What One Tool Is the Most Useful in Guiding Clinical Drug Development?

The title question may seem unrealistic: the scientific depth, medical intricacies, high cost, significant resources, and cross-functional logistics needed to bring a molecule from pre-IND through approval involve head-spinning complexity. Yet seasoned drug developers have found that one tool is central to ensuring a focused path through the labyrinth. That tool is the label. At this point, you might be asking how on earth the label could serve this role. Isn’t the label a long list of details, printed on tissue-like paper, written at the very end of phase III to include conclusions from pivotal trials? The answer is yes and no. Here is how the label, officially called Physicians’ Prescribing Information (PI), serves as an indispensible compass. The First PI—It’s Foundational Many companies use essential label components to drive decisions from pre-IND through approval. Market Planning PI (MPPI) is the first draft of options for claims in the eventual PI, typically including the desired indication statement, efficacy outcomes, key safety features and others. This document is based on an assessment of preclinical results, competitive landscape and clinical outcomes needed for a commercially viable, approvable new drug. Typically, there is a MPPI for each major market for the drug (e.g. US, EU, Japan), and each includes key label attributes in several sections: 1. minimum for registration and break-even commercialization, 2. target for success and 3. high commercial success. The reason for dividing into markets is that they vary in regulatory requirements and competitor drugs, and in some cases variations in clinical trials will be required. For example, the minimum case for US efficacy might be statistically significant superiority vs....

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,...