<p>PK-QTc analyses are routinely done as part of most drug development programs. Usually, the PK concentration of a single compound is related to the QTc effect. However, in many instances there are several active compounds, for example a parent drug and its metabolite, or combination drugs. Previous authors have shown that doing separate PK-QTc analyses for each of the potentially active compounds may lead to biased results, and recommended to do joint modeling of the impact of both compounds on the corrected QT interval. In this paper we go one step further and propose a formal hypothesis test to exclude a <InlineEquation ID="IEq1"> <EquationSource Format="TEX">\(\varvec{10} \,\)</EquationSource> </InlineEquation>msec effect based on a joint modeling approach when there are potentially two active compounds. In analogy to the situation with just one active compound, where the upper limit of a <InlineEquation ID="IEq2"> <EquationSource Format="TEX">\(\varvec{90}\)</EquationSource> </InlineEquation>% confidence interval for <InlineEquation ID="IEq3"> <EquationSource Format="TEX">\(\varvec{\vartheta C}_{\varvec{max}}\)</EquationSource> </InlineEquation> (with <InlineEquation ID="IEq4"> <EquationSource Format="TEX">\(\varvec{\vartheta }\)</EquationSource> </InlineEquation> being the slope of a linear exposure-response relationship and <InlineEquation ID="IEq5"> <EquationSource Format="TEX">\(\varvec{C}_{\varvec{max}}\)</EquationSource> </InlineEquation> being the expected maximum concentration of some supra-therapeutic dose) needs to be below <InlineEquation ID="IEq6"> <EquationSource Format="TEX">\(\varvec{10} \,\)</EquationSource> </InlineEquation>msec, we use the upper confidence intervals for <InlineEquation ID="IEq7"> <EquationSource Format="TEX">\(\varvec{\vartheta }_{\varvec{1}} \varvec{C}_{\varvec{1,max}}\)</EquationSource> </InlineEquation>, <InlineEquation ID="IEq8"> <EquationSource Format="TEX">\(\varvec{\vartheta }_{\varvec{2}} \varvec{C}_{\varvec{2,max}}\)</EquationSource> </InlineEquation>, and <InlineEquation ID="IEq9"> <EquationSource Format="TEX">\(\varvec{\vartheta }_{\varvec{1}} \varvec{C}_{\varvec{1,max}} \varvec{+} \varvec{\vartheta }_{\varvec{2}} \varvec{C}_{\varvec{2,max}}\)</EquationSource> </InlineEquation> and exclude a <InlineEquation ID="IEq10"> <EquationSource Format="TEX">\(\varvec{10} \,\)</EquationSource> </InlineEquation>msec effect if all three upper confidence limits are below the <InlineEquation ID="IEq11"> <EquationSource Format="TEX">\(\varvec{10} \,\)</EquationSource> </InlineEquation>msec threshold. We propose a bootstrap approach for decision making, and show via simulations that this approach controls the type I error of <InlineEquation ID="IEq12"> <EquationSource Format="TEX">\(\varvec{5}\)</EquationSource> </InlineEquation>%. We focus on the situation where exposure-response is linear in both compounds, but also indicate how this can be extended to non-linear situations.</p>

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Concentration response analyses for QT data with several active compounds

  • Günter Heimann,
  • Giulia Lestini,
  • Jochen Zisowsky

摘要

PK-QTc analyses are routinely done as part of most drug development programs. Usually, the PK concentration of a single compound is related to the QTc effect. However, in many instances there are several active compounds, for example a parent drug and its metabolite, or combination drugs. Previous authors have shown that doing separate PK-QTc analyses for each of the potentially active compounds may lead to biased results, and recommended to do joint modeling of the impact of both compounds on the corrected QT interval. In this paper we go one step further and propose a formal hypothesis test to exclude a \(\varvec{10} \,\) msec effect based on a joint modeling approach when there are potentially two active compounds. In analogy to the situation with just one active compound, where the upper limit of a \(\varvec{90}\) % confidence interval for \(\varvec{\vartheta C}_{\varvec{max}}\) (with \(\varvec{\vartheta }\) being the slope of a linear exposure-response relationship and \(\varvec{C}_{\varvec{max}}\) being the expected maximum concentration of some supra-therapeutic dose) needs to be below \(\varvec{10} \,\) msec, we use the upper confidence intervals for \(\varvec{\vartheta }_{\varvec{1}} \varvec{C}_{\varvec{1,max}}\) , \(\varvec{\vartheta }_{\varvec{2}} \varvec{C}_{\varvec{2,max}}\) , and \(\varvec{\vartheta }_{\varvec{1}} \varvec{C}_{\varvec{1,max}} \varvec{+} \varvec{\vartheta }_{\varvec{2}} \varvec{C}_{\varvec{2,max}}\) and exclude a \(\varvec{10} \,\) msec effect if all three upper confidence limits are below the \(\varvec{10} \,\) msec threshold. We propose a bootstrap approach for decision making, and show via simulations that this approach controls the type I error of \(\varvec{5}\) %. We focus on the situation where exposure-response is linear in both compounds, but also indicate how this can be extended to non-linear situations.