Date post: | 27-Mar-2015 |
Category: |
Documents |
Upload: | hannah-mccurdy |
View: | 215 times |
Download: | 2 times |
26-27 Jan 2005 Page 1
FOCUS Kinetics training workshop
Chapter 7
Recommended Procedures to Derive Endpoints for Parent Compounds
Practical Exercise
Ralph L. Warren, Ph.D.DuPont Crop Protection
Delaware, USA
26-27 Jan 2005 Page 2
FOCUS Kinetics training workshop
Goal of the exercise
The goal of this exercise is to calculate the 2 error and to conduct a visual assessment for kinetic model fits to measured levels of parent compound in soil. Based on this information, the most appropriate kinetic model and endpoints for comparison with regulatory triggers and for use in regulatory exposure modelling should be identified.
You will need• ModelMaker 4 results from this morning for Example 1 and Example 2. Try Example 3 if time allows (you will need to first do the optimization using MM4).
• Excel file “Parent degradation kinetic_training_ unprotected.xls”
• Excel file “t_test.xls”
• Excel file “DFOP_DT50.xls”
26-27 Jan 2005 Page 3
FOCUS Kinetics training workshop
In the interest of time, we will not iteratively modify the fitting routines (e.g. excluding outliers, constraining MO, weighting).
Also assume that there are no experimental artifacts (e.g. microbial die off).
General instructions for the exercise• Follow the parent only flow chart for triggers, then the flow chart for modelling to determine which fits are needed.
• Generate optimized results from ModelMaker (record necessary information!)
• Create plots for observed versus fitted values and for residuals using Excel (record necessary information!)
• Calculate the 2 error percentages using Excel (record!).
• Decide which kinetic model and endpoints to use for triggers and for modelling.
• Record your conclusions and be prepared to report them to the class.
Page 4
Triggers flowchart
FOCUS Kinetics training workshop
NO
YES see text
YES
RUN SFO, FOMC
Data entry M0 free, use all data, no weighting
SFO more appropriate than FOMC and gives
acceptable fit?
RUN DFOP (unmodified &
modified fitting routine)
Does the best-fit model give an acceptable description
of the data?
STEP 1: SFO appropriate?
STEP 2: Identify best model other than SFO
Deviation from SFO due to experimental
artifact/decline in microbial activity?
NO
Case-by-case decision (see text)
Determine which of the models (FOMC, DFOP)
is best
NO
YES STOP
STEP 3: Evaluate goodness of fit
NO
Modify fitting routine stepwise: 1. Exclude outliers 2. Constrain M0 3. Weighting
RUN modified fitting
SFO more appropriate than FOMC & fit acceptable?
(modified fitting)
YES STOP
STOP
26-27 Jan 2005
26-27 Jan 2005 Page 5
Modelling flowchart
FOCUS Kinetics training workshop
NO YES
RUN SFO
Data entry M0 free, use all data, no weighting
SFO statistically and visually acceptable? Modify fitting routine for
SFO stepwise: 1. Exclude outliers 2. Constrain M0 3. Weighting until best SFO fit achieved
STEP 1: SFO appropriate?
RUN modified SFO
Use SFO DT50 for fate modelling
Aim: modelling fate of parent only?
YES
YES 10% initially measured concentration reached
within experimental period?
NO RUN FOMC
RUN HS or DFOP
Use DT50 from slow phase of HS of DFOP
model for fate modelling
Case-by-case decision (see text)
NO
HS or DFOP statistically and
visually acceptable?
YES
FOMC statistically and visually acceptable?
YES
Back-calculate DT50 from DT90 for FOMC (DT50 = DT90 / 3.32)
Case-by-case decision (see text)
NO
YES
Use SFO DT50 (modified fitting routines) for fate modelling
NO
Bi-phasic pattern? (assess experimental
artefacts!)
SFO statistically and visually acceptable?
YES
Case-by-case decision (see text)
NO
STEP 2:Correction procedure
Aim: modelling metabolite fate linked to
parent?
see text
YES
YES
Page 6
Time(days)
Obs.(% AR)
Calc.(% AR)
00
22
77
1414
2121
2929
4545
6464
8989
119119
96.7105.0
83.397.5
81.987.2
46.343.1
35.236.5
24.519.7
9.89.3
4.13.0
1.11.6
0.30.2
EXAMPLE 1 - SFO
Parameter Optimized value
Standard error
Different than 0 by
t-test?
M0
k
Not required
Endpoint Value(days)
DT50
DT90
Fitting statistic Value(%)
2 error (%)
Page 7
EXAMPLE 1 - SFO
0 20 40 60 80 100 120
t (days)
0
20
40
60
80
100
% A
R
-15
-10
-5
0
5
10
15
0 10 20 30 40 50 60 70 80 90 100 110 120
t (days)
Res
idu
al (
Cal
cula
ted
- M
easu
red
)
Draw the fitted line to the observed data points.
Does the fitted line adequately describe the data?
Are there obvious over or under predictions?
Does the line cross the y-axis near the Day 0 data?
Other comments?
Draw in the residual points (approximate).
Do the residuals have a distinct pattern?
Are most of the residual points above or below 0?
Are the residual magnitudes large?
Other comments?
Page 8
Time(days)
Obs.(% AR)
Calc.(% AR)
00
22
77
1414
2121
2929
4545
6464
8989
119119
96.7105.0
83.397.5
81.987.2
46.343.1
35.236.5
24.519.7
9.89.3
4.13.0
1.11.6
0.30.2
EXAMPLE 1 - FOMC
Parameter Optimized value
Standard error
Different than 0 by
t-test?
M0
alpha
beta
Not required
Not required
Not required
Endpoint Value(days)
DT50
DT90
Fitting statistic Value(%)
2 error (%)
Page 9
EXAMPLE 1 - FOMC
0 20 40 60 80 100 120
t (days)
0
20
40
60
80
100
% A
R
-15
-10
-5
0
5
10
15
0 10 20 30 40 50 60 70 80 90 100 110 120
t (days)
Res
idu
al (
Cal
cula
ted
- M
easu
red
)
Draw the fitted line to the observed data points.
Does the fitted line adequately describe the data?
Are there obvious over or under predictions?
Does the line cross the y-axis near the Day 0 data?
Other comments?
Draw in the residual points (approximate).
Do the residuals have a distinct pattern?
Are most of the residual points above or below 0?
Are the residual magnitudes large?
Other comments?
26-27 Jan 2005 Page 10
FOCUS Kinetics training workshop
Conclusions – Example 1
Triggers flowchart
Most appropriate kinetic model (SFO, FOMC, other):
Most appropriate endpoint values (days): DT50 = DT90 =
Modelling flowchart
Most appropriate kinetic model (SFO, FOMC, other):
Most appropriate endpoint value (days): DT50 =
Page 11
Time(days)
Obs.(% AR)
Calc.(% AR)
00
11
33
77
1414
2828
4242
6161
9191
118118
96.7102.5
71.278.6
51.069.4
42.741.5
28.522.4
18.614.3
10.38.4
6.35.6
6.02.8
2.93.0
EXAMPLE 2 - SFO
Parameter Optimized value
Standard error
Different than 0 by
t-test?
M0
k
Not required
Endpoint Value(days)
DT50
DT90
Fitting statistic Value(%)
2 error (%)
Page 12
EXAMPLE 2- SFO
-15
-10
-5
0
5
10
15
0 10 20 30 40 50 60 70 80 90 100 110 120
t (days)
Res
idu
al (
Cal
cula
ted
- M
easu
red
)
Draw the fitted line to the observed data points.
Does the fitted line adequately describe the data?
Are there obvious over or under predictions?
Does the line cross the y-axis near the Day 0 data?
Other comments?
Draw in the residual points (approximate).
Do the residuals have a distinct pattern?
Are most of the residual points above or below 0?
Are the residual magnitudes large?
Other comments?
0 20 40 60 80 100 120
t (days)
0
10
20
30
40
50
60
70
80
90
100
% A
R
Page 13
Time(days)
Obs.(% AR)
Calc.(% AR)
00
11
33
77
1414
2828
4242
6161
9191
118118
96.7102.5
71.278.6
51.069.4
42.741.5
28.522.4
18.614.3
10.38.4
6.35.6
6.02.8
2.93.0
EXAMPLE 2 - FOMC
Parameter Optimized value
Standard error
Different than 0 by
t-test?
M0
alpha
beta
Not required
Not required
Not required
Endpoint Value(days)
DT50
DT90
Fitting statistic Value(%)
2 error (%)
Page 14
EXAMPLE 2- FOMC
-15
-10
-5
0
5
10
15
0 10 20 30 40 50 60 70 80 90 100 110 120
t (days)
Res
idu
al (
Cal
cula
ted
- M
easu
red
)
Draw the fitted line to the observed data points.
Does the fitted line adequately describe the data?
Are there obvious over or under predictions?
Does the line cross the y-axis near the Day 0 data?
Other comments?
Draw in the residual points (approximate).
Do the residuals have a distinct pattern?
Are most of the residual points above or below 0?
Are the residual magnitudes large?
Other comments?
0 20 40 60 80 100 120
t (days)
0
10
20
30
40
50
60
70
80
90
100
% A
R
Page 15
Time(days)
Obs.(% AR)
Calc.(% AR)
00
11
33
77
1414
2828
4242
6161
9191
118118
96.7102.5
71.278.6
51.069.4
42.741.5
28.522.4
18.614.3
10.38.4
6.35.6
6.02.8
2.93.0
EXAMPLE 2 - DFOP
Parameter Optimized value
Standard error
Different than 0 by
t-test?
M0
g
k1
k2
Not required
Not required
Endpoint Value(days)
DT50
DT90
DT50 fast phase
DT50 slow phase
Fitting statistic Value(%)
2 error (%)
Page 16
EXAMPLE 2- DFOP
-15
-10
-5
0
5
10
15
0 10 20 30 40 50 60 70 80 90 100 110 120
t (days)
Res
idu
al (
Cal
cula
ted
- M
easu
red
)
Draw the fitted line to the observed data points.
Does the fitted line adequately describe the data?
Are there obvious over or under predictions?
Does the line cross the y-axis near the Day 0 data?
Other comments?
Draw in the residual points (approximate).
Do the residuals have a distinct pattern?
Are most of the residual points above or below 0?
Are the residual magnitudes large?
Other comments?
0 20 40 60 80 100 120
t (days)
0
10
20
30
40
50
60
70
80
90
100
% A
R
26-27 Jan 2005 Page 17
FOCUS Kinetics training workshop
Conclusions – Example 2
Triggers flowchart
Most appropriate kinetic model (SFO, FOMC, other):
Most appropriate endpoint values (days): DT50 = DT90 =
Modelling flowchart
Most appropriate kinetic model (SFO, FOMC, other):
Most appropriate endpoint value (days): DT50 =
Page 18
Time(days)
Obs.(% AR)
Calc.(% AR)
0
7
14
28
56
84
112
292
380
91.5
64.1
53.6
68.8
25.6
14.0
18.6
1.2
0.04
EXAMPLE 3 - SFO
Parameter Optimized value
Standard error
Different than 0 by
t-test?
M0
k
Not required
Endpoint Value(days)
DT50
DT90
Fitting statistic Value(%)
2 error (%)
Page 19
EXAMPLE 3 - SFODraw the fitted line to the observed data points.
Does the fitted line adequately describe the data?
Are there obvious over or under predictions?
Does the line cross the y-axis near the Day 0 data?
Other comments?
Draw in the residual points (approximate).
Do the residuals have a distinct pattern?
Are most of the residual points above or below 0?
Are the residual magnitudes large?
Other comments?
0 50 100 150 200 250 300 350 400
t (days)
0
10
20
30
40
50
60
70
80
90
100
% A
R
-20
-15
-10
-5
0
5
10
15
20
0 50 100 150 200 250 300 350 400
t (days)
Res
idu
al (
Cal
cula
ted
- M
easu
red
)
Page 20
Time(days)
Obs.(% AR)
Calc.(%AR)
0
7
14
28
56
84
112
292
380
91.5
64.1
53.6
68.8
25.6
14.0
18.6
1.2
0.04
EXAMPLE 3 - FOMC
Parameter Optimized value
Standard error
Different than 0 by
t-test?
M0
alpha
beta
Not required
Not required
Not required
Endpoint Value(days)
DT50
DT90
Fitting statistic Value(%)
2 error (%)
Page 21
EXAMPLE 3 - FOMCDraw the fitted line to the observed data points.
Does the fitted line adequately describe the data?
Are there obvious over or under predictions?
Does the line cross the y-axis near the Day 0 data?
Other comments?
Draw in the residual points (approximate).
Do the residuals have a distinct pattern?
Are most of the residual points above or below 0?
Are the residual magnitudes large?
Other comments?
0 50 100 150 200 250 300 350 400
t (days)
0
10
20
30
40
50
60
70
80
90
100
% A
R
-20
-15
-10
-5
0
5
10
15
20
0 50 100 150 200 250 300 350 400
t (days)
Res
idu
al (
Cal
cula
ted
- M
easu
red
)
26-27 Jan 2005 Page 22
FOCUS Kinetics training workshop
Conclusions – Example 3
Triggers flowchart
Most appropriate kinetic model (SFO, FOMC, other):
Most appropriate endpoint values (days): DT50 = DT90 =
Modelling flowchart
Most appropriate kinetic model (SFO, FOMC, other):
Most appropriate endpoint value (days): DT50 =