A general procedure to select calibration drugs for lab-specific validation and calibration of proarrhythmia risk prediction models: An illustrative example using the CiPA model
| Autor: | Søren Friis, Jiansong Sheng, Tim Strassmaier, David G. Strauss, Tom A. Goetze, Wendy W. Wu, Zhihua Li, Phu N. Tran, Sonja Stoelzle-Feix, Maria Giustina Rotordam, Yuri A. Kuryshev, James Kramer, Xiaomei Han, Nina Brinkwirth, George Okeyo, Caiyun Wu, Bradley J. Ridder, Markus Rapedius, Nadine Becker, Mohammadreza Samieegohar, Aaron Randolph |
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| Rok vydání: | 2020 |
| Předmět: |
Drug-Related Side Effects and Adverse Reactions
Computer science Calibration (statistics) Model prediction Drug Evaluation Preclinical 030204 cardiovascular system & hematology Toxicology Machine learning computer.software_genre Risk prediction models 030226 pharmacology & pharmacy Electrocardiography 03 medical and health sciences 0302 clinical medicine medicine Humans Myocytes Cardiac Sensitivity (control systems) Pharmacology Proarrhythmia business.industry Arrhythmias Cardiac medicine.disease Pharmaceutical Preparations Calibration Biological Assay Model implementation Artificial intelligence business computer |
| Zdroj: | Journal of Pharmacological and Toxicological Methods. 105:106890 |
| ISSN: | 1056-8719 |
| DOI: | 10.1016/j.vascn.2020.106890 |
| Popis: | Introduction In response to the ongoing shift of the regulatory cardiac safety paradigm, a recent White Paper proposed general principles for developing and implementing proarrhythmia risk prediction models. These principles included development strategies to validate models, and implementation strategies to ensure a model developed by one lab can be used by other labs in a consistent manner in the presence of lab-to-lab experimental variability. While the development strategies were illustrated through the validation of the model under the Comprehensive In vitro Proarrhythmia Assay (CiPA), the implementation strategies have not been adopted yet. Methods The proposed implementation strategies were applied to the CiPA model by performing a sensitivity analysis to identify a subset of calibration drugs that were most critical in determining the classification thresholds for proarrhythmia risk prediction. Results The selected calibration drugs were able to recapitulate classification thresholds close to those calculated from the full list of CiPA drugs. Using an illustrative dataset it was shown that a new lab could use these calibration drugs to establish its own classification thresholds (lab-specific calibration), and verify that the model prediction accuracy in the new lab is comparable to that in the original lab where the model was developed (lab-specific validation). Discussion This work used the CiPA model as an example to illustrate how to adopt the proposed model implementation strategies to select calibration drugs and perform lab-specific calibration and lab-specific validation. Generic in nature, these strategies could be generally applied to different proarrhythmia risk prediction models using various experimental systems under the new paradigm. |
| Databáze: | OpenAIRE |
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