Innovations and Combinations for

Novel Anticancer Strategies

Axel-R. Hanauske, MD, Ph.D., MBA

Senior Medical Fellow

Oncology Early Phase

Eli Lilly and Company

© 2017 Eli Lilly and Company

Disclosure Information

I am an employee of Eli Lilly and

Company.

I will not discuss off-label or

investigational treatments in my

presentation.

6/19/2017 © 2016 Eli Lilly and Company 2

Oncology Drug Development: The

Traditional Rocket Model

Phase III

RegistrationGlobal Launch

Global Optimization

CommercializationCandidate Development

Lead Optimization

Pre-Clinical Develop

-ment

Phase I

Phase II

© 2017 Eli Lilly and Company

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Cost of Developing a New Drug Over

Time

Adapted from: DiMasi et al. J Health Econ. 10: 107, 1991; Tufts Center for the Study of Drug Development; data for 2000 and 2015 are estimates

R&D Efficiency by Year

Jack W. Scannell et al; Diagnosing the decline in pharmaceutical R&D efficiency: Nature Reviews/Drug Discovery, Volume 11, March 2012

© 2017 Eli Lilly and Company

How Does Anticancer Drug Late

Development Compare?

♦ „Probability of Success“ in Phase III studies bytherapeutic area:

Autoimmune: 63% Respiratory: 61% Endocrinology: 60% Infectious Disease: 55% Neurology: 55% Cardio-Vascular: 46%

Oncology: 34%

M.Silverman; BioStrategics Consulting GmbH, 2012; http://biostrategics.wordpress.com/2011/06/27/clinical-trial-probability-of-success-just-how-

probable-is-a-great-outcome/ retrieved 11-Nov-2012;

© 2017 Eli Lilly and Company

informedRx Drug Information Services. RxOutlook; American Cancer Society. Cancer Facts and Figures, 2010; 1 Buffery Am Health & Drug Benefits 8: 216, 20152 http://phrma-docs.phrma.org/sites/default/files/pdf/oncology-report-2015.pdf Accessed: June 11 2017

Cancer type

Estimated

New Cases

2010

# Pipeline

Products

Phase II + III

Cancer type

Estimated

New Cases

2010

# Pipeline

Products

Phase II + III

Lung 222.520 89

(123)1,2

Non-

Hodgkin‘s

Lymphoma

65.540 35

(92)

Prostate 217.730 31 Kidney 53.581 25

Breast 207.090 90 (82) Thyroid 44.670 10

Colon +

Rectal

142.570 41 Endometrial

(Ovarian)

43.470 6

(48)

Bladder 70.530 7 Pancreatic 43.140 29

Melanoma 68.130 40

(skin: 53)

Leukemia 43.050 1

(106)

Estimated New Cases in USA in 2010

and # of Pipeline Compounds

© 2017 Eli Lilly and Company

US 2015: 836 drugs+vaccines in clinical development – 3137 clinical trials active

How to Develop the Right Drug for the Right

Patient in a Disease with Heterogeneity at Multiple

Different Levels

♦ Define diversity in disease• Genetic – somatic & germline• Functional• Tumor components

♦ Segregate by defined criteria• Target/pathways• Biologic processes

♦ Predict clinical benefit of a drug• Signatures of target dependence• Host genetic makeup

mutations

copy changes

protein IHCon tissue arrays

overexpression

chromosomes

Types of Innovative Trial Designs

♦ Master Protocol

♦ Basket Trials

♦ Umbrella Trials

♦ Platform Trials

♦ Either Or or Neither

• Strategy trials

• Bayesian Adaptive Platform Designs

• etc.

Master Protocol Design

Hallmarks of Master Protocols

♦ One scoping study protocol

♦ Beneath: Separate parallel drug trials with

• Different biomarkers

• Different treatment designs

♦ Require collaboration of many stakeholders:

• Academic

• Industry

– Diagnostic

– Pharmaceutical

• Regulatory

Why Master Protocols and not

Separate Studies?♦ Enhanced genomic screening efficiency

♦ Inclusion of wide array of molecular subtypes

♦ ↑ willingness of patients and HCPs to participate

♦ Deletion/insertion of new subprotocol by amendment instead ofcompletely new protocol development

♦ ↑ and faster accrual c/w separate studies

♦ More rapid clinical development

♦ Better streamlined clinical development

Master Protocols: Basic Design

Renfro Ann Oncol October 11, 2016

Substudies often with low sample size:

• Single arm trials > focus on large efficacy signal

• Randomized trial > focus on large treatment effect

(vs. marker-negative or SOC)

Master Protocols: Higher Efficiency

than separate studies if…

♦ Use of common genomic platform or diagnostic tests

♦ Screening for variants of multiple genomic targets in each

tumor sample (requires sufficient tumor material)

♦ Rapid inclusion of patients based on screening results

♦ Organizational setting that allows for addition/deletion of

subprotocols

Master Protocols: Faster Clinical

Development than separate studies if…

♦ Upfront Regulatory/Institutional review of Master Protocol:

• Less administrative delay:

– Subsequent addition of subprotocols are considered amendments and may be

reviewed accordingling

– Simplified process of deletion/addition of new substudies or changes in

substudies

– No need to put complete Master protocol or unaffected substudies on hold

♦ Potential for faster approval by Regulatory Agencies in case of

convincing treatment effects

Master Protocols: Stakeholder

Enthusiasm if…

♦ Availability of a large number of different substudies

♦ Inclusion of „all marker negative“substudy

• All patients signing the ICF know there will be a treatment option for them

♦ Simplified local processes:

• IRB approval

• Contracting

Basket Design

Hallmarks of Basket Protocols

♦ Terminology used differently in literature

♦ Pragmatic definition:

TUMOR TYPE-AGNOSTIC APPROACH

=

HISTOLOGY-REPLACING APPROACH

♦ Hypothesis: The response to targeted therapy is determined by

the underlying molecular variant and (largely)

independent of histologyRenfro Ann Oncol October 11, 2016

Basket Trial: Basic Design

Renfro Ann Oncol 11-Oct_ 2016; Billingham Lancet Oncol 17-Feb-2016

• Enrollment based on molecular variant

• Subtrials may consist of different histologies or tumor types

• Randomization within molecular cohorts is uncommon and may bechallenging (different SOCs across tumor types)

• Usually single-arm substudies, hypothesis-generating objectives

Drug-Development-Oriented Basket

Trial: Potential Design

Renfro Ann Oncol October 11, 2016

Basket Trials: Pros and Cons

Prerequisites:1. Drug must sufficiently inhibit target

2. Tumor must depend on target

• Benefits:

• Access to trial for patients with rare tumors(but must have respective molecular marker)

• Testing may be done locally

• Small cohorts (usually single arm) may suffice to detect activity

• Quick results

• Challenges:

• Molecular variant(s) may not be the only driver of tumor

• Contextual complexities in various histologies

• Single biomarkers may be inferior to multi-gene signature

• Structural variants may need to be complemented with functional studies

• Different tumor types have different prognoses: single primary endpoint (eg

ORR) may skew results

Basket trial: NCI MATCH(“Molecular Analysis for Therapy CHoice”)

https://www.cancer.gov/multimedia/infographics/nci-match/nci-match-clinical-trial-infographic, accessed 23-Jan-2017

Phase II study, Target: 800-1000 patients in 25 substudies (N=30),

screen 6000 pts

US only, > 1071 sites participating in the NCI‘s National Cancer Trials Network

TTYPES:

Advanced, recurrent, refractory solid tumors

Lymphoma

Multiple Myeloma

24 drugs, including:

Afatinib

AZD5363 (AKT inh.)

Binimetinib

Crizotinib

Dabrafenib

Dasatinib

Defactinib

AZD4547 (FGFR Inh.)

Nivolumab

Osimertinib

Palbociclib

GSK2636771 (PI3K-ß inh.)

Sunitinib

Taselisib

Tametinib

Trastuzumab emtansine

Vismodegib

• Co-PEPs: ORR, 6-mo-PFS

• Goal: increase ORR from 5% to >16%

• Re-bx allowed to understand temporal

molecular development and re-assignment

of pts

Umbrella Design

Hallmarks of Umbrella Protocols

♦ Terminology used differently in literature

♦ Pragmatic definition:

TUMOR TYPE-BASED APPROACH

=

HISTOLOGY-REFINING APPROACH

♦ Hypothesis: The response to targeted therapy is primarily

determined by histologic context

Renfro Ann Oncol October 11, 2016

Umbrella Trials: Characteristics

Renfro Ann Oncol October 11, 2016

• Screening and enrollment before

identification of a targetable

molecular variant

• Use of central laboratory for

standardized screening

• Subprotocols may be single-arm or

randomized

Umbrella Trials: Pros and Cons

• Benefits:• Conclusions are specific for a given tumor type

• Tumor heterogeneity limited to one tumor type

• For randomized substudies:• Potential to better understand the difference of targeted therapy vs SOC

• Potential to differentiate between prognostic and predictive markers

• Easier path to negotiate approval with Regulatory Agencies

• Challenges:• Requires

• Strong collaboration between academia and industry

• Defined marker profile, comparability of cohorts (bx, assay, Tx)

• Feasibility• Subclassification into rare populations (particularly with rare cancers to start out

with)

• → ↓ speed of accrual

• Randomization requiring a larger sample size may be challenging

• Appearance of new SOCs during trial conduct changes the environment

Umbrella Trial: FOCUS 4 Design

Kaplan J Clin Oncol 36, 4562, 2013

Platform Design (“Standing Trial“)

Hallmarks of Platform Protocols

♦ Randomized

♦ One control arm, several experimental arms

♦ Allow for exit and entry of experimental arms

♦ Use of Bayesian hierarchical models for decision making

♦ Biomarker-positive subpopulations not necessarily separated

♦ Adaptive randomization with mid-trial randomization ratio shifts

Renfro Ann Oncol October 11, 2016

Platform Protocols: Design

30

Control Exp 1Exp 3

Exp 2Exp 4

Randomize

Exp 5

Potential Advantages:

• Reduced overall sample size

• Improved efficiency compared to sets of indivdual two-arm trials

Platform Design (“Standing Trial“)

- Adapted for Early Phase Drug Development -

Platform Protocols for Phase I Combination

Trials

• One Master Protocol– Includes design for dose-escalation AND expansion cohorts

• Identical Primary Endpoint(s) for all cohorts

• One backbone agent

• Tumor-type defined or open

• Exit and entry of combination cohorts allowed throughamendment

• Use of Bayesian models for decision making allowed

• Biomarker-positive subpopulations may be used in combinationcohorts

Platform Protocols: Design

33

Backbone

compound

+

Combo

agent 1

Platform Phase 1 Protocol with Expansion Cohorts

Backbone

compound

+

Combo

agent 6

Potential Advantages:

• Increased flexibility to include new scientific evidence into

ongoing trial

• Increased speed to identify active combination regimens

• Improved efficiency to identify active combination regimens

Backbone

compound

+

Combo

agent 2

Backbone

compound

+

Combo

agent 3

Backbone

compound

+

Combo

agent 4

Backbone

compound

+

Combo

agent 5

Strategy Trials

Hallmarks of Strategy Protocols

♦ 2-arm randomized trials: non-targeted SOC vs. targeted tx

♦ Cross-over in case of PD

• SHIVA trial: SOC vs. targeted therapy

- if PD on targeted tx → cross-over to Physician‘s choice

- 10 regimens with 11 targeted agents were studied

PEP: PFS

RES: mPFS 2.3 vs. 2.0 months (HR 0.88, p=0.41)

• NCI MPACT: non-targeted therapy > targeted therapy

Renfro Ann Oncol October 11, 2016, LeTourneau Lancet Oncol 16: 1324, 2015; Catenacci Lancet Oncol September 2, 2015

Refractory solid

tumorscreened: 741 pts

Randomized: 195 pts

Targeted therapy

Physician‘s choiceRR

Strategy Trial: NCI MPACT Design(“Molecular Profiling-based Assignment of Cancer Therapy“)

Do Chin Clin Oncol 4: 31, 2015

DNA repair,

PI3K

RAS/RAF/MEK

2:1

NCI MPACT

• Total of 4 experimental arms

• Anticipated sample size:

• 700 pts screened

• > 180 pts randomized to the initial 4 arms

• Possibility to add additional cohorts

• PEPs: ORR, 4-month PFS

• Trial is ongoing

Bayesian Adaptive Trials

Hallmarks of Bayesian Adaptive Design

♦ Randomized trial with Master Protocol• Subprotocols may leave or enter during trial

♦ Pts assigned to specific targeted therapy arms based on molecularsignature

♦ Adaptive change of randomization based on treatment‘s observedactivity• ↑ randomization probability if activity is observed

• ↓ randomization probability if unpromising activity

♦ Requirements to perform well:• swift marker assessment

• quick endpoint to inform adaptive randomization

• slow accrual rate to ensure subsequent pts benefit from randomizationadaptation

Renfro Ann Oncol October 11, 2016

Bayesian Adaptive Design

Notable Trials:

♦ BATTLE-1

♦ BATTLE-2

♦ I-SPY2

Renfro Ann Oncol October 11, 2016

Bayesian Adaptive Design: BATTLE-1(“Biomarker-integrated Approaches of Targeted Therapy

for Lung Cancer Elimination (BATTLE)-1”)

• First completed, biomarker-based, adaptive randomized clinical trial (N = 255)

Liu Chin Clin Oncol 4: 33, 2015

Mandatory bx

11 pre-specified biomarkers

►20 different treatment-by-biomarker subgroups,

→ evaluation of performance of each treatment arm in each marker group

(After 1 pt in each subgroup)

Bayesian Adoptive Design:

Pros and Cons

• Benefits:• Identification of potential new predictive biomarkers

• Enhanced individual ethics through adaptive randomization

• Greater efficiency compared to stand-alone randomized Phase II trials

• Real-time biomarker analysis (if possible)

• Challenges:• Prespecification of biomarkers without information whether they are

prognostic or predictive

• Combination of markers may dilute predictive effects of individual markers

• Rare biomarkers may lead to late start of adaptive randomization

• Need of short-term outcome measure to guide adaptive randomization

• Patients with advanced cancer may not be eligible for treatment with all

compounds due to medical condition

Novel Study Designs: Summary

• Potential Benefits:• Greater efficiency in drug development

• Faster detection of innovative cancer agents

• More accurate selection of patients

• Exposure of less patients to potentially inactive agents

• Less resource consumption

• Potential Challenges:• Retention of integrity of trial designs

• Susceptibility for bias

• Complexity of safety monitoring

• Robustness of results observed

• Overestimation of beneficial effect

• Assessment by Competent Authorities

• unclear how central Ct approval (≥ 2018) will handle new designs

THANK YOU

The Pharmaceutical Industry has Increased its Oncology Efforts

EFPIA: A Vision Towards a Life Science Strategy in Europe, Brussels 2014; http://www.efpia.eu/uploads/documents/EFPIA-health&growth_MANIFESTO_V11_pbp.pdf; May 4, 2015

# of Pipeline Compounds: USA 2015

836 drugs+vaccines in

clinical development –

3137 clinical trials active

http://phrma-

docs.phrma.org/sites/default/files/pdf/onco

logy-report-2015.pdf Accessed: June 11

2017