An informatic approach to estimating ecological risks posed by pharmaceutical use.

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An informatic approach to estimating ecological
risks posed by pharmaceutical use.
M. Kostich, J. Lazorchak, G. Toth.U.S.
Environmental Protection Agency, Cincinnati,
Ohio, USA.
Although this work was reviewed by EPA and
approved for presentation, it may not
necessarily reflect official Agency policy.
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Why worry about pharmaceuticals?

• In the USA, 2000 drug products are approved for
  use in humans
• Active ingredient or active metabolites often
  excreted
• Many at ppt or higher levels in WWTP influents,
  effluents, sludge, surface water, ground water,
  drinking water, fish, etc
• Designed to have biological effects at low
  concentrations
• Some (i.e. EE2) known to affect fish at ppt
  levels in lab
• Reasonable suspicion of contributing to intersex,
  etc. observed in wild populations

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An informatics guided approach
Drug count
Uncertainty
Cost
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General principles

• Calculate likely worst-case for each active
  ingredient
• Assume most likely toxicity is mechanism based
• physical properties unlikely cause of tox at ng/L
• toxic thru therapeutic target or close homolog
• Normalize based on potency in humans
• potencies span 6 orders of magnitude
• Estimate range of susceptible species based on
  molecular conservation of therapeutic target
• Guide toxicity testing based on known MOA
• Account for human metabolism
• metabolism affects activity excreted
• metabolites often partially or fully active
• metabolites often more prevalent than parent
• Account for waste disposal (5-15)

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Normalization

• Two approaches based on potency in humans
• often give very different (but complementary)
  views
• Minimum adult daily dose (per unit surface area)
• readily interpretable for human risk assessment
• how much water would you need to drink for 1 DD?
• for modeling fish, represents a flux approach
• flux in vs. flux out, exploring extreme
  assumptions
• how long would it take to extract one dose?
• how low would CL have to be to reach Cmax?
• Therapeutic unbound plasma concentration
• peak plasma concentrations (Cmax) in humans known
• represents aqueous protein bound cell bound
• aqueous/free fraction represents what is
  available
• for interaction with molecular target
• for passive or active renal clearance
• for phase I and II metabolic clearance
• for modeling fish, represents a fugacity approach

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Pilot summary excreted activity
Based on an analysis of 200 name brand
products Poster presented at Setac-Baltimore,
November 2005
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Pilot summary normalized PECs
Based on an analysis of 200 name brand
products Poster presented at Setac-Baltimore,
November 2005
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Pilot summary molecular targets
Based on an analysis of 200 name brand
products Poster presented at Setac-Baltimore,
November 2005
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Step 1 mass dispensed per year

• 347 active ingredients
• 939 products, brand name and generic
• not included vitamins, minerals, contrast
  agents, bile acid sequestrants, electrolytes, and
  caffeine
• Use available marketing data for 2004
• Pricing
• Red Book relatively complete pricing guide
• wide range of prices for individual products
• choose lowest available price/unit (mg or IU)
• Sales in dollars
• three published lists (IMS, NDC, Verispan)
• very incomplete top sellers only
• biggest single source of uncertainty
• OTC activity not accounted for
• Aggressive upper-end estimates
• typically order of magnitude
• sometimes totally unrealistic
• trying to identify upper bounds of potential
  problem
• highlights candidates with high uncertainty

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Step 1 mass dispensed per year
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Step 1 mass dispensed per year
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Step 2 daily doses per year
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Step 3 mechanism of action
Also an anti-androgen
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Step 3 mechanism of action
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Step 3 mechanism of action
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Step 4 human excretion
Step 5 aqueous sludge stability

• List of contaminants ranked on maximum risk
• Corresponding list of analytes and active agents
• 1st order ecological impact estimate
• humans (may be better than 1st order)
• fish
• A model for understanding our measurements
• source-to-sink disposition and effects model
• guide for research and remediation

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Concluding comments

• Major uncertainty marketing data
• especially low volume sales
• limits downstream estimates to order of magnitude
  (sometimes 2)
• still useful as range is 9 orders of magnitude
• rankings more robust to uncertainty
• hi estimate seems pretty reliable ceiling
• Other data gaps
• stability in water at relevant pHs
• resistance to waste water treatment
• geographic and temporal variation
• bioavailability and (especially) clearance in
  fish
• relative bioavailability of active metabolites
• receptor affinity in non-mammals

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Acknowledgements

• Christian Daughton
• US EPA,
• Las Vegas, Nevada
• Kevin Bisceglia
• Johns Hopkins University,
• Baltimore, Maryland
• Susan Glassmeyer
• US EPA,
• Cincinnati, Ohio
• Kathy Schenck
• US EPA,
• Cincinnati, Ohio