This project evaluated current approaches and alternative methodologies to the derivation of health based guidance values for chemical exposures. Although the report relies on evaluations of pesticides the basic considerations apply to other areas of chemical risk assessment. Pesticide evaluations were reviewed to determine studies and endpoints utilised to derive guidance values, safety factors applied and any aspects routinely debated during peer review. Approaches that would be applicable to the derivation of the recently proposed 'Acute Acceptable Operator Exposure Level' and supporting data were evaluated. A common topic of discussion during the interpretation of toxicological data is whether effects seen in animal studies are relevant to humans. Literature relating to end-points routinely used in deriving reference values was evaluated together with responses to a questionnaire and proposals developed for producing a more consistent approach. Alternative approaches to the No Observed Adverse Effect Level (NOAEL) were evaluated. Particular consideration was given to the Benchmark Dose (BMD) approach, with a number of case-studies performed to determine practicalities of current software programs. Alternative approaches to the use of the default 100 fold safety factor to address uncertainties in extrapolating between animal data and human exposures were evaluated. Conclusions and recommendations included: Current approaches are protective of human exposures but there is potential for improvement using alternative methods and revised test guidelines. The ARfD can be a basis for derivation of AAOELs. BMD offers significant benefits and should be utilised routinely on the end-points used to derive guidance values. A number of findings in animal studies might be of no relevance to humans but this needs to be demonstrated in each case. Allometric scaling is a viable alternative approach whereas CSAF and PBPK are too data intensive for general use. Description of the uncertainty surrounding guidance values should be improved.