Quantitative approach for cardiac risk assessment and interpretation in tuberculosis drug development View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2018-06

AUTHORS

Sebastian Polak, Klaus Romero, Alexander Berg, Nikunjkumar Patel, Masoud Jamei, David Hermann, Debra Hanna

ABSTRACT

Cardiotoxicity is among the top drug safety concerns, and is of specific interest in tuberculosis, where this is a known or potential adverse event of current and emerging treatment regimens. As there is a need for a tool, beyond the QT interval, to quantify cardiotoxicity early in drug development, an empirical decision tree based classifier was developed to predict the risk of Torsades de pointes (TdP). The cardiac risk algorithm was developed using pseudo-electrocardiogram (ECG) outputs derived from cardiac myocyte electromechanical model simulations of increasing concentrations of 96 reference compounds which represented a range of clinical TdP risk. The algorithm correctly classified 89% of reference compounds with moderate sensitivity and high specificity (71 and 96%, respectively) as well as 10 out of 12 external validation compounds and the anti-TB drugs moxifloxacin and bedaquiline. The cardiac risk algorithm is suitable to help inform early drug development decisions in TB and will evolve with the addition of emerging data. More... »

PAGES

457-467

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s10928-018-9580-2

DOI

http://dx.doi.org/10.1007/s10928-018-9580-2

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1101391898

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/29520534


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