This Clark_Proarrhythmia_2022_README.txt file was generated on 20220621 by Alexander P. Clark ## Data in support of: An in silico-in vitro pipeline for drug cardiotoxicity screening identifies ionic proarrhythmia mechanisms ### By: Alexander P. Clark, Siyu Wei, Darshan Kalola, Trine Krogh-Madsen, David J. Christini ### Abstract: **Background and Purpose:** Before advancing to clinical trials, new drugs are screened for their proarrhythmic potential using a method that is overly conservative and provides limited mechanistic insight. The shortcomings of this approach can lead to the misclassification of beneficial drugs as proarrhythmic.
**Experimental Approach:** An in silico-in vitro pipeline was developed to circumvent these shortcomings. A computational human induced pluripotent stem cell-derived cardiomyocyte (iPSC-CMs) model was used as part of a genetic algorithm to design experiments, specifically electrophysiological voltage-clamp (VC) protocols, to identify which of several cardiac ion channels were blocked during in vitro drug studies. Such VC data, along with dynamically clamped action potentials (AP), were acquired from iPSC-CMs before and after treatment with a control solution or a low- (verapamil), intermediate- (cisapride), or high-risk (quinidine or quinine) drug.
**Key Results:** Significant AP prolongation (a proarrhythmia marker) was seen in response to both high-risk drugs. The VC protocol identified block of IKr (a source of arrhythmias) by all strong IKr blockers, including cisapride, quinidine, and quinine. The protocol also detected block of ICaL by verapamil and Ito by quinidine. Further demonstrating the power of the approach, the VC data uncovered a previously unidentified funny current (If) block by quinine, which was confirmed with experiments using a HEK-293 expression system and automated patch-clamp.
**Conclusion and Implications:** We developed an in silico-in vitro pipeline that simultaneously identifies proarrhythmia risk and mechanism of ion channel-blocking drugs. The approach offers a new tool for evaluating cardiotoxicity in the preclinical drug screening phase. **Subject Keywords:** Arrhythmias, patch-clamp, iPSC-CM, computational modeling **Financial Support:** Research reported in this publication was supported by the National Heart, Lung, And Blood Institute of the National Institutes of Health under Award Number F31HL154655 (to A.C.) and U01HL136297 (to D.J.C.). --- -------------------------- SHARING/ACCESS INFORMATION -------------------------- Licenses/restrictions placed on the data, or limitations of reuse: This dataset is shared under an Attribution 4.0 International (CC BY 4.0) license (https://creativecommons.org/licenses/by/4.0/). The material can be shared and built upon, but attribution to the original authors and a statement of changes made is required. Recommended citation for the data: Alexander P. Clark, Siyu Wei, Darshan Kalola, Trine Krogh-Madsen, David J. Christini. (2022) Data from: An in silico-in vitro pipeline for drug cardiotoxicity screening identifies ionic proarrhythmia mechanisms. [Dataset] Cornell University eCommons Repository. https://doi.org/10.7298/c883-s773 Citation for and links to publications that cite or use the data: Alexander P. Clark, Siyu Wei, Darshan Kalola, Trine Krogh-Madsen, David J. Christini. (2022) An in silico-in vitro pipeline for drug cardiotoxicity screening identifies ionic proarrhythmia mechanisms. Br J Pharmacol (submitted) Links/relationships to ancillary or related code: Clark, A. (2022). Christini-Lab/vc-optimization-cardiotoxicity: Updated CSV references (v1.0.1) [Computer software]. Zenodo. https://doi.org/10.5281/ZENODO.6685265 You can use this data to reproduce figures from the paper with code on GitHub, archived in Zenodo (https://doi.org/10.5281/ZENODO.6685265). To do this, place all of the data in `/figures/exp_data`. --- **This dataset contains the following files and folders:** - `ga_results/` – This folder contains the results of genetic algorithm optimizations that were run as a part of this project. The pickle files contain GA results from every generation of the voltage clamp protocol optimizations. The `.csv` files contain the time and voltage data for each current's best voltage protocol (e.g. `/vc_proto_I_*.csv`). - `cells/` – This folder contains the raw data acquired from iPSC-CM experiments in `.h5` format. The file name indicates the date that it was acquired and the name of the drug that was applied to the cell (e.g. `021021_2_control.h5`). These files are used by code in the VC protocol repository. - `ipsc_csv/` – This folder contains `.csv` files with time, voltage, and current information from the iPSC-CM experiments. This data can also be found in the `.h5` files in `cells/`. The data in this folder is used to create all of the statistical analyses throughout the manuscript. - `cell_metadata/` – Information (e.g. capacitance, seal resistance) about each iPSC-CM experiment. The name of these files match the `.h5` file names in the `cells` folder. This data is used by the repository to select the correct trials from the raw `.h5` data. - `hcn_results/` – Raw data from the HCN1 experiments. The `.xls` files contain metadata about the experiment. The `.dat` files were generated by Patchmaster. The code uses this data to create the IV and dose-response curves in the paper. - `hcn_csv/` – IV and dose-response data formatted as `.csv` files. - `cell_stats.csv` – Information about the cells before drug application (e.g. APD90). Below is a list of the columns: - `cell_num` – order that cells were acquired - `file` – name of the corresponding files for a given cell in `cells/`, `cell_meta/`, and `ipsc_csv` - `drug_type` – type of drug used on cell - `vc_*` – total current during the regions of the VC protocol designed to isolate the specified currents - `dvdt_max`, `rmp`, `apa`, `apd*`, `triangulation` – AP feature values - `cell_change_stats.csv` – Change in AP and VC features after drug application for all cells. - `cell_num` – order that cells were acquired - `file` – name of the corresponding files for a given cell in `cells/`, `cell_meta/`, and `ipsc_csv` - `drug_type` – type of drug used on cell - `vc_*` – change, in pA/pF, from pre- to post-drug application during the regions of the VC protocol designed to isolate the specified current - `dvdt_max`, `rmp`, `apa`, `apd*`, `triangulation` – change in these AP features from pre- to post-drug application