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. 2018 Sep;11(5):498-505.
doi: 10.1111/cts.12560. Epub 2018 Jun 7.

Prediction of Safety Margin and Optimization of Dosing Protocol for a Novel Antibiotic using Quantitative Systems Pharmacology Modeling

Jeffrey L Woodhead  1 , Franziska Paech  2 , Martina Maurer  3 , Marc Engelhardt  3 , Anne H Schmitt-Hoffmann  3 , Jochen Spickermann  3 , Simon Messner  4 , Mathias Wind  3 , Anne-Therese Witschi  3 , Stephan Krähenbühl  2 , Scott Q Siler  1 , Paul B Watkins  1 , Brett A Howell  1
Affiliations

Prediction of Safety Margin and Optimization of Dosing Protocol for a Novel Antibiotic using Quantitative Systems Pharmacology Modeling

Jeffrey L Woodhead et al. Clin Transl Sci. 2018 Sep.

Abstract

Elevations of liver enzymes have been observed in clinical trials with BAL30072, a novel antibiotic. In vitro assays have identified potential mechanisms for the observed hepatotoxicity, including electron transport chain (ETC) inhibition and reactive oxygen species (ROS) generation. DILIsym, a quantitative systems pharmacology (QSP) model of drug-induced liver injury, has been used to predict the likelihood that each mechanism explains the observed toxicity. DILIsym was also used to predict the safety margin for a novel BAL30072 dosing scheme; it was predicted to be low. DILIsym was then used to recommend potential modifications to this dosing scheme; weight-adjusted dosing and a requirement to assay plasma alanine aminotransferase (ALT) daily and stop dosing as soon as ALT increases were observed improved the predicted safety margin of BAL30072 and decreased the predicted likelihood of severe injury. This research demonstrates a potential application for QSP modeling in improving the safety profile of candidate drugs.

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Figures

Figure 1
Figure 1
Pictorial representation of the workflow for this research, including the processes of determining toxicity parameters from in vitro data, refining those parameters based on clinical data, and extrapolating in order to determine potential safety margin of novel dosing protocols. PK, pharmacokinetic.
Figure 2
Figure 2
DILIsym simulations of BAL‐30072 clinical trials SFM‐CP‐001, SFM‐CP‐002, and SFM‐CP‐003 in the v3B‐1 SimPops (population sample) using the clinically optimized toxicity parameters. ALT, alanine aminotransferase; ULN, upper limit of normal.
Figure 3
Figure 3
DILIsym simulations of prospective BAL30072 dosing protocols including 750 and 1,000 mg t.i.d. given over 4 hours in the SimPops version 3B‐1 (population sample) using the clinically optimized toxicity parameters. The alanine aminotransferase (ALT) dose stopping criterion was included in the simulations.
Figure 4
Figure 4
DILIsym simulations of BAL30072 in SimPops version 3B‐1 administered t.i.d. over 4 hours at escalating non‐weight‐adjusted doses to estimate the margin of safety for BAL30072 with respect to liver. BAL30072 doses were simulated at low, median, and high levels. The alanine aminotransferase (ALT) dose stopping criterion was included in the simulations. The purple brackets represent the dosing range that contains the lowest simulated dose at which DILIsym would predict a Hy's Law case. Outcomes related to hepatic effects, along with the peak plasma concentration (Cmax) range of BAL30072, are shown.
Figure 5
Figure 5
DILIsym simulations of BAL30072 in SimPops version 3B‐1 administered t.i.d. over 4 hours at escalating weight‐adjusted doses to estimate the margin of safety for BAL30072 with respect to liver. BAL30072 doses were simulated at low, median, and high levels. The alanine aminotransferase (ALT) dose stopping criterion was included in the simulations. The purple brackets represent the dosing range that contains the lowest simulated dose at which DILIsym would predict a Hy's Law case. Outcomes related to hepatic effects, along with the peak plasma concentration (Cmax) range of BAL30072, are shown.
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References

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