Présentation PosterInternational audienceOne goal of the Comprehensive in vitro ProArrhythmia Assay initiative is to predict more accurately potentially torsadogenic compounds in an earlier stage of drug development. To that aim one of the CiPA component is to assess capabilities of label-free in vitro assays (impedance and extracellular field potential signals) applied to human stem cell-derived cardiomyocytes

Atienzar, Franck

Bastogne, Thierry

Batista, Levy

Delaunois, Annie

Valentin, Jean-Pierre

INRIA a CCSD electronic archive server

HAL Id: hal-01670012https://hal.archives-ouvertes.fr/hal-01670012Submitted on 21 Dec 2017HAL is a multi-disciplinary open accessarchive for the deposit and dissemination of sci-entific research documents, whether they are pub-lished or not. The documents may come fromteaching and research institutions in France orabroad, or from public or private research centers.L’archive ouverte pluridisciplinaire HAL, estdestinée au dépôt et à la diffusion de documentsscientifiques de niveau recherche, publiés ou non,émanant des établissements d’enseignement et derecherche français ou étrangers, des laboratoirespublics ou privés.A data-driven modeling method to analyzecardiomyocyte impedance dataLevy Batista, Thierry Bastogne, Franck Atienzar, Annie Delaunois,Jean-Pierre ValentinTo cite this version:Levy Batista, Thierry Bastogne, Franck Atienzar, Annie Delaunois, Jean-Pierre Valentin. A data-driven modeling method to analyze cardiomyocyte impedance data. Safety Pharmacology Society2017 Annual Meeting, SPS 2017, Sep 2017, Berlin, Germany. ￿hal-01670012￿ A data-driven modeling method to analyze cardiomyocyte impedance data L. BATISTA1,2,3, T. BASTOGNE1,2,3 , F. ATIENZAR4, A. DELAUNOIS4, J.-P. VALENTIN4 1CRAN, 2INRIA BIGS, 3CYBERnano, 4UCB 	Background. One goal of the Comprehensive in vitro ProArrhythmia Assay initiative is to predict more accurately potentially torsadogenic compounds in an earlier stage of drug development. To that aim one of the CiPA component is to assess capabilities of label-free in vitro assays (impedance and extracellular field potential signals) applied to human stem cell-derived cardiomyocytes. The proposed solution relies on three main steps. The first one consists in calculating five indicators (FASTI) characterizing the time variations of frequency, amplitude, shape, trends and irregularity of beatings. In a second phase, two summary statistics are proposed to test the concentration effect of compounds on the five FASTI indicators. Finally, results of the previous statistical tests are aggregated in a cardio-effect grade to compare the tested molecules in a cardio-impact scale graduated from 0 (no influence) to 10 (highly disturbed beating). This innovative approach was tested using in vitro data obtained from cell impedance analysis of three known molecules (2 cardiotoxic and 1 non-cardiotoxic compounds). Fig.3: Summary of concentration-effects induced by Famotidine (left), Droperidol (middle) and Sunitinib (right) on mouse cardiomyocytes. A. Global effect scores. Minimum score (0) means that the FASTI parameters are not significantly different compared to control data (cardiomyocytes exposed to 0.1% DMSO). A score of 10 corresponds to severe effects often manifested by a beating arrest of the cardiomyocytes. B. Estimated EC50 value: N.S. for Famotidine and 1.3μM for Sunitinib. C. FASTI indices: blue dots correspond to control values, green dots indicate no significant change w.r.t. control and red dots point out significant changes compared to control data. Results These preliminary results have corroborated the ability of the proposed method to efficiently discriminate the effects of the tested drugs. The main advantage of this approach is that it provides rapid and reliable analysis of complex signals. Median concentrations of the contractility effects have been estimated for the three tested molecules are consistent with the recent publications. Conclusion The proposed solution speeds up the analysis of cardiomyocyte impedance data and allows biologists to quickly know when alterations of the cardiomyocyte contractility occur, which characteristics is disturbed and the concentration responses of tested compounds. In perspective, to confirm the obtained results, the next step will evaluate this new method to a larger batch of molecules. To improve the risk classification efficiency, one main perspective consists in testing the added value brought by coupling the analysis of impedance and field potential signals. Annual Meeting of Safety Pharmacology Society, Berlin, 24-27 Sep. 2017 Fig.2: FASTI indices over time from cardiomyocytes exposed to Famotidine (blue: negative compound) and Sunitinib (red: positive compound) Fig.1Real-time measurement of cardiomyocyte impedance responses (left) and Overview of the method used to analyze the CI data (right) Methods Each cardiomyocyte impedance assay may contain more than 25000 signals recorded with a sampling rate of 77.5Hz during periods of 20s. Therefore, the objective is to automate the processing and analysis of those data to assess contractility effects in early steps of drug development. Objectives Characterization of Cardiomyocyte Impedance ResponsesDouble Normalization ProcessConcentration-Effect AnalysisCritical Effect ScoringFASTI Indicators:        t-Test:               Effect scoreNormalized signalsX(t); X 2 {F,A, S, T, I}; t 2 [0, ..., T   1]Xnn(t); t 2 [0, ..., T   1]E(d); d 2 [1, ..., D](H0 :  (j)X,d = 0H1 :  (j)X,d 6= 0timeCell Index (A.U.)0y ti(k)ti T   1CardiomyocyteImpedanceTrendi-th Cardio Sweepy tj(k)j-th Cardio SweepkkT S A F I T S I A F 100nM   1uM  10uM 100uM012345678910Scores Famotidine (P-Value=0.01)T F A I S10-9 10-8 10-7 10-6 10-5 10-4 10-3 10-2 10-1Concentration012345678910ScoreFamotidineModelDataB00.10.2TS100.20.4S200.10.2F01200.10.2A02400.020.04I00.020.04  0100nM  1uM 10uM100uM00.20.4S  0100nM  1uM 10uM100uM024ACGlobal Effect ScoreTFA I SConcentration 10nM  30nM 100nM 0.3uM   1uM   3uM  10uM  30uM012345678910Scores Sunitinib (P-Value=0.01)T F A I S024TS1024S2024F02040024A051000.51I00.51  0 10nM 30nM100nM0.3uM  1uM  3uM 10uM 30uM024S  0 10nM 30nM100nM0.3uM  1uM  3uM 10uM 30uM0510TFA I SConcentrationGlobal Effect Score10-9 10-8 10-7 10-6 10-5 10-4 10-3 10-2 10-1Concentration012345678910ScoreSunitinib A EC50=1.3e-06ModelDataABCF: Frequency (bpm) A: Peak-to-T rough Amplitude S: Beating Shape T: Cell Impedance Trend I: Beating Irregularity  10nM  30nM 100nM 0.3uM   1uM   3uM  10uM  30uM012345678910Scores droperidol (P-Value=0.01)T F A I S00.51TS1012S200.51F05012A051000.51I00.51  0 10nM 30nM100nM0.3uM  1uM  3uM 10uM 30uM012S  0 10nM 30nM100nM0.3uM  1uM  3uM 10uM 30uM051010-9 10-8 10-7 10-6 10-5 10-4 10-3 10-2 10-1Concentration012345678910Scoredroperidol A EC50=2.3e-06ModelDataABCConcentrationGlobal Effect ScoreT	F	A	I	S	

A data-driven modeling method to analyze cardiomyocyte impedance data

https://hal.archives-ouvertes.fr/hal-01670012/document

A data-driven modeling method to analyze cardiomyocyte impedance data

Abstract

Similar works

Full text

Available Versions

INRIA a CCSD electronic archive server