While a number of phase I dose-finding designs in oncology exist, the commonly used ones are either algorithmic or empirical model-based. We propose a new framework for modeling the dose-response relationship, by incorporating dynamic PK/PD modeling, as well as modeling of the relationship between a latent cumulative pharmacologic effect and a binary toxicity outcome. This modeling framework naturally incorporates the information of dose, schedule and method of administration. The resulting design is an extension of the existing designs that make use of pre-specified summary PK information (such as AUC). Our simulation studies show that, with moderate departure from the hypothesized mechanisms of the drug action, the performance of the proposed design on average improves upon those of the common designs. In case of considerable departure from the underlying drug effect mechanism, the performance of the design is shown to be comparable to that of the other designs. We illustrate the proposed design by applying it to a phase I trial setting for a gamma-secretase inhibitor in metastatic or locally advanced solid tumors. We also provide an R package to implement the proposed design.