Translational mixed-factor benchmark-dose risk assessment

Project Summary/AbstractQuantifying detrimental risks from hazardous inputs is a critical component in disease risk evaluation. Althoughstatistical methods in risk analysis have been well-studied for a single hazardous exposure, a critical gap existsin the practical development of these methods when mixed input factors might affect the adverse outcome(s)under study. The focus of this small, self-contained research project is to develop and study new methods ofstatistical inference for use in quantitative risk assessment, with focus on mixed quantitative and qualitativeinput factors. Project emphasis will center on estimation of benchmark doses (BMDs) associated with a pre-selected level of benchmarked response (BMR). Motivated by a translational risk-analytic application inchildhood respiratory disease, this research project will develop methods for developing benchmark markers(the ?doses?) of an adverse health outcome when additional, qualitative, multi-level factors are critical to theanalysis. The theoretical, asymptotic characteristics of the estimators will be established, and from these large-sample benchmark dose confidence limits (BMDLs) will be constructed. Besides the targeted application to childhood respiratory health, translational application is anticipated forany biomedical, toxicological, pharmacological, environmental, or occupational studies where human or animaldata are used to set benchmark markers or other safe, low-dose levels with mixed inputs. The resultingguidelines will improve public health planning and disease risk management when dealing with joint exposureswhere combinations of harmful agents/mixed inputs may interact or otherwise act jointly to amplify risk ofdisease. The research will fill critical gaps in multi-factor benchmark analysis, and will have potential translationalapplication to non-standard/non-traditional settings across a wide variety of public health scenarios. Evaluationphases of the project will study the small-sample operating characteristics of the estimators via Monte Carlocomputer calculations, and will explore the methodology's capabilities for practical application with motivatingdata on childhood asthma. The aim will be to assess the methodology's (1) practical capabilities, and (2) itsviability for estimating benchmark doses in these translational settings. The validated procedures for BMDestimation and for calculating the confidence limits will be coded for public use and ported to download site(s)on the Internet to facilitate dispersal across the widest possible corps of users.