cardiac microtissues as a model to predict effects on ... · cibenzoline -ve inotrope 1.42 100...

Cardiac Microtissues as a Model to Predict Effects on Cardiac Contractility

James PillingELRIG Pharmaceutical Flow Cytometry & Imaging 22nd November 2016

Contents

High Content Biology at AstraZeneca

Cardiotoxicity as a cause of drug attrition

Functional 3D Micro-Tissues for Cardiotoxicity

Development of an In Vitro Imaging Assay

2

5 Summary

22nd November 2016 IMED Biotech Unit | Discovery Sciences

4

3

2

1

1. High Content Biology at AstraZeneca

4

Sweden

Boston HCB Core Facility, Cambridge

MedImmune, Cambridge

HTS Centre, Alderley Park

High Content Imaging across AstraZenecaA global network of scientists


High Content BiologyAn Introduction

5

• We work in partnership with all therapy areas across AZ to develop and apply

high-content phenotypic assays for Target Identification (Phenotypic Drug

Discovery) and Validation, Mechanistic Understanding and Toxicity Prediction

• We are focused on developing and applying capability across three areas:

imaging and analytics, cell biology and functional genomics

• We also aim to provide support for all High-Content Imaging & Flow Cytometry

platform users worldwide through a cross-AZ/MedI Imaging & Flow Cyt

Forum and Open-Access Cell Sciences Laboratory and Scientific Compute

Platform


6

High Content Imaging across AstraZenecaOpen access core facility in Cambridge, UK

Cells

Image

Storage

Cells

Data processing

Cells

Image

Acquisition

Cells

Image analysis

Cells

Assay

Automation

• Operating as an open access lab means we have uses from multiple disciplines with divergent needs.

• Architectural Complexity – Multiple imaging platforms, metadata databases and analysis requirements.


2. Cardiac Toxicity

Cardiotoxicity is a Major Cause of Attrition

Trends and Observations

8

Need for better Detection, Risk Assessment and Translation

Adapted from J Pharmacol. Toxicol. Methods 2008, 58 (2)

Ref: Nature Rev Drug Discovery 13 (Feb 2014), 85-89

Annual FDA Approvals since 1993

Num

ber

of

dru

gs a

ppro

ved

0

10

20

30

40

50

60

New Molecular Entities…Biologics Licence…

High attrition due to

lack of efficacy

lack of safety

Increasing costs for

projects

Number of NMEs

static

Disease Relevance

Cost

Throughput

Challenges to front-

load disease

relevant models


34%

14% 15%

3% 4% 3%

Main Reasons for drug discontinuation during non-clinical or clinical

development, 1993-2006

We want to avoid drugs that… Since that can/may lead to…

Increase QT interval Torsades de Pointes

Decrease QT interval Cardiac arrhythmia

Increase QRS duration Ventricular Tachycardia

Increase PR interval Atrio-Ventricular block

Increase heart rate Myocardial infarction/stroke

Increase blood pressure Myocardial infarction/stroke

Decrease blood pressure Syncope

Decrease cardiac contractility Heart failure

Damage heart values Heart failure

Damage cardiac myocytes Heart failure

ECG

Haemodynamics

Structure

Cardiovascular effects that we want to avoid

9

This shapes what we want to assess in nonclinical studies

ClinicalPre-clinicalLead OptimizationLead

GenerationTarget

Selection

In silico In vitroMolecular or

“Black box”

In vivoRoutineor

Bespoke

Species Safety

PharmacologyEffects on function

(single dose)?

Toxicology

Effects on structure (repeat dose)?

Non-

rodent (usually dog)

ECG, Blood

Pressure, Heart Rate

Histopathology

& Clinicalpathology

Rodent

(usually rat)

Not required Histopathology

& Clinicalpathology

10 22nd November 2016 IMED Biotech Unit | Discovery Sciences

This means in vitro assays ideally should:

• Be predictive of risk in man

• Drive understanding of SAR

• Have a short loop-time

• Be low cost

• Avoid use of animal tissues

1. Stem cell-derived

cardiomyocytes

2. Complex culture

Pre-clinical Cardiotoxicity Screening Portfolio

3. Functional 3D Micro-Tissues for Cardiotoxicity

Improved Screening

Monitoring the frequency and amplitude of hiPS-CM calcium transients produces an

integrated readout of cardiac function influenced by multiple cellular-factors. Overall good

correlation to cardiac contractility in primary canine cardiomyocytes.

Applicable to detect acute direct inotropic agents.

hiPS-CMs

FLIPR Tetra

Measuring Calcium transients with hiPS-Cardiomyocytes

FLIPR 30 min vs canine ionoptix

0 1 2 3 4 5 6 7 8 9 100

1

2

3

4

5

6

7

8

9

10

Spearman r 0.7886

FLIPR 30 min pIC50

Can

ine I

on

Op

tix p

IC50 Parameter Definition Score

Sensitivity Ability to detect true positive

compounds

77%

Specificity Ability to detect true negative

compounds

70%

Pointon et al .Toxicological Sciences (2015);144(2):227-37


R= 0.75

2D Monolayers Provide Limited Risk Assessment

• Measurement of Ca2+ transients in monolayers

does not give mechanistic information.

• Imaging beat rate gives a direct measurement of

phenotype.

• Ca2+ based readouts are insensitive to ATPase

independent mechanisms of toxicity eg.

actin/myosin inhibitors (blebbistatin).

13

10-11 10-10 10-9 10-8 10-7 10-6 10-5 10-4

0

50

100

150

200

250

hIPS-CMs peak height Canine CMs sarc. short.

hiPS-CM calcium flux

[Digoxin] M

Resp

on

se (

% c

on

tro

l)

22nd November 2016 IMED Biotech Unit | Discovery SciencesPointon et al .Toxicological Sciences (2015);144(2):227-37

Development of a more predictive cardiac in vitro model

14

Three key cardiac cell types reformed into a

human 3D micro-tissue using ULA plates

200μm

Bright-field

iPS-derived HumanCardiachCMEC

Day 14

After 2 weeks the spheroid

begins to beat

Day 0 Day 2-3

Cell mixture is seeded into

ULA 384 well plate

Cells are counted and mixed

together at desired ratio

•Micro tissues formed in 384 well format

•Human Primary cells from commercial sources

•Mixed cell types dispersed within spheroid


Cardiac structure: 3D microtissues


Cell population mixed throughout the microtissue

H&E Staining

Nuclei

α-actinin

Collagen I

CD31

16

Pharmacological characterisation

10

11

12

13

14

15

No pacing 1Hz 2Hz 3Hz

10 Sec

Time

Peak h

eig

ht

•Cardiac Microtissues respond to electrical pacing.

•Are stable over several weeks

•Sensitive to inotropes


17

5 minutes treatment

Verapamil – calcium channel blocker, negative inotrope

Isoproterenol – b1/ b2 adrenoreceptor agonist, positive inotrope

Control – 0.1% DMSO

Cardiac Microtissues respond to Inotropes

Isoproterenol 10 µM Verapamil 1 µMControl


4. Development of an In Vitro Imaging Assay for

Functional Cardiotoxicity

Image CaptureImage Capture on the ImageXpress XLM

• Uses a series of 5 journals to call “Stream

Acquisition” function and fluidics operations.

Imaging• “Stream Acquisition” decoupled from database and

images stored locally.

• Image frame rate faster as a consequence as less

image/metadata saving time.

• Acquired with TL at 1 ms exposure bin (4) gives

frame rate of ~ 35fps

19

≈400 frames

I(n)I(400)

I(1)

Compound Treatment• Sample addition under timed control. Incubation

time of 5 minutes interleaved with pre and post

treatment image.

• 180 wells processed in ~ 5 hours versus ~15 hours

for sequential.


Capturing Movement

Quantifying movement in a

heterogeneous label free

image is challenging.

Optical flow approach used to

capture pixel based vectors.

22nd November 2016 IMED Biotech Unit | Discovery Sciences22

Cardiac contractility: 3D microtissues

Cardiac microtissues

ImageXPresspre-image

Compound Addition

ImageXpress post-image

Optical Flow Analysis

0 1 2 3 4 5 6 7 8 9 100.15

0.20

0.25

0.30

0.35

0.40

0.45

0.1% DMSO

Time (Seconds)

Vecto

r m

ag

nit

ud

e (

a.u

.)

0 1 2 3 4 5 6 7 8 9 100.15

0.20

0.25

0.30

0.35

0.40

0.45

1M verapamil

Time (Seconds)

Vecto

r m

ag

nit

ud

e (

a.u

.)

10-8 10-7 10-6 10-5 10-4

0

50

100

150

[Verapamil] M

Acti

vit

y (

% c

on

tro

l)

Development of a plate based approach

Experimental workflow developed to allow plate based

assessment


22

Automation of Signal Processing

IMED Biotech Unit | Discovery Sciences

Signal processing – quantifying the output from the optical flow trace.

A combination of Savitzky-Golay filtering and

Wavelet processing techniques enabled

automation signal processing and QC

22nd November 201624

23

Demonstrating Predictivity of the Assay

• Validation set of 42 compounds tested

• 6pt dose response

• In duplicate, n=4

• Compound set representing positive and

negative inotropes and negative cardiotoxins.

Parameter Definition

Sensitivity Ability to detect true positive

compounds

91.3%

Specificity Ability to detect true negative

compounds

80.3%

Accuracy Proportion of correct results

detected

90.5%

Direction of

Effect

Proportion of correctly

determined effect direction

96.7%


Translation between assay approaches in vitro and in vivo

3D microtissue assay correlates well

with dog myocyte sarcomeric

shortening and measurement of

calcium transients

Greater the safety margin in vivo the

less likely to be predicted in vitro


R=0.7 R=0.8

Assay translates between measurement modality

and between in vitro and in vivo models

Th

era

peu

tic I

nd

ex

(EC

50/c

max)

5. Summary

25

Summary

• 3D Tri-culture Microtissues are a good physiological model of

cardiac contractility.

• A flexible imaging and data analysis approach can be built to

quantify complex endpoints

• Compound treatment can be applied at throughput to support early

project risk assessment


Discovery SciencesYinhai WangThierry Dorval

DSM Amy PointonCaroline Archer

Chris Pollard

University of LiverpoolStephanie Ravenscroft

Molecular DevicesBen Howarth

Acknowledgements


5. Additional Information

Validation Compound Set

Drug

In vivo

contractility

effect

Cmax (μM)

Top

concentration

tested (μM)

Amitriptyline -ve inotrope 0.95 30

Atenolol -ve inotrope 3.75 30

AZ1 +ve inotrope 38.4 100

AZ2 +ve inotrope 113 100

AZ3 -ve inotrope 421 300

AZ4 -ve inotrope 4.31 100

AZ5 -ve inotrope 168 300




Bepridil -ve inotrope 6.2 10

Chloroquine -ve inotrope 0.96 100

Cibenzoline -ve inotrope 1.42 100

Digoxin +ve inotrope 0.001 10

Diltiazem -ve inotrope 0.35 100

Disopyramide -ve inotrope 20.61 100

Dobutamine +ve inotrope 0.81 10

Doxorubicin -ve inotrope 15.34 100

Epinephrine +ve inotrope 0.002 1

Flecainide -ve inotrope 1.68 100

Glibenclamide +ve inotrope 0.4 100

Haloperidol -ve inotrope 0.04 30

Isoproterenol +ve inotrope 0.01 1

Levosimenden +ve inotrope 0.13 10

Milrinone +ve inotrope 1.18 100

Nifedipine -ve inotrope 0.19 10

Quinidine -ve inotrope 11.29 100

Sunitinib -ve inotrope 0.25 30

Verapamil -ve inotrope 0.5 10

Drug

In vivo

contractility

effect

Cmax (μM)

Top

concentration

tested (μM)

Amoxacillin Non-inotrope 300

Aspirin Non-inotrope 100

AZ6 Non-inotrope 100

Captopril Non-inotrope 100

Cimetidine Non-inotrope 100

Enalapril Non-inotrope 100

Furosemide Non-inotrope 100

Lapatinib Non-inotrope 100

Lisinopril Non-inotrope 3

Paracetamol Non-inotrope 100

Pravastatin Non-inotrope 100

Ramipril Non-inotrope 100

Tolbutamide Non-inotrope 100

#

Positive Inotropes 9

Negative Inotropes 20

Non Inotropic 13

30

Measurement Parameters

Name Meaning

Number of Peaks The number of peaks per 5 minutes of signal.

Ave. AmplitudeThe average value of the amplitudes per 5 minutes of

signal.

Ave. Amplitude

Robust

Robust mean of the amplitudes per 5 minutes signal.

Robust mean only consider the data points within 10% -

90% quintiles’ of the detected peak amplitude values –

hence eliminating outliers.

Median Amplitude The median value of the amplitudes per 5 minutes signal.

Flag

Indicate if the software is confident about these results. If

yes, a word “Good” is written. If not, an “Unsure” is

written, which suggest users to manually compare the

signal plot.

URLIt gives a (clickable) link to where the plot image is stored

for easy comparison.

31

• A core of multidisciplinary permanent staff

supplemented by post-docs, PhD students

and research collaborators from academia

and industry.

• Key remit is phenotypic assay development

and application using high content imaging

modalities.

• Our assays typically involve the use of

complex & physiologically relevant cell

systems: Human cells, primary cultures,

tissue slices, differentiated stem cells, co-

culture and 3D.

High Content Imaging across AstraZenecaHigh Content Biology Group, Cambridge UK

Target Validation

Target Discovery

Predictive Toxicity

Mechanistic Understanding


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