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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