Introduction

One of the challenges for the medicinal chemist in the new drug discovery process is the need to find a new chemical entity (NCE) that has the right combination of properties that satisfies the long list of requirements that is put on any molecule that is being brought forward as a compound that is suitable for development. In the past, if a compound showed pharmacological activity in the animal model, that was sufficient for progressing the NCE into development. Currently, lead optimization includes subjecting the current lead compounds to a series of drug metabolism and pharmacokinetic (DMPK) tests in order to improve the chances that the NCE selected for development will not fail for pharma-cokinetic (PK) reasons when it gets into the clinic.

This newer strategy of testing the PK parameters as part of the lead optimization phase of new drug discovery has proven to be effective. As reported recently by Frank and Hargreaves [1], the reasons for attrition of new chemical entities (NCEs) during the clinical development phase changed between 1991 and 2000. In 1991, the major reason for failure of an NCE in clinical development was due to (human) PK issues, which accounted for 40% of the failures. In 2000, PK issues accounted for less than 10% of the failures in the clinical phase. This dramatic shift was due in large part to the fact that most major pharmaceutical companies added DMPK requirements to the lead optimization phase of new drug discovery, thereby improving the DMPK characteristics of the NCEs that were subsequently recommended for development.

One view of how to implement this newer strategy of adding DMPK requirements to the new drug discovery process is shown in Fig. 13.1. Figure 13.1 shows the stages of new drug discovery that lead up to the clinical phase. In this view, compounds must pass through a series of screens that sift out the problem compounds until a small number have been selected for more rigorous testing in the development phase. The series of screens is organized so that the earlier screens are higher throughput assays while the later screens are those that require significantly more resources to complete the study. One common feature that most of

Fig. 13.1 Stages of new drug discovery. This figure shows the various screens that could be used to select the compounds that proceed into development. At the top is Chemistry where many compounds are produced. After each screen, fewer compounds remain. Adapted from [6], used with permission from Taylor and Francis Group.

Fig. 13.1 Stages of new drug discovery. This figure shows the various screens that could be used to select the compounds that proceed into development. At the top is Chemistry where many compounds are produced. After each screen, fewer compounds remain. Adapted from [6], used with permission from Taylor and Francis Group.

these screens share is that the analytical step in the screen is typically performed via high performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) [2-11].

From a DMPK perspective, a common goal is to be able to compare multiple compounds based on their absorption, distribution, metabolism and excretion (ADME) properties as well their preclinical PK properties [8, 12-22]. Therefore, lead optimization typically is performed as an iterative process that uses the DMPK data to select structural modifications that are then tested to see whether the DMPK properties of the series have been improved. This iterative process is shown schematically in Fig. 13.2. Clearly an important element for the successful lead optimization of a series of NCEs is the ability to perform the DMPK assays in a higher throughput manner. The focus of this chapter will be to discuss ways that mass spectrometry (MS), particularly HPLC-MS/MS can be used to support the early PK studies for NCEs in a higher throughput manner.

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