predictive toxicology advances through stem cells

Imagination at work.

Applications of human stem cell derived cardiomyocytes for predictive toxicology

Predictive toxicology advances through stem cells

2

Drug development & cardiotoxicityNeed for earlier toxicity testing and improved prediction

businessreview webinar | 19 March 2014

Drug withdrawals for safety reasons

1976-2007

HepatotoxicityNephrotoxicityCardiotoxicityRhabdomyolysisOther

Data from: Wilke et al. Nature Reviews Drug Discovery (2007) 6:904-916

Drug Development Time & Cost

Research

Preclinical

NDA

Clinical

3

Predicting drug toxicityWhere can we do better?


Integration of assays

& endpoints

Kirkland et al. Mutat Res. 2005 584(1-2):1-256

Disparate assays and differing combinations yield varying predictivity

Testing multiple endpoints increases sensitivity but at the expense of specificity

Assay Combinations

Sensitivity

Specificity

Relevance of model systems

Animals ≠ Humans Animal ≠ Animal Cross species testing

may increase false positives

Metabolism & MOA ?

Quantity & robustness of cell

models Primary cells/tissues:

source variability & scale limitations

Immortalized & engineered cells: more abundant, but limited predictivity

Human stem cell derived modelsA way forward for more predictive toxicity testing

businessreview webinar | 19 March 2014 4

Self-renewing

Scalable

Pluripotent

Reproducible

Convenient

5

Stem cell derived human heart cellsIndustrial production of cardiomyocytes (CytivaTM Plus)


Functional Performance Metrics (MEA)

FPD

ISI

Amp

6

CytivaTM Plus CardiomyocytesDifferentiated human cells for safety & efficacy testing


DNA Troponin I a-ActininSpontaneous contractility

7

ElectrophysiologyhERG block Na+ & Ca2+

channels QT prolongation contractility

Cardiomyocytes in drug safety testingIntegrated surveillance across platforms & assays


Patch Clamp

Multi-Electrode Arrays

ImpedanceHigh Content

Imaging

Respiration

Biochemical Analysis

Functional Integritymitochondrial function membrane integrity Ca2+ homeostasis morphology

8

Assessing effects in contextCardiac action potential reflects net ion channel function


Ca2+

Na+

K+

Planar patch clampVoltage clamped whole cell currents

Verapamil

9

Assessing pro-arrhythmic potentialWhole cell patch clamp to assess cardiac AP modulation


TerfenadineAntihistamine

CisaprideGI motility

AP Prolongation 3 – 100 nM

AP Prolongation

3 – 30 nMEAD 100nM

Withdrawn from market due risk of adverse cardiac events

VerapamilArrhythmia

Mixed effectsIKr and ICa,L

Safe in clinical use

10

Comparative pharmacologySpecies variation in sensitivity of model systems


CompoundRABBIT Purkinje Fibre

CANINE Purkinje Fibre

HUMAN hESC-VM

Terfenadine 1.0 mM False Negative 0.03 mM

Quinidine 1.0 mM 1.0 mM 0.3 mM

Cisapride 0.1 mM 0.1 mM 0.01 mM

Sotalol 10 mM 100 mM 10 mM

Chromanol 293B False Negative False Negative 300 mM

E-4031 N/A 0.1 mM 0.1 mM

Nifedipine N/A >10 mM 0.03 mM

Most

First equal

Least

None

Relative Sensitivi

ty

Positive response defined as a change in APD90 >10%

Peng, S. et.al., Journal of Pharmacological and Toxicological Methods 61 (2010) 277–286

11

Increasing throughput of electrophysiological tests


Higher throughput Multi-well formats >> screening

‘ECG-like’ traces, data-richFPD (“QT”), beat rate, amplitude & slope, conduction velocity, etc.

Non-disruptive label-free recordingPreserves cell function and cellular connectivity. Chronic vs. acute effects

Multiple recording sites in parallelAction potential propagation

Ease of use Less skill required compared to manual patch clamp

Monolayer culture High success rate

Spontaneous &Consistent beat rate

Expected shape & pharmacology

Multi-Electrode Arrays (MEA)

Cardiomyocyte requirements

12

FPD (‘QT’) prolongation & contractilityEffect of quinidine assessed by multi-electrode arrays


[Quinidine]0.0 mM

0.3 mM 1.0 mM 3.0 mM

FPD (“QT”) ProlongationContractility

Changes

Beat Rate (bpm)

Interval (ms)

Q T

13

ElectrophysiologyhERG block Na+ & Ca2+

channels QT prolongation contractility

Cardiomyocytes in drug safety testingIntegrated surveillance across platforms & assays


Patch Clamp

Multi-Electrode Arrays

ImpedanceHigh Content

Imaging

Respiration

Biochemical Analysis

25%

Functional Integritymitochondria plasma membrane intracellular calcium morphology

14

Functional integrityHigh Content Analysis (HCA)


Membrane IntegrityDissipation of gradients,

organelle disruption, loss of homeostasis

Biochemical IntegrityDisruption of signal

transduction, synthesis, metabolism, cytoskeletal

machinery

75%

15

High Content Analysis (HCA) & screening


Extracting and interpreting multi-parameter data obtained from high-throughput sub-cellular

imaging

[cells + sensors] [images + data] [information + knowledge]

Why choose High Content Analysis?Cellular detail extracted rapidly in situ and in context

businessreview webinar | 19 March 2014 16

Position-dependent expression

Changes in orientation

Colonies, tissues, whole organisms

Spatial Relationships Structure, Location, ShapeStructural detail (e.g. sarcomere formation)

Localization (e.g. Golgi trafficking)

Morphology classification (e.g. apoptosis)

Temporal Information

Drug induced changes in heart cell beat rate

Cell migration & division tracked over 37 hours

17

High content analysis solutions

Automated microscopy and analysis for high throughput, high content cell imaging


IN Cell Analyzer 2200Faster, Brighter, Better

IN Cell Analyzer 6000Cell analysis redefined

Flexible modular wide field imagingOn-board image restoration

7-wavelength solid state illuminationScientific grade CMOS camera

Laser based confocal imagingIris variable aperture technology

405, 488, 561 & 642 nm laser illuminationScientific grade CMOS camera

18

CytivaTM HCA kits: cell health & integrityLive interrogation of multiple cell health markers


Amiodarone

Nifedipine

Amiodarone

Nifedipine

Characteristic “signature” for each compound

Cellular Parameters

nucleimitochondriacell viabilitycalcium or apoptosis

19

Cardiotoxic potential of selective kinase inhibitors

Using stem cell derived cardiomyocytes & High Content Analysis (HCA)


In collaboration with

Hirdesh UppalAriel Kauss

20

Cancer & cardiotoxicityTyrosine kinase inhibitors

Drug TK Target Indications

Cardiotoxicity

Imatinib Bcr-Abl, c-kit, PDGFR CML, PhALL, GIST, CMML, CEL, DFSP

CHF, LVEF depression

Dasatinib

Bcr-Abl, c-kit, PDGFR, Src

CML QT prolongation, oedema

Nilotinib Bcr-Abl, c-kit, PDGFR CML QT prolongation

Sunitinib

VEGFR, RET, PDGFR, c-kit

RCC, GIST Hypertension, LVEFdepression, CHF, MI

Sorafenib

VEGFR, c-kit, PDGFR, FLT3, RAF1

RCC, HCC Acute coronary syndrome, MI, Hypertension

Lapatinib

EGFR, ERBB2 Breast Ca Asymptomatic LVEF depression

Gefitinib EGFR NSCLC Not reported

Erlotinib EGFR NSCLC, Ca pancreas

Not reported

Data from: Orphanos G.S. et.al. Cardiotoxicity induced by tyrosine kinase inhibitors 2009; Acta Oncologica, 48: 964-970

21

Cardiotoxicity of anticancer drugsOverlapping cardiac signalling & oncology targets

Hypertrophic Stimuli

Physiological Stimuli

Energy Stress

Growth Factors

Cell Proliferation

Hypertrophy

Autophagy

Cell Death

AKT GSK3

ERKRAS

RAF

AKT BAD

AKT

LKBAMPK

Pathological Stimuli

[Ca2+]

PLKJNK

GSK3

NFAT

RTK

RTK

PI3K

PI3KmTO

R

MEK1

Adapted from; Force T & Kolaja K.L. Nature Reviews Drug Discovery (2011) 10, 111-126

22

Cardiotoxicity study compoundsPanel of 134 compounds, kinase inhibitor focus, range of classes


Nifedipine Neg ControlAmiodarone Pos Control

23

Cardiotoxicity screen workflowHigh content analysis (HCA)

384-well format, 7-point dose curves24h, 48h, 72h time points

n=3 wells per treatment condition, 4 images per well


Cells Imaging Image Analysis Data Analysis

Compounds

Fluorescent probes

24

Data analysis & interpretationMulti-parameter high content data


Pharmacodynamics Phenotypic profiling

Mitochondrial Count ATP 100μM0.05μM

25

PD 325901 (MEK1)D [Ca2+] only


Mitochondrial Integrity Calcium Viability

-

26

Entinostat (HDAC)Mitochondrial count and D [Ca2+]


-


27

Imatinib/Gleevec (TK)Mitochondrial count & morphology, D [Ca2+], viability


-


28

Profile clusteringSelf organizing maps


-

+

See tutorial regarding confidentiality disclosures.

29

Clustering results


*

*

**

*reported clinical cardiotoxicity

-

+ *

30

Stem cell models in toxicology


Stem cell technology offers a way forward for abundant

and reproducible supply of human cell models

Assessing drug effects in electrophysiological context may reduce likelihood of false negative & positive results

hESC-Cardiomyocytes (CytivaTM Plus) provide a relevant model for integrated cardiotoxicity assessment

Complementary high content imaging approaches yield mechanistic insights that aid informed decision making

31

Stem cell models in toxicologyVision for future development


o Connectivity in cell modelso Integration of interrogation methodso Comprehensive liability surveillance

Learn more at the Drug Discovery Knowledge Center

The Drug Discovery Knowledge Center gives you access to a wide variety of information to help you achieve deeper insights at every stage of drug discovery from target identification to lead optimization

CytivaTM Cardiomyocytes are sold under licence from Geron Corporation and Wisconsin Alumni Research Foundation under US patent and publication numbers : US 7,425,448, US 2009/0017465, US 6,800,480, US 5,843,780, US 6,200,806, US 7,029,913, US 7,582,479, US 7,413,902, US 7,297,539, US 2009/0047739 and US 2007/0010012 and equivalent patent and patent applications in other countries.

The IN Cell Analyzer system and the IN Cell Investigator software are sold under use license from Cellomics Inc. under US patent numbers US 5989835, 6365367, 6416959, 6573039, 6620591, 6671624, 6716588, 6727071, 6759206, 6875578, 6902883, 6917884, 6970789, 6986993, 7060445, 7085765, 7117098, 7160687, 7235373, 7476510 ; Canadian patent numbers CA 2282658, 2328194, 2362117, 2381344; Australian patent number AU 730100; European patent numbers EP 0983498, 1095277, 1155304, 1203214, 1348124, 1368689; Japanese patent numbers JP 3466568, 3576491, 3683591, 4011936 and equivalent patents and patent applications in other countries.Notice to purchaser: Important license information.

© 2014 General Electric Company – All rights reserved. www.gelifesciences.com, GE Healthcare UK Limited. Amersham Place, Little Chalfont, Buckinghamshire, HP7 9NA UK Presented as a businessreview webinar, Predictive toxicology advances through stem cells, 19 March 2014.

Thank You !

predictive toxicology advances through stem cells

Science

assays businessreview

businessreview

platforms

beat rate

patent applications

amp

data

gt