OBJECTIVE: Although drug manufacturers have gained competence in pharmacoeconomic analysis, they have been slow to bring these tools and techniques to bear on important "go/no-go" decisions for compounds in development. This may be due to difficulties in modeling the cost-effectiveness of products that have yet to undergo clinical trials, wherein critical data on important model parameters would be collected. Yet, in the current cost-conscious environment, it is risky to invest in the development of a product without first exploring its potential pharmacoeconomic profile. METHOD: We developed an analytic apparatus for use in conjunction with traditional cost-effectiveness models to illustrate how good a developmental compound would need to be in terms of key clinical parameters (e.g., adverse event rate, failure rate) for it to be cost-effective versus competing products. Borrowing constructs from microeconomic theory, we demonstrate how two-way threshold analyses on a new product's adverse event rate and failure rate can be used to trace "iso-cost" and "iso-QALY" curves depicting combinations of these parameters yielding equivalent costs and QALYs, respectively, compared to an existing standard of care. RESULTS: Graphical analyses of the iso-cost and iso-QALY curves highlight four distinct regions of parameter combinations in which a new product would be dominant, incrementally cost-effective (at a given threshold), incrementally cost-ineffective, or dominated. Prior probability distributions on these parameters can be used to predict the likelihood of being in each of these regions, and value-of-information analysis can be used to assess formally the expected net benefit of proceeding with clinical development, reflecting the present value of its future revenue stream less the total costs of bringing it to market. Modeling performed in psychiatry will be used to illustrate the concepts. CONCLUSIONS: Methods for "go/no-go" modeling of compounds in the development pipeline provide a means of incorporating pharmacoeconomic criteria into drug development decision-making.