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Claude Beigel, PhD. Exposure Assessment Senior Scientist Research Triangle Park, USA Theory Metabolites

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Outline Introduction Kinetic endpoints –Degradation Vs. Dissipation endpoints –Trigger Vs. Modeling endpoints General fitting recommendations –Description of metabolic pathway –Data handling –Selected kinetic models –Evaluation of goodness of fit –Decision schemes Conclusions

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Introduction Metabolites need to be considered in environmental assessment The assessment of the relevancy of a metabolite normally involves performing an exposure analysis (soil, groundwater, water-sediment-systems) Kinetic endpoints are needed as triggers for subsequent studies, and for the modeling of the metabolites in the different environmental compartments

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Introduction More complex than for parent because formation and degradation occur simultaneously Complexity increases with complexity of pathway –Number of successive degradation steps, number of metabolites formed at each step & number of precursors Complexity increases with complexity of kinetic models –Formation & degradation

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Maximum kP*ffM*P=kM*M Formation phase kP*ffM*P>kM*M Decline phase kM*M> kP*ffM*P Time ( days ) Substance (% of applied ) Metabolite Curve

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Degradation Vs. Dissipation Metabolite DT50 (decline) = 49.7 d Metabolite DegT50 = 32.0 d

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Trigger Vs. Modeling Endpoints for Metabolites Trigger endpoints (degradation or dissipation DT50/DT90) Triggers for further studies, as provided in Annex II, III and VI of Dir. 91/414/EEC and in Guidance Documents on Aquatic and Terrestrial Ecotoxicology –Use best-fit model kinetics based on statistical and visual analysis

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Trigger Vs. Modeling Endpoints for Metabolites Modeling endpoints (formation rate, formation fraction and degradation rate parameters) No restriction on kinetic model (e.g. PEC soil) –Use best-fit model kinetics based on statistical and visual analysis Restricted to specific kinetic model(s) (e.g. FOCUS groundwater models) –Standard versions of most fate models use SFO –Preference for SFO when an adequate SFO fit is obtained based on statistical and visual analysis –Correction procedures or higher-Tier approaches if an adequate SFO fit is not obtained

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General Fitting Recommendations Metabolites applied as test substance and decline of metabolite from max. are treated as parent Kinetic endpoints for metabolites from studies with parent or precursor can be determined with help of compartment models Substances are represented by different compartments Flows between substances (formation/degradation) are described with differential equations Overall flow from one compartment (e.g. parent) to several compartments (e.g. metabolites + sink) is split using formation fractions

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Compartment Models Parent Metabolite1 Metabolite2 Sink (other metabolites, bound residues, CO2) FP * ffM2FP * ffM1 FP*(1-ffM1-ffM2) FM1 FM2 Parent: dP/dt = – FP Metabolite 1: dM1/dt = FP · ffM1 – FM1 Metabolite 2: dM2/dt = FP · ffM2 – FM2 Sink: dS/dt = FP · (1 – ffM1 – ffM2) + FM1 + FM2

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Description of Metabolic Pathway Formation and degradation of metabolite are linked, and the parameters can be highly correlated Formation of metabolite = degradation of precursor x formation fraction Pathway Conceptual model must reflect actual degradation or dissipation pathway Flows to sink are initially included for formation of other metabolites (identified or not), bound residues and CO 2 Essential to describe precursor correctly (especially first 90%)

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Parent Others Metabolite Parent Metabolite DT 50 Parent: 5.8 d DT 50 Metabolite: 16 d Formation fraction: 1 DT 50 Parent: 3.3 d DT 50 Metabolite: 38 d Formation fraction: Pathway: Including Flow to Sink

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Data Handling Follow general guidance with regard to replicates, experimental artifacts and outliers Correction of time-zero data Add metabolites + bound residues to parent, set metabolites and sink time-zero to 0 Data points below LOQ/LOD Set concentrations between LOD and LOQ to measured value or 0.5 x (LOD+LOQ) Set samples < LOD to 0.5 x LOD Omit all but one < LOD samples before first detect Omit samples after first non-detect unless later samples > LOQ

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DT 50 Parent: 12.7 d DT 50 Metabolite 1: 41.5 d DT 50 Metabolite 2: 133 d DT 50 Parent: 17.6 d DT 50 Metabolite 1: 47.3 d DT 50 Metabolite 2: 369 d Unweighted fit Weighted fit (fractional) Always use unweighted data as a first step! Weighting Method

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Selected Kinetic Models for Metabolites SFO model Preferred model, constitutive autonomous differential equation available Common problem with biphasic models: differential equations include time, not suitable for metabolites that are formed over time FOMC model may only be used in integrated form, cannot be implemented in environmental models DFOP model can still be implemented with system of differential equations using two sub-compartments biphasic model of choice HS model not appropriate for metabolites because of breakpoint

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DT 50 Parent: 0.94 d DT 50 Metabolite: 18.3 d DT 90 Metabolite: 60.9 d DT 50 Parent: 0.94 d DT 50 Metabolite: 15.6 d DT 90 Metabolite: 113 d Metabolite SFOMetabolite DFOP Metabolite Kinetic Models

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Stepwise Approach for Complex Cases 1)Fit parent substance 2)Add primary metabolite(s), fit with parent parameters fixed to values obtained in 1), check flow to sink and simplify if justified 3)Fit parent and primary metabolite(s) using values obtained in 1) and 2) as starting values 4)Add secondary metabolite(s), fit with parent and primary metabolite(s) parameters fixed to values obtained in 3), check flow to sink and simplify if justified ---- n)Final step: fit all substances together using values obtained in n-1) as starting values

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Evaluation of Goodness of Fit Statistical indices where C = calculated value O = observed value Ō = mean of observed err = measurement error T-test for rate constant parameters If 2 > 2 m, then the model is not appropriate at the chosen significance level where m = degrees of freedom (No. of obs. used in the fitting – No. of optimized model parameters) = level of significance, typically 5% 2 test, minimum 2 error

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Evaluation of Goodness of Fit Graphical Evaluation (Visual Assessment) Minimum 2 error: 9.2% (parent) and 4.9% (metabolite) Plot of Residuals (Fitted – Observed) Plot of Fitted Vs. Observed with Time Statistical Evaluation

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Decision Schemes: Trigger Endpoints (1) Goal: find best-fit model (same approach for PEC soil) Start with parent, compare SFO to most simple biphasic model (FOMC) If SFO same or better, and SFO acceptable, keep SFO model If FOMC better, compare with DFOP, keep best-fit model Run parent SFO Vs. FOMC SFO better and acceptableUse SFO for parent yes no, FOMC better Biphasic, run DFOP and compare with FOMC Use Best-fit Model for parent

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Decision Schemes: Trigger Endpoints (2) Add metabolites, stepwise for complex cases, run parent best-fit and metabolites SFO If SFO acceptable for metabolites, keep SFO model If not, run appropriate biphasic model for metabolite (DFOP or FOMC), if acceptable, use best-fit model for metabolite SFO acceptable for metabolitesUse SFO yes no Run parent best-fit and test appropriate biphasic model for metabolite (DFOP or FOMC) Use Biphasic Model Run parent best-fit with metabolites SFO Biphasic model acceptable for metabolite yes

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Decision Schemes: Modeling Endpoints (2) Goal: kinetic model compatible with environmental model First step: check if SFO is acceptable, if yes use SFO model If not, higher-Tier options to implement biphasic degradation pattern Start with parent, is SFO acceptable for at least first 90% of dissipation? Run parent SFO SFO good enough ?Use SFO for parent yes no Run parent with appropriate biphasic model, e.g. DFOP or PEARLneq Biphasic model good enough ? Use Biphasic model for parent yes

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Decision Schemes: Modeling Endpoints (2) Add metabolites, stepwise for complex cases, run with metabolites SFO If SFO acceptable for metabolites, keep SFO model If not, use conservative approaches, on case-by-case basis –Degradation rate constant of metabolite not significantly 0, use conservative default of 1000 days –Metabolite biphasic, use higher-tier approach (DFOP or PEARLneq), or set SFO DT50 to DFOP DT90/3.32 if terminal metabolite SFO acceptable for metabolitesUse SFO yes no Case-by-case conservative approaches Run parent with metabolites SFO

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Guidance provided for deriving kinetic endpoints for metabolites Trigger endpoints: degradation/dissipation DT 50 and DT 90 Modeling endpoints: formation fraction, formation and degradation rates Harmonized approach for reproducible results independent of software tool used Better acceptance of generated endpoints Facilitates review process Conclusions

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