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Modeling How the Human Body Handles Drugs and Toxicants. Crispin Pierce, Ph.D. UWEC Faculty / Academic Staff Forum 27 October 2004. http://www.uwec.edu/piercech/model.ppt. UWEC Student-Faculty Research. Mia Jewell, Laura Schrage, Julie Friedhoff, Alison Deneen, and Ashley LaCasse.

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Modeling how the human body handles drugs and toxicants l.jpg

Modeling How the Human Body Handles Drugs and Toxicants

Crispin Pierce, Ph.D.

UWEC Faculty / Academic Staff Forum

27 October 2004

http://www.uwec.edu/piercech/model.ppt


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UWEC Student-Faculty Research

Mia Jewell, Laura Schrage, Julie Friedhoff, Alison Deneen, and Ashley LaCasse


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Crispin Pierce, Mia Jewell, and Karen Bartosh

Not pictured: Erin Moritz, Chris Judkins-Helpsmeet, and Kristin Hardy


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Acknowledgements

  • Michael Morgan and Russell Dills, University of Washington, Seattle

  • UWEC Office of Research and Sponsored Programs

  • NIOSH SERCA Grant 5 K01 OH00164

  • Superfund Basic Research program, NIEHS ES 04696

  • NIH/ NIBIB Grant 2 P41 EB001975



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Voluntary exposure

  • Eating and drinking

http://www.runslinux.net/~belanaomi/Friends.htm



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http://www.quantico.usmc-mccs.org/business/retail-services.htm





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How Do We Predict the Effects of These Chemicals?

  • Empirical Observations

    • Exposure to air pollution reduces lung function in children.

    • “I take two aspirin to relieve pain.”

    • Regular dosing with folic acid during the first trimester of pregnancy lowers risk of fetal health risks.

    • Chronic consumption of fatty meats raises risks of cardiovascular disease and cancer.


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Dose-Response Relationships

  • We use animal dosing experiments and results from epidemiological studies to make observations about dose-response relationships.

http://homepage.psy.utexas.edu/HomePage/class/Psy308/salinas/Psychopharmacology/Psychopharm.html


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All Substances Are Poisons at the Wrong Dose

http://homepage.psy.utexas.edu/HomePage/class/Psy308/salinas/Psychopharmacology/Psychopharm.html


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Can We Open Up This “Black Box”?


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Yes, We Can Examine the Changing Chemical Concentration in Blood

From these data, we can estimate the rates of

absorption and excretion.


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Half-Life is a Valuable Descriptor Blood

http://www.geo.arizona.edu/palynology/geos462/10radiometric.html


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We Can Also Create Models for How the Body Eliminates Chemicals

  • The Georgia Center for Continuing Education


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Why Would We Want to Understand How the Body Handles the Chemical?

  • To answer the following questions:

    • Why are some chemicals more toxic to test animals than humans, and vice versa?

    • Are cancer risks that we measure at very high doses in animal studies linear down to the low exposures that we receive?

    • Can we make drugs more effective and less toxic?

    • Can we develop new antidotes to poisons?



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Student Project 1: same dose of the same substance.Toxicokinetics of Toluene

  • “Toxicokinetics” = toxicon (poison) + kinetic (movement) = movement of poisons throughout the body.

  • Toluene is the most widely-used industrial solvent.

  • An understanding of how the body handles toluene, a less toxic substance, can help us understand the much higher risks from similar substances such as benzene, which causes cancer.


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  • Methods: Seven males inhaled 50 ppm of 13C- and 2H-toluene over a two hour period. Blood, breath, and urine samples were collected for up to 100 hr post-exposure and were analyzed for parent and metabolite concentrations. This portion of the study took place at the University of Washington and was approved by the Human Subjects Division.


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  • This macro determined the kinetic parameters of k-elimination, terminal half-life, area under the curve (AUC), clearance (Cl), mean residence time for the central compartment (MRTC), and volume of distribution at a steady state (Vdss).


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  • Multiple regressions were used to determine which anthropometric characteristic were predictors of clearance, terminal half life, Vdss(the volume into which toluene distributes), MRTC (the average time a chemical spends in the body), maximum peak height/dose, and AUC/dose (how quickly the body gets rid of toluene).


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What About the Mechanism of How the Body Handles Chemicals? anthropometric characteristic were predictors of clearance, terminal half life, Vdss(the volume into which toluene distributes), MRTC (the average time a chemical spends in the body), maximum peak height/dose, and AUC/dose (how quickly the body gets rid of toluene).


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Student Project 2: Examining MTBE Risk anthropometric characteristic were predictors of clearance, terminal half life, Vdss(the volume into which toluene distributes), MRTC (the average time a chemical spends in the body), maximum peak height/dose, and AUC/dose (how quickly the body gets rid of toluene).


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What Are MTBE and ETBE? anthropometric characteristic were predictors of clearance, terminal half life, Vdss(the volume into which toluene distributes), MRTC (the average time a chemical spends in the body), maximum peak height/dose, and AUC/dose (how quickly the body gets rid of toluene).

  • Fuel additives that increase O2 in gasoline

  • 1990 Clean Air Act Amendments

  • Reduce carbon monoxide & ozone components in air pollution

  • 30% of U.S. gasoline is “oxygenated”

  • 87% of oxygenated gas contains MTBE


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Problems With MTBE anthropometric characteristic were predictors of clearance, terminal half life, Vdss(the volume into which toluene distributes), MRTC (the average time a chemical spends in the body), maximum peak height/dose, and AUC/dose (how quickly the body gets rid of toluene).

  • Associated with complaints of headaches, nausea, disorientation

  • Ubiquitous in urban areas

  • Unpleasant odor and taste

  • Leaks into drinking water

  • Contaminated ground water in all 50 states

  • Possible human carcinogen


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Methods of Exposure anthropometric characteristic were predictors of clearance, terminal half life, Vdss(the volume into which toluene distributes), MRTC (the average time a chemical spends in the body), maximum peak height/dose, and AUC/dose (how quickly the body gets rid of toluene).

  • Contaminated Water

    • Drinking

    • Showering

  • Inhalation

    • At the gas pump

    • While driving

    • Work environments


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Previous Experiment anthropometric characteristic were predictors of clearance, terminal half life, Vdss(the volume into which toluene distributes), MRTC (the average time a chemical spends in the body), maximum peak height/dose, and AUC/dose (how quickly the body gets rid of toluene).

  • 10 Healthy Caucasian volunteers: 5 women, 5 men.

  • Target inhaled concentrations of 2.5 ppm 2H12-MTBE and 2.5 ppm ETBE.

  • Two hours of exposure with alternating periods of 30 min 50W exercise and 15 min rest.


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  • Model representing MTBE path through the body anthropometric characteristic were predictors of clearance, terminal half life, Vdss(the volume into which toluene distributes), MRTC (the average time a chemical spends in the body), maximum peak height/dose, and AUC/dose (how quickly the body gets rid of toluene).


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Experimental Goals anthropometric characteristic were predictors of clearance, terminal half life, Vdss(the volume into which toluene distributes), MRTC (the average time a chemical spends in the body), maximum peak height/dose, and AUC/dose (how quickly the body gets rid of toluene).

  • Statistical testing of MTBE, ETBE, and TBA models

  • Risk assessment based on cancer- AUC


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Statistical Testing anthropometric characteristic were predictors of clearance, terminal half life, Vdss(the volume into which toluene distributes), MRTC (the average time a chemical spends in the body), maximum peak height/dose, and AUC/dose (how quickly the body gets rid of toluene).

  • Monte Carlo

    • Used PopKinetics software to create a 95% confidence interval around the mean predicted line


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Compare the differences between the yellow data points and the mean model prediction (black line) to the differences between the upper or lower confidence interval (gold or yellow line) and the mean prediction (black line).


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Monte Carlo : 0.06718 => the mean model prediction (black line) to the differences between the upper or lower confidence interval (gold or yellow line) and the mean prediction (black line).Model Fits


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Risk Determination the mean model prediction (black line) to the differences between the upper or lower confidence interval (gold or yellow line) and the mean prediction (black line).

  • Used lowest literature standards for MTBE

    • Inhalation

    • Drinking water

  • Calculated a dose based on above values

  • Ran models with calculated dose as input

  • Determined overall risk

    • Used SAAM’s AUC


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MTBE Regulations the mean model prediction (black line) to the differences between the upper or lower confidence interval (gold or yellow line) and the mean prediction (black line).


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Assumptions Used the mean model prediction (black line) to the differences between the upper or lower confidence interval (gold or yellow line) and the mean prediction (black line).

  • 70 kg body weight and 25% adipose content

  • Alveolar ventilation and cardiac output rates were set as low and constant

  • Drinking water experiment

    • Drink 2 L of water per day (10 ppb MTBE)

    • 70-year lifetime

  • Inhalation experiment

    • 40 year working lifetime (40 ppm)


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Area Under the Curve the mean model prediction (black line) to the differences between the upper or lower confidence interval (gold or yellow line) and the mean prediction (black line).


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Results: Single-day AUCs the mean model prediction (black line) to the differences between the upper or lower confidence interval (gold or yellow line) and the mean prediction (black line).

  • Typical daily exposure

    • Drinking water: 9.17e-3 umol-hr/L

    • Inhalation (Gas pump): 1.36e-1 umol-hr/L

    • 15 times higher risk from gas pump exposure


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Results: Lifetime AUCs the mean model prediction (black line) to the differences between the upper or lower confidence interval (gold or yellow line) and the mean prediction (black line).

  • Based on standards

    • Drinking water: 2.44e2 umol-hr/L

    • Inhalation (Work exposure): 2.18e6 umol-hr/L

    • 9,000 times higher risk from work exposure.


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Conclusions the mean model prediction (black line) to the differences between the upper or lower confidence interval (gold or yellow line) and the mean prediction (black line).

  • Empirical and mechanistic approaches can be used to understand how the body handles chemicals

  • Anthropometric characteristics affect how different people handle a chemical.

  • Models can be used to predict risk of toxicity from different kinds of chemical exposures.