You get what you screen for: Standards for experimental design and data fitting in drug discovery

A common mantra in drug discovery is that "You get what you screen for." This is not a promise that you will always get an effective drug candidate, but rather a warning that inaccuracies in your protocol for screening will more likely produce a compound that fails to be an effective candidate because it matches the properties of your screen, not the desired features of an ideal lead compound. It is with this in mind that we examine the current protocols for evaluating drug candidates and highlight some deficiencies while pointing the way to better methods. Many of the errors in data fitting can be rectified by abandoning the traditional equation-based data fitting methods and adopting the more rigorous mechanism-based fitting afforded by computer simulation based on numerical integration of rate equations. Using these methods bypasses the errors in judgement in choosing the appropriate equation for data fitting and the approximations required to derive those equations. In this chapter we outline the limitations and systematic errors in conventional methods of data fitting and illustrate the advantages of computer simulation and introduce the methods of analysis.