Genetically engineered mice (GEMs) that either overexpress (transgenic) or lack (gene-targeted, or "knock-out") genes are used increasingly in industry to investigate molecular mechanisms of disease, to evaluate innovative therapeutic targets, and to screen agents for efficacy and/or toxicity. High throughput GEM construction in drug discovery and development (DDD) serves two main purposes: to test whether a given gene participates in a disease condition, or to determine the function(s) of a protein that is encoded by an expressed sequence tag (EST, an mRNA fragment for a previously uncharacterized protein). In some instances, phenotypes induced by such novel GEMs also may yield clues regarding potential target organs and toxic effects of potential therapeutic molecules. The battery of tests used in phenotypic analysis of GEMs varies between companies, but the goal is to define one or more easily measured endpoints that can be used to monitor the disease course--especially during in vivo treatment with novel drug candidates. In many DDD projects, overt phenotypes are subtle or absent even in GEMs in which high-level expression or total ablation of an engineered gene can be confirmed. This outcome presents a major quandary for biotechnology and pharmaceutical firms: given the significant expense and labor required to generate GEMs, what should be done with "negative" constructs? The 14th century philosophical principle known as Occam's razor-that the simplest explanation for a phenomenon is likely the truth-provides a reasonable basis for pruning potential therapeutic molecules and targets. In the context of DDD, Occam's razor may be construed to mean that correctly engineered GEMs lacking obvious functional or structural phenotypes have none because the affected gene is not uniquely essential to normal homeostasis or disease progression. Thus, a "negative" GEM construct suggests that the gene under investigation encodes a ligand or target molecule without significant therapeutic potential. This interpretation indicates that, at least in a market-driven industrial setting, such "negative" projects should be pruned aggressively so that resources may be redirected to more promising DDD ventures.