approach to clinical development in order to minimize the potential for Phase 3 attrition. The below infographic, previously published on the blog highlights some of the approvability and economic reasons cited for Phase 3 failure , and the clinical development issues which may have had an impact.
In a 2016 article ( Bolognese et al 2016 )(1) published in Therapeutic Innovation and Regulatory Science the authors ( including Cytel’s Jim Bolognese, Nitin Patel and Jaydeep Bhattacharyya) examine how simulations can be used to optimize a clinical trial program. Their detailed analysis explores the impact which several Phase 2 design features ( including Phase 2 sample size, decision rules to select Phase 3 dose and sample size, and number of Phase 3 trials) have on the probability of Phase 3 success and the expected net present value (eNPV) of a product.
The publication, which focuses on the example of neuropathic pain, extends a framework originally discussed by Patel et al (2) . Whereas in the 2012 paper, 1 dose was selected from the Phase 2 trial results to simulate the Phase 3 trials, in the 2016 publication, the authors expand the approach with an option to take 2 doses to Phase 3, the potential to market 1 or 2 of the Phase 3 doses, and add an additional 1 or 2 Phase 3 trials based on certain criteria.
Based on the simulations, the authors concluded that taking 2 doses to Phase 3 outperforms taking 1 dose unless the weight of Phase 2 evidence strongly rules out the potential for marketing of 2 doses.
They also noted that including more doses in Phase 2 yielded generally higher eNPVs than fewer doses. This occurred especially when the true underlying efficacy and/or tolerability DR curves were at borderline levels of acceptable/optimal value.
The abstract and details of article access are available here.
To download Cytel's white paper on adaptive designs click below.