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Kansas State University College of Veterinary Medicine Mississippi State University College of Veterinary Medicine Virginia-Maryland Regional College of Veterinary Medicine Texas A & M University College of Veterinary Medicine. |
This site demonstrates our approach to evidence based antimicrobial dosing. As such, you should expect that features may change and content will increase with time. Although we believe the current information to be accurate, it is NOT complete and should NOT be used as a guide to therapy at this time .
We encourage you to contact us with questions or comments.
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Absorption Compartment: Abs
Receives Formulation PPG
Absorption Flow [Ka] to Compartment Plasma
Central Compartment: Plasma
Flow [CL0] to Compartment Elim
Elimination Compartment: Elim
1. Abs: Absorption Compartment
Amount Variable: A1
Initial Amount: 0
Outputs:
A1 {unit}
2. CL0: Flow
From: Central Cpt. Plasma
To: Elimination Cpt. Elim
Forward Rate CL0 = K10_variability default(0)
Inputs:
F = 1
CL0 = K10_variability default(0) {1/h}
3. Concentration: Response
Adherence model: One-coin
Inputs:
i = C default(0)
Dt = 0 {h}
P = 0
Outputs:
Concentration
4. Elim: Elimination Compartment
Amount Variable: A0
Initial Amount: 0
Outputs:
A0 {unit}
5. K10_variability: Continuous Distribution
Units: {1/h}
Type: Lognormal
Level: Subject Parameter
True Mean(x):
sd(x):
Inputs:
mean = 2.8516 {1/h}
sd = 1.7321 {1/h}
mult = 1
lo = -2.34496 {1/h}
hi = 8.04812 {1/h}
Outputs:
K10_variability {1/h}
Comment:
Low and High are plus or minus 3 SD
6. Ka: Flow
From: Absorption Cpt. Abs
To: Central Cpt. Plasma
Forward Rate Ka = Ka_variability default(1)
Inputs:
F = 1
Ka = Ka_variability default(1) {1/h}
7. Ka_variability: Continuous Distribution
Units: {1/h}
Type: Lognormal
Level: Subject Parameter
True Mean(x):
sd(x):
Inputs:
mean = 0.113197 {1/h}
sd = 0.049678 {1/h}
mult = 1
lo = -0.0367128 {1/h}
hi = 0.261356 {1/h}
Outputs:
Ka_variability {1/h}
Comment:
Low and High are plus or minus 3 SD
8. Plasma: Central Compartment
Concentration Variable: C
Initial Concentration: 0
Volume V = Vd_Kg default(1000)
Inputs:
V = Vd_Kg default(1000) {mL}
PlasmaIRate = 0 {unit/h}
Outputs:
A {unit}
C {unit/mL}
9. population: Covariate Distribution Model
Covariates:
Weight: Units {kg}
Sub-Population: Default1
Distribution: Weight
Type: Normal
Mean(x): 100
cv(x)%: 5
Low: 96
High: 104
10. PPG: Formulation
Dose into compartment: Abs
Adherence model: One-coin
Inputs:
Dt = 0 {h}
P = 0
Outputs:
PPG
11. Vd_Kg: Expression
Vd_variability* Weight
Outputs:
Vd_Kg {mL}
12. Vd_variability: Continuous Distribution
Units: {mL/kg}
Type: Lognormal
Level: Subject Parameter
True Mean(x):
sd(x):
Inputs:
mean = 438.443 {mL/kg}
sd = 186.483 {mL/kg}
mult = 1
lo = -121.006 {mL/kg}
hi = 997.892 {mL/kg}
Outputs:
Vd_variability {mL/kg}
Comment:
Low and High are plus or minus 3 SD
|
Parameter {Units} |
Default Value |
|
CL0_F |
1 |
|
Concentration_Dt {h} |
0 |
|
Concentration_P |
0 |
|
K10_variability_hi {1/h} |
8.04812 |
|
K10_variability_lo {1/h} |
-2.34496 |
|
K10_variability_mean {1/h} |
2.8516 |
|
K10_variability_mult |
1 |
|
K10_variability_sd {1/h} |
1.7321 |
|
Ka_F |
1 |
|
Ka_variability_hi {1/h} |
0.261356 |
|
Ka_variability_lo {1/h} |
-0.0367128 |
|
Ka_variability_mean {1/h} |
0.113197 |
|
Ka_variability_mult |
1 |
|
Ka_variability_sd {1/h} |
0.049678 |
|
PlasmaIRate {unit/h} |
0 |
|
PPG_Dt {h} |
0 |
|
PPG_P |
0 |
|
Vd_variability_hi {mL/kg} |
997.892 |
|
Vd_variability_lo {mL/kg} |
-121.006 |
|
Vd_variability_mean {mL/kg} |
438.443 |
|
Vd_variability_mult |
1 |
|
Vd_variability_sd {mL/kg} |
186.483 |
1. if(iSubPop==0) then Weight = normal1(1,100,(100)*(5)/1d2,96,104){kg} endif
2. Temp_00 = lgnMeanSD(1, Vd_variability_mean, Vd_variability_sd, Vd_variability_lo, Vd_variability_hi){mL/kg}
3. Vd_variability = Vd_variability_mult*Temp_00
4. Vd_Kg = Vd_variability*Weight
5. Temp_01 = lgnMeanSD(1, Ka_variability_mean, Ka_variability_sd, Ka_variability_lo, Ka_variability_hi){1/h}
6. Ka_variability = Ka_variability_mult*Temp_01
7. Temp_02 = lgnMeanSD(1, K10_variability_mean, K10_variability_sd, K10_variability_lo, K10_variability_hi){1/h}
8. K10_variability = K10_variability_mult*Temp_02
9. V = Vd_Kg
10. Ka = Ka_variability
11. CL0 = K10_variability
12. C = A/V
13. A1' = -(A1*Ka)
14. A0' = C*V*CL0
15. Concentration_i = C
16. A' = A1*Ka-C*V*CL0
Learn TS2 1-cmpt model
Total number of subjects: 1000
.Number of centers: 1.
Center sizes:
|
Center Number |
Center Name |
Center Size |
|
1 |
Center 1 |
1000 |
Each center has same population: Default1.
Inclusion Criteria
None.
Exclusion Criteria
None.
Lead-in Phase
No lead-in phase.
Study Type: Parallel.
Treatments:
· Treatment Arm 1
Block Randomized allocation.
|
Include |
Treatment Arm |
Allocation Ratio |
Subject Count |
|
Yes |
Treatment Arm 1 |
1 |
1000 |
|
Block Size: |
2 |
|
|
|
Total Subject Count: |
1000 |
||
Treatments used in the study:
|
Treatment Arm |
Drug/Formulation |
Dose |
Schedule |
|
Treatment Arm 1 |
PPG |
15000 unit / kg |
Dose(s) at 0, 12, 24, 36, 48, 60, 72 Hours |
Observations in the study:
|
Response(s) |
Measurement Schedule |
|
Concentration |
Every hr for 84 hours: Sample(s) at: 0Hr every 1 Hours for 85 Hours. |
Follow-up Phase
No follow-up phase.

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Treatments / Observations |
Treatment Arm 1 |
Observations |
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Time / Event |
Week |
Day |
Hour |
Minute |
PPG 15000 unit / kg |
Concentration |
|
Dosing/ Sampling Times |
1 |
1 |
0 |
0 |
X |
X |
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1 |
1 |
1 |
0 |
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1 |
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0 |
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1 |
8 |
0 |
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1 |
1 |
9 |
0 |
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1 |
10 |
0 |
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1 |
11 |
0 |
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12 |
0 |
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1 |
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0 |
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1 |
14 |
0 |
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1 |
15 |
0 |
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1 |
16 |
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1 |
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0 |
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0 |
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0 |
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0 |
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0 |
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X |
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13 |
0 |
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14 |
0 |
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15 |
0 |
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0 |
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0 |
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18 |
0 |
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0 |
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0 |
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23 |
0 |
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10 |
0 |
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11 |
0 |
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12 |
0 |
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14 |
0 |
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0 |
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0 |
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0 |
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8 |
0 |
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4 |
9 |
0 |
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10 |
0 |
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4 |
12 |
0 |
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TimeVal |
Mean of Concentration |
Standard Deviation of Concentration |
CV% of Concentration |
P5 of Concentration |
|
0 |
0 |
0 |
|
0 |
|
1 |
1.60444 |
1.14949 |
71.6444 |
0.425586 |
|
2 |
1.69535 |
1.34973 |
79.6135 |
0.402704 |
|
3 |
1.58018 |
1.3111 |
82.9717 |
0.379286 |
|
4 |
1.43031 |
1.20464 |
84.2224 |
0.350451 |
|
5 |
1.28308 |
1.08491 |
84.5546 |
0.312359 |
|
6 |
1.14786 |
0.97021 |
84.5231 |
0.279064 |
|
7 |
1.02647 |
0.866258 |
84.3922 |
0.244908 |
|
8 |
0.918427 |
0.77415 |
84.2909 |
0.22299 |
|
9 |
0.822584 |
0.693298 |
84.2829 |
0.200774 |
|
10 |
0.737635 |
0.622557 |
84.3991 |
0.179317 |
|
11 |
0.662319 |
0.560673 |
84.653 |
0.161398 |
|
12 |
0.595486 |
0.506454 |
85.0487 |
0.143524 |
|
13 |
2.14056 |
1.47628 |
68.9671 |
0.617187 |
|
14 |
2.17865 |
1.66923 |
76.6174 |
0.560621 |
|
15 |
2.01642 |
1.61379 |
80.0321 |
0.504023 |
|
16 |
1.82458 |
1.48846 |
81.5783 |
0.452003 |
|
17 |
1.63986 |
1.35003 |
82.3259 |
0.401424 |
|
18 |
1.4711 |
1.21753 |
82.7636 |
0.361314 |
|
19 |
1.31965 |
1.09691 |
83.1215 |
0.324235 |
|
20 |
1.18465 |
0.989317 |
83.5112 |
0.288342 |
|
21 |
1.06459 |
0.89412 |
83.9869 |
0.264738 |
|
22 |
0.957866 |
0.810106 |
84.574 |
0.22926 |
|
23 |
0.862937 |
0.735936 |
85.2827 |
0.20071 |
|
24 |
0.77842 |
0.670335 |
86.1149 |
0.176069 |
|
25 |
2.30753 |
1.56552 |
67.8441 |
0.669071 |
|
26 |
2.3312 |
1.75695 |
75.3668 |
0.611298 |
|
27 |
2.15591 |
1.7003 |
78.8671 |
0.535565 |
|
28 |
1.95224 |
1.57317 |
80.5827 |
0.477956 |
|
29 |
1.7568 |
1.43249 |
81.5395 |
0.435469 |
|
30 |
1.57831 |
1.29745 |
82.205 |
0.394434 |
|
31 |
1.41802 |
1.1741 |
82.7987 |
0.346289 |
|
32 |
1.27498 |
1.06367 |
83.426 |
0.317767 |
|
33 |
1.14761 |
0.965566 |
84.1374 |
0.273684 |
|
34 |
1.03421 |
0.878623 |
84.956 |
0.243067 |
|
35 |
0.933199 |
0.801527 |
85.8902 |
0.209314 |
|
36 |
0.843132 |
0.733026 |
86.9409 |
0.18511 |
|
37 |
2.36717 |
1.59449 |
67.3583 |
0.693395 |
|
38 |
2.3862 |
1.78559 |
74.8297 |
0.627049 |
|
39 |
2.20667 |
1.72944 |
78.3732 |
0.552797 |
|
40 |
1.99912 |
1.60263 |
80.1669 |
0.492618 |
|
41 |
1.80012 |
1.46205 |
81.2196 |
0.453817 |
|
42 |
1.61836 |
1.3269 |
81.9905 |
0.404141 |
|
43 |
1.45508 |
1.20327 |
82.6945 |
0.357739 |
|
44 |
1.30929 |
1.0924 |
83.4345 |
0.321141 |
|
45 |
1.17938 |
0.993743 |
84.2595 |
0.277889 |
|
46 |
1.06366 |
0.906144 |
85.191 |
0.245937 |
|
47 |
0.96051 |
0.828315 |
86.2369 |
0.213943 |
|
48 |
0.868472 |
0.759019 |
87.3971 |
0.188605 |
|
49 |
2.3907 |
1.60487 |
67.13 |
0.699955 |
|
50 |
2.40805 |
1.7959 |
74.579 |
0.629635 |
|
51 |
2.22698 |
1.7402 |
78.1417 |
0.562266 |
|
52 |
2.018 |
1.6138 |
79.9704 |
0.504827 |
|
53 |
1.81768 |
1.47353 |
81.0665 |
0.454751 |
|
54 |
1.63471 |
1.33859 |
81.8857 |
0.405765 |
|
55 |
1.4703 |
1.21507 |
82.6412 |
0.362169 |
|
56 |
1.32346 |
1.10423 |
83.4346 |
0.321225 |
|
57 |
1.19259 |
1.00552 |
84.3141 |
0.279844 |
|
58 |
1.07598 |
0.917818 |
85.3009 |
0.246044 |
|
59 |
0.971998 |
0.839826 |
86.402 |
0.215288 |
|
60 |
0.879192 |
0.770324 |
87.6173 |
0.189176 |
|
61 |
2.4007 |
1.6088 |
67.0138 |
0.704474 |
|
62 |
2.4174 |
1.79982 |
74.4527 |
0.632191 |
|
63 |
2.23571 |
1.74439 |
78.0238 |
0.568344 |
|
64 |
2.02616 |
1.61826 |
79.868 |
0.508362 |
|
65 |
1.82532 |
1.47821 |
80.9837 |
0.459022 |
|
66 |
1.64185 |
1.34344 |
81.8251 |
0.407563 |
|
67 |
1.47698 |
1.22005 |
82.6047 |
0.364179 |
|
68 |
1.32972 |
1.1093 |
83.4236 |
0.321236 |
|
69 |
1.19845 |
1.01065 |
84.3295 |
0.280454 |
|
70 |
1.08147 |
0.922961 |
85.3433 |
0.247986 |
|
71 |
0.977144 |
0.844957 |
86.4721 |
0.215635 |
|
72 |
0.884016 |
0.775416 |
87.7152 |
0.189321 |
|
73 |
2.40523 |
1.61032 |
66.951 |
0.708022 |
|
74 |
2.42165 |
1.80135 |
74.3852 |
0.633125 |
|
75 |
2.2397 |
1.74606 |
77.9599 |
0.570149 |
|
76 |
2.0299 |
1.62009 |
79.811 |
0.50848 |
|
77 |
1.82883 |
1.48017 |
80.9356 |
0.459939 |
|
78 |
1.64515 |
1.34552 |
81.7874 |
0.409362 |
|
79 |
1.48008 |
1.22223 |
82.5784 |
0.364919 |
|
80 |
1.33264 |
1.11155 |
83.4095 |
0.321238 |
|
81 |
1.2012 |
1.01295 |
84.3283 |
0.280649 |
|
82 |
1.08405 |
0.925296 |
85.3556 |
0.2499 |
|
83 |
0.979573 |
0.847313 |
86.4983 |
0.215653 |
|
84 |
0.886302 |
0.77778 |
87.7556 |
0.189556 |

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