Document J319LrjXYOxGQGwRd3n0XpJ9K

CHEMICAL MANUFACTURERS ASSOCIATION January 6,1995 Dear Vinyl Chloride Health Committee Members: A copy of the cover letter sent to James Cogliano of EPA along with Richard Reitz's draft vinyl chloride risk assessment manuscript is enclosed. Please review this letter and the manuscript prior to the next meeting. We will discuss the manuscript and our course of action with EPA at the meeting on January 30. I also have enclosed records of meeting or conference call for the following dates: October 6 pre-meeting; October 6 EPA meeting; October 7; October 24; October 31; November 7; November 22; and, December 5. If you have any questions, please call me at (202) 887-1192. I look forward to seeing you on January 30. Sincerely, Enclosures Hasmukh C. Shah, Ph.D. Manager, Vinyl Chloride Panel JAN 91996 SL 107868 2501 M Street, NW, Washington, DC 20037 Telephone 202-887-1100 Fax 202-887-1237 Uy Responsible Care* f A PublicCommitment CHEMICAL MANUFACTURERS ASSOCIATION Vinyl Chloride Health Committee Record of Meeting Date: Time: Place: October 6,1994 10:30 a.m. -1:30 p.m. General A CMA Offices Washington, D.C. List of Attendees: James Barter Ed Beeler Mike Gargas Mark Gruenwald James Knaak Patrick Logue David Penney Jonathan Ramlow Dick Reitz James Swenberg PPG Industries GEON ChemRisk/McLaren Hart Borden Occidental Chemical Georgia Gulf Vista Chemical Dow Chemical ChemRisk University of North Carolina Has Shah CMA 1.0 The Committee discussed the risk assessment of vinyl physiologically-based pharmacokinetic model (PB-PK). The model was developed by Richard Reitz. Dr. Reitz will present this model to EPA scientists at the meeting this afternoon. The model predicts the true risk more accurately because it is based on actual pharmacokinetic data. For vinyl chloride, the unit risk based on the PB-PK principles is 150-fold lower than that predicted by non PB-PK models (Heast Table, May 1993, EPA). The PB-PK model is described in the attachment. 2.0 James Swenberg described his research proposal to determine Tw of the ethenoguanine DNA adduct in rats using [l3C2] vinyl chloride, and quantifying the amount of the methyl purine DNA glycosylase and P450 2 El in tissues of humans of different ages. The Committee will consider Dr. Swenberg's proposal in relation to other research projects and decide if funds are available for his proposal. 3.0 The meeting adjourned at approximately 11:45 a.m. Subject to Approval o ---- Hasmukh C. Shah, Ph.D. Manager, Vinyl Chloride Panel SL 107869 Estimating Human Risk from Exposure to VC Quantification with PB-PK Modeling Richard H. Reitz Michael L. Gargas McLaren/Hart, ChemRisk Division for Environmental Protection Agency October 6,1994 Collaborators! . McLaren/Hart; R. H. Reitz M. L. Gargas ICI Toxicology Lab (Zeneca) T. L. Green W. M. Provan 1LSJ.-P. A. (Res Tri Park) M. E. Andersen 108** 1 lQf5*4 VC Historyj Low Acute Toxicity Occup. Expos. Limits - 500 ppm Viola (1970,1971) Rats, Increased Tumor Incidence Maltoni (1974) Confirmed Viola's Results Identified Rare Liver Angiosarcoma Dose Response Fiat > 1,000 ppm Creech & Johnson (1974) Found Same Cancer Type (Liver Angiosacroma) in Humans Human Tumor Registry (to Present) 14,000 Subjects, 19 VC Plants Objectives / Opportunity! Develop A Process for Quantitatively Estimating Risk in Humans + Low, Non-Occupatkmal Exposures - Superfund Sites * Fugitive Emission - Drinking Water Test the Utility of our Cancer Risk Assessment Procedures + Rich Animal Data Set in Rats and Mice + Unique Opportunity to Compare Risk Assessment with Actual Results in Humans 108*4 3 105*4 SL 107870 Expectations for Pharmacokinetic Modeling Modeling Cannot Eliminate ALL Uncertainty from Risk Assessments Modeling Can Quantitatively Describe: Metabolic Saturation Changes in Dose Route Physiological Differences in Species PREMISE: Risk Assessments based on Estimates of "Delivered Dose" will be More Reliable than Risk Assessments based Only on Administered Dose Advantages of PB-PK Models: Compound Specific Information Vapor Pressure Solubilities (Partitioning) in Tissues Species Specific Information Physiology Metabolism Route Specific Information Oral Route, 1st Pass Through Liver Allow Extrapolations Between Dose Routes Between High Dose / Low Dose Between Species to/sm s tQtt/M 6 anr >neI.wim*aHw . w fra L, FIMi, -[Mqtrl.l Crcl***-. IlitvHr, U7i) 10/5/94 10/5/94 SL 107871 Metabolites Eased on Ramsey Andeisoi, 1984. 8 WPAFB Model for VC| December 1990: Crump Div Clement Inter. Collaborators: J. Fisher H. Cleweiun M. Andersen M. Gargas Also Based on Ramsey/Andersen Model Two Metabolic Pathways for VC Saturable (MFO) Low Affinity (Non-Saturable) Enhancements (SimuSolv): Sensitivity Analyses, Optimization Single Metabolic Pathway New In Vivo Rat Data (Watanabe) Human In Vivo Studies (Baretta) EXTRAPOLATION TO HUMANS 10/S/W 9 Approach; VC PBPK ModeTj (1) Parameterize Model Physiological Constants - Andersen et al., 1987 Partition Coefficients - Vial Equilibration - Fat, Liver, Muscle, Blood Metabolic Rate Constants - In Vivo (Rats, Mice) (2) Validate Model Independent Rat, Mouse and Human In Vivo Studies (3) Extrapolate Risks Rats to Mice Rats to Humans lOftflM IQ Gas Uptake Data (Male Rats) Gas Uptake Data (Female Rats) lOrttf* II IOV94 SL 107872 12 In Vivo Metabolism (Watanabe) High Specific Activity 14C-Vinyl Chloride Six Hour Inhalation Exposure Several Different Concentrations Above and Below Metabolic Saturation Radioactivity Quantitates Metabolite Production DIRECT measurement of metabolism (Gas Uptake Indirect Measure) One or Two Metabolic Pathways Validation of Rat Model (Watanabe et al., 1976) I0/5/W 13 10W94 14 Estimating Mouse Metabolic Rate Constants Small, Halogenated Hydrocarbons Metabolized by CyP450 2E1 In Vivo VMax's from Experiments Methylene Chloride (MeCI2) (Rats, Mice, Humans) Chloroform (CHCfo) (Rats, Mice) Calculate VMax / gram Liver Normalize to Rat In Vivo MeCl2 CHC13 Average Mouse 2.57 2.71 2.64 Human 0.21 - 0.21 Parallelogram Approach! In Vivo In Vivo Rats Humans, Mice In Vitro In Vitro SL 107873 Testing Estimated Mouse Metabolic Constants Optimized Mouse Data 10/5/94 17 105/94 18 Validation of Human Model (Baretta et al,, 1969) DerivingRatPoteiicyJ Based on Maltoni's Experiments 12 Months Exposure 0,1,5,10,25,50,100,150,200,250,500, 2500,6000,10000,30000 ppm tested Poor Survival 10000 and 30000; Use Remaining 13 Dose Groups Use PB-FK Model to Calculate Dose Average Amount VC Metabolites per day per Liter of Liver Tissue Howe & Crump's GLOBAL83 Multistage Model Dose Response (Maximum Likelihood Estimate) Comparison: Linear Model Fitted to Top Two Doses (MTD, MTD/2) 10/3/94 19 1 (VS/94 SL 107874 Predicted Tumor Incidence in Rats Administered and PB-PK Dose Scales Risk Specific Dose (1(H) = 1.77 x 101 (mg metabolite/liter/day) ____ Extrapolating Rat -> Mouse (Maltoni, Swiss Albino Mice) Cone 0 50 250 500 2,500 Males 0/80 1/30 9/30 6/30 6/29 Females 0/70 0/30 9/30 8/30 10/30 LADD 0.0 38.4 173.1 265.2 331.0 Equivalent Amounts of Metabolite produce Equivalent Tumor Yields No Surface Area Correction Factor Used. The 1(H RSD = 0.80 x KH Comparing RSD's) Maltoni et al., (Rat) Maltoni et al., (Mouse) Lee et al., (Mouse) 0.177 0,080 0.120 Drew et al., (B6 Mouse)^^w0j0032 Diagnostic Criteji Drewp^aL reported angiosacromas in cpntfols. Lee and Maltoni saw none. R6C3F1 Ultrasensitive? Reported to have partial oncogene activation in absence of any chemical treatment. Extrapolating Rat -> Humans | (Maltoni, Rat Potency)I Equivalent Amounts of Metabolite produce Equivalent Tumor Yields No Surface Area Correction Factor Used. Calculated "Unit Risk", Lifetime Exposure to lpg/m3, 24 hr/day. PBPKMLE = 4 x 10-7 PBPKUCL = 6 x 10-7 IRIS Number = 840 x 107 SL 107875 VC Tumor Registry (Simonato et al., 1991) 12,706 Individuals from Population of 14,351 Completeness of Followup = 97.7 % Cohort has > 25 Years since 1st Exposure to VC Exposure Groupings: + 0 - 2,000 ppm years + 2,000 6,000 ppm years + 6,000 -10,000 ppm years + > 10,000 ppm years Absolute Risks Estimated to Range from 6.2/100,000 to 280/100,000 PBPK Risk Assessment Versus Simonato et al (1991) PPM PPM Yean T*n Yaat* &pourt 50 500 100 1000 200 2,000 4000 500 5000 -- 1000 8000 10000 -- 2000 >10000 20000 Twenty Yean Esnxwur 50 100 200 -- 500 -- 1000 2000 1000 2000 4000 8000 10,000 15,000 20,000 40000 PB-PK LADD PB-PK Prediction por 100,000 Observed Cave* per 100,000 3.35 6.63 13.06 -- 2668 -- 31.28 -- 36.03 188 374 736 -- 1,497 * 1,753 -- 2532 _ (6.2)* 422 _ 152.3 -- (280.0)6 -- 6.66 13.26 26.11 _ 53.35 -- 62.57 72.07 376 747 1,465 -- 2,971 -- 3,476 3,993 (6.2)* 42.2 152,3 (280.0)6 10/5/94 25 10/5/94 26 Summary| Straight-Forward Modification of Existing PBPK Model Based on Rat In Vivo Studies, Validated with Mouse and Human Data Described Tumor Data 1-6,000 ppm in Rats and Predicted Tumor Data in Mouse Studies Unit Risk Based on PBPK Principles 150 Fold Lower than Current IRIS Value. Tumor Predictions Most Accurate WITHOUT Surface Area Correction Factor * When Mechanism is Known, PBPK Procedures Should Be Capable of Giving Much More Accurate Estimates of Risk. 10/5/94 27 SL 107876