calculate recovery times for organisms, or establish extrapolations from the model to toxicity of untested toxicants and species. history of tktd models it has been argued that the current challenges facing risk assessments can be addressed with tktd modeling. tktd models were derived in response to a couple of factors. one is the lack of time being considered as a factor in toxicity and risk assessment. some of the earliest developed tktd models, such as the critical body residue (cbr) model and critical target occupation (cto) model, have considered time as a factor but a criticism has been that they are for very specific circumstances such as reversibly acting toxicants or irreversibly acting toxicants. further extrapolation of the cto and cbr models are debtox, which can model sublethal endpoints, and hazard versions of the cto, which takes into account stochastic death as opposed to individual tolerance. another significant step to developing tktd models was the incorporation of a state variable for damage. by using damage as a toxicodynamic state-variable, modeling intermediate recovery rates can be accomplished for toxicants that act reversibly with their targets, without the assumptions of instant recovery (cbr model) or irreversible interactions (cto model). tktd models that incorporate damage are the damage assessment model (dam) and the threshold damage model (tdm). for what may seem like straightforward endpoints, a variety of different tktd approaches exist. a review of the assumptions and hypotheses of each was previously published in the creation of a general unified threshold model of survival (guts). advantages for risk assessment as referenced above, tktd models have several advantages to traditional models for risk assessments. the principal advantages to using tktd models are: the consequences of time-varying or repeated exposures can be explained and simulated by the tktd model. carry-over toxicity as well as delayed effects can be simulated, whether the carry-over toxicity is due to tk or td or both. in this way, tktd models can quantify risks from pulsed or fluctuating exposures. organism recovery time depends on the time course of tk and td, which makes the tktd models suitable for calculating organism recovery time. tktd models have the potential to predict effects of mixtures, including both environmental and chemical stressors and also be used as mechanism-based extrapolation to untested toxicants or untested species. linking tktd models with individual based models (ibm) may improve risk assessment of toxicants by simulating temporal aspects as well as ecological aspects. due to its advantages, tktd models may be more powerful than the traditional dose-response models because of their incorporation of chemical concentrations as well as temporal dimensions. toxicodynamic modeling (such as tktd models) has been shown to be a useful tool for toxicological research, with increasing opportunities to use these results in risk assessment to permit a more scientifically based risk assessment that is less reliable on animal testing. overall, these types of models can formalize knowledge about the toxicity of toxicants and organism sensitivity, create new hypotheses, and simulate temporal aspects of toxicity, making them useful tools for risk assessment.