Key Considerations for Implementation of

Efficient Effective HTS

Steve Young

A Presentation in four parts …

1. General overview of HTS- overview of the aims and issues of HTS

Options in more detail …

2. Generic screening Technologies3. Quality control methodology4. HTS as a process

- overview of management and organisation at Welwyn

Model linking Efficiency, Effectiveness and Economy

Input Output

Objectives

Efficiency

EffectivenessEconomy

HTS: 20k-50k samples/week (per screen)250-625 96 well plates/week65-160 384 well plates/week

Key Considerations for Implementation ofEfficient Effective HTS

Screening: The Primary Objective:

Rapidly identify a tractable chemical series with the requisite biological activity against the target of choice

(using the minimum practicable resource)

Factors which Impact Efficiency/Effectiveness

• Integration of the HTS department within the company.

• Integration of the pivotal screening activities

• Compound supply• Assay design and execution• Data analysis and tracking

• Segregation of peripheral activity (i.e. technology development).

• Automation / computerised data handling

• Reduce random error• (be alert to systematic errors)

• Quality Control• Far better to screen fewer compounds well

Integration of the HTS Department within the Company

Thorough involvement with all interested parties (i.e. biologists AND chemists) at an early stage in target evaluation / screen development

• Screen prioritisation.

• Assay to screen transition.

• Reagent requirements• recombinant material• external supply limitations (availability, delivery timescales)

• Assay format decisions.

• Compound input (number, type, concentration etc..).

• Secondary / selectivity assays (synergy / resourcing).

• Lead development (resourcing)• assay support for chemists and natural product teams (if any)

• Rescreening.

Compound Supply : Preparation / Storage

The logistics of compound supply (weighing and solubilisation) dictates the use of large pre-prepared liquid sample arrays. These

may be generated by a combination of manual and automated labour

This forces some compromises :-

• Standardisation of procedure is inflexible

• Repetitive generation of liquid stores may be wasteful

• Liquid storage accelerates decomposition

Regular monitoring of sample condition is essential

Compound Supply : Preparation / Storage Considerations

• Solvent : e.g. aqueous vs pure DMSO

• Temperature : 20oC, 4oC or lower ?

• Humidity : water uptake and compound stability

• Storage structures :- open/closed plates, densities, volumes etc.

• Shelf life : consider deterioration after 6 months

Regular monitoring of sample condition is essential.

Compound Supply : Selection of Sample Source

a) Traditional Medicinal Chemistry

Hits tractable.

Discrete entities- ready identification of pharmacophore

x Non-renewable resource.

x Decomposition in historic collections.

Compound Supply : Selection of Sample Source

b) CombiChem arrays & Bead Libraries

Hits tractable.

- Restricted diversity within libraries ideal for focussed screening simple SAR from primary screenx limitations for random screening

Novel formats offer unique possibilities. e.g:-- tagged beads

- “Abbot” HDF protocol

! Pharmacophore identification complicated by- mixture effects- bioactive precursors or side-products

Compound Supply : Selection of Sample Source

c) Natural products : plants, bacteria, fungi, marines

Exceptionally diverse.

x Pharmacophore identification difficult (impossible ?)- synergies- mixture effects- toxic contaminants

x Often have low chemical tractability.

x Contaminant interference (pigment, surfactant).

x Poor reproducibility.

x Procurement of additional material difficult.

Compound Supply : Determining Compound Input

Evaluate the minimum number of compounds which cover thelargest possible “diversity space”. Utilise the services of a

computational chemist

• If a compound is unacceptable to the chemists DO NOT screen it ! Get expert chemical input early.

• Follow up hits rapidly. Use combichem to generate analogue libraries around potential pharmacophores.

• Re-evaluate for each new target being screened.

Compound Supply : Determining Compound Input

Example of sample input:

• Pre-screen to provide comparative evaluation of assay performance

- i.e. pilot of 12,800 compounds (always screened)

• 60-70% of selected trad. med. chem. compounds- selected by project , HTS and computational chemist

• 30-40% combichem templates.

• No natural products ? (discuss !).

Compound Supply : Pooling

Can efficiency gains be achieved by pooling compoundse.g. 10 per well ?

• Disproportionate increase in ‘hit’ rate.

• Deconvolution complex- mixture effects- possibility of side reactions- logistic problems/informatics challenges

• Concentration restrictions.

• Solubility problems compounded.

Compound Supply : Miniaturisation

1x(96) 4x(384) 9x(864) 16x(1536)

36x(3456)

Reduced reagent consumption. Increased screening rate. 384 format the current default.x Increasing technical challenges.x Stores compatibility

- the control problem- reformatting considerations

x “off-the-peg” solutions for the higher densities limited/costly.

Assay Development: Important Aspects

Keep it clean, simple and cheap !

• Safety.• Robustness

- quenching, stripping, non-specific effects- use of “Robustness test kit”- reagent stability- signal:noise ratio, Z’ factor etc

• Reagent availability/cost.• Simplicity (easiest workable technique)

- minimise assay steps (e.g. liquid handling)• Validity (e.g. substrates at Km).• Waste disposal (isotopes, scintillant etc.).• Sample concentration.• Appropriate automation.• Hit threshold and performance prediction (“Rep pilot”).

Generic Screening Technologies

• SPA

• Fluorescent / colourimetric

• hTRF

• Fluorescence polarisation

• Immunoassay

• Cell based assays• in vitro assays using well characterised reagents

Summary

• Simplicity

• Innovation

• Quality control

• Integration

• Forward planning

• Multidisciplinary teamwork

• Regularly re-evaluate prejudices

Where Next ?

Generic Screening Technologies

Quality Control/performance indicators

Defining the HTS process

Generic Screening Technologies

including Specific Examples

• Suitable for use with 3H, 125I, 33P• Beads precoated with SA, Biotin, WGA, Ab’s• Versatile homogenous assay format

Generic Screening Technologies: SPA

3H-NTPdNTP’s

Capture on StreptavidinSPA beads

signal

Biotinylated primer

TemplatePol

Example: SPA Assay for Polymerase

[3H]-glycosyl Peptide Biotin

Example: SPA Assay for Glycosyl Transferase

• versatile• proven• cost-effective (ish) BUT isotopic

-emission

light signal

SPABEAD

Strepavidin[3H]-glycosyl Peptide Biotin

Streptavidin-SPA bead

Substrate Peptide Biotin

[3H]-glycosyl-CoAEnz

• Quenched-fluorescence assay for a viral protease using EDANS (fluorophore) and DABSYL (quencher)

Generic Screening Technologies: Fluorescent Intensity

• Fluorescent tracer (small molecule) binds to large molecule (enzyme, nucleic acid or antibody)

• Tracer is excited with plane-polarised light and tumbles randomly

• Quick tumbling w.r.t fluorescence lifetime - fluorescence depolarises

• Slow tumbling (molecule bound) - fluorescence remains polarised

Generic Screening Technologies: Fluorescence Polarisation

Example: Fluorescence Polarisation Kinase Assay

plane polarised excitation beam

depolarised

smallfluorescentsubstrate

rapidlyrotating

reducedrotation

4G10

large AbP-peptidecomplex

polarised

TYROSINE KINASE

ATP

ADP

• Similar to fluorescence intensity except that detection is gated

• Substantially enhanced sensitivity

• Need long lived fluorescent compounds - lanthanides (Europium, Terbium, Dysprosium Samarium)

• Lanthanides are held in ‘cages’ (chelates/cryptates) to protect them from solvents and to enhance fluorescence

• Conventional TRF requires enhancement before detection so is not single step

• Homogenous TRF (hTRF/LANCE) is preferable

Generic Screening Technologies:Time Resolved Fluorescence (TRF)

Example: Kinase TRF assay

GST

Peptide Substrate

GlutathioneY

Anti Phospho Substrate

Anti Rabbit Europium

YKinase + ATP

P

• hTRF is based on FRET (Fluorescence Resonance Energy Transfer)

• FRET relies on energy transfer from a donor to an acceptor fluorophore.

• hTRF uses Europium as the donor and APC/XL665 as the acceptor

• hTRF/FRET is versatile and suitable for enzymic, protein-protein, binding, DNA hybridisation, and immuno assays)

• Homogeneous assay

• Many reagents can be labelled with donors and acceptors (antibodies, Streptavidin, biotin)

Generic Assay Technologies:Homogeneous Time Resolved Fluorescence (hTRF)

• versatile/modular - Other Ig fusion's, kinases etc.• non-isotopic• modest reagent demands• amenable to miniaturisation

Example: hTRF Protein-Protein Interaction Assay

Biotinylatedanti rat IgG2b

XL665anti human IgG1

Protein 2:hIgG fusion

Protein 1:rIgG Fusion

Eu-labelledstreptavidin

665nm

337nm

Key features

Example: hTRF Kinase Assay

ser73

GST subx

ATP

KINASEGST sub

x Ser73-phosphate

GST subx

Ser73-P Ab

Eu labelled Ab

APC labelled anti GST

Excitation

SIGNAL

Where Next ?

Generic Screening Technologies

Quality Control/performance indicators

Defining the HTS process

Performance Indicators and Quality Control

including example data from Pilot screens

Pilot screening typically involves screening 12,800 cmpds in duplicate

• Intraplate variations• Interplate variations• Day to day variations

• Standard inhibitor IC50 (r2, Hill Coefficient)

• Compound ‘spiking’

• Reproducibility of a pilot screen

Assessing the Robustness of an Assay

• Control means (window)• standard deviation• %CV• Z’ factor (measure of assay variability incorporating SD):

Assessing the Robustness of an Assay

Z’ = 1 -3*S.D.high + 3*S.D.lowmean ( high ) – mean ( low )

Zhang et al. 1999

Routine measurements:

-10

10

30

50

70

90

110

170

0 8 16 24 32 40 48 56 64 72 80 96

150

130

Poor Assay despite “good” S:N. Z’ Factor a better indicator

S/B=10

Z’=0.1

Zhang et al. 1999

Sample #

Act

ivit

y (a

rbit

rary

un

its)

Good assay despite lower S:N. Z’ Factor a better indicator

-10

0

10

20

30

40

50

60

70

0 8 16 24 32 40 48 56 64 72 80 96

S/B=5

Z’=0.5

Zhang et al. 1999

Sample #

Ac

tivi

ty (

arb

itra

ry u

nit

s)

Origin

Hit threshold

• Distribution around origin• 10 hits highlighted• Negative skew on curve due to cmpd absorbance at 340nM

Pilot Screen - Histogram of simple absorbance assay

%age inhibition

# cm

pd

s

-100 0 100

8000

Histogram Showing Distribution of full Screen

%age inhibition

# cm

pd

s

0

0

20

40

60

80

100

120

140

160

0

10

20

30

40

50

60

70

80

90

Determination of Hit Threshold

Readout

Cu

mu

lati

ve F

req

uen

cy %

Fre

qu

ency

0

0.2

0.4

0.6

0.8

1

1.2

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42

Plate

0

0.2

0.4

0.6

0.8

1

1.2

-CNTRL

+CNTRL

STND

Z' FACTOR

COMP REG

Typical Screen Result:Activity Base Analysis

• A pilot screen can also highlight plate edge effects (Spotfire analysis) May indicate automation problems Can predict liability of complete screen

Example of a Pilot Screen

Impact of Systematic Errors

Diagnosis96 well pipetting into 384 well plates:mechanical variation

All plates averageBlue < 0%Orange > 15%Red > 40%

Visualisation of primary screening

Reflected in retest rates

7%9%

8%

76%

1 2 3 4

Quadrant for primary screen

15

28

24

60Primary Hits

Confirmed hits Retest rate

7%

10%

10%

3%

40 plates assayed twice independently• Tight correlation (some scatter around origin)• 10 hits (>50% inhibition - total agreement)• Indicates highly reproducible assay

Predicted hit rate: 0.078%Actual hit rate (full screen): 0.083%

Pilot Screen: Assessment of reproducibility

Pilot Screen: Assessment of reproducibility

Expanded view of hit correlation

Single Outlying point

Compound Run 1 Run 2 Average s.dCmpd1 95.1 95.5 95.30 0.28Cmpd2 92.8 92.5 92.65 0.21Cmpd3 67.8 66.3 67.05 1.06Cmpd4 82.7 82 82.35 0.49Cmpd5 69.4 64.8 67.10 3.25Cmpd6 92.3 91.5 91.90 0.57Cmpd7 52.4 48.5 50.45 2.76Cmpd8 96.4 95.3 95.85 0.78Cmpd9 89.9 89.1 89.50 0.57Outlier 62.2 80.3 71.25 12.80

Numerical Comparison of Independently DeterminedHit Values

Plots showing deviations between duplicates(cumulative plot for population (12800 compounds))

Abs_1: 95.94% determinations closer than 10%

Investigate how hit selection/threshold affects value of screen output

Gather similar detailed data for future/current screens

Use information to refine interpretation of quality control data generated during pilot screen and enhance effectiveness

All actives confirmed in biochemical assay using solid compound

Analysis and categorisation of hits by project chemists

Comprehensive decision data to be recorded

This will enable comparison of results and lessons between HTS campaigns for different targets.

This should highlight further areas for improvement

Further Work: (Ongoing)

Advances in Data Reporting

New format web page enables version control on screen updates to projects

Spreadsheet format single view consideration of spectrum of data:Primary (n=1)Retest (n=2)IC50 (10pt determination in duplicate) curveCurve fit parameters:

r squaredhill coefficientIC50

LCMS (compound purity/integrity) datasolid availabilitylibrary flags

There is also an opportunity to use the automation to carry out selectivity experiments: (e.g. with resistance mutants)

This process is now standard (although still being tweaked!)

Screen shot of example HTS output

Where Next ?

Generic Screening Technologies

Quality Control/performance indicators

Defining the HTS process

HTS as a Process

Overview of management and organisation at Welwyn

DEVELOPHTS

ASSAY

OBTAIN HITSFROMRCD

Project ChemistsREMOVE

UNDESIRABLECOMPOUNDS

AUTOMATEDIC50

AUTOMATEDSPECIFICITY ASSAY

THE HTS PROCESS

PROJECT GP/TAGREQUEST

HTSSCREEN

ASSEMBLEROCHE

LIBRARY

RUN HTS

SCREENCONFIRM

HITS

BIOLOGYLT ASSAY

INTERIMDATATO

PROJECT GROUPS

KEY

INFORMATION TRANSFER

INTERACTION WITH OTHER DEPTS

WORK WITHIN HTS

LCMS

All residual material to Adam for LCMS evaluation

Purity data

DATAPACKAGE TO

PROJECT GROUPS

RoNoStructureMr1o %inhib (n=1)2o %inhib (n=2)s.d. (2o)IC50Hill coefficientr2 (curve fit)Curve (graph)(Mutant IC50’s ?)Purity data (LCMS)solid availability

RUN PILOT

SCREEN

Global library management

Adam communicates all purity data to global library management

Opportunity to include ca. 4K compounds selected by Vscr methods in pilot screen and

thus provide data feedback to chemoinformatics

Fig1:Current Situation

Time in months (nominal average for typical screen in past two years)0 1 2 3 4 5 6 7 8 9 10

Retest1o

Completion

Assay development

Decision to screen

Primary screen

Maximum efficiency highflux screening

Retest

Information generation to increase

effectiveness

Pilot

Decision to screen

Assay development Pilot

Screen 1

Screen 2

Screen 3

(Optimal example of one screener being fed by one assay developer)

IC50

mutantwt

mutantwt

IC50

Pil.set.Vscr

Time in months (nominal average for typical screen in past two years)0 1 2 3 4 5 6 7 8 9 10

Primary screen

Maximum efficiency highflux screening

Retest

Information generation to increase effectiveness

Fig 2:Greater MTS Activity within HTSu could enable and accelerate generation of large numbers of IC50 data to facilitate decision making within Projects

100+ IC50’s at each step

Virtual screening

HT

SuO

utsi

deH

TSu

Ca. 4K Vscr hits

Feedback data:single conc.

n=2

GAP:No capacity for iteration

Hits from Vscr compounds

Confirmatory assays

Chemkill

Prioritised cmpds

Smart RCD analogues for

IC50

SAR

Project specific combichem libs.

100-1000’s compounds

IC50 IC50 IC50

mutantwt

mutantwt

mutantwt

Pilot

Pil.set.Vscr

Fig 3: Impact of Increasing MTS work on HTSu Function/timelines(example only - exact overlap of phases will vary)

Time in months (est)0 1 2 3 4 5 6 7 8 9 10 11

Previous screen

Next screen

Assay development

Retest

Current screen

Primary screening

mutantwt

Yellow stars indicate disruption to high efficiency primary screening

Primary screen

Analogue CombiC

mutantwt

mutantwt

IC50

CombiCAnalogue

mutantwt

mutantwt

Pilot

Pilot

Pil.set.Vscr

Where Next ?

Generic Screening Technologies

Quality Control/performance indicators

Defining the HTS process