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Novel Assays for Drug Discovery and Toxicology Using Human iPS Cell-derived Neurons and Cardiomyocytes Susan DeLaura (CDI) Oksana Sirenko, Ph.D. (Molecular Devices) February 7, 2012

Introduction

A major goal of the pharmaceutical industry has been to reduce late stage compound attrition.

One area given significant focus in hopes of optimizing this process is the development of more relevant in vitro disease models.

Stem cells provide a biologically relevant model useful for disease modeling, drug discovery and toxicity testing.

Present demands from the drug discovery process have propelled a shift in focus from high-throughput screening to high content analysis in the assay and drug discovery technology arena.

When joining these two technologies,(high content analysis and stem cells) together, a powerful opportunity arises to develop more physiologically relevant biochemical and cell-based assays for compound screening.

Presentation Outline

iPS Cell Technology Cardiomyocytes

─ Characterization (Genomic, Protein, Electrophysiological) ─ Utility (Functional Screens, Mechanistic Insight)

Neurons ─ Characterization (Protein, Electrophysiological)

High Content Screening and Assay Development ─ iPSC-derived Neurons (Network development & neurotoxicity

assays) ─ iPSC-derived Cardiomyocytes (Cardiomyocyte beating assay)

Scope of the problem is large 10,000’s of untested chemicals in current commerce

Problem cannot be solved by animals Practical constraints; cost, time, logistics

Ethical constraints

Societal and regulatory pressures in US and Europe stimulating rapid move to animal-free systems

Stem Cells for Safer Medicine (SC4SM), IMI, REACH, ToxCast, Tox21,

In vitro cell systems are a critical part of the solution ToxCAST, Tox21, IMI, NCGC, 9 NIH screening centers (Burnham, Stanford, etc)

The Need for Better Systems to Predict Toxicity

Toxicity Forecaster (ToxCast)

Current Cell Models are an Inadequate Solution

Primary Cells Limited and sporadic supply Variable phenotype and quality (donor genetics, handling time at harvest, ischemia/reperfusion injury) Gain or loss of function (rapidly de-differentiate, change proliferation state)

Transformed Cells Proliferating, potentially aneuploid, do not closely recapitulate in vivo biology

Cell Type Genetic Stability

Phenotypic Stability

Quantity Availability Cellular

Variability Gene

Targeting

Transformed Cells

Aneuploid Stable Unlimited Available on

demand Change as

culture Yes

Primary Human Cells

Diploid Rapidly

dedifferentiate in vitro

Restricted Restricted and highly variable

Highly donor dependent

No

Cell models derived from cadavers and animals, and engineered cells, are minimally effective

Cell TypeGenetic Stability

Phenotypic Stability

Quantity AvailabilityCellular

VariabilityGene

Targeting

Transformed Cells

Aneuploid Stable UnlimitedAvailable on

demandChange as

cultureYes

Primary Human Cells

DiploidRapidly

dedifferentiate in vitro

RestrictedRestricted and highly variable

Highly donor dependent

No

Unlimited

iPS Cell Technology Unlimited Potential

Reprogram sample tissue into iPS cells

iPS cells multiply and expand in culture indefinitely

Draw 1 small sample from 1 person

Differentiate iPS cells into any cell type in the body (unlimited numbers)

iPS cells are uniquely useful stem cells Derived from adult tissue via non-invasive methods Can be expanded indefinitely Can be differentiated into any cell type in the body Fully pluripotent

iPS cells offer distinct advantages to ES cells Can be created via streamlined & non-invasive methods Eliminates political/social issues regarding tissue source Enables diversity of genotype and phenotype

7

CDI Overview Cell Manufacturing Pipeline

ISO and GMP processes ensure highest quality

Highly pure populations of differentiated cell types

Industrial quantities of iPS cells and differentiated cell types

Manufacturing process is translatable, scalable and IP protected

Scaling to include parallel simultaneous reprogramming and differentiation from multiple lines

Large Scale

Manufacturing • High Quality • High Purity • Billions of Cells

iCell® Cardiomyocytes

iCell Cardiomyocytes

Human iPS cell-derived

99% pure, cryopreserved, ready to use.

Available in virtually unlimited quantities

Full product solution; cells, media, protocols

Demonstrate normal human cardiac biology,

electrophysiology, and toxicity responses

Broad platform utility for discovery and

preclinical development

Sarcomeric a-actinin (Vala Sciences)

cTNT / MLC cTNT / Cx-43

Stable and vigorous beating for > 9 months in culture

cTNT / MHC

M-Lot1474888_compressed_09Aug11.avi

Transcriptome Analysis

Stem cell

Transition

Cardiomyocyte

Gene Category

iCell Cardiomyocytes d28 and d120

Primary Heart cultures

Comparative Analysis

“More human than human”

iCell® Cardiomyocytes Genomic and Transcript Characterization

Gene expression analysis by Roche Pharmaceuticals.

250 cardiac genes identified from the Novartis GNF expression atlas were plotted in rank-order along X axis.

● ‘Primary’ cells do not necessarily recapitulate in vivo biology.

● iCell Cardiomyocytes show stable expression pattern similar to adult mRNA.

iCell® Cardiomyocytes Electrophysiology Characterization

INa ICa-L

Ito IKr

Ifunny IK1

Spontaneous Action Potentials Ionic Currents

Gai – m2 Carbachol

Gas – b1 Isoproterenol

Gaq – a1 Phenylephrine

GPCR Activity

Control Drug Ma et al., AJP 2011 In press

Elicited Action Potentials

iCell® Cardiomyocytes Utility – Functional Screens

IKr BlockAPD prolongation

Electrophysiology

Determined by edge detection

Mechanical Activity Energetics

Determined by edge detection

160150140130Time (ms) Sw eep:1939 Visible:4 of 2284

Imem

b(n

A)

-3

-2.5

-2

-1.5

-1

-0.5

0

0.5

1

1.5

5 ms

1 n

A

0.3 µM

vehicle

3 µM

30 µM

N = 10N = 5

V1/2 = -80 mV

vehicle 0.3 µM3 µM

30 µM

wash

PatchXpress Current Block

Analyze

Quantitate

Cytotoxicity

0 20 40 60 80 100100

200

300

400

Addcompound

Time, sec

RFU

FLIPR® Tetra System

Epinephrine

-5 -3 -2 -1 0 110

20

30

40

50

ControlLog[epinephrine] M

Bea

ts/m

in

GPCR

xCELLigence RTCA Cardio

0

1

2

3

4

5

6

7

0 20 40 60 80 100 120 140

Cel

l Ind

ex

Time (hours)

1 sec0.02 CI

Label-Free

Olson, E.N., et. al., Genes & Dev (2003); 17, 1937 Bernardo, B.C., et. al., Pharmacology & Therapeutics (2010); 128, 191

Cardiac Hypertrophy; Increase in heart mass, due to increase in size of cardiomyocytes

iCell® Cardiomyocytes – Utility Disease Modeling

Key Levers ─ Cell density ─ Pre-plate duration ─ Incubation media ─ Application duration ─ Endpoint Assay

iCell Cardiomyocyte Assay

Field potential voltage (µV)

Multi-Electrode Array (MEA) Field Potential Recordings LQT2 Phenotype

Delayed repolarization Prolonged QT interval Polymorphic ventricular

tachycardia

iPSC-derived Cardiomyocytes - Utility Patient Specific Lines

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

LQT2 Control

Frequency

(

Hz)

MEA Frequency

0

500

1000

1500

2000

2500

LQT2 Control

FPD

(ms)

MEA FPD

LQT2

Control

iCell® Neuron Characteristics & Functional Tests

• Morphology Bipolar or multi-polar neurite outgrowths

• Molecular Markers Analysis Including: - bIII-Tubulin - Map2 - Neuron-specific Enolase - Synapsin - Synaptophysin - vGAT (GABAergic) - vGLUT (Glutamatergic) - Tyrosine Hydroxylase (Dopaminergic)

• Functional Tests - Electrophysiology: Evoked and spontaneous

action potentials; Inhibitory and excitatory post-synaptic currents; Ion channel blocks (Na+ and K+)

- Cytotoxicity - Neurite outgrowth - Mitochondrial integrity

250200150100500Time (ms) Sweep:11 Visible:1 of 11

In#0

(mV

)

-40

-30

-20

-10

0

10

20

250.00 ms-34.84 mV

1

0.00 ms0.00 mV

2

0.00 ms-34.85 mV

3

250.00 ms0.01 mV

4

10 mV 25 ms

5 ml Pellet of Pure Neurons = ~4 Billion Neurons (~4% of total neurons in brain)

250200150100500Time (ms) Sweep:11 Visible:1 of 11

In#0

(mV

)

-40

-30

-20

-10

0

10

20

2121

0.00 ms-34.85 mV

3

250.00 ms0.01 mV

42421214121

10 mV10 mV25 ms25 ms

iCell® Neurons Characterization Post-Thaw Morphology & Purity

Day 5

200x

Day 19 Day 1

Post-thaw iCell Neurons provide efficient cell recovery, high purity and morphologically display mature processes.

Lot 1-well 2

Parameter 12

A48

8 Tu

j1

100 101 102 103 104 105 106 10710010110

210310

410510

6107

98.16% 0.34%

1.18% 0.31%

TuJ1

Nestin

Lot 1 d5 Tuj-Nes

Parameter 12

A48

8 Tu

j1

100 101 102 103 104 105 106 10710010110

210310

410510

6107

96.95% 0.26%

2.59% 0.19%

TuJ1

Nestin

40-Day 20

A647 NestinA

488

Tuj1

100 101 102 103 104 105 106 10710010110

210310

410510

6107

91.82% 3.77%

4.32% 0.09%

TuJ1

Nestin

iCell ® Neurons Characterization Neuron Subtype Immunocytochemistry

ICC data demonstrates the presence of a mixed neuronal cell population consisting largely of:

• GABAergic (inhibitory) neurons • Glutamatergic (excitatory)

neurons • small percentage of

Dopaminergic neurons (<1%)

18 vGAT / vGLUT2 MAP2 / GABA / Hoechst

Beta III Tubulin/Nestin/Hoechst

iCell® Neurons Characterization Pre- and Post-synaptic Markers

19

SYP / vGAT / vGLUT2

Gephyrin / vGAT / SYP MAP2 / PSD-95 / HOECHST

iCell Neurons exhibit co-localization of pre-synaptic and post-synaptic markers.

iCell® Neurons Electrophysiological Activity and Responses

Ion Currents

Synaptic Responses

Evoked

Spontaneous

Action Potentials iCell Neurons exhibit typical neuronal electrical responses as demonstrated by: • Evoked action potentials

• Spontaneous action potentials

• Inhibitory post-synaptic currents

• Excitatory post-synaptic currents

• Ion channel blocks

Methods used: • Single-cell current patch clamps

• Single-cell voltage patch clamps

• Multi-electrode arrays

• Automated patch clamping

MEA

20

Novel Assays for Drug Discovery and Toxicology using Human iPS Cell-Derived Neurons and Cardiomyocytes Oksana Sirenko, Ph.D. February 7, 2012

Molecular Devices products are for Research Use Only. Not for use in diagnostic procedures. Molecular Devices, the Molecular Devices logo, and all other trademarks unless otherwise indicated are the property of Molecular Devices, Inc. 2012

Assays for Predicative Toxicology

Neurotoxicity

• Neuronal development & toxicity

• Stem cell derived neurons

• Cardio Safety & Toxicity

• Live contracting cardiomyocytes

Cardiac Beating

assay


Impact of Drug Toxicity

S.R. Raj et al, Circulation, Sept 2009, 120(12): 1123-1132 (NIHPA)

What if we can predict failure?


Future of Predictive Toxicology

• Prediction of drug toxic effects remains one of the industry’s greatest challenges1

• Overall success rate from “first-in-man” is ~11%

• ~30% of compounds fall out for safety reasons

• The important trend in drug discovery is to adopt in vitro assays2

• More predicative, disease relevant

• Reduce use of animals

• Efficiently identify adverse effects

• What is needed? • Improved cell based models, more complex biology

• Advancements in assay techniques & instrumentation

1Kola & Landis, Nat. Rev. Drug Discov., 3, 711, Aug. 2004 2Toxicity Testing in the 21st Century, National Academies Press, 2007


High Throughput Cell-Based Cardiotoxicity Assays

Detail Graph

Time (Seconds)0 50 100 150

Rel

ativ

e Li

ght U

nits

2000

3000

4000

Detail Graph


Rel

ativ

e Li

ght U

nits

2000

3000

4000

Control

EpinephrineDetail Graph


Relati

ve Lig

ht Un

its

2000

2500

3000

Control Verapamil

Graphs of Calcium 5 Intensity vs Time for Single Wells from FLIPR Tetra

Concentration, uM

0.001 0.01 0.1 1 10

0

10

20

30

40

50

60

70

80

90

100

4-P Fit: y = (A - D)/( 1 + (x/C)^B ) + D: A B C D R^2iso (Isoproterenol: Concentration vs MeanValue) 32.1 1.51 0.0075 87.3 0.998doxa (doxazosin: Concentration vs MeanValue) 31.6 2.28 0.626 11.4 0.826vera (verapamil: Concentration vs MeanValue) 28.9 1.03 0.0534 -0.214 0.983epi (Epinephrine: Concentration vs MeanValue) 30.6 0.734 0.0155 83.5 0.999dopamine (didoxine: Concentration vs MeanValue) 32.7 0.893 0.187 58.5 0.99

__________Weighting: Fixed

Bea

ts/m

in

Concentration, uM

1e-4 0.001 0.01 0.1 1 10 100

0

10

20

30

40

4-P Fit: y = (A - D)/( 1 + (x/C)^B ) + D: A B C D R^2Plot#5 (Doxazosin: Concentration vs MeanValue) 19 0.37 1.1e+16 -4.6e+06 0.976Isoproterenol (Isoproterenol: Concentration vs Me... 18.2 1.25 0.00201 38.5 0.983Plot#3 (Epinephrine: Concentration vs MeanValue) 17.4 0.576 0.00919 38.1 0.965Plot#2 (Propanolol: Concentration vs MeanValue) 19.4 0.692 1.49 6.87 0.974verapamil (Verapamil: Concentration vs MeanVal... 18.4 0.642 0.0112 -0.669 0.978Dopamine (Dopamine: Concentration vs MeanVal... 17.5 0.673 0.339 36.2 0.987


PositiveChronotropes:

NegativeChronotropes:

IsoproterenolEpinephrineDopamine

DoxazosinVerapamilPropranolol

Bea

ts/m

in

384w format 96w format

Concentration, M Concentration, MConcentration, uM

0.001 0.01 0.1 1 10

0

10

20

30

40

50

60

70

80

90

100



Bea

ts/m

in

Concentration, uM

1e-4 0.001 0.01 0.1 1 10 100

0

10

20

30

40







Bea

ts/m

in


Concentration, M Concentration, M

Measures rate and beating pattern of live iCell® Cardiomyocytes


High Throughput Cell-Based Cardiotoxicity Assays

Detail Graph


Rel

ativ

e Li

ght U

nits

2000

3000

4000

Detail Graph


Rel

ativ

e Li

ght U

nits

2000

3000

4000

Control



Relati

ve Lig

ht Un

its

2000

2500

3000

Control Verapamil


Concentration, uM

0.001 0.01 0.1 1 10

0

10

20

30

40

50

60

70

80

90

100



Bea

ts/m

in

Concentration, uM

1e-4 0.001 0.01 0.1 1 10 100

0

10

20

30

40







Bea

ts/m

in


Concentration, M Concentration, MConcentration, uM

0.001 0.01 0.1 1 10

0

10

20

30

40

50

60

70

80

90

100



Bea

ts/m

in

Concentration, uM

1e-4 0.001 0.01 0.1 1 10 100

0

10

20

30

40







Bea

ts/m

in



Measures rate and beating pattern of live cardiomyocytes

ScreenWorks® Peak Pro™ Software for the FLIPR® Tetra System

• Characterize Ca+2 oscillations from beating cardiomyocytes • Fast, automated peak detection • Enhanced analysis features - Frequency, Width, Rise & Decay times


iCell® Cardiomyocytes Beating


Analysis of Beat Rate from Imaging

Epinephrine

-5 -3 -2 -1 0 110

20

30

40

50

ControlLog [Agonist] M

Bea

ts/m

in

Isoproterenol

-5 -3 -2 -1 0 110

20

30

40

50

ControlLog [Agonist] M

Bea

ts/m

in

0

1

2

3

4

5

6

7

8

9

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39

Images

% T

resh

old

% T

hres

hold

Time Point

Intensity Differential Derivative vs Time


Analysis of Beat Rate from Ca2+ Flux

Control Epinephrine Verapamil

• Ca2+ levels fluctuate with contraction events

• Provide surrogate assessment of beat rate and sarcolemmal activity

• Cell contractions visualized with Ca2+ sensitive dye

• Calcium 5 Kit from Molecular Devices


Predictive Assay for Cardio Effects

Pos

itive

C

hron

otro

pes

Neg

ativ

e C

hron

otro

pes

Concentration, uM

1e-4 0.001 0.01 0.1 1 100

2

4

6

8

10

12

14

16

18

20

4-P Fit: y = (A - D)/( 1 + (x/C)^B ) + D: A B C D R^2Epinephrine (Epinephrine: Concentration vs MeanV... 9.47 0.53 0.0077 20.5 0.949Plot#2 (verapamil: Concentration vs MeanValue) 9.89 1.81 0.00876 0.367 0.982


Bea

ts/ 2

3 se

c

Concentration, M

epinephrine

verapamil


FLIPR Tetra System delivers a HT solution for cardiomyocyte assays

• HTS mechanics increases assay speed and throughput • 96-, 384-, and 1536-well simultaneous

reads • Camera captures 8 images per second

• Assay simplicity • FLIPR Calcium Dye measures transient

calcium signals • Signal patterns of beating

cardiomyocytes

• Enables early risk assessment • Pre-screen to remove cardio-toxic

compounds from lead generation • Quickly direct SAR and Med Chem efforts

on a larger scale

NEW: ScreenWorks® Peak Pro™ Software delivers on the fly analysis of important peak characteristics, enabling assessment of compound effects on cardiomyocytes earlier in the drug discovery process.


Cardiac Toxicity and Long QT syndrome

• Cardiotoxic drugs often cause Long QT syndrome or Torsades de Pointes

• TdP is a form of ventricular tachycardia, which can lead to sudden death

• TdP is associated with long QT syndrome observed on the ECG

• Most drugs that cause long QT are the IKr current blockers (hERG)

• erythromycin, terfenadine, and ketoconazole

QT

RR Normal

Long QT: Long QT:Long QT:Long QT:Long QT:Long QT:Long QT:

Torsades de Pointes


34

• Electrophysiology measures activities of individual channels (e.g. hERG)

• Measurements of contractions allows more holistic approach

• Measure FLIPR Calcium 5 Assay signal Calcium 5 Signal During Cardiomyocyte Contraction

200

220

240

260

280

300

320

340

360

380

400

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5

Time (sec)

Inte

nsity

Control

Isoproterenol

Predicative Assays for Cardiac Toxicity


Cardiac Beating Assay Work flow

Plate iCell® Cardiomyocytes into gelatin coated plates

Load the cells with FLIPR Calcium 5 dye (2x solution)

Observe cardiomyocyte beating after 3-5 days in culture

Add compounds and read calcium signal

Analyze data using ScreenWorks software

20k 96; 4k 384

PBS + 20mM HEPES 37oC +5%CO2 for 1 hour

Post 5-15min, 37oC !


FLIPR Tetra Protocol

Parameter 384-Well Settings

Read Mode Fluorescence

Excitation/Emission (nm) 470-495 / 515-575

LED Power 40%-70%

Camera Gain 2,000

Exposure Time 0.05 sec

Gate Open 6%-100%

Read Interval 0.125 sec

Reads Before Pipetting 80-180

Reads During First Interval 300-800


37

High Throughput Cardiac Beating Assay: FLIPR® Tetra system

All

A

B

C

D

E

F

G

H

I

J

K

L

M

N

O

P

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

10 9 9 8 10 9 9 9 9 8 9 8 9 9 9 8 9 8 9 9 8 7 9 10

19 18 19 19 18 18 0 0 0 17 15 17 0 0 0 8 8 8 2 1 4 2 3 1

19 18 18 18 17 18 15 15 14 15 15 16 0 0 0 8 7 8 3 4 3 4 5 3

19 18 19 19 17 18 10 11 10 14 14 14 0 0 0 9 8 8 6 5 4 6 6 6

19 18 18 17 17 16 9 8 9 13 13 14 0 0 1 9 8 7 7 5 6 7 4 7

19 17 18 16 15 16 8 9 9 11 12 11 0 1 2 8 9 9 7 7 7 7 7 8

18 16 18 15 16 14 8 9 8 10 10 10 2 4 3 8 8 8 9 8 8 8 8 9

19 17 16 16 15 14 8 8 8 9 10 8 2 6 4 9 8 8 9 9 10 8 8 8

15 14 14 13 13 12 8 8 8 9 8 8 4 6 4 9 8 8 9 10 8 8 9 9

17 13 16 13 13 11 8 9 9 8 9 9 6 9 6 9 8 8 9 9 9 9 9 8

10 10 8 9 8 9 8 9 8 8 8 9 9 9 8 9 8 9 9 10 8 9 10 11

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

control

isoproterenol epinephrine digoxin verapamil dopamine propranolol doxazosin ac-choline

concentr

atio

n


All

A

B

C

D

E

F

G

H

I

J

K

L

M

N

O

P

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

1 2 5 1 1 1 2 0 1 0 0 1 1 0 0 0 0 0 4 3 1 2 1 1

10 9 9 8 10 9 9 8 8 8 9 8 9 9 9 7 9 8 9 9 9 9 9 11

19 17 18 18 18 18 1 1 1 17 15 16 0 0 0 8 7 8 5 4 4 1 3 2

19 18 18 18 17 18 14 15 14 15 15 14 1 1 0 8 7 8 3 4 3 4 5 3

18 18 19 17 17 18 10 11 10 14 14 14 3 0 0 8 8 8 5 5 4 5 6 6

19 17 18 16 17 16 9 8 9 13 13 13 0 0 1 9 8 7 6 4 6 7 7 7

19 17 18 16 15 16 8 9 9 11 11 11 0 3 2 8 8 9 7 7 7 7 7 8

17 16 18 15 15 14 8 9 8 9 10 10 2 4 3 8 8 8 8 8 8 8 8 9

19 17 16 15 15 14 8 8 8 9 10 8 2 6 4 9 8 8 9 9 9 9 8 9

15 14 14 13 13 11 8 8 8 9 8 8 4 5 3 9 8 8 8 9 8 8 9 9

17 13 16 13 13 11 8 9 9 8 9 9 6 8 6 9 8 8 9 9 9 9 9 9

10 10 8 9 8 9 7 9 8 8 7 8 8 9 8 9 8 9 9 10 8 9 10 12

1 0 2 0 1 0 1 0 0 1 1 0 0 1 0 0 0 0 0 4 1 6 3 2

0 0 0 0 1 2 1 0 2 0 0 0 1 1 0 0 0 0 0 0 1 3 1 0

1 2 0 0 0 1 1 2 0 0 0 0 3 0 0 0 0 0 1 1 2 0 1 2

2 0 0 1 0 1 1 2 2 0 2 2 0 0 2 0 2 1 0 3 3 2 3 1

Excellent Reproducibility of Beat Rates

FLIPR Tetra System Assay Quality

…

… Comparison of Beat Rates for Control Wells

0

2

4

6

8

10

12

14

16

18

20

Row B Row L

Bea

ts p

er M

inut

e

(n=24)

CV’s < 10%


ScreenWorks Peak Pro Software: Analysis Output Parameters

• Peak Count & Frequency • Peak Position (time) and Amplitude • Peak Width (FWHM) • Rise Time (10% to 90%) • Decay Time (90% to 10%)

Calcium 5 Response on FLIPR: Epinephrine High Dose (C06)

-20000

-10000

0

10000

20000

30000

40000

10.5 11 11.5 12 12.5 13 13.5

Time (sec)

Amplitude & Time

Decay Time Rise Time

Peak Width (FWHM)

• Average and standard deviation of all important parameters

• Identifies irregular spacing for finding missing peaks, extra peaks, and arrhythmias

Peak Width 10% amplitude


New ScreenWorks Peak Pro Software Features

Measure critical peak parameters associated with beating Cardiomyocytes, within ScreenWorks Software

• Configure Kinetic Reduction • Show Kinetic Values • Auto-Export Data


Development of Predicative Cell-Based Assays: Positive and negative chronotrope effects

Concentration, uM

0.001 0.01 0.1 1 10

0

10

20

30

40

50

60

70

80

90

100



Bea

ts/m

in

Concentration, uM

1e-4 0.001 0.01 0.1 1 10 100

0

10

20

30

40







Bea

ts/m

in



Detail Graph


Rel

ativ

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ght U

nits

2000

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4000

Detail Graph


Rel

ativ

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ght U

nits

2000

3000

4000

Control



Relati

ve Lig

ht Un

its

2000

2500

3000

Control Verapamil



Prospective Cell-based Model for Testing Cardiac Drugs

• Beat rate increased by epinephrine

• Cells treated with alpha- and beta- blockers

• Measure effect on beating rate

Concentration, uM

0.01 0.1 1 10

0

10

20

30

40

4-P Fit: y = (A - D)/( 1 + (x/C)^B ) + D: A B C D R^2Plot#2 (propanolol: Concentration vs MeanValue) 28.6 3.5 0.187 3.98 0.989doxa (doxazosin: Concentration vs MeanValue) 32.7 0.692 1.27 -9.03 0.975Plot#1 (pinodol: Concentration vs MeanValue) 31.3 1.5 2.51 -0.557 0.993


propranolol doxasozin pindolol

Bea

ts/m

in

Concentration, M Verapamil

Propranolol

Control

Epinephrine (speeds up)

Cardiac drugs slow down beat rate

Dose with epinephrine followed by cardiac drugs:

alpha - and beta - blockers

G2 - Group:NO_GROUP - Concentration:10.000000


Relative L

ight Units

100

120

A1 - Group:NO_GROUP - Concentration:10.000000


Relative

Light Un

its

100

120

140

E8 - Group:NO_GROUP - Concentration:10.000000


Relative

Light Un

its

80

90

100

110

E7 - Group:NO_GROUP - Concentration:10.000000


Relative

Light Un

its

80

90

100

110


FAIL EARLY: Identification of compounds that affect beat rate and rhythm of iPSC cardiomyocytes

• Dose-dependent atypical patterns and changes in cell beating rate caused by several known cardiotoxic compounds including hERG, Ca2+ and Na+ channel blockers

Bea

ts/

30 s

ec

Bea

ts/

30 s

ec

Concentration, uM

1e-4 0.001 0.01 0.1 1 10 100

0

5

10

15

20

4-P Fit: y = (A - D)/( 1 + (x/C)^B ) + D: A B C D R^2Plot#1 (Astemisole: Concentration vs MeanValue) 13.7 29.4 0.0744 -1.25e-12 0.995Plot#4 (Cisarpide: Concentration vs MeanValue) 13.4 2.23 0.0432 0.0999 0.98Plot#2 (Pimoside: Concentration vs MeanValue) 14.5 85.9 0.292 3.64e-22 0.985Plot#3 (Terfenadine: Concentration vs MeanValue) 13.7 3.65 0.545 0.0069 0.994


Concentration, uM

1e-4 0.001 0.01 0.1 1 10 100

0

5

10

15

20

4-P Fit: y = (A - D)/( 1 + (x/C)^B ) + D: A B C D R^2cis (cisapride: Concentration vs MeanValue) 12.7 2.08 0.0389 0.161 0.98ttx (TTX: Concentration vs MeanValue) 13 2.06 4.02 3.79 0.918nif (nifedipine: Concentration vs MeanValue) 13.4 2.52 0.122 -0.113 0.985


IC50, MCisapride 0.04Nifedipine 0.12Tetrodotoxin 4.02


IC50, MAstemisole 0.07Cisapride 0.04Pimoside 0.29 Terfenadine 0.54

Ion Channel Blockers hERG Channel Blockers


44

Prolongation of Repolarization Stage by hERG Blockers

Detail Graph

Time (Seconds)0 20 40 60 80 100 120 140

Rel

ativ

e Li

ght U

nits

2000

3000

4000

5000

Astemizole 1M

Detail Graph

Time (Seconds)0 20 40 60 80 100 120 140

Rel

ativ

e Li

ght U

nits

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4000

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Cisapride 0.3M

Overlap of beating patterns leading to high frequency low amplitude oscillations


Effect of hERG inhibitors

Time (Seconds)

0 50 100 150

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ativ

e Li

ght U

nits

3000

4000

5000

Time (Seconds)

0 50 100 150

Rel

ativ

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ght U

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Time (Seconds)

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ativ

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ght U

nits

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Time (Seconds)

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ght U

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Time (Seconds)

0 50 100 150

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ght U

nits

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Time (Seconds)

0 50 100 150

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ativ

e Li

ght U

nits

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4000

5000

Cisapride

Astemizole

Concentration


Software identifies peak irregularity

Detail Graph


Relat

ive Li

ght U

nits

3000

4000

5000

Detail Graph


Relat

ive Li

ght U

nits

4000

6000

Detail Graph


Relat

ive Li

ght U

nits

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5000

Detail Graph


Relat

ive Li

ght U

nits

3000

4000

Control Lidocaine

Isoproterenol Astemizole

OK

Missing

Extra peaks

Irregular


Surrogate Markers for Cardiac Toxicity Assay

• Measuring peak width, peak spacing and other parameter may predict compounds inducing long QT syndrome, arrhythmia and other potentially dangerous events

Detail Graph


Relat

ive L

ight U

nits

2000

3000

Prolonged re-polarization (cisapride) Modulation of peak decay time

0

2

4

6

8

10

12

epinephrine cisapride lidocaine propranolol

Sec

onds

controlmed conc.high conc.

Concentration, M1e-4 0.001 0.01 0.1 1 10 100 10000

1

2

3

4

5

6

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8

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11

10%

Pea

k W

idth

(sec

)


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k W

idth

(sec

)

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)


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k W

idth

(sec

)

Peak Width (10%)


48

Comparing Cardiomyocyte Response to Various Compounds

Peaks = 12 Freq = 12.0 bpm Rise = 0.39 sec Decay = 0.76 sec



Control

Propranolol

Isoproterenol


Variability of Cardiac Beating Assay

• Variability of different parameters across 384w plate

Statistics average stdev % stdev average stdev % stdev average stdev % stdev

Peak Count 8.8 0.7 8.2 8.5 1.4 16.8 15.9 2.5 15.8

Average Peak Width 1.0 0.2 20.9 2.3 0.3 12.0 3.0 0.4 14.5

Average Peak Amplitude 18.0 5.0 27.7 2249.3 530.3 23.6 195.1 31.8 16.3

Average Peak Baseline 59.4 5.5 9.2 2805.6 199.7 7.1 265.1 23.4 8.8

Average Peak Spacing 4.1 0.3 8.3 6.9 1.0 15.1 6.4 1.0 16.4

Average Peak Rise Time 0.4 0.1 12.7 0.4 0.1 20.2 0.8 0.1 15.6

Average Peak Decay Time 1.0 0.1 13.5 1.4 0.2 16.6 1.0 0.1 13.5Average Peak Width at 10% Amplitude 1.7 0.2 9.1 2.7 0.4 15.0 3.6 0.5 14.7

Exp1 24 wells Exp2 200 wells Exp3 24 wells


FLIPR Tetra system and ScreenWorks Peak Pro Software

• FLIPR Tetra system HTS mechanics dramatically increases safety throughput

• ScreenWorks Peak Pro expands peak detection for beating cardiomyocytes and other primary cells with Ca+2 oscillations

• Enables analysis of samples with multiple peaks per response

• ScreenWorks Peak Pro speeds up peak detection analysis

• Easy to use analysis methods, performed directly within ScreenWorks

• Built on proven ScreenWorks Software platform

• Fail poor compounds early = Large cost savings in clinical trials and product liability


Neuronal Toxicity Assays Using iPSC Derived Neurons: iCell® Neurons

• Nervous system is a target organ for the toxic effects of chemical compounds & environmental agents

• HTS assays are in high demand

• There is a great interest in developing more predictive cell-based models and efficient screening tools • Neurodegenerative diseases

Alzheimer’s or Parkinson’s

• Excitotoxicity

• We present here several assays for assessment of neural toxicity • Neurite outgrowth

• Integrity of mitochondria

• Live cell assays

B04


Neuronal Cell Imaging & Analysis

• Imaging: ImageXpress® Micro XL • Image analysis: MetaXpress® software,

Neurite Outgrowth module

Overlayed Image Neurite Outgrowth Module

B-tubulin (green) Nuclear (DAPI)


ImageXpress® Micro XL Automated Imaging System

High Content Image Acquisition & Analysis

Cells: ~500

Cells: ~120

• High sensitivity and dynamic range improves ability to quantify features


Neurite Outgrowth : Fast and Biologically Relevant Assay for Neurotoxicity

Antimycin A Staurosporin MK571 Mitomycin C

Concentration, M

0.001 0.01 0.1 1 10 100 1000 0

10000

20000

30000

Tota

l Out

grow

th

Total neurite outgrowth

% cells with outgrowth

Compound IC50 (M) IC50 (M)Antimycin A 13 14

Staurosporine 0.9 1.7MK571 4.1 3.9

Mitomycin C 0.7 0.7

NMDA n/d n/dSNAP 68 84

PD98059 31 46

Mitomycin C

0.01M 1M 10M

Acquisition Time = 4:00 Analysis Time = 7 min Z-prime ~ 0.7


Effect of Growth Factors on Neural Development

Control

BDNF

-0.3

-0.2

-0.1

0

0.1

0.2

0.3

0.4

cell

No

out M

AP

2

out T

UJ

bran

ches

proc

esse

s

MA

P2

TU

Jlog

chan

ge

control

NFG

BDNF

EPO

• Multi-parametric profiling

• Multiplexed analysis to maximize information

• Outgrowth, branches, processes, cell number, process length, etc.


Neural Regeneration: Live Cell Real Time Neurite Outgrowth

Untreated Cells Staurosporine

• Re-growth of neurons after injury is mediated by neurotrophic factors that stimulate cell adhesion, migration, and extension of neurites

• Measured in real time using time lapse acquisition in transmitted light


Real Time Neurite Outgrowth Assay

• Inhibition of neurite outgrowth by staurosporine

• Transmitted light

• Time-lapse acquisition (14h)

• Automated analysis

Staurosporine Untreated

0

10

20

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40

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60

0 2 4 6 8 10 12

Time post-plating (hours)

Me

an

Ou

tgro

wth

/ce

ll

Untreated

BDNF (12 nM)NGF (49 nM)

Staurosporine (10 uM)


Compound IC50 (nM) CompoundCompoundAntimycin A

IC50 (nM)46 Antimycin A

Valinomycin 46

0.15

Antimycin A AntimycinAAntimycin AA

Valinomycin ValinomycinValinomycin

Concentration, M 1e - 5 1e - 4 0.001 0.01 0.1 1 10 0

10

20

30

Tota

l Out

grow

th

Concentration, Concentration, 0.1

MConcentration, Concentration, Concentration, Concentration, MM 1e1e 1e1e1e-- 5---5 1e1e 1e1e1e1e-- 4---4 0.0010.001 0.010.01 0.10.10.1 11 1010 00

1010

2020

3030

Tota

l Out

grow

thTo

tal O

utgr

owth

Control Antimycin A 3 M Control Antimycin A 3 A 3 M • Mitochondrial depolarization is an early signal for exitotoxicity, hypoxic damage or oxidative stress • Mitochondria membrane

potential monitored with the mitochondria active dye JC-10

• Analyzed using the Granularity module

• End-point or real time assay

Integrity of Mitochondria


HTS Assay for Predicative Toxicology

Methyl Mercury

CalceinAM - Neurite outgrowth Hoechst – Nuclear condensation

Concentration, uM

0.01 0.1 1 10 100 10000

100

200

300

4-P Fit: y = (A - D)/( 1 + (x/C)^B ) + D: A B C D R^2dex (dex: Concentration vs MeanValue) 270 1.62 152 -10.4 0.972ret acid (ret acid: Concentration vs MeanValue) 255 6.54 168 5.06 0.988MK (MK801: Concentration vs MeanValue) 255 3.33 295 11.1 0.984mer (mercury: Concentration vs MeanValue) 266 2.14 4.44 12.2 0.998valp acid (kain acid: Concentration vs MeanValue) 285 1.33 1.79e+03 1.79 0.938


Dexamethasone 152 uM Retinoic acid 168 uM Methyl Mercury 4.4 uM MK801 295 uMValproic acid >1000 uM

Concentration, uM

0.01 0.1 1 10 100 10000

100

200

300

4-P Fit: y = (A - D)/( 1 + (x/C)^B ) + D: A B C D R^2dex (dex: Concentration vs MeanValue) 270 1.62 152 -10.4 0.972ret acid (ret acid: Concentration vs MeanValue) 255 6.54 168 5.06 0.988MK (MK801: Concentration vs MeanValue) 255 3.33 295 11.1 0.984mer (mercury: Concentration vs MeanValue) 266 2.14 4.44 12.2 0.998valp acid (kain acid: Concentration vs MeanValue) 285 1.33 1.79e+03 1.79 0.938


live

dead

Nuclei

Concentration, uM

Neu

rite

outg

row

th


Predictability of Neurotoxicity Assay

IC50, uM in vivo

Neurotoxicity Description

Methyl Mercury 4 + metal

Dexamethasone 77 + anti-inflammatory (steroid)

Retinoic acid 197 + vitamin A, anti-cancer

MK801 270 + anti-convulsant, NMDA rec.ant.

Kainic acid 723 + neurostimulant, receptor agonist

Valproic acid >1000 + anti-convulsant

Cytosine arabinoside 151 + anti-cancer

Hydroxyurea n/d - anti-cancer

5-Fluorouracil n/d - anti-cancer

Ochratoxin A n/d - mycotoxin

Ascorbic acid n/d - vitamin C

Aspirin n/d - anti-inflammatory

Kno

wn

Neu

roto

xins

A

nti-

Pro

lifer

atio

n S

afe

n/d = not detectable


HCA for Predicative Toxicology

• We have demonstrated several automated neurotoxicity assays suitable for screening environments:

• Neural network integrity (fixed or live cells)

• Mitochondrial integrity (live cells)

• Nuclear condensation (fixed or live cells)

• These assays can be used to for:

• Testing biologics or chemical compounds on neuronal development

• Screening and validation of drug candidates

• Evaluating potential neurotoxic effects of different agents


Acknowledgements

• Evan Cromwell

• Carole Crittenden

• Jayne Hesley

• Blake Anson

• Steve Kattman

• Lucas Chase

• Monica Strathman

• Debra Gallant

• Grischa Chandy

Contact: [email protected] [email protected]

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