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Pharmaceutical Research

, Volume 32, Issue 10, pp 3391–3402 | Cite as

Application of Adaptive DP-optimality to Design a Pilot Study for a Clotting Time Test for Enoxaparin

  • Abhishek Gulati
  • James M. Faed
  • Geoffrey K. Isbister
  • Stephen B. Duffull
Research Paper

Abstract

Purpose

Dosing of enoxaparin, like other anticoagulants, may result in bleeding following excessive doses and clot formation if the dose is too low. We recently showed that a factor Xa based clotting time test could potentially assess the effect of enoxaparin on the clotting system. However, the test did not perform well in subsequent individuals and effectiveness of an exogenous phospholipid, Actin FS, in reducing the variability in the clotting time was assessed. The aim of this work was to conduct an adaptive pilot study to determine the range of concentrations of Xa and Actin FS to take forward into a proof-of-concept study.

Methods

A nonlinear parametric function was developed to describe the response surface over the factors of interest. An adaptive method was used to estimate the parameters using a D-optimal design criterion. In order to provide a reasonable probability of observing a success of the clotting time test, a P-optimal design criterion was incorporated using a loss function to describe the hybrid DP-optimality.

Results

The use of adaptive DP-optimality method resulted in an efficient estimation of model parameters using data from only 6 healthy volunteers. The use of response surface modelling identified a range of sets of Xa and Actin FS concentrations, any of which could be used for the proof-of-concept study.

Conclusions

This study shows that parsimonious adaptive DP-optimal designs may provide both precise parameter estimates for response surface modelling as well as clinical confidence in the potential benefits of the study.

KEY WORDS

Adaptive design DP-optimal design Response surface modelling enoxaparin factor Xa 

Abbreviations

ACS

Acute coronary syndrome

aPTT

Activated partial thromboplastin time

AT

Antithrombin

BSV

Between subject variability

CT

Clotting time

DVT

Deep vein thrombosis

LMWH

Low molecular weight heparin

PE

Pulmonary embolism

PT

Prothrombin time

RE

Relative error

TenaCT

Ten-a clotting time

TT

Thrombin time

UFH

Unfractionated heparin

VTE

Venous thromboembolism

Variables and Symbols

g

Unit of acceleration

j

Index for a parameter

J

Jacobian matrix

k

Index for iteration

KD

Affinity constant

MF

Fisher information matrix

|MF(⋅)|

Determinant of the Fisher information matrix

p

Total number of parameters

T

Transpose

U

Utility function

ξ0

Initial design

ξD*

D-optimal design

ξDP*

DP-optimal design

β

Any parameter in a model

\( \widehat{\beta} \)

Estimate of any parameter in a model

\( \overline{\beta} \)

Mean of any parameter in a model

β

Vector of parameters in the model

\( \widehat{\boldsymbol{\upbeta}} \)

Vector of the estimated parameters

Σ

Covariance of the residual error

Notes

ACKNOWLEDGMENTS AND DISCLOSURES

The authors acknowledge the support of University of Otago Postgraduate Scholarship and the University of Otago Research Grant 2011.

Supplementary material

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Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • Abhishek Gulati
    • 1
    • 2
  • James M. Faed
    • 3
  • Geoffrey K. Isbister
    • 4
  • Stephen B. Duffull
    • 2
  1. 1.Division of Clinical PharmacologyIndiana University School of MedicineIndianapolisUSA
  2. 2.School of PharmacyUniversity of OtagoDunedinNew Zealand
  3. 3.Department of Pathology, School of MedicineUniversity of OtagoDunedinNew Zealand
  4. 4.School of Medicine and Public HealthUniversity of NewcastleNewcastleAustralia

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