Derivation of a Risk-Based Remediation Standard for Methamphetamine

1. Derivation of a Risk-Based Remediation Standard for Methamphetamine Charles Salocks, Ph.D., DABT California Environmental Protection Agency

2. Remediation Standards for Meth • Current • OR, AR: 0.05 µg/100 cm2 • WA, eight others: 0.1 µg/100 cm2 • CO, MI: 0.5 µg/100 cm2 • Proposed • California: 1.0 – 1.5 µg/100 cm2

3. Overview • Toxicity of methamphetamine • Qualitative: adverse effects on health • Quantitative: doses that elicit toxic effects • Development of a reference dose (RfD) • Models for estimating exposure • Standard Operating Procedures (SOPs) • SHEDS-Multimedia • Calculation of a cleanup standard

4. Fundamental Risk Equation • Toxicity extremes: water and botulinum toxin • Toxicity never equals zero • Exposure may be zero • Toxicity is constant; we reduce or eliminate risk by controlling exposure Risk = Toxicity x Exposure

5. Strategy for Setting a Standard • Develop an RfD for methamphetamine • Estimate exposure from surface residues • Identify a surface residue level that produces a daily dose  the RfD

6. Reference Dose (RfD) “…an estimate (with uncertainty spanning perhaps an order of magnitude) of a daily exposure level for the human population, including sensitive subpopulations, that is likely to be without an appreciable risk of deleterious effects.” • Reflects toxicity and data uncertainty • Calculation: No Effect Level / Uncertainty Factor(s) = RfD

7. Identifying an RfD for Meth • Based on the most sensitive endpoint for toxicity • For methamphetamine, we considered any effect to be a toxic effect • Rationale: a dose low enough to prevent the occurrence of the most sensitive toxicity endpoint will prevent the occurrence of all other toxic effects

8. Effects of Meth in Humans • Increased blood pressure • Sense of well-being • Dilation of pupils • Improved repetitive and complex task performance • Reduced appetite and caloric intake • Sleep disturbance and insomnia

9. Minimally Effective Doses • Absorption rate into the CNS is critical; route of exposure and drug formulation are essential considerations • Adults appear to be more sensitive than children • 5 mg/day (oral) generally produces subtle effects in children and adults

10. Principal Study: Basis of RfD Control of Weight Gain in Pregnancy, Utilizing Methamphetamine (Chapman, 1961) • Not an evaluation of birth outcomes; maternal weight gain and side effects were the endpoints of concern

11. Study Design • Desoxyn® Gradumet® (Abbott) • Sustained release formulation • Three doses: 5, 10 and 15 mg/day • Placebo control, double blind • Total of 84 participants • Initial dose: 22nd - 25th gestation week • Dosing duration: 15-16 weeks

12. Results • Dose-related reduction in weight gain, highly statistically significant • EKG and lab tests normal • No consistent dose-related side effects • Lowest Observed Adverse Effect Level (LOAEL) = 5 mg/day = 0.08 mg/kg-day

13. Uncertainty Factors • 10 – LOAEL to NOAEL extrapolation • 10 – variation in human sensitivity • 3 – incompleteness of toxicity database • Particular concern: potential neuro-developmental toxicity in young children • Total aggregate uncertainty factor: 300

14. RfD Calculation LOAEL / UF = 0.08 mg/kg-day / 10x10x3 = 2.7 x 10-4 mg/kg-day = 0.3 µg/kg-day

15. Exposure Dynamics of Active Lab Air Contamination Exposure Surface Contamination Time

16. Exposure Pathways • Complete exposure pathways have: • Source of contamination • Release mechanism • Transport medium • Point of contact • Route of uptake (inhalation, ingestion, absorption across the skin) • Pathways operational during active and post-cleanup phases may differ substantially

17. Post-Cleanup Exposure Pathways • AB 1078 timeline: remediation to re-occupancy requires 190 days • We assume inhalation of meth is not a significant exposure pathway • Post-cleanup exposure pathways include • Dermal contact & absorption across skin • Dermal contact & ingestion (skin-to-mouth) • Object contact & ingestion (object-to-mouth)

18. Post-Cleanup Exposure Scenario • Populations of greatest concern: babies, toddlers, young children • Their behavior increases their exposure to surface contaminants • Frequent skin contact with floors and walls • Frequent mouthing activities

19. Surface Exposure Model Direct Ingestion Dermal Uptake Incidental Ingestion Route of Uptake Inhalation 2° Medium Air Objects/Toys Skin Dermal Contact Removal Mechanism Resuspension Volatilization Transfer Contaminants Dust VOCs Contaminants SURFACE VOCs

20. Daily Dermal Exposure Profile Zartarian et al., 2000

21. Dermal Uptake of Meth • Dermal absorption studies using human skin were conducted at UC San Francisco • Dermal absorption  60% • This greatly improves our estimate of the hazard resulting from contact with meth-contaminated surfaces

22. Exposure Scenario Assumptions • Uniform concentration on all surfaces • Non-depleting source concentration • Target population: 6-18 months old • No airborne methamphetamine • Duration of exposure: 90 days • No unremediated sources (e.g., air ducts) that could increase surface load

23. Standard Operating Procedures • “SOPs” (U.S. EPA, 1997; revised 2001) • Provides a screening level (high end) estimate of absorbed dose • Deterministic: single value for each parameter in the exposure equation • Justification for parameter values is weak • Generates a point estimate of exposure

24. Deterministic Analysis • Example: inhalation of toluene • Inhalation rate = 10 m3/8-hour workday • Concentration = 50 mg/m3 (8-hour TWA) • Dose = 500 mg/day • 10 m3/8 hours is an example of a default parameter value

25. SOP Absorbed Dose Estimates • Meth residue level: 0.001 µg/cm2 Dose (µg/kg-day) Dermal absorption, carpet residue 3.2 Dermal absorption, floor residue 1.6 Non-dietary ingestion 0.15 TOTAL 4.95 • Total absorbed dose  5 µg/kg-day

26. SHEDS-Multimedia • Stochastic Human Exposure and Dose Simulation (U.S. EPA, 2007) • Stochastic: most parameters represented by a distribution, not point values • Monte Carlo simulation: distributions sampled 100-1000 times to generate a distribution of absorbed dose estimates

27. Stochastic Analysis Inhalation Rate Toluene Concentration Absorbed Dose

28. SHEDS Absorbed Dose Estimates • Meth residue level: 0.001 µg/cm2 Dose (µg/kg-day) Dermal absorption from body 0.016 Dermal absorption from hands 0.002 Non-dietary ingestion 0.002 TOTAL 0.019 • 95th percentile total  0.02 µg/kg-day, or about 250x  SOP estimate

29. SHEDS Exposure Pathways

30. SHEDS Individual Exposure

31. Current Status of SOPs • “DRAFT - DO NOT QUOTE OR CITE” • Weak experimental support for default parameter values • Available data suggest default values generate “high end” dose estimates • Last updated in 2001 • U.S. EPA does not appear to be pursuing further development of this model

32. Current Status of SHEDS • Reviewed at three FIFRA SAP meetings • “…the best information on input variables at this time has been used” (December, 2003) • Most recent meeting: August, 2007 • U.S. EPA promoting model development • Validation studies ongoing • Model improvement assured as new data become available • Represents state-of-the-art

33. Cleanup Standard Calculation • RfD = 0.3 µg/kg-day • SHEDS was run iteratively at increasing surface concentrations until the 95th percentile dose estimate was  RfD • Target remediation standard: 0.015 µg/cm2, or 1.5 µg/100 cm2 • Subject to peer review and comments

34. Reviewer Questions: RfD • Justification for selecting Chapman (1961) as primary study for RfD • Statistical analysis of the data • Adequacy & relevance of supporting studies • Consistency of primary and supporting studies • Justification for uncertainty factors

35. Reviewer Questions: Exposure • Exposure scenario assumptions • Focus on 6-18 month old children • Model descriptions • Justification for SHEDS assumptions • Justification for SHEDS parameters • Rationale for selecting SHEDS dose estimates to calculate cleanup standard

36. Send Your Comments to… Mr. Leon SurgeonIntegrated Risk Assessment BranchOEHHAP.O. Box 4010, MS - 12BSacramento, California 95812-4010Fax:  (916) 322-9705E-mail:  irab@oehha.ca.gov

37. Thank you! • Corey Yep (Cal/EPA, DTSC) • Jim Sanborn (Cal/EPA, OEHHA) • Xiaoying Hui (UC San Francisco) • Dave Siegel (Cal/EPA, OEHHA) • Mari Golub (Cal/EPA, OEHHA) • Farla Kaufman (Cal/EPA, OEHHA)