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Comprehensive Guidelines for Metabolite Kinetics Assessment

Understand the complexities of metabolite pathways, from formation to degradation, for environmental impact analysis. Learn about triggers, models, data handling, and fitting recommendations for accurate assessments.

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Comprehensive Guidelines for Metabolite Kinetics Assessment

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

  2. 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

  3. 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

  4. 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

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

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

  7. 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

  8. 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

  9. 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

  10. Parent FP * ffM1 FP * ffM2 FP*(1-ffM1-ffM2) Metabolite1 Metabolite2 FM2 FM1 Sink (other metabolites, bound residues, CO2) Compartment Models 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

  11. 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 CO2 • Essential to describe precursor correctly (especially first 90%)

  12. Metabolite Metabolite Parent Parent Others Pathway: Including Flow to Sink DT50 Parent: 5.8 d DT50 Metabolite: 16 d Formation fraction: 1 DT50 Parent: 3.3 d DT50 Metabolite: 38 d Formation fraction: 0.466

  13. 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

  14. Weighting Method Unweighted fit Weighted fit (fractional) DT50 Parent: 17.6 d DT50 Metabolite 1: 47.3 d DT50 Metabolite 2: 369 d DT50 Parent: 12.7 d DT50 Metabolite 1: 41.5 d DT50 Metabolite 2: 133 d Always use unweighted data as a first step!

  15. 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

  16. Metabolite Kinetic Models Metabolite SFO Metabolite DFOP DT50 Parent: 0.94 d DT50 Metabolite: 18.3 d DT90 Metabolite: 60.9 d DT50 Parent: 0.94 d DT50 Metabolite: 15.6 d DT90 Metabolite: 113 d

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

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

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

  20. Run parent SFO Vs. FOMC yes SFO better and acceptable Use SFO for parent no, FOMC better Use Best-fitModel for parent Biphasic, run DFOP and compare with FOMC 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

  21. Run parent best-fit with metabolites SFO yes SFO acceptable for metabolites Use SFO no Run parent best-fit and test appropriate biphasicmodel for metabolite (DFOP or FOMC) yes Use BiphasicModel Biphasic model acceptable for metabolite 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

  22. Run parent SFO yes no SFO good enough ? Use SFO for parent Run parent with appropriate biphasic model, e.g. DFOP or PEARLneq yes Use Biphasic modelfor parent Biphasic model good enough ? 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?

  23. Run parent with metabolites SFO yes SFO acceptable for metabolites Use SFO no Case-by-case conservative approaches 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

  24. Conclusions • Guidance provided for deriving kinetic endpoints for metabolites • Trigger endpoints: degradation/dissipation DT50 and DT90 • 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

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