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Analysis of Zidovudine pharmacokinetics to determine whether there is a genetic component to the variability and to determine the bioequivalence of seven formulations
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Angelina Fahmay
AZT Case study
1) Involving 100mg AZT: 24 healthy subjects (12 Female, 12 Male) Weights of healthy subjects (Range: 50-77kg) (Average: 62kg) Given FOUR different oral formulations of 100mg of AZT at
SEVEN day intervals ONE reference and THREE generics (Oral) Blood samples collected after: 0, 0.25, 0.5, 0.75, 1, 1.5, 2, 2.5, 3, 4, 5,
6, 8h
2) Involving a combination of 300mg AZT + Lamivudine: Another/different set of 24 healthy subjects (12 Female, 12 Male) Weights of healthy subjects (Range: 51.5 – 82.8 kg) (Average: 64kg) Given THREE different oral formulations of the combination at
SEVEN day intervals ONE reference and TWO generics (Oral) Blood samples collected after: 0, 0.25, 0.5, 0.75, 1, 1.5, 2, 3, 4, 6,
9, 12h
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Research questions
Is the pharmacokinetic variability seen in the AZT data likely to be due to a genetic component? Model the data using NONMEM VII (Non Linear Mixed Effects
Modeling) Compute the genetic component coefficient (RGC) Between
Occasion Variability (BOV) and Between Subject Variability (BSV) for clearance to look for possible genetic association
Does compartmental modeling and non-compartmental analysis produce similar results in a bioequivalence study of AZT data? Perform a non-compartmental analysis (R software) Use a compartmental modeling approach to estimate
bioavailability
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Zidovudine
Zidovudine also known as azidothymidine (AZT)
Synthesized in 1964 by Jerome P.Horwitz as a potential anti-cancer drug
First Anti-HIV drug
Nucleoside reverse transcriptase inhibitor (NRTI)
Chemically known as: 3’-azido-3’-deoxythymidine
An analogue to the nucleoside deoxythymidine triphosphate (dTTP)
The difference in structure that causes chain termination is that AZT lacks a hydroxyl group on the 3’ of the deoxyribose sugar moiety and instead contains an azido group
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Mode of action of AZT
Zidovudine activated by cellular kinases Zidovudine triphosphate
Zidovudine triphosphate acts as a competitive inhibitor for reverse transcriptase in the place of deoxythymidine triphosphate (dTTP) i.e. nucleoside analogue
Zidovudine triphosphate is then incorporated into the growing viral DNA chain chain termination occurs
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Plots of Raw data using R created
Individual plots using ID column (an individual plot for each of the 48 subjects)
Individual plots using PID column (an individual plot for each formulation for each patient)
A plot of all the data (all 48 healthy subjects)
A plot for each formulation (i.e. 1-7)
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Plots of the Raw data using R
Concentration vs. time plots for formulation 1- 4 for 100mg AZT data
Concentration vs. time plots for formulation 1- 3 for 300mg AZT + 5TC data
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NONMEM models
Omega fixed
Omega on Cl
Omega on Cl, V
Omega on Cl, V, Ka
Omega on LAG
LAG theta 0.2
LAG theta 0.5
BLQ values included
Omega on Cl, V, Ka, LAG
2 Comp
Omega on Cl, V, LAG
PID into ID
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Final model : 8h
RUN MIN OBJ ClearanceVolume of
distributionAbsorption
rate constantLAG time
Proportional error
Additive error
Form 2 Form 3 Form 4 Form 2 Form 3
100mg 100mg 100mg 300mg 300mg
8h ✓ 16922.354 150 173 1130 0.249 0.398 6.6 -0.0231 0.176 -0.597 -0.0211 0.159
• ID column used (ID ranged from1-48)• 1 compartment• Omega on Ka fixed• Dataset: Includes both 100mg + 300mg data• M3 method used for BLQ• LOQ = 3• Weight added as a covariate for clearance and volume of
distribution• Bioequivalence• BOV on clearance was added25.05.12 9
BLQ
11.11% of the 1944 observations had a concentration of AZT in plasma below the LOQ
0.25 0.5 5 6 8 9 120.00%
2.00%
4.00%
6.00%
8.00%
10.00%
12.00%%BLQ
Sampling Time (hr)
%B
LQ
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Weight as a covariate on Clearance and Volume of Distribution
A plot to show the relationship between weight and clearance (eta 1) / volume of distribution (eta 2), respectively, in run8g.mod i.e. before weight was added as a covariate
A plot to show the relationship between weight and clearance (eta 1) / volume of distribution (eta 2), respectively, in run8h.mod i.e. after weight was added as a covariate
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Goodness of Fit Plots
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Visual Predictive Check
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BIOEQUIVALENCE STUDY
Run Form 4/1 (100mg) Dataset8d 0.00341 100mg dataset used only Bioequivalence 8e - 300mg dataset ued only Bioequivalence 8f -0.511 100mg + 300mg Bioequivalence 8g -0.518 100mg + 300mg BOV and BSV8h -0.597 100mg + 300mg Weight added to Cl + V 40.30
%
100.341%
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Bioequivalence for each of the 7 formulations using Non-compartmental and compartmental analysis
Comparison of bioequivalence for formulation 4 throughout final set of model runs
Genetic component on clearance
RGCCL= 1 – (0.00867/0.047) = 0.8155 (to 4 sig fig)
BSV GREATER than BOV
σ2 = Between occasion variance (BOV) ω2 = Between subject variance (BSV)
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Metabolism of Zidovudine
ZIDOVUDINEAMT
GAMT
GAZT
UGT 3 potential N-glycosylation sites in UGT2B7 (asparagine at positions 67, 68 and 315
Genetic polymorphism of the UGT2B7 enzyme is proven to NOT be significant
Decrease the affinity of AZT for glucurinodation.
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