Download Immuno-Oncology – Where is the next Checkpoint?

Photo Credit: Wellcome Trust/Ann Weston, LRI, CRUK
Immuno-Oncology –
Where is the next Checkpoint?
Germo Gericke, MD
Global Program Head Oncology,
Novartis Global Drug Development
HLG Winter Conference
January 30, 2017
Disclaimer
"This presentation represents the thoughts and opinions of the presenter and
does not necessarily reflect those of Novartis and its affiliated companies.
This presentation may contain strategies/concepts/projects which may be
aspirational in nature and may need significant modifications before
implementation.
Novartis will only implement programs that are fully consistent with all
applicable laws and regulations as well as Novartis policies."
Agenda
 What’s the hype? – IO in the context of Cancer Therapy
 What do we know? – Scratching the surface of science
 What’s next? – Place your bets!
What's the Hype about?
Why talk about Immuno-Oncology?
 $$$: Rapid adoption, high revenue
projections for IO assets
 Science: Fundamentally new approach,
complementary to existing modalities
 Potential cure: Regaining the
status quo of „normal“
Immune Evasion is ONE key Mechanism of Cancer
Hallmarks of cancer
Active
invasion and
metastasis
Resisting
cell death
Angiogenesis
Sustained
proliferative
signaling
Hallmarks
of cancer
Replicative
immortality
Avoid
immune
destruction
Evasion
of growth
suppressors
As normal cells evolve into
a neoplastic state, they
acquire a combination of
antvantegous capabilities;
including the ability to avoid immune destruction
Deregulating
cellular
energetics*
Hanahan D, Weinberg RA. Cell. 2011; 144(5) 646-674.
Pardoll DM. Nat Rev Cancer. 2012;12:252-264
Kirkwood JM, et al. CA Cancer J Clin. 2012; 62:309-335
Mellman I, et al. Nature. 2011;480:480-489
Cancerous cells are part of normal biology
Dynamic balance between cancerous cells and immune system
Elimination
Effective Surveillance
Equilibrium
Escape
Cancer Dormancy
Cancer Progression
• Effective antigen
processing/presentation
• Genetic instability
• Effective activation and
function of effector cells
• Immune selection
CD4+ T cell
CD8+
T cell
• Tumor heterogeneity
• Tumors can suppress, disrupt,
or “escape” the immune
system
NK cell
Treg
Tumor Cells
Normal Cells
Vesely MD et al. Ann Rev Immunol. 2011;29:235-71.
IO in the Context of Cancer Therapy
Evolution and principles of cancer therapy
Genetic engineering etc.
– „Manipulate the scale“
Immuno-Oncology
– Elimination of „foreign“ (Immune Response)
Targeted therapy
– Slow the Escape (block tumor growth drivers)
Chemotherapy / Radiotherapie
– Slow the Escape (kill fast-growing / impaired repair)
Surgery
– Complete Elimination (before it spreads)
C
O
M
B
I
N
A
T
A
T
I
O
N
S
Immuno-Oncology – Where to start?
Basic steps of immune response
1. Education
 Recognition and
processing of
tumor-antigens
2. Activation
 Antigen presentation
 Selection and expansion
of specific effector cells
3. Targeted response
Tumor infiltration and
targeted killing
 Cytotoxic T-cells
 NK cells
+ B-cell mediated (mAbs)
+ Complement-supported
Source: Mellman I, et al. Nature. 2011;480(7378):480-489, copyright 2011.
8
CONCEPTUAL
Paradigm Shift in Patient Benefit
IO is bending the curve of long-term survival
„classic“ survival curve
Survival
„IO“ Survival curve
Survival
Benefit
Benefit
Time
Time
Other Trends in Cancer Therapy Development
For discussion!
 Study population - From orphan disease to individual therapy:
• Prior and subsequent therapies
• Combinations, combinations, ...
• Biomarker-based selection
 Clinical end points - How to get approved and reimbursed?
• Overall Survival -> Progression-Free Survival -> Cure Rate?
• “Marginal Benefit” within reasonable time frame and rapidly changing
Standard of Care / relevant comparator
• Conditional approval pathway evolution
 Taxonomy – What’s the indication?
• From primary tumor location and histochemistry of archival samples to real-time
genetic fingerprint (Next Generation Sequencing, circulating tumor cells and
circulating DNA/RNA)
Other Trends in Cancer Therapy Development
Integrated data becoming a critical value driver
 Study population - From orphan disease to individual therapy:
• Prior and subsequent therapies
• Combinations, combinations, ...
• Biomarker-based selection How
to value
 Clinical end points assets
- How toin
getdevelopment
approved and reimbursed?
• Overall Survival -> Progression-Free Survival -> Cure Rate?
• “Marginal Benefit” and
within individual
reasonable timecomponents
frame and rapidly changing
Standard of Care / relevant comparator
of combinations?
• Conditional approval pathway evolution
 Taxonomy – What’s the indication?
• From primary tumor location and histochemistry of archival samples to real-time
genetic fingerprint (Next Generation Sequencing, circulating tumor cells and
circulating DNA/RNA)
Thank You
Photo Credit: Wellcome Trust/Ann Weston, LRI, CRUK