Welcome to the - UBM Medicaimaging.ubmmedica.com/.../cancernetwork/pdfs/roundtable_slides.pdf · Welcome to the Cancer Drug Development Roundtable at Ohio State May 4, 2011

Welcome to theCancer Drug Development Roundtable at Ohio StateMay 4, 2011

2

The Ohio State University Comprehensive Cancer Center –Arthur G. James Cancer Hospital and Richard J. Solove Research Institute

Michael Caligiuri, MD(Co-host and Panelist)

OSUCCC-James

Director, OSUCCC; CEO, The James

Ellen Sigal, PhD (Co-host)

Friends of Cancer Research

Chair and Founder

James Doroshow, MD(Panelist) NCI Director, Division of Cancer

Treatment and Diagnosis

Eric Rubin, MD (Panelist) Merck VP, Oncology Clinical Research

Janet Woodcock, MD(Panelist) FDA Director, Center for Drug

Evaluation & Research

Robert Brueggemeier, PhD (Q&A Moderator) Ohio State Dean, College of Pharmacy

Public Session

3


Brian Cummings Ohio State VP, Technology Commercialization

Anthony Dennis PhD BioOhio President and CEO

Richard Gaynor MD

Eli Lilly and Company

VP, Clinical Development & Medical Affairs, Oncology Business Unit

Courtney Granville PhD, MSPH Battelle Toxicologist/Study Director

Michael Grever MD

OSUCCC-James

Chair & Professor, Dept of Internal Medicine; Associate Dean of Medical Services; Co-Leader, Experimental Therapeutics Program

Additional Roundtable Participants

4


Joanne Lager MD

Sanofi-Aventis

Senior Director and Oncology Drug Project Head

Michael Mitchell JD Ohio State Assistant VP and

Associate General Counsel

Christine Poon MBA Ohio State Dean, Fisher College of Business

David Roth MD Pfizer VP, Early Development,

Oncology Business Unit

David Schmickel JD, PhD FoxKiser Legal Counsel

Allen SingerDVM Battelle VP, Center for Life Sciences Research


5


Ira Steinberg MD

Sanofi-Aventis

Associate VP & Global Medical Affairs Leader

Miguel Villalona MD

OSUCCC-James

Director, Division of Medical Oncology & Professor, Dept of Internal Medicine

Tim Wright Signal Hill Advisors Biotech and Pharmaceutical Consultant


Ellen Sigal, PhD Chair and Founder,Friends of Cancer Research

Janet Woodcock, MD DirectorCenter for Drug Evaluation and ResearchU.S. Food and Drug Administration

James Doroshow, MD DirectorDivision of Cancer Treatment and DiagnosisNational Cancer Institute

OSU Comprehensive Cancer CenterColumbus, OH

May 4, 2011

Developing Experimental Drug Combinations: Opportunities and Challenges

James H. Doroshow, M.D.Director

Division of Cancer Treatment and Diagnosis, NCI

Challenges to Development of Combination Targeted Therapeutics

• Incomplete understanding of mechanisms of action for a growing number of targeted agents available for trial

• Inability to assess target effect– Lack of assays, imaging tools– Lack of assay standardization– Lack of commercially-available agents formulated for in vitro use– Lack of available investigational agents for in vitro use

• Lack of preclinical models for combinations– To evaluate efficacy, schedule effects, biomarker utility, toxicity

• Clinical trials methodology– Need to screen large numbers of patients?– Need for tumor biopsies?– Is histologic homogeneity relevant?– Pharmacokinetic interactions? SD vs RR?

• Intellectual property & regulatory challenges to novel combinations

Drug BiomarkerAnti-estrogens ER, PR, genomic signature

Trastuzumab Her2 FISH, IHC

EGFR small molecule inhibitors Mutation status

B-Raf, ALK inhibitors Mutation statusAnti-VEGF/VEGFR agents ??

IGF-I receptor antagonists ??

Src inhibitors ??Cdk/Cyclin D1 inhibitors ??

HDAC/DNMT inhibitors ??

Anti CTLA-4 Antibody ??

Lack of Molecular Markers with Proven Clinical Utility

Concept Feasibility & Development Validation Launch

Target Application Platform Feasibility Development Analytical Validation

Preclinical Modeling

Specimen SOPs

Assay Transfer

Clinical Validation

Support NCI Clinical

Trials

Transfer to Scientific

CommunityBiopsy Assays

γ-H2AX Protein(tumor)

DNA Damaging Agents ELISA P P l

γ-H2AX Protein(tumor)

DNA Damaging

AgentsqIFA P P P P P l l l

Top 1 Protein TOPO Inhibitors ELISA P P P l P

METTK domain and Grb2

Docking SiteKinase Inhibitors

IFACommerci

al Reagents

P P l l l l

METTK domain and Grb2

Docking SiteKinase Inhibitors

IFACustom

ReagentsP P P l

PARG mRNA PARP Inhibitors RT-qPCR P P P P P P P R

PARP 1 mRNA PARP Inhibitors RT-qPCR P P P P P P P R

PARP 1,2 Activity(PAR levels)

PARP Inhibitors IA P P P P P P P l l

PARP 2 mRNA PARP Inhibitors RT-qPCR P P P P P P P R

Stem Cell Proteins -ALDH 1A1-OCT 3/4-NANOG-CD44v6

Tumor Stem Cell Inhibitors IFA P l H l

KEY:l In Progress P Completed X Dropped

l Delayed CA Commercially Available NA/UIN Not Applicable or Uninformative

l Technical Difficulty H On Hold R Ready

Pharmacodynamic Assay Development

Cryobiopsy: Freeze

Excisional BiopsyCryobiopsy: Excise

Standard 18 gauge Bx


• Incomplete understanding of mechanisms of action for a growing number of targeted agents available for trial

• Inability to assess target effect– Lack of assays, imaging tools– Lack of assay standardization– Lack of commercially-available agents formulated for in vitro use– Lack of available investigational agents for in vitro use




• COMBO set 1– 87 compounds of diverse mechanism– Includes many older FDA-approved anticancer agents

• FDA-approved COMBO set (9/09):

NCI “COMBO Plates”Plated Compounds for Combination Studies

Molec. Cancer Ther. 9:1451-1460, 2010


• Incomplete understanding of mechanisms of action and a growing number of targeted agents available for trial

• Inability to assess target effect– Lack of assays, imaging tools– Lack of assay standardization– Lack of commercially-available agents formulated for in vitro use– Lack of available investigational agents for in vitro/in vivo use










Modeling Therapeutic Combinations in NCI 60

For any 2-drug combination:

MCF7DU-145

PC-3UO-31TK-10

SN12CRXF-393

CAKI-1ACHNA498786-0

SK-OV-3NCI/ADR-RES

OVCAR-8OVCAR-5OVCAR-4OVCAR-3

IGROV1UACC-62

UACC-257SK-MEL-5

SK-MEL-28SK-MEL-2

MDA-MB-435M14

MALME-3M

Bars to right indicate overall benefit to using combo relative to best single-agent results

Bars to leftindicate loss

of benefit relative to best single-agent results

MDA-MB-468T-47D

BT-549HS 578T

MDA-MB-231/ATCCMCF7

DU-145PC-3

UO-31TK-10

SN12CRXF-393

CAKI-1ACHNA498786-0

SK-OV-3NCI/ADR-RES


IGROV1UACC-62

UACC-257SK-MEL-5

SK-MEL-28SK-MEL-2

MDA-MB-435M14

MALME-3MLOX IMVI

U251SNB-19SNB-75SF-539SF-295SF-268

SW-620KM12HT29

HCT-15HCT-116

HCC-2998COLO 205NCI-H522NCI-H460

NCI-H322MNCI-H23

NCI-H226HOP-92HOP-62

EKVXA549/ATCC

SRRPMI-8226

MOLT-4K-562

HL-60(TB)CCRF-CEM

-10 -5 0 5123127_226080

Doxorubicin + Rapamycin Bortezomib + Cladribine (2CDA)

MDA-MB-468T-47D

BT-549HS 578T

MDA-MB-231/ATCCMCF7

DU-145PC-3

UO-31TK-10

SN12CRXF-393

CAKI-1ACHNA498786-0

SK-OV-3NCI/ADR-RES


IGROV1UACC-62

UACC-257SK-MEL-5

SK-MEL-28SK-MEL-2

MDA-MB-435M14

MALME-3MLOX IMVI

U251SNB-19SNB-75SF-539SF-295SF-268

SW-620KM12HT29

HCT-15HCT-116

HCC-2998COLO 205NCI-H522NCI-H460

NCI-H322MNCI-H23

NCI-H226HOP-92HOP-62

EKVXA549/ATCC

SRRPMI-8226

MOLT-4K-562

HL-60(TB)CCRF-CEM

Cel

l line

-10 -5 0 5 10 15 20 25681239_606869

Cel

l lin

e

cellname

CCRF-CEMHL-60(TB)K-562MOLT-4RPMI-8226SRA549/ATCCEKVXHOP-62HOP-92NCI-H226NCI-H23NCI-H322MNCI-H460NCI-H522COLO 205HCC-2998HCT-116HCT-15HT29KM12SW-620SF-268SF-295SF-539SNB-75SNB-19U251LOX IMVIMALME-3MM14MDA-MB-435SK-MEL-2SK-MEL-28SK-MEL-5UACC-257UACC-62IGROV1OVCAR-3OVCAR-4OVCAR-5OVCAR-8NCI/ADR-RESSK-OV-3786-0A498ACHNCAKI-1RXF-393SN12CTK-10UO-31PC-3DU-145MCF7MDA-MB-231/ATCCHS 578TBT-549T-47DMDA-MB-468

CCRF-CEMHL-60(TB)K-562MOLT-4RPMI-8226SRA549/ATCCEKVXHOP-62HOP-92NCI-H226NCI-H23NCI-H322MNCI-H460NCI-H522COLO 205HCC-2998HCT-116HCT-15HT29KM12SW-620SF-268SF-295SF-539SNB-75SNB-19U251LOX IMVIMALME-3MM14MDA-MB-435SK-MEL-2SK-MEL-28SK-MEL-5UACC-257UACC-62IGROV1OVCAR-3OVCAR-4OVCAR-5OVCAR-8NCI/ADR-RESSK-OV-3786-0A498ACHNCAKI-1RXF-393SN12CTK-10UO-31PC-3DU-145MCF7MDA-MB-231/ATCCHS 578TBT-549T-47DMDA-MB-468

cellname

C

C

718781

_70754

5718

781_45

388226

080_71

8781

609699

_71878

1718

781_10

2816

732517

_71878

1675

74_718

781718

781_10

5014

226080

_40996

2226

080_22

1019

123127

_22608

0681

239_10

5014

681239

_70754

5681

239_60

6869

732517

_755

732517

_22101

9732

517_24

6131

83265_

732517

747971

_12275

8747

971_71

423613

327_72

1517

123127

_74575

0750

690_10

2816

19893_

241240

609699

_26604

6609

699_82

151609

699_70

7545

613327

_10501

4123

127_31

2887

266046

_19893

266046

_10501

4

718781

_70754

5718

781_45

388226

080_71

8781

609699

_71878

1718

781_10

2816

732517

_71878

1675

74_718

781718

781_10

5014

226080

_40996

2226

080_22

1019

123127

_22608

0681

239_10

5014

681239

_70754

5681

239_60

6869

732517

_755

732517

_22101

9732

517_24

6131

83265_

732517

747971

_12275

8747

971_71

423613

327_72

1517

123127

_74575

0750

690_10

2816

19893_

241240

609699

_26604

6609

699_82

151609

699_70

7545

613327

_10501

4123

127_31

2887

266046

_19893

266046

_10501

4







Principles of Combination Therapy:Then (1975) and Now (2010)

• Drugs are each active against the tumor in question (ORR)

• Drugs have different mechanisms of action to minimize resistance

• Drugs have different clinical toxicities to allow full dose therapy

• Intermittent intensive > continuous treatment for cytoreduction & to reduce immunosuppression

Frei, Cancer Res., 32: 2593, 1972DeVita, Cancer, 35: 98, 1975

• Agent has therapeutic effect on molecular pathway in vivo

• Agents have complementary effects on the same target or other targets in the same pathway or pathways that cross-talk to control tumor growth

• Toxicities do not overlap with cytotoxicsand are moderate to allow prolonged administration

• Schedule chosen to maximize target inhibition: Either continuous Rx or high dose to suppress target a reasonable goal

Kummar, Nat. Rev. Drug Disc., 9: 843, 2010

Cytotoxic Targeted

Accelerating Cancer Diagnosis and Drug Development

DCTD Division of Cancer Treatment and Diagnosis

Developmental Therapeutics

Jerry CollinsJoe TomaszewskiMelinda HollingsheadRalph ParchmentRobert KindersTom PfisterJay Ji

Center for Cancer Research

Yves PommierLee HelmanBob WiltroutShivaani KummarWilliam Bonner

DCTDJason CristofaroBarbara MrochowskiMichael Difilippantonio

CTEPJamie ZweibelJeff Abrams

Cancer ImagingPaula Jacobs

Cancer DiagnosisBarbara Conley

Eric Rubin, MD Vice PresidentOncology Clinical ResearchMerck

Approaches to solving the combinations problem in

oncology therapeutics

Eric H RubinMerck Research Laboratories

The Most Effective Treatments Involve Combinations

• Probability of drug-resistant cells = 1 – e[-x(N-1)],where N is number of cells and x is the spontaneous drug resistance rate– Assuming a resistance rate of 1 of every million cells, for a 1 mm3

tumor, this probability is 0.64

• Principles of combination chemotherapy– Additive or synergistic anti-tumor activity without additive toxicity– Non-cross-resistance

Combinations Problem in Oncology

• For every 10 new drugs approved, 45 trials would be required to test each possible 2-drug combination

• If the trials were done separately and sequentially, this would take about 90 years

• This problem is amplified by a need to identify responsive subgroups (e.g. by biomarkers)

The Combinations Problem in Cancer: Lung Cancer Example

New Compounds (5)– AKTi– HGFi– IGFRi– mTORi– CHK1i

Biomarkers (4)– RAS– IGFR– MET– EGFR

Possible drug doublets = (7 x 6)/2 -1 (SOC doublet) = 20 possible all comer ph2 trialsPossible biomarker groups (if independent) = 24 = 16 possible patient subgroupsPossible drug doublet-biomarker groups = 20 x 16 = 320 possible enrichment ph2 trials

Standard-of-care drugs (2)–EGFRi (e.g. erlotinib)–VEGFRi (e.g. bevacizumab)

Solutions to the Combinations Problem

1. Identify most promising combinations from preclinical studies and combine them early in the clinic– IGF1Ri + mTORi– AKTi + MEKi– Caveat is that the historical success rate of preclinical prediction is low

2. Use branched adaptive trials– BATTLE – lung cancer– I-SPY – breast cancer

Enhancer Screen for IGF1R inhibition

IGF1Ri-treated

cell lines(dalotuzumab)

UntreatedCell lines

Candidate Enhancers

siRNALibrary

mTOR shRNA

shRNA=small hairpin RNA

Rationale for Combined mTOR and IGFR1 Targeting

• mTOR is top hit in dalotuzumab enhancer screen

• IGF1R is top hit in ridaforolimus enhancer screen

Dalotuzumab Enhancer Screen

Anti-proliferative effect

pre-therapy on-therapy

Rationale for Combined mTOR and IGFR1 Targeting

Co-treatment with IGFR1 inhibitor prevents feedback activation of AKT by mTOR inhibition in preclinical models

Tabernero, et al., J Clin Oncol. 2008

pAK

T-S4

73 s

tain

ing

4EBP1

PI3K

TORC1

S6K

Rheb

S6

PIP3

Tuberin

PTEN

Akt PDK1

IRS

IGFR-1

RIDAFOROLIMUS

DALOTUZUMAB

Tumor sample of a patient on treatment with everolimus

Feedback activation of AKT following mTOR inhibition by rapalogs

Ridaforolimus (Rida) + Dalotuzumab (Dalo): Phase I Design

• Presented at oral session ASCO 2010– DiCosimo et al, abstract # 3008

• Serena Di Cosimo, Johanna Bendell, Andres Cervantes-Ruiperez, Desamparados. Roda, Ludmilla Prudkin, Mark Stein, Ann Leighton-Swayze, Yang Song, Scot Ebbinghaus, and José Baselga

Part A

5 dose levels37 patients

Cohort 112 patients

Cohort 213 patients

Part B - 2 dose cohorts

36

Example of a Partial Response to Ridaforolimus + Dalotuzumab

• 56 year-old female – Stage IV breast cancer

• ER+/PR+/HER2 neg, Ki67 20%• Adjuvant chemotherapy• 4 prior chemotherapy regimens

– Cyclophosphamide + doxorubicin, docetaxel + vinorelbine, paclitaxel + gemcitabine, capecitabine

• 3 prior hormone therapies– Tamoxifen, fulvestrant, anastrazole

• Patient remained on study treatment for 9 months before progression

2 cycles

37

Summary of Efficacy Signals in Breast Cancer

• Overall, 10 of 23 breast cancer patients had objective evidence of anti-tumor activity– 6 of 11 (54%) patients with ER+/high proliferation breast tumors– 0 of 5 patients with ER+/low proliferation breast tumors

Breast Cancer Subpopulation N

FDG-PET PR (EORTC)

PFS > 6 months

Tumor Marker RECIST PR

n % n % n % n %ER+ 18 2 4 7 3ER+/high proliferation 11 2 4 5 3ER+/low proliferation 5 0 0 0 0HER2+ 3 3 0 2 0All breast cancer 23 5 22 4 17 8 35 3 13.0

PR=partial response; PFS = progression-free survival; tumor marker decline > 25% for CA-125, CA15.3 or CA27.29

Inter-Company 2 NME Combination

• Allosteric AKT inhibitor (MK-2206) + allosteric MEK inhibitor (AZD6244)

• Collaboration signed June 2009– First example of two companies collaborating on combining 2 NMEs in

early development

• First patient dosed in phase 1 trial December 2009• Results to be presented at ASCO 2011• Combination also to be studied in BATTLE2

Acknowledgements

• Merck– Gary Gilliland– Stephen Friend– Pearl Huang– Keaven Anderson– Li Yan– David Mauro

• Astra Zeneca– Alan Barge– Paul Smith– Ian Smith– Grahme Smith– Victoria Zazulina

• MD Anderson Cancer Center – Roy Herbst– Vali Papadimitrakopoulou– J Jack Lee– Don Berry

Michael Caligiuri, MDDirector, The Ohio State University Comprehensive Cancer CenterCEO, James Cancer Hospital and Solove Research Institute

42


Success with New Trials at The James

Developed nude rat model of human primary CNS EBV+ lymphoma (PCNSL)

NCI R01 funded in 1997 Rat model of PCNSL: Identified

tumor upregulation of viral thymidine kinase by XRT & cytotoxicity with high dose AZT & GCV

Phase I clinical trial developed 1st Patient: cured of fatal EBV+

PCNSL (10 years disease-free survival)

43


Success with New Trials at The James

44


An Astonishing Range of Molecular Interactions Occurs in Cancer Cells

Biochemical pathways control cancer-cell growth and survival of cancer cells

45


Drugs Designed to Target Key Molecules In Biomedical Pathways

Blocks PI3K, which drives growth

Turns on protectivegenes that the cancer process has turned off

46


Preclinical Evidence: Targeted Agents In Combination Will Improve Patient Outcomes

They cripple several key pathways simultaneously As a result, they may slow development of

resistance and extend patient lives

47


Dr. Bhuvaneswari RamaswamyAssistant Professor of Medical OncologyThe Ohio State University School of Medicine and Public Health

A link to the full video will be sent to those participating virtually following the session.

48


Major Stakeholders Need to Develop COOPERATIVE Policies and Procedures

Pharmaceutical industry

Regulatory agencies

National Cancer Institute

Academia

Patient advocacy groups

49


Great FirstStep by FDA

50


CCCs & Academic Institutions Can Help

Basic research Patients

51



Basic research Patients Science-based combination

strategies Pre-clinical studies

52



Basic research Patients Science-based combination

strategies Pre-clinical studies Bring stakeholders together Academic expertise in

intellectual property CCCs can file

investigational new drug (IND) applications

53


Today’s Roundtable

Battelle

BioOhio

Eli Lilly and Company

FDA

FoxKiser

Friends of Cancer Research

Merck

NCI

Ohio State

OSUCCC-James

Pfizer

Sanofi-Aventis

Signal Hill Advisors

54


Solve Critical Business and Legal Issues:Co-developing Agents in Combination

Define roles Intellectualproperty

Commercialization

ProfitsPrices

AdverseEffects

Experimental combinations

Patentprotection

Financingthe science

Concentrated effort on broad

coalition

Createworkable template

Draw up agreements

55


Question and Answer SessionThank you for attending.To view related material, please visit cancer.osu.edu/go/CancerDrugRoundtable.

Documents

Welcome to the - UBM Medicaimaging.ubmmedica.com/.../cancernetwork/pdfs/roundtable_slides.pdf · Welcome to the Cancer Drug Development Roundtable at Ohio State May 4, 2011