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Benchmark Dose Software (BMDS)

Benchmark Dose Modeling: Theory and Application of Basic Modeling Methodologies in Risk Assessment

Benchmark Dose Modeling: Advanced Methodologies and Tools for Performing More Complex Dose-Response Analyses

Organizers/Instructors: J. Allen Davis, MSPH, US Environmental Protection Agency (EPA); Jeff Gift (EPA); Jay Zhao, MD, MPH, PhD (EPA), Andrew Shapiro, MS (ICF))

Registration fee: Half-day workshop: $75.00, Student Half-day workshop: $50.00

http://toxicologyandriskassessmentconference.org/index.htm Exit EPA Disclaimer

Participants do NOT need to bring laptops to the workshops. Abstracts for the two workshops are shown below:

AM Course (W-5):

Benchmark Dose Modeling: Theory and Application of Basic Modeling Methodologies in Risk Assessment

The objectives of this course are to provide participants with an introduction to the evaluation of dose-response data in accordance with EPA’s Benchmark Dose (BMD) guidelines and how to use the Agency’s Benchmark Dose Software (BMDS) to facilitate BMD analyses in risk assessments. Specific topics covered will include a general overview of the BMD process, determination of data adequacy, model fitting, model comparison, and selection, and choice of a benchmark response level. This course will cover all the BMD models available in the current version of BMDS – including the recently added dichotomous hill and exponential models. In addition, key concepts will also be presented using new features in BMDS version 2.2.

By the end of the course, users will know:

  • When to apply BMD modeling, how to apply BMD modeling to a dataset, and how to decide which BMD should be selected.
  • What a BMD is, and the advantages and disadvantages of using a BMD instead of using LOAEL and/or NOAEL
  • How to select a data-set to be modeled, define a benchmark response, and use the BMDS modeling software to calculate a BMD/BMDL
  • Understand how BMD values are calculated and various approaches to better approximate equivalent dose in humans using alternative dose metrics

PM Course (W-8):

Benchmark Dose Modeling: Advanced Methodologies and Tools for Performing More Complex Dose-Response Analyses

This half-day course focuses on how to use advanced benchmark dose modeling applications and an overview of Excel-based tools which organize BMD modeling results and other information used in a chemical dose-response assessment. Participants are expected to have a general understanding of benchmark dose modeling, or, have taken the course offered in the AM (W-5), “Benchmark Dose Modeling: Theory and Application of Basic Modeling Methodologies in Risk Assessment”.

This course will provide an overview of modeling continuous and dichotomous datasets using Excel-based software packages called the BMDS Wizard and DRAGON, both of which will be provided to those registered for the course. The BMDS Wizard allows users to build BMDS input from Excel, run BMDS, and import results into an Excel file. In addition to importing all results, it is capable of recommending best-fitting models using customizable decision criteria. It will also demonstrate how to use an additional Excel software package titled the Dose Response Analysis Generator and Organizational Network (DRAGON). The DRAGON is designed to store key dose-response information (BMD, NOAEL, LOAEL, etc.) from multiple studies in one Excel-based database. This course will demonstrate how to use the software, including how to enter information, perform batch BMD modeling for multiple endpoints, calculate standard dosimetric conversions, and generate result reports and documentation.

In addition, this course will demonstrate how to use the following advanced BMD models, and provide fundamental understanding of the approach and model-framework used for the following models:

  • The MS_Combo model for assessing the risk of developing any number of independent, multiple tumors observed in a single bioassay.
  • The Multistage Weibull Time-to-Tumor Model (MSW) for cancer analyses when survival rates are observed to differ due to exposure
  • The Toxicodiffusion Model for analyzing repeated response data common to many neurotoxicity test guidelines
  • Categorical Regression Modeling (CatReg) for modeling data from multiple bioassays or for multiple species simultaneously

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