enabling cancer immunotherapy: from discovery to combinations

1

Enabling Cancer Immunotherapy:

From Discovery to Combinations

Abhi Saharia, PhD

2

The Cancer-Immunity Cycle & Targeted TherapiesMultiple potential intervention steps to develop anti-cancer therapies

Oncology Meets Immunology: The Cancer-Immunity Cycle. Immunity. 39 (1): 1-10

3

Fundamental questions for drug development

Screening & Lead

Optimization

Efficacy & Biomarker Selection

Safety & Pre-clinical

Studies

Clinical Combination Strategies

How do I screen for a functionally active lead molecule?

How can I determine efficacy in a human tumor microenvironment (TME)?

Is my drug active outside the context of the TME?

How does my drug act in a combination therapy?

Translating Discoveries into Drugs

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Target-based & Phenotypic Assays from DiscoverXProducts and services to support drug development

0% KinasesGPCRs Interleukins Pathways Epigenetics Checkpoint

100%

Primary Cell Profiling

Depth

of

Covera

ge

28

4

41

0

40

35

34

6

5

From drug discovery to clinical combinations

Screening & Lead

Optimization



Studies


Enabling Anti-cancer Immunotherapies

PathHunter®

Checkpoint AssaysPathHunter® Bioassays for

QC Lot Release Testing

BioMAP®

Oncology Systems

BioMAP

Diversity PLUS™

BioMAP®

Combo ELECT

6

Challenges:

Requires specific cell-based assays for each target

Requires human cells with complex TCR signaling

Donor variability

Longer assay times and complicated protocols

Screening & Lead

Optimization



Studies


How Do I Screen for Functionally Active Lead Molecules?

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Cancer Cell

Immune Cell

EFC Technology

PD-1 Signaling Assay

PathHunter® Checkpoint AssaysIdeal for screening and lead optimization

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1 0 -1 0 1 0 -9 1 0 -8 1 0 -7 1 0 -6 1 0 -5 1 0 -4

0

2 0 0 0 0

4 0 0 0 0

6 0 0 0 0

8 0 0 0 0

A n ti-P D -1 D ru g [g /m L ]

RL

U

P e m b ro lizu m a b

N iv o lu m a b

HillSlope

IC50

Pembrolizumab

-2.010

6.630e-009

Nivolumab

-1.921

9.398e-009

Robust Screening & Lead Optimization Platform

1 0 -1 1 1 0 -1 0 1 0 -9 1 0 -8 1 0 -7 1 0 -6 1 0 -5 1 0 -4

0

1 0 0 0 0 0

2 0 0 0 0 0

3 0 0 0 0 0

4 0 0 0 0 0

RL

U

C o m p o u n d [M ]

X L -2 8 8 0

D a s a tin ib

HillSlope

IC50

Dasatinib

-1.979

5.762e-009

XL-2880

-1.045

4.740e-007

Screen Biologics in the PathHunter PD-1 Assay

Screen Small Molecule Inhibitors in the PathHunter PD-1 Assay

PathHunter® assays support both biologics and small molecules

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PD-1

OX40

CD40

HVEM

VISTA

TIM3

Biologically relevant responses for co-stimulatory & co-inhibitory agents

Easy protocol with results in <5hrs

Supports development of biologics and small molecules

Screen confidently with highly sensitive response

Applicable for QC lot release of biologic drug

Summary for PathHunter® Checkpoint Assays

1 0 -1 2 1 0 -1 1 1 0 -1 0 1 0 -9 1 0 -8 1 0 -7 1 0 -6 1 0 -5

0

5 0 0 0 0

1 0 0 0 0 0

1 5 0 0 0 0

O X 4 0 S ig n a lin g A s s a y

O X 4 0 L [g /m L ]

RL

U

+ O X 4 0

n o O X 4 0

Assays currently available

Enabling screening & lead optimization for co-stimulatory & co-inhibitory molecules

10

Challenges:

In vitro assays do not mirror the complexity of TME

Animal-xenograft models are not high throughput

Lack of appropriate response biomarkers

How Can I Determine Efficacy in a Human TME?

Screening & Lead

Optimization



Studies


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Large or Small

Molecules and

Combinations

BioMAP® Models of Human Disease BiologyValidated systems that provide predictive results

BioMAP Data &

Knowledgebase

56+ BioMAP

co-culture systems

Human Primary Cells

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Development of BioMAP® Human TME ModelsBioMAP systems mirror intratumoral immune suppression

48h Assay Incubation

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Validation of BioMAP® Human TME ModelsBioMAP systems mirror intratumoral immune suppression

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Validation of BioMAP® Human TME ModelsBioMAP systems are robust and reproducible

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CD87/uPAR

CEACAM5 / CD66e

Collagen I

Collagen III

Keratin 20

P

PBMC Cytotoxicity

sGranzyme B

sIFNg

SRB

sVEGF

tPA

uPA

Lo

g R

atio

Profiles

Trametinib, 1.5 nM

Trametinib, 510 p...

Trametinib, 170 p...

Trametinib, 19 pM

StroHT29

sGranB

CEA

a

uP

AR

CE

AC

AM

5

Co

llag

en

I

Co

llag

en

III

Ke

r

P

PB

MC

Cyto

toxic

ity

sG

ran

zym

e B

sIF

Ng

SR

B

sV

EG

F

tPA

uP

A

Lo

g R

atio

Profiles

Trametinib, 1.5 nM

Trametinib, 510 pM

Trametinib, 170 pM

Trametinib, 19 pM

StroHT29

sGranB

CEACAM5

a


Validation of BioMAP® Human TME Models

BioMAP profile shows compound effects on TME biomarkers

Protein Biomarker Readouts

Rela

tive E

xpre

ssio

n (

Log R

atio)

95% Historical Control Envelope

BioMAP profiles reveal translational response biomarkers

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Rela

tive E

xp

ressio

n L

evels

|L

og

10

ratio|d

rug/v

ehic

le c

ontr

ol)

Pembrolizumab Restores Immune ResponsesIncreased cytokine production with decreased tumor-cell derived sVEGF in human TME

Identify response biomarkers

CD

87/u

PA

R

CE

AC

AM

5 /

CD

66e

Colla

ge

n I

Co

llage

n III

Ke

ratin

20

P

PB

MC

Cyto

toxic

ity

sG

ran

zym

e B

sIF

Ng

SR

B

sV

EG

F

tPA

uPA

CD

40

CD

87

/uPA

R

CE

AC

AM

5 /

CD

66e

Colla

ge

n IV

Ke

ratin

20

PB

MC

Cyto

toxic

ity

sG

ran

zym

e B

sIF

Ng

SR

B

Profiles

Pembrolizumab, 50000 ng/...


Pembrolizumab, 1900 ng/ml


StroHT29 VascHT29

Keratin 20sGranB

sIFNg

sVEGF

Keratin 20sGranB

sIFNg

sTNFa

Profiles





Keratin 20sGranB

sIFNg

sVEGF

Keratin 20sGranB

sIFNg

sTNFa

sTNFa

VascHT29StroHT29


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Shared Activities of Pembrolizumab and Nivolumab Both agents similarly increase cytokine production and decrease sVEGF levels

Confirm target class signature biomarkers

CD

87

/uP

AR

CE

AC

AM

5 /

CD

66

e

Co

llag

en

I

Co

llag

en

III

Ke

ratin

20

P

PB

MC

Cyto

toxic

ity

sG

ran

zym

e B

sIF

Ng

SR

B

sV

EG

F

tPA

uP

A

CD

40

CD

87

/uP

AR

CE

AC

AM

5 /

CD

66

e

Co

llag

en

IV

Ke

ratin

20

PB

MC

Cyto

toxic

ity

sG

ran

zym

e B

sIF

Ng

SR

B

Profiles


Nivolumab, 10000 ng/ml

StroHT29 VascHT29

Keratin 20

sGranB

sIFNgsTNFa

sVEGF

sGranB

sIFNg

Profiles


Nivolumab, 10000 ng/ml

Keratin 20

sGranB

sIFNg

sTNFa

sVEGF

sTNFasGranB

sIFNg

StroHT29 VascHT29


Rela

tive E

xp

ressio

n L

evels

|L

og

10

ratio|d

rug/v

ehic

le c

ontr

ol)

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Both Large And Small Molecules Can Be Tested

Screen and prioritize drug candidates

Anti-CD73 antibodies and Paclitaxel show increased immune cytokine production

CD

87

/uPA

R

CE

AC

AM

5 / C

D6

6e

Co

llage

n I

Colla

gen

III

Ke

ratin

20

P

PB

MC

Cyto

toxic

ity

sG

ran

zym

e B

sIF

Ng

SR

B

sV

EG

F

tPA

uPA

CD

40

CD

87

/uPA

R

CE

AC

AM

5 /

CD

66e

Colla

ge

n I

V

Ke

ratin

20

PB

MC

Cyto

toxic

ity

sG

ran

zym

e B

sIF

Ng

SR

B

Profiles

Paclitaxel, 14 nM

,

StroHT29 VascHT29sIFNg

sTNFa

sVEGF

uP

sIFNg

Profiles

Paclitaxel, 14 nM

,

sIFNg

sTNFa

sVEGF

uP

sTNFa

sIFNg

StroHT29 VascHT29

Anti-Human CD73 was profiled as part of a collaborative study with MedImmune/AZ


Rela

tive E

xp

ressio

n L

evels

|L

og

10

ratio|d

rug/v

ehic

le c

ontr

ol)

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Challenges:

Current approaches rely on single cell or organ types

Bias towards specific targets and target pathways

Less complex and often isolated biology

Limited testing of broad-scale human biology with drug

Is My Drug Active Outside the Context of the TME?

Screening & Lead

Optimization



Studies


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F

P

f

P

F

f f

K

P

tP P

P

C

K

P

tP P

F

P P

f

C

P

f

P

P

P

Lo

g R

atio

Profiles

Erlotinib, 1.1 uM

Erlotinib, 370 nM

3C 4H LPS SAg BT BF4T BE3C CASM3C HDF3CGF KF3CT MyoF lMphg

uPAR uPAR

P

tPAuPA

uPAR

EGFR

F

P

f

P

F

f f

K

P

tP P

P

C

K

P

tP P

F

P P

f

C

P

f

P

P

P

Lo

g R

atio

Profiles

Erlotinib, 1.1 uM

Erlotinib, 370 nM


uPAR

Eot3

uPAR

IL1a

MMP1

MMP9

P

tPA

uPA

uPAR

EGFR

IL8

Evaluation of Erlotinib Effects Outside the TMEBiomarker activity of EGFR-inhibitors

• Inform mechanism of action

• Identify biomarkers of efficacy

Activities detected at both concentrations are annotated

Re

lati

ve

Ex

pre

ss

ion

Le

ve

ls

|Lo

g10

ratio

|dru

g/v

eh

icle

co

ntr

ol)

Monocyte Activation

T cell Activation

B cell Activation

Macrophage Activation

Matrix-modulation, fibrosis, tissue remodeling responses

Vascular EC Inflammation

Epithelial Inflammation and Matrix Remodeling

Vascular SM Inflammation

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F

P

f

P

F

f f

K

P

tP P

P

C

K

P

tP P

F

P P

f

C

P

f

P

P

P

Lo

g R

atio

Profiles

Paclitaxel, 41 nM

Paclitaxel, 4.6 nM


TF uPAR

uPAR

sIgG

F

P

f

P

F

f f

K

P

tP P

P

C

K

P

tP P

F

P P

f

C

P

f

P

P

P

Lo

g R

atio

Profiles

Paclitaxel, 41 nM

Paclitaxel, 4.6 nM


TF uPAR

IL8uPAR

VEGFR2

sIgG

CD69

Proliferation

Proliferation

Proliferation

Evaluation of Paclitaxel Outside the TMEBiomarkers for cardiovascular AE, anti-angiogenic and anti-metastatic potential

• Inform mechanism of action

• Identify activities that may highlight potential for adverse events

Activities detected at both concentrations are annotated

Re

lati

ve

Ex

pre

ss

ion

Le

ve

ls

|Lo

g10

ratio

|dru

g/v

eh

icle

co

ntr

ol)

Monocyte Activation

T cell Activation

B cell Activation






22

F

P

f

P

F

f f

K

P

tP P

P

C

K

P

tP P

F

P P

f

C

P

f

P

P

P

Lo

g R

atio

Profiles




F

P

f

P

F

f f

K

P

tP P

P

C

K

P

tP P

F

P P

f

C

P

f

P

P

P

Lo

g R

atio

Profiles




Evaluation of Pembrolizumab Outside the TMEAnti-PD1 antibodies are not inherently inflammatory

• Confirm selectivity• Determine on/off target effects and even target related secondary effects

• Inform mechanism of action• Nivolumab has an identical profile in this panel

Monocyte Activation

T cell Activation

B cell Activation






No activities detected

Re

lati

ve

Ex

pre

ss

ion

Le

ve

ls

|Lo

g10

ratio

|dru

g/v

eh

icle

co

ntr

ol)

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Challenges:

Pre-clinical testing is technically challenging

Current models are poorly predictive & expensive

Often directly tested in patients

Screening & Lead

Optimization



Studies


How Do My Drugs Act in Combination Therapy?

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Combination Matrix

Enhanced Immune Response with Combinations

Re

lati

ve

Ex

pre

ss

ion

Le

ve

ls

|Lo

g10

ratio

|dru

g/v

eh

icle

co

ntr

ol)


Pembrolizumab plus Paclitaxel combination enhances cytokine production

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Lead Molecule:

PathHunter® assays can help identify and optimize a lead candidate

Efficacy:

BioMAP® Oncology Systems determine drug efficacy in a human TME model

Safety:

Diversity PLUS™ evaluates drug activity outside the context of the TME

Combinations:

Combo ELECT tests the impact of drug interactions in a human TME model

Summary

Screening & Lead

Optimization



Studies


https://www.discoverx.com/checkpoint

https://www.discoverx.com/services/drug-discovery-development-services/primary-cell-phenotypic-profiling/oncology-panels

https://www.discoverx.com/services/drug-discovery-development-services/primary-cell-phenotypic-profiling/diversity-plus

https://www.discoverx.com/services/drug-discovery-development-services/primary-cell-phenotypic-profiling/combo-elect-combination-study

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DiscoverX: Enabling Testing to Therapy

www.discoverx.com

Send your questions to : [email protected]@discoverx.com

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enabling cancer immunotherapy: from discovery to combinations

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