Refined exposure estimation to support an Environmental Assessment for a veterinary medicine

Transcription

1 May 25, 2016 Refined exposure estimation to support an Environmental Assessment for a veterinary medicine Christopher Holmes, Isha Khanijo, Joshua Amos and Amy Ritter Waterborne Environmental, Inc. Holly Zahner and Eric Silberhorn US FDA Center for Veterinary Medicines Dawn Merritt, Zoetis SETAC Europe 26 th Annual Meeting Nantes, France

2 Introduction The U.S. Food and Drug Administration (FDA), Center for Veterinary Medicine (CVM), evaluates whether significant environmental impacts would occur with the approval of new animal drugs pursuant to the National Environmental Policy Act (NEPA) The approval process may require the preparation of an environmental assessment (EA) Contains sections addressing problem formulation, environmental fate, exposure, effects and risk characterization Guidance for Industry 89 (VICH GL 6) and 166 (VICH GL 38) Using a recent EA as a framework 1, this presentation will focus on the refinement of environmental exposure estimates (i.e., PECs) 1 Zoetis Environmental Assessment for Synovex ONE Feedlot and Grass for Beef Steers and Heifers.

3 Standard Risk Quotient Assessment Exposure Assessment Predicted Environmental Concentration (PEC) Environmental Release (Use Pattern) Environmental Fate Modelling RQ = PEC PNEC 1 unacceptable risk Effects Assessment Predicted No Effect Concentration (PNEC) = Effects Concentration (NOEC/LC50/EC50) Assessment Factor (10/100/1000)

4 Goals of refined exposure assessment Develop refined methods to estimate aquatic environmental exposure from uses of a veterinary drug (i.e., higher-tier PECs) Use spatial techniques to identify representative and protective environmental scenarios Link these scenarios to accepted exposure models used in the U.S. Environmental Protection Agency (USEPA) pesticide registration process Address all potential sources of chemical loading within a watershed

5 Approach Use a Geographic Information System (GIS) to identify regions of high exposure potential across the US based on beef cattle characteristics and climatic conditions From within each region, select a vulnerable watershed to characterize for watershed-scale chemical fate & transport modeling

6 Approach Conduct watershed scale exposure modeling for surface water following the USEPA Tier-2 drinking water pesticide exposure modeling approach Address three potential sources of chemical: feedlots, agricultural fields applied with manure collected from the feedlots, and pasture cattle Model runoff and erosion inputs to surface water from these sources over a 30-year timeframe to produce final concentrations suitable for use in the effects portion of the EA (i.e., PEC water ) Runoff Erosion

7 Conceptual Model Mixed Use Watershed Scale Model

8 National Vulnerability Identify beef cattle regions in United States with highest potential for exposure Spatial overlay of areas of high beef cattle production with high precipitation Beef feedlots Cropland applied with manure Pasture cattle Long term average rainfall (annual & seasonal) Five regions identified for exposure characterization & modeling Iowa, Pennsylvania, Ohio, Michigan, Texas

9 Density of Feedlot Beef Cattle USDA NASS Census of Agriculture, 2012

10 Density of Acres of Manure Applied USDA NASS Census of Agriculture, 2012

11 Density of Pastured Beef Cattle USDA NASS Census of Agriculture, 2012

12 Long Term Average Total Annual Rainfall PRISM Climate Group, Oregon State Univ.

13 Watershed Selection Select highly vulnerable watershed within each region for chemical fate and transport modeling Characterize watersheds in each region Average area approx. 40 mi 2, n = 38 to 42 Amount of feedlot cattle, manured cropland, pastured cattle Data from IA DNR, TX DEQ, USDA Census of Agriculture, Select watershed with a 90 th centile total annual mass loading entering watershed from three modeled sources Based on baseline EPA s Iowa corn scenario Feedlot mass > manured cropland mass >> pasture mass Distribution of watershed mass loading within each region

14 Iowa Watershed Area = 33 mi 2 90% cropland Feedlots = 20 Feedlot cattle = 15,783 head Manured cropland = 11,983 acres (57% total watershed area) Pasture cattle = 1,525 head

15 Final Metrics of Selected Watersheds Watershed Area (miles) # Beef Cattle in <1,000 head feedlots # Beef Cattle in >1,000 head feedlots # Beef Pasture Cattle Iowa Lyon + Sioux Counties Texas Castro County Michigan Huron County Ohio Mercer County Pennsylvania Lancaster County , ,233 1,822 10,410 20,965 1,513 1,000 1,000 1,525 3,720 1, ,350

16 Exposure Modeling USEPA s Tier-2 framework for estimating drinking water exposure Watershed level assessment 30 year weather data and repeated annual applications Includes 128 regional crop-soil-weather scenarios 1 in 10 year endpoint Agricultural field simulated by USEPA model PRZM Predicts edge-of-field chemicals loadings in runoff and erosion Percent Cropped/Treated Area (PCA) factor can be used to scale the concentrations based on portion of watershed treated Waterbody simulation modeled with USEPA model EXAMS Edge of field loading transported directly into waterbody

17 Index Reservoir Environment Field level Direct edge-of-field into surface water Drift Runoff / erosion PRZM Water body Watershed level Scaled by composition

18 Cropland Application of recoverable solid manure is generated from all feedlots in the watershed Runoff from collection ponds was also applied to cropland Manure mass application rate calculated for 300 kg animal based on daily P 2 O 5 excreted in manure and allowable P 2 O 5 application rate to crop (corn silage) USEPA s standard corn scenario (soil, weather and crop)

19 Pasture Modeled the daily loading of the veterinary drug excreted by cattle on pasture land incorporate beginning and ending dates for grazing Application rate based on daily drug release rate from cattle multiplied by stocking density (3.15 head/acre) USEPA Standard corn scenario for soil & weather coupled with pasture grass Source:

20 Feedlot PRZM was used to model the daily loading of the drug excreted by cattle on feedlot based on the dates for scraping the feedlot Concentration of the drug in manure stays constant during the entire simulation period Drug lost only thru runoff and erosion losses No degradation of the drug in manure Application rate based on daily drug release rate from cattle multiplied by stocking density (270 head/acre) Drug concentration is evenly mixed in top 10 cm of manure layer

21 Results Daily mass loadings from three sources combined into water body Cropland Pasture Daily Concentration in Water Feedlot Feedlot manure surface is highly susceptible to runoff and erosion because of bare surface, feedlot is biggest contributor of edge-of-field loadings compared to pasture and cropland From distribution (peak or TWA), select 30 annual maxima, then 90 th %ile PEC value

22 Conservative Assumptions Assumed all cattle in each watershed were implanted (100% of the market share in each watershed) Assumed that 25 and 50% of feedlots directly discharge their runoff into surface water Using USDA data, only 17% of all feedlots (<1000 head) in the US are in need of controls for runoff of discharge Losses due to feedlot runoff were not accounted for in the manure application scenarios (i.e., assumed 100% of compound mass was present in the manure and irrigation water applied to crop land) Assumed no degradation or transformation occurs in the manure Use of vegetative buffer strips and other farm best management practices was not accounted for in the exposure assessment modeling And many more discussed in the EA

23 Summary Developed refined methods to estimate exposure using spatial techniques to identify representative and protective environmental scenarios Linked these scenarios to accepted EPA exposure models Addressed all potential sources of chemical loading Feedlots, manured cropland, and pastured cattle Produced a series of surface water PECs (based on 30-yr simulations) suitable for risk characterization Present a robust and viable Tier 2 framework which incorporates real world information but maintains conservatism

24 Conclusion Based on the aggregate aquatic exposure (90th percentile of annual maximum 21-day time weighted average) for the five mixed-use watersheds over a 30-year period, no significant effects were identified, and along with other submission documents, a Finding of No Significant Impact (FONSI) was determined 1. 1 USFDA Center for Veterinary Medicine Finding of No Significant Impact (FONSI) in support of a supplemental New Animal Drug Application for SYNOVEX CHOICE.

25 FDA listing of EAs for animal drugs EnvironmentalAssessments/ucm htm

26 Thank You Chris Holmes waterborne-env.com (703)