Quality: Your “Q” to Increase R&D Productivity

The year 2014 found the FDA approving an unprecedented 41 new molecular entities (NMEs) [1]. Interestingly, only 44% of the NMEs approved in 2014 were from Big Pharma [2]. Now more than ever, there is substantial opportunity for innovative NMEs developed by biotechnology companies to reach approval status. This increased number of approvals indicates not only the success of the FDA’s recent PDUFA V reauthorization of performance goals and procedures, but also an overall increase in R&D productivity. This is good news, given that only 5 years ago NME approval rates slumped so much it was considered the dawn of a pharmaceutical “ice age”. Phase 2 and 3 attrition has, by far, the largest impact on R&D cost and productivity. If the Phase 2 attrition rate increases to 75% (it typically sits at approximately 66%), the total cost for developing an NME jumps by 29% to 2.3 billion USD [3]. Attrition is typically both associated with the complexity of pursuing new drug targets and with the heightened scrutiny by the regulators of efficacy and safety data contributing to benefit-risk assessments [3]. Controlling the complexity of drug targets may not be realistic, but ensuring the highest clinical trial data quality is a “low-hanging fruit” for increasing regulator confidence in benefit-risk assessments. So, how does one improve clinical trial data quality? Here are 5 easy defense strategies for your fight against poor data quality. First, carefully consider the method used to collect clinical trial data: the Case Report Forms (CRFs). Be they electronic or paper, CRFs must collect data appropriately in order to accomplish the goals of the study. It may seem obvious,...