title: Bayesian methods for uncertainty factor application for derivation of reference values.
abstract: In 2014, the National Research Council (NRC) published Review of EPA's Integrated Risk Information System (IRIS) Process that considers methods EPA uses for developing toxicity criteria for non-carcinogens. These criteria are the Reference Dose (RfD) for oral exposure and Reference Concentration (RfC) for inhalation exposure. The NRC Review suggested using Bayesian methods for application of uncertainty factors (UFs) to adjust the point of departure dose or concentration to a level considered to be without adverse effects for the human population. The NRC foresaw Bayesian methods would be potentially useful for combining toxicity data from disparate sources-high throughput assays, animal testing, and observational epidemiology. UFs represent five distinct areas for which both adjustment and consideration of uncertainty may be needed. NRC suggested UFs could be represented as Bayesian prior distributions, illustrated the use of a log-normal distribution to represent the composite UF, and combined this distribution with a log-normal distribution representing uncertainty in the point of departure (POD) to reflect the overall uncertainty. Here, we explore these suggestions and present a refinement of the methodology suggested by NRC that considers each individual UF as a distribution. From an examination of 24 evaluations from EPA's IRIS program, when individual UFs were represented using this approach, the geometric mean fold change in the value of the RfD or RfC increased from 3 to over 30, depending on the number of individual UFs used and the sophistication of the assessment. We present example calculations and recommendations for implementing the refined NRC methodology.
authors.affiliation: Ted Simon LLC, 4184 Johnston Road, Winston, GA 30187, United States. Electronic address: ted@tedsimon-toxicology.com.
authors.forename: Ted W
authors.initials: TW
authors.lastname: Simon
authors.affiliation: Department of Epidemiology and Biostatistics, University of South Florida, 13201 Bruce B. Downs, MDC56, Tampa, FL 33612, United States.
authors.forename: Yiliang
authors.initials: Y
authors.lastname: Zhu
authors.affiliation: Toxicology Excellence for Risk Assessment (TERA) Center, University of Cincinnati, College of Medicine, 160 Panzeca Way, Cincinnati, OH 45267-0056, United States.
authors.forename: Michael L
authors.initials: ML
authors.lastname: Dourson
authors.affiliation: Regulatory Science Policy, Regulatory and Technical Affairs, American Chemistry Council, 700 2nd Street NE, Washington, DC 20002, United States.
authors.forename: Nancy B
authors.initials: NB
authors.lastname: Beck
mesh_terms: D000284:Administration, Oral; D000818:Animals; D001499:Bayes Theorem; D003198:Computer Simulation; D004305:Dose-Response Relationship, Drug; D004812:Epidemiologic Methods; D015386:Hazardous Substances / Q000493:pharmacokinetics / Q000633:toxicity*; D057166:High-Throughput Screening Assays; D006801:Humans; D019570:Inhalation Exposure; D015233:Models, Statistical; D009010:Monte Carlo Method; D012016:Reference Values; D018570:Risk Assessment; D018675:Toxicity Tests / Q000379:methods* / Q000592:standards; D035501:Uncertainty
chemical_list: D015386:Hazardous Substances
keywords: Bayesian methods; Hazard assessment; Reference concentration; Reference dose; Risk assessment; Uncertainty factor