W3-G.1 Walderhaug MO, Mitkus R, Hess M, King D; mark.walderhaug@fda.hhs.govFDA CBERUPDATED SAFETY ASSESSMENT OF ALUMINUM EXPOSURESFROM VACCINATION IN INFANTS USING PHARMACOKINETICMODELINGAluminum salts (hydroxide or phosphate) are important adjuvants <strong>for</strong> specificvaccines. These specific, adjuvanted vaccines are more effective in eliciting an immuneresponse when the antigens are complexed with aluminum particles, whichactivate specific cellular responses in antigen presenting cells. During the first yearof life, infants receive vaccinations according to a set schedule recommended by theAdvisory Committee on Immunization Practices (ACIP). Despite the therapeuticbenefit of aluminum in specific vaccines, some of the public remain concerned aboutthe safety of aluminum. We evaluated the relative contribution to aluminum levelsin infants from vaccines and from diet, by updating both the pharmacokinetic modeland the parameters used by the Agency <strong>for</strong> Toxic Substances and Disease Registry,which evaluated the safety of aluminum in 2002. We revised the analysis by using a2010 vaccination schedule, a more recent aluminum retention function from humanvolunteers, an adjustment <strong>for</strong> the kinetics of aluminum efflux from the site of injection,the latest minimal risk levels (MRLs), baseline aluminum levels at birth, and themost recent infant body weight data available <strong>for</strong> children from the National Healthand Nutrition Examination Survey (NHANES). The results show that despite morestringent exposure standards, infant aluminum exposure levels from vaccinations anddiet remain safe.P.54 Walker JT, Walker TD, Walker OA; walker.teneille@epa.govUS Environmental Protection AgencyAN ANALYSIS OF THE GROWTH CURVES OF CONTROL SPRAGUE-DAWLEY RATS FED AD-LIBITUM FROM WEANING TO 90 DAYS OFAGESprague-Dawley (SD) rats have been extensively used in 90-day toxicity studies<strong>for</strong> the purpose of understanding the effects of drugs, environmental chemicals,and other agents on growth. Currently, however, no suitable mathematical modelsexist that can describe the growth of these animals. In an attempt to solve this problem,we fitted the growth data of these animals, utilizing a Diphasic-Logistic Growth(DPLG) model. The model assumes that the total body weight, during the periodfrom weaning to 90 days of age, is due primarily to the combined effects of a pubertaland post-pubertal growth process. The model’s biological parameters were estimatedby applying a Levenberg-Marquardt nonlinear least squares fitting technique. Ourresults demonstrated that the DPLG model was very effective and efficient in describingthe growth of these animals. The fits resulted in high R2 and adjusted R2188values, large F values, low residual means, Durbin-Watson statistics that were veryclose to 2, and small standard error estimates <strong>for</strong> the model parameters. Furthermore,the graphs of the residuals essentially showed no model bias. Male Sprague-Dawleyrats were found to have large pubertal and post-pubertal growth rates compared tofemales. The timing of the pubertal and post-pubertal growth spurts in males wasalso found to be larger. We conclude that the model is an excellent tool <strong>for</strong> describingthe growth of Sprague-Dawley rats in a 90-day study period and can be used <strong>for</strong>studying the growth of other rodents. We also discuss how the model can be appliedin risk assessment. Disclaimer: The views expressed in this presentation are those ofthe author and do not necessarily reflect the views or policies of the U.S. EnvironmentalProtection AgencyP.55 Walker JT, Walker TD, Walker OA; walker.james-doctor@epa.govUS Environmental Protection AgencyA MATHEMATICAL DESCRIPTION OF NATIONAL TOXICOLOGYPROGRAM (NTP) 2-YEAR GROWTH CURVES OF MALE AND FE-MALE F344/N RATSIt is well known that the NTP routinely presents rodent growth data and curvesin 2-year bioassay studies. These serve as useful and comprehensive sources of growthdata that can be used <strong>for</strong> age-specific PBPK modeling and other risk assessment ef<strong>for</strong>ts.Currently, however, suitable mathematical models are not available to the riskassessment community that can properly describe these curves. In this study, we usedthe Triphasic-Logistic Growth (TPLG) Model to describe NTP growth curves ofcontrol male and female F344/N rats taken from 2-year bioassay studies. The modelwas fitted to average weight growth data of F344/N rats obtained from five NTPbioassay studies, utilizing a Levenberg-Marquardt nonlinear least squares fitting techniqueto estimate the model parameters. Our results demonstrated that the TPLGmodel was very effective and efficient in describing the growth of these animals.The fits from each of the five studies resulted in high R2 and adjusted R2 values,large F values, low residual means, Durbin-Watson statistics that were very close to2, and small standard error estimates <strong>for</strong> the model parameters. In addition to an agingcomponent, we identified three major growth components or processes in bothmale and female growth curves according to the period when they reached their peakweight velocity: pubertal, young adult, and adult. The model parameters were used tocharacterize the growth of these animals from weaning to old age. Our results are significant,because the new model is able to accurately describe the age specific weight,weight velocities, and specific growth rates of NTP male and female F344/N rats <strong>for</strong>the entire period from weaning to 2 years of age. The impact of these results on riskassessment will be discussed. Disclaimer: The views expressed in this presentationare those of the author and do not necessarily reflect the views or policies of the U.S.Environmental Protection Agency
P.12 Waller RR, Dinis MF; rw@protectheritage.comProtect Heritage Corp., Faculdade de Ciências e Tecnologia da Universidade Nova de LisboaINTERNATIONAL SYMPOSIUM ON CULTURAL PROPERTY RISKANALYSIS: REPORT ON AN SRA SPONSORED EVENTAn International Symposium on Cultural Property <strong>Risk</strong> <strong>Analysis</strong>, sponsored bySRA, was held in Lisbon, 2011 September 14-16. The Symposium offered 34 papersfrom 14 countries dealing with all aspects of risk assessment and management tobetter preserve cultural heritage, whether sites, monuments, architecture or collections.Presentations included case studies, methodological developments, advancesin balancing energy demands <strong>for</strong> preservation with pressure <strong>for</strong> energy conservation,and perspectives of management and educators. Case studies ranged from applicationsto large (ten million object) collections to simple guidance on general prioritiesin small museums. Methodological developments included examples detailed riskmodeling, modeling from different perspectives, and integration of risk descriptionsand vulnerability assessments. The issue of balancing sustainability issues with energyrequirements <strong>for</strong> preservation was addressed as a planning and communication issueand as a standards issue, critical knowledge gaps were identified, and risks wereevaluated in controlled, uncontrolled, and intentionally intermittently controlled situations.Management and education issues were addressed from institutional, nationaland international perspectives. Abstracts of all papers will be available at: http://protectheritage.com/Lisbon2011/ Application of risk analysis to the protection ofcultural property provides a helpful, simple model <strong>for</strong> more general risk analysis. Thegoal of preservation of material heritage is persistent over long times and consistentacross diverse (though not all) cultures. The relative simplicity of cultural propertyrisk analysis, its widely recognized societal importance, and its relatively undevelopedstate combine to create opportunities <strong>for</strong> risk analysis professionals to make importantcontributions. Your help is sought, will be appreciated, and could lead to betterunderstanding of risk analysis in more complex settings.M3-E.3 Walls I; iwalls@nifa.usda.govUSDA National Institute of Food and AgricultureFUTURE ADVANCEMENTS: RECOMMENDATIONS FROM THEIRAC-JIFSAN LISTERIA DOSE-RESPONSE WORKSHOPA workshop was held March 17 & 18, 2011 in Arlington VA, to facilitate anopen dialogue among participating experts to identify key factors and data to be consideredwhen updating L. monocytogenes dose-response models. The two majordose-response models <strong>for</strong> L. monocytogenes were developed by FDA/FSIS/CDCin 2003 and by FAO/WHO in 2004. Since then, knowledge about the bacteria, thehost, and their interaction has increased, notably concerning the physiopathology ofthe infection, the virulence of the strains, and/or the susceptibility of individuals.In addition, new data from experimental infections in animal models are available.The workshop sought inputs from the participants about the latest science on L.monocytogenes epidemiology, pathology, interaction with the host, virulence, anddose response, to help answer to the following questions: • What new knowledgeabout L. monocytogenes and listeriosis could be applied to update the 2003 FDA/FSIS/CDC and/or 2004 FAO/WHO dose-response models? • What approach ormodeling methodology could be used to update these dose-response models now?• What additional data could help to improve the L. monocytogenes dose-responsefunction in the future? A variety of recommendations were suggested as approachesto updating current dose response models. Among the ideas discussed, participantsidentified short, medium and long term approaches. In the short term, some participantssuggested that relevant data developed since the existing models were preparedbe used to update the models. In the medium term, it was suggested that researchersstart collecting data in animal models more closely reflective of humans, e.g., gerbils.In the long term, it was suggested that a mechanistic model be developed, based onkey events that occur in humans during L. monocytogenes infection.M4-I.3 Wallsten TS; tswallst@umd.eduUniversity of MarylandENCODING THE MEANINGS OF PROBABILITY TERMSThere are domains in which the in<strong>for</strong>mation base available to <strong>for</strong>ecasters is soimprecise that they prefer to use imprecise linguistic expressions of uncertainty (e.g.,likely, very small chance) rather than numerical probabilities to communicate degreesof belief that future events will occur or be true. Examples include intelligence analysisand IPCC reports and <strong>for</strong>ecasts on global climate change. Although many decisionanalysts consider this <strong>for</strong>m of communication to be problematic, it has the potentialadvantage of communicating both the magnitude and the precision of one’s opinion.This potential cannot be realized by legislating or assigning numerical values orintervals to terms, as has often been suggested in the literature, because people revertto their natural understandings of terms despite instructions to do otherwise. However,the meanings can be made explicit to decision or policy makers by representingthem as second-order probability distributions, which we call probability signatures,uniquely derived <strong>for</strong> each <strong>for</strong>ecaster. This is true despite the fact that meanings oflinguistic expressions of uncertainty vary enormously across individuals and are influencedby context. This talk first describes some well established context effects on themeanings of linguistic probability expressions and then illustrates how the probabilitysignatures are derived empirically <strong>for</strong> individual <strong>for</strong>ecasters using their own lexiconsof uncertainty. We will present at least two studies. One demonstrates that individual<strong>for</strong>ecasters’ probability signatures are meaningful in a measurement-theoretic senseby using the signatures to predict the <strong>for</strong>ecasters’ binary choice probabilities on a distincttask. The second study is simply a demonstration that the meanings of probabilityexpressions, represented as probability signatures, vary as much across intelligenceanalysts, who use these terms regularly in their work, as they do across unselectedindividuals.189
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