Why High Quality Data?
It is well recognized that, despite significant increases in R&D spending, the number of new drug approvals has been flat. This has contributed to increases in new drug development costs and concerns about stagnation in the industry.
How does this relate to quality? In an effort to better identify unacceptable pharmacokinetic characteristics earlier in the drug development process, in vitro ADME models were developed to help identify these liabilities early and eliminate those molecules from further consideration. This constituted part of the “fail fast-fail cheap” model resulting from high throughput profiling of early discovery compounds. Frequently, the quality of the data is compromised to accommodate the quantity of compounds to be profiled.
After the decision of what, and how, to measure has been made, the challenge of using the data remains. The concept of minimally acceptable values for the individual properties has often been used to advance or reject candidates.
A problem with this approach, particularly in HTS assays, is propagation of uncertainty error in the measurement. If each assay is 90% accurate in differentiating between acceptable and unacceptable values, by the time several properties have been selected for, the “yield” of compounds meeting the desired profile is significantly reduced. The impact of accuracy on compound selection can be minimized by improving the accuracy of the assay, generally at the cost of throughput.
Knowing that minimally acceptable values are context dependent with respect to other characteristics of the molecule, alternative methods of using the data to make advancement decisions are also necessary. Use of imprecise data evaluated in an inappropriate context runs the risk of eliminating potentially successful drug candidates.
How many times has this happened already and has it contributed to the lack of approvable drug candidates? A company’s intellectual property deserves the best, careful consideration and evaluation using the best technologies available in making decisions.