Risk assessment models strive to predict risks to humans from toxic agents. Safety factors and assumptions are incorporated into these models to allow a margin of error. In the case of cancer, substantial evidence shows that the carcinogenic process is a multistage process driven by the interaction of exogenous carcinogenic exposures, genetic traits, and other endogenous factors. Current risk assessment models fail to consider genetic predispositions that make people more sensitive or resistant to exogenous exposures and endogenous processes. Several cytochrome P450 enzymes, responsible for metabolically activating carcinogens and medications, express wide interindividual variation whose genetic coding has now been identified as polymorphic and linked to cancer risk. For example, a restriction fragment-length polymorphism for cytochrome P4501A1, which metabolizes polycyclic aromatic hydrocarbons, and cytochrome P4502E1, which metabolizes N-nitrosamines and benzene, is linked to lung cancer risk. Cytochrome P4502D6, responsible for metabolizing many clinically important medications, also is linked to lung cancer risk. The frequency for each of these genetic polymorphisms vary among different ethnic and racial groups. In addition to inherited factors for the detection of sensitive populations, determining the biologically effective doses for carcinogenic exposures also should quantitatively and qualitatively enhance the risk assessment process. Levels of carcinogen-DNA adducts reflect the net effect of exposure, absorption, metabolic activation, detoxification, and DNA repair. These effects are genetically predetermined, inducibility notwithstanding. The combination of adduct and genotyping assays provide an assessment of risk that reflects recent exogenous exposure as well as one's lifetime ability to activate and detoxify carcinogens.