Chronic adult periodontitis is a bacterially induced chronic inflammatory disease that destroys the connective tissue and bone that support teeth. Concepts of the specific mechanisms involved in the disease have evolved with new technologies and knowledge. Histopathologic observations of diseased human tissues were used previously to speculate on the causes of periodontitis and to describe models of pathogenesis. Experimental evidence later emerged to implicate bacterial plaque deposits as the primary factor initiating periodontitis. At the same time, specific bacteria and immunoinflammatory mechanisms were differentially implicated in the disease. In the mid-1990s, early insights about complex diseases, such as periodontitis, led to new conceptual models of the pathogenesis of periodontitis. Those models included the bacterial activation of immunoinflammatory mechanisms, some of which targeted control of the bacterial challenge and others that had adverse effects on bone and connective tissue remodeling. Such models also acknowledged that different environmental and genetic factors modified the clinical phenotype of periodontal disease. However, the models did not capture the dynamic nature of the biochemical processes, i.e., that innate differences among individuals and changes in environmental factors may accelerate biochemical changes or dampen that shift. With emerging genomic, proteomic, and metabolomic data and systems biology tools for interpreting data, it is now possible to begin describing the basic elements of a new model of pathogenesis. Such a model incorporates gene, protein, and metabolite data into dynamic biologic networks that include disease-initiating and -resolving mechanisms. This type of model has a multilevel framework in which the biochemical networks that are regulated by innate and environmental factors can be described and the interrelatedness of networks can be captured. New models in the next few years will be merely frameworks for integrating key knowledge as it becomes available from the "-omics" technologies. However, it is possible to describe some of the key elements of the new models and discuss distinctions between the new and older models. It is hoped that improved conceptual models of pathogenesis will assist in focusing new research and speed the translation of new data into practical applications.