phenotypic high throughput screening (hts)...phenotypic high throughput screening (hts) roger clark...

Phenotypic High Throughput

Screening (HTS)

Roger Clark

Associate Principal Scientist

Global HTS Centre

Discovery Sciences

Past success & future

challenges

2

DISCOVERY

SCIENCES

Discovery Sciences | Screening Sciences - Global HTS Centre

1. HTS & the Drug Discovery process

2. Phenotypic HTS – Some definitions

3. The Phenotypic HTS challenge

4. Adding value through High Content annotation

5. When is a RIA target not just a RIA target?

6. Conclusion

1. Drug Discovery Process

Global HTS Centre Support for multiple Therapeutic areas & External collaborators

4 Discovery Sciences | Screening Sciences - Global HTS Centre

CVMD

Neuroscience

RIA

Oncology

Infection

HTS

FBLG

ELT

Sub set

The Drug Discovery process

5

Bleicher KH, Bohm HJ, Muller K, Alanine AI., Nature Reviews, 2003, 2, 369-378

HTS



Seems simple... What’s the problem?

A screening paradigm that enables coverage of broad chemical diversity

in a single activity, with few target prerequisites. Hundreds of thousands

of compounds can be screened in a given experimental run, in order to

deliver fast, efficient and (most crucially) consistent data.

Determine at what point a compound is active

Select the ‘active’ wells

Follow the remainder workflow (shown opposite)

Find a blockbuster drug that makes a meaningful

difference to patients lives

HTS (Diversity Screening)

HTS

The problem of false positives

• Single point HTS data can be noisy when compared with XC50 data

• Inactive compounds vastly outnumber active compounds

• We typically underestimate the problem of false positives

• A lot of false positives can make it much harder to find the true positives

• For example:

- Imagine we have a population of 1,000,000 compounds

- Our assay is 99.9% accurate (so 99.9% of active compounds are called correctly and 99.9% of

in-actives are called correctly)

- Let’s assume 1 in 1000 compounds are active (this is actually a pretty high ratio)

- From the 1,000,000 compounds we would expect: • 0.999 x 1000 = 999 true positives

• 0.001 x 999,000 = 999 false positives

- If the true hit rate was 1 in 10,000 then we would have 10 false positives for every true positive • 0.999 x 100 = 99.9 true positives

• 0.001 x 999,900 = 999.9 false positives


But we do find hits….

1 : 1

1 : 10

Success varies by target class & technology?

Biochemical & Cellular (target-based & phenotypic)

8 Discovery Sciences | Screening Sciences - Global HTS Centre Clark, R. et al. (2013) European Pharmaceutical Review, 18(6)

** Success taken as campaigns which identified 1 or more chemical series & active chemistry resource deployed to progress these

2. Phenotypic HTS? … Some definitions

Phenotypic HTS?

HTS (Diversity Screening) A screening paradigm that enables coverage of broad chemical diversity

in a single activity, with few target prerequisites. Hundreds of thousands

of compounds can be screened in a given experimental run, in order to

deliver fast, efficient and (most crucially) consistent data.

Phenotypic HTS A diversity screening approach which employs a functional cellular assay

as the primary screen. In this instance it will be unclear as to MOA of the

small molecules that appear as ‘hits’


Why would we run Phenotypic Drug Discovery?

11

• Target Based drug discovery alone does not deliver a sustainable big Pharma

model

• Phenotypic Screening offers an opportunity for

• Novel Molecules

• Novel Targets

• Novel indications for existing chemical equity

First-in-class Follower drugs

Swinney and Anthony, Nature Reviews, 2011, 10, 507-519


Historic (Target-based vs. Phenotypic)


Growth of Cellular HTS campaigns for Oncology


** Success taken as campaigns which identified 1 or more chemical series & active chemistry resource deployed to progress these

Cellular campaigns appear consistently

more successful

So why don’t we always screen in phenotypic assays?...

16 Deconvolution…

Running phenotypic assays is difficult…

• Complex and time-consuming assays to run at scale

• Automation can be tied-up for long periods of time

• Edge-effects for extended time-point assays can lead to ‘wasted space’ on plates

• Difficult to understand SAR - requires more annotation

• However…. Read-out can be fairly simple & cost-effective e.g. Proliferation • Key is to pick the right cell line (mutant vs. WT)

• It might be logistically complex, but…..


…. Biology is complex too!…


3. The phenotypic HTS challenge: HTS can lead to a complex data deluge without proper annotation… How do we progress phenotypic hits?

Compound set stratification on diversity


Chemical space (diversity)

Incre

asin

g c

luste

r p

op

ula

tio

n

(as m

ore

‘la

yers

’ scre

en

ed

)

What if we thought in more dimensions?...

?

? ?

?

?

Stratification on annotation?....

Multi-dimensional Data Cube


Mining historical compound activity

data vs. cell line expression data can

help to identify pathways

‘Black-holes’ in activity data from

historic layer screening vs. full

collection

Phenotype

Expression

profile

Target

Activity

Mutation

status

Tox

liability

Cell

permeability

Annotation never fully complete

Data cells with higher annotation = screened preferentially

Requires capability to build screening sets on-the-fly?

Toxicity is a key reason for failure of compounds in the clinic

- Evidence to suggest that compounds with pIC50 >4 are 5 times more likely to

cause whole organ toxicity than compounds with pIC50 <4

Mammalian Tox annotation

Using a phenotypic endpoint to annotate


Early view of Tox liability should enable early decisions on series

progression or compound set selection for limited phenotypic screens

Keep in mind that certain disease settings (eg. Oncology) may well

want compounds that cause cell death

Key is to annotate compounds to further populate the Data Cube

Simple assay run in THP-1

(monocyte derived line) could allow

pre-emptive full collection screening

% effect at 10uM % effect at 50uM

Compounds active in whole organism phenotypic screen

Profiled for mammalian tox liability

Proliferation… an easy phenotype to screen?

Particularly for Oncology…


SYTOX Green (504EX/523EM)

Hoechst nucleic acid stain (350EX/461EM)

CyQUANT Assay (480EX/535EM)

Shouldn’t we just pick the right cell line and screen the whole collection against this line to find hits?

4. Case study – IDOL (E3 ligase) Adding value through High Content Annotation

Sawamura T Clin Chem 2009(55:12) 2082-2084 2009

IDOL is expressed in the liver and in peripheral WBCs

IDOL a new player in regulation of

LDL receptor (LDLr) levels

IDOL also targets VLDLr and ApoER2

Discovery Sciences | Screening Sciences - Global HTS Centre 25

HEK293 clone expressing LDLR-GFP, 48 h post

transient transfection with Wild Type or Mutant IDOL


Hoechst LDLR-GFP

Wild Type IDOL

Untransfected

Mutant IDOL

Hoechst + LDLR-GFP

Science 325, 100(2009), Tontonoz

27

Schematic of assay (IDOL LDLR-GFP + wt IDOL) DMSO Max signal control

Assay performance: Quality Control Plate


IDOL HTS validation – Whole well FI

Adding value with imaging

Cell Seeding

Incubation at

37ºC for 20hrs

Compound

dosing

Incubation at

37ºC for 6 hrs

Fixation +

Hoechst

Incubation at

RT for 20mins

Measure FI at

485/520nm

LDLR-GFP HEK293 parental

Image 2x channels

1x fov

Analysis on-the-fly

IDOL

LDLR-GFP

0.14%

HEK293

parental

0.07%

0.09%

GeneData

Screener

Cellomics DB Image Store

IDOL: Image based phenotypic analysis

Max signal control AZ1

(False positive)

False positive (FP) rate increased

through fluorescent compounds

Images analysed for distinctive

features (granules, texture,

area measurements).

Supervised classification

methods used to cluster false

positives and reject them from

the pipeline

Other forms of FP (toxic

compounds, etc.) can be

integrated in the model.

AZ1

(False positive)

DMSO

Max signal control

Compound A Compound B Compound C

Active only in LDLR-GFP assay Active in both LDLR-GFP & HEK293

parental assays

False positives characterisation performed using the HTS validation compound set

Different MOAs can potentially be distinguish at this early stage of the pipeline (Compound A vs. B)

View of what ‘active’ means can change with increasing observations over a screen

IDOL: Image based phenotypic analysis

Discovery Sciences | Screening Sciences – Global HTS Centre

5. Q. When is a RIA target not just a RIA target?

A. When it’s also an Oncology target

RIA goes looking for inhibitors of T-Cell

proliferation…

… And finds chemical equity with excellent in-vitro efficacy

32 Innovative Medicines | Respiratory Inflammation & Autoimmune

Target deconvolution


Total

protein

Photolabelled

protein

MCT1 target identified by

photo-affinity labelling

• Photo-affinity labelled probes built to pull-down molecular target • Sub cellular fractionation 2D Gel chromatography Mass Spec

• MCT1 identified as probable molecular target

NH2

COOH

Extracellular

Intracellular

NH2

COOH

Extracellular

Intracellular

MCT % ID

100

27

11 27

12 22 23

9 23

Lactate transporter

MCT

38 4 42 6 7 26

5 28

14

8 22

Lactate transporter

10 22

58 2 1

3

13 31

MCT1 Transporter and family

• 12 TM spanning symporter

• Transports lactate & pyruvate along with protons in / out of cell



MCT1 activity confirmed in functional assay

MCT Inhibitor MCT-1

Lactate/H+

Activated

T-cell

MTX Leflunomide

TCR

MHC/Ag

Calcineurin

NFAT IL2

CsA

FK506

IL2R

Rapa

TOR

Gene

transcription

Glycolysis

Glucose Lactate

DNA synthesis

Nucleotide

precursors

Proliferation

Novel mechanism of immunosuppression

You might think you know where you’re going…

Oncology iMed discovers that certain haematological & solid tumours are

extremely sensitive to MCT1 inhibition

Oncology pick-up chemical equity from RIA project and validate in

relevant cancer lines.

AZD3965 currently in Phase 1 trials in partnership with CRUK

37

… but when targets stop being the focus you can end up somewhere different…

6. Conclusion

The only way to truly deliver a Phenotypic

portfolio is through teamwork….


Building the right assays

… in the right cell lines

… screened at the right scale & diversity

…. To enable discovery of:

Novel Molecules

Novel Targets

Novel indications for existing equity

To conclude….

Phenotypic screening is not a new paradigm, but rather a realisation that the

reductionist approach may not be the only way to identify new molecules of

therapeutic value

Phenotypic screening output will take longer to annotate fully and deconvolute

appropriately.

Rationalising the compound set before screening is an approach to simplify

deconvolution Won’t discover new chemistry, but might find new indications /

targets.

Screening every compound through every target-based screen helps to build

the eternally expanding ‘data cube’


Of course – Breaking down all the metrics and attempting to rationalise phenotypic screening as a paradigm is a fairly reductionist approach..... You can’t underestimate serendipity!

Thanks to:

Mark Wigglesworth

Dave Murray

Carolyn Blackett

Sinead Knight

Helen Plant


Thierry Dorval

Helen Boyd

Johan Brengdahl

Sanna Engberg

Graham Belfield

Clare Murray

42

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phenotypic high throughput screening (hts)...phenotypic high throughput screening (hts) roger clark...

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