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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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$ 54$ 231
$ 802
$ 2000
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