An overview of the

McKinsey Cancer Center

Qualifications and services

Oncology in numbers

>1.8x
pharma
market growth
2018–24 (12%)

1.5x
higher launch
value than
other TAs

60%
external
innovation USD
26% 300bn
of pharma in healthcare
market cost
in 2022 >4,500
compounds in
(pre)clinical
development

40%
of industry
pipeline
>150
1 drug launches
in last 10 years
death every
4 seconds
46%
first-in-class
pipeline
compounds
500
molecular
targets
in the clinic

SOURCE: McKinsey
NOTE: Numbers refer to oncology and immunomodulators

2
Key trends in oncology

Smaller, stratified ▪ 1.5x higher growth rate in low-incidence tumors,

patient populations, 50% of top-10 players’ Phase III trials with CDx
complex treatment ▪ Treatment paradigms with sequential
paradigms subpopulations

Accelerated ▪ Ca. 50% of pivotal trials were phase I/II and there
innovation and is an increased use of basket and umbrella trials
product lifecycles ▪ Product lifecycles shortened from >5 years to
1–2

Increased role of ▪ High-growth companies with >50% external

combinations and innovation
collaborations ▪ ~50% of PD(L)-1 trials in combinations

Value shifts, big ▪ More than USD100bn in value expected to shift

data, and novel ▪ Big data allowing more nuanced value capture
access models

Wave of new ▪ Next wave of innovation (CAR-T, mRNA, etc.)

technologies and driving growth
innovation ▪ Increased opportunities for personalization in
therapy and diagnostics plus earlier detection

3
The McKinsey Cancer Center and oncology –
what we do

Client service Cutting-edge Conferences Publications and

across sectors oncology knowledge and meetings perspectives

Industry-leading Rapid access to cutting- McKinsey events at key Publications in peer-

oncology expertise edge oncology expertise oncology conferences reviewed and other
through client service through network of experts across the world journals
across sectors and and internal investment
geographies

▪ Pharmaceutical and ▪ External scientific ▪ McKinsey Cancer ▪ Lancet International

biotech companies advisory board of top Congress Series at Cancer Benchmarking
▪ Specialty pharmacies oncology KOLs – ASCO since 2008 Partnership (ICBP):
▪ National health research and clinical ▪ Satellite Meeting at cancer survival study
systems ▪ Internal experts with ESMO ▪ World Innovation
▪ Providers oncology background ▪ Regular participation Summit for Health on
▪ Private and public ▪ Market research ASH, AACR and Affordable Cancer Care
payors collaboration with other ▪ McKinsey Health
▪ Cross-sector service Gerson Lehrman ▪ Roundtables and International on health
Group, Research Now, other events on systems and cancer
and AlphaSights selected deep-dive care
▪ Dedicated knowledge topics ▪ Pathway-based CRC
development efforts on care improvement
key topics, e.g., approach
combination therapies, ▪ Over 20 other
new technologies, international publications
oncology clinical
development

4
How we support our clients

Key project types

Pharmaceutical ▪ Business unit, commercial, and R&D strategies

companies ▪ Optimization of pipeline and in-line portfolios
▪ Clinical trial design and regulatory pathways
▪ Clinical operations and asset optimization
▪ Product launch, go-to-market, and turnaround
strategies
▪ Pricing and market access strategy
▪ Outcome-based collaboration arrangements

Health systems and ▪ National/regional cancer strategy

payors ▪ Real-world data capture and outcomes
improvement strategy
▪ Clinical practice diagnostic vs. evidence base
▪ Cost allocation/outcomes maximization
▪ Identification of value pools and road map

Providers ▪ Cancer center design

▪ Cancer center strategy
▪ Diagnostic on clinical pathways
▪ Prioritization of interventions
▪ Operational improvement program

5
Overview of our client impact

Engagement types across functions

Oncology engagements, 2012–17
Percent

2
3 2
9
Digital
Operations
Corporate finance
Organization
Marketing and sales 39
18 R&D

Strategy

29

Operating in all
geographies including
We regularly work with mature and developing
 Biotechs markets, MNCs, and
 Cancer centers local players
 Nonprofit organizations
 Payors Annual client engagements
 Pharmacos  Over 100 pharma teams
 Private investors  Over 20 biotech teams
 Wholesalers  Over 10 cancer centers
 ~5 payors/systems
 ~5 private equities/investors
 ~5 nonprofit organizations

6
5 example stories of impact

Changing the entire Added USD2bn commercial revenues and increased R&D focus
portfolio of a leading ▪ Supported carve-out of ~USD2bn oncology franchise
oncology player ▪ Strengthened R&D capabilities and partnership in retained
innovation unit
▪ Integrated portfolio into a ~USD10bn oncology franchise and
out-licensed Phase II/III assets

Delivering 1 Drove uptake of USD3bn blockbuster drug at 4x analyst

of pharma’s top-3 expectations
product launches ▪ Defined launch readiness road map for regional organization and
>15 affiliates
▪ Supported launch performance of USD300m first-year sales
▪ Closed country launch execution gaps and enabled 5x
outperformance of analyst projections

Building a cancer Built a >USD2bn oncology go-to-market franchise in 12 months

franchise from ▪ Supported licensing deals and M&As worth USD3bn
scratch ▪ Blueprinted >150-person launch franchise with global, regional,
and local organizations
▪ Supported integration of acquired oncology portfolio and
organization

Reducing cancer Saved 400 lives for colorectal cancer patients annually
mortality by 10% ▪ Redesigned care pathway in 5 health systems across the globe
▪ Identified care improvements to reduce mortality by up to 15%
▪ Defined cost savings opportunities of USD100m or 10% of health
system spend annually

Defining new ways Designed suite of completely new approaches for pharma to
for outcomes-based partner with systems
partnering ▪ Developed suite of over 400 solutions for outcomes-based
partnering on different products
▪ Designed solutions to allow earlier patient access to specific
medicines by several months
▪ Enabled availability of drug in multiple additional health systems

7
Pharma example – building a cancer franchise from
scratch

Situation
Client description Engagement objectives Unique/specific challenges
▪ Medium-sized US-based ▪ Define ambition for ▪ Limited to no oncology
carve-out building oncology business portfolio or capabilities
oncology portfolio, ▪ Build pipeline through ▪ New company with limited
organization, and business development or no relevant market
market presence
▪ Design oncology BU history
including customer facing ▪ Rapid buildup required
functions within 2-year time frame
▪ Define go-to-market model
Approach

▪ Defined financial Key elements of the solution

ambition, indication ▪ 5-year growth plan and financial forecast including
and technology focus, pro-forma P&L
and growth road map ▪ Tumor type focus for development and BD, MOA and
▪ Performed ca. 10 technology selection and prioritization for research
McKCC Rapid DD ▪ Rapid technical due diligence assessment and
modules for individual valuation of preclinical to Phase II assets
asset licensing ▪ Preparation for licensing discussions including value
▪ Supported 1 large proposition and presentations
M&A strategic ▪ Strategic valuation of 1 larger M&A, preparation for
valuation negotiation and subsequent integration support
▪ Developed pipeline ▪ Development of launch readiness road map, broad
model and financial launch readiness program in HQ and affiliate in US
forecast and Europe for 2 lead assets
▪ Supported 2 product ▪ Specific resource ramp-up plan over time in HQ and
launch preparations affiliate informed by benchmarks and internal
▪ Blueprinted requirements
organization and
growth plan

Impact
▪ Built USD2bn vertical oncology business ▪ 1 successful M&A bringing in 2 assets in
unit from scratch within 24 months solid and haematological indications
▪ 4 individual assets in-licensed and ▪ Full resource ramp-up and launch
integrated into pipeline readiness of lead assets

8
Health systems example – the Colorectal Cancer
Improvement Program

Background
Client description Engagement objectives Unique/specific challenges
▪ 5 health systems with ▪ Improve colorectal cancer ▪ Unique requirement to
goal to optimize care pathway through understand and map clinical
cancer care cost-neutral initiatives to pathway in detail
▪ Budget restrictions reduce mortality ▪ Deep medical understand-
required cost ▪ Save on long-term ding and cost transparency
neutrality healthcare costs by to develop value pool tool
improving earlier detection ▪ Development of tool that for
first time allowed to estimate
costs and benefits of earlier
detection

Approach
Ara Darzi (Chair)  1-year program to improve care in colorectal cancer
Imperial College, London  Use data available in health systems
 Former UK MoH  Collaborative approach across project teams
 Colorectal through frequent contact
cancer
surgeon  Identification of discrete value pools where cost per
intervention did not match outcome benefit
 Reallocation of investment to most outcome
effective interventions across pathway
 Improvement initiatives to capture value within
2 years

Impact

Mortality
reduction Budget savings
Percent USD millions p.a.
NHS Lothian ~11 1–3

NHS Central South Coast Cancer Network ~10 4–6

Singapore Ministry of Health ~11 7–10

Queensland Department of Health ~9 10–25

Victoria Department of Health ~9 15–30

9
10
Overview of our scientific advisory board and internal
expert infrastructure

McKinsey Cancer Center Advisory Board

Roy Herbst Jorge Cortes

MD Anderson Cancer Center, MD Anderson Cancer Center,
Houston, US Houston, US

Eric Winer Al Benson

Dana-Farber Cancer Institute, Northwestern University,
Boston, US Chicago, US

Stan Kaye Helmut Friess

Royal Marsden Hospital/Institute of Technical University of
Cancer Research, UK Munich, Germany

Ron Bukowski Robert J. Soiffer

Cleveland Clinic Foundation, Dana-Farber Cancer Institute,
Cleveland, US Boston, US

Adrian Harris Tak Mak

UK Molecular Oncology Laboratories, The Campbell Family Institute,
Oxford, UK Toronto, Canada

Philip Kantoff Peter Bach

Dana-Farber Cancer Institute, Memorial Sloan Kettering Cancer Center
Boston, US (MSKCC), New York, US

Ching-Hon Pui Manfred Dietel

St. Jude Children's Research Hospital, Medical Director of the Institute of
Memphis, US Pathology, Berlin, Germany

Aymen Elfiky Vincent Miller

Harvard Medical School and Dana- Foundation Medicine,
Farber Cancer Institute, Boston, US Cambridge, US

John Seffrin Ashish Kamat

Former CEO American Cancer Society MD Anderson Cancer Center,
Houston, US

Infrastructure and experts

▪ Consultant team of oncologist MDs, PhDs, ▪ Proprietary databases of competitor

and health system experts, each with 10 years resourcing, RWE, disease pathways,
consulting experience or more organization
▪ Dedicated service lines for strategy ▪ Standing collaboration with Gerson Lehrman
development, financial modeling, BD&L, IO, Group, Research Now, and AlphaSights
and others
▪ Team of analysts for market research, data
analytics and modeling, pricing models, clinical
trial design, and optimization

11
McKinsey oncology publications – recent examples

Launches in Highlights recent changes in the market environment and

oncology: The their implications on successfully launching oncology
elements of therapies including competitive positioning, medical affairs
success support, stakeholder management, and operational
excellence

Pursuing Describes key changes in the oncology drug development

breakthroughs paradigm and the role of data as well as explores how
in cancer drug companies can deliver the right medicines to the right
development patients faster. It also suggests 5 imperatives for relevant
stakeholders and opportunities which arise as a result

The next wave Highlights the new wave of therapeutic and diagnostic
of innovation in technologies making their way from the bench to clinic in
oncology oncology. This includes therapeutic technologies as well
as diagnostic approaches such as personalized biopsies

McKinsey Highlights critical issues facing pharma, biotech, and

Personalized diagnostics companies in personalized medicine and
Medicine provides perspectives on winning strategies for each type
Compendium of player

McKinsey Health Outlines key challenges and proposes solutions for health
International on systems as they set out to maximize their cancer budgets
health systems to get the best possible outcomes for their cancer patients
and cancer

World Innovation A structured view on current and future challenges to fund

Summit of Health cancer care and recommendations for improved funding
(WISH) across countries and potential socioeconomic divides

McKinsey Describes an approach to identify value pools along a

pathway-based disease-specific population-based prevention and care
improvement of pathway that allows systemwide cost reallocation to create
CRC care outcome benefit

12
McKinsey Cancer congress series – annual satellite
symposium at ASCO

Program topics over the years

2008 2011 2013 2015 2017

Future of Linking care Oncology Oncology One trial
oncology delivery to disease combination to launch
outcomes pathways therapies

2010 2012 2014 2016 2018

Oncology Personalized Big data in Next wave I/O – the
care model medicine oncology of innovation $60bn
in oncology experiment

Participants
▪ >150 clients from pharma and
biotech industry, intermediaries,
professional associations, and
cancer centers
▪ Heads of global, regional, and US
oncology business units, biotech
CEOs, global functional leads,
world-leading clinician scientists

13
14
Suite of platforms we offer – novel tools
and methodologies

Cancer labs Cancer data and Cancer access and Cancer strategy and
advanced analytics outcomes go to market

New platforms for rapid Data aggregation and Innovative market Growth strategy
market insights and data analytics platform for access strategies and simulation platform and
analytics advanced analytics and capability building innovative GtM
insights generation programs approaches

▪ Rapid, quantitative ▪ Data aggregation from ▪ >400 treatment ▪ Ready-made growth

high-prescriber market over 30 databases pathway-based strategy frameworks,
research and analysis covering >10m cancer collaboration models portfolio simulation and
▪ Big data analytics patients combining across >10 tumor types P&L modeling
including real-world EHR, RWE, PRO, for pharma, medical ▪ Suite of innovative go-
evidence, patient consumer, and other device, and payors to-market approaches
finder, etc. data ▪ Comprehensive across different tumor
▪ Advanced analytics oncology market types and geographies
platform including access academy with
machine-learning multiformat capability
insights generation building programs

15
Cancer IO/ Cancer Cancer drug
MIOSS rapid DD development/CAO

Comprehensive deterministic Approach to rapid Suite of assets

scenario modeling engine for asset/technology due to optimize clinical development
IO assets and portfolios diligence and forecasting strategies for single assets or
asset portfolios

▪ Simulation engine ▪ Highly detailed rapid DD on ▪ Optimizer tools and

forecasting multiple different preclinical, clinical, and in- approaches to optimize
IO market scenarios to market assets clinical strategy design and
inform strategic and ▪ Pipeline screen model and execution
competitive decision making refined forecasting for ▪ TPP and TVP design
▪ Clinical trial and indication assets and portfolios approaches and clinical
sequencing, combination outcome scenario modeling
therapy design, and IO approaches
asset ownership simulations

16
Cancer labs – rapid quantitative market
research reaching 250–300 prescribers
in 5 days

Large-scale, multicountry cancer survey …

Major cancer types ▪ Prostate ▪ Colorectal
▪ Lung ▪ Other available upon request
▪ Breast (e.g., CLL, CML, MM)

5 EU countries

Other international
markets

>50 participants ▪ Up to 50% cheaper than other providers plus real insights
and synthesis

Cost level ▪ Sample size of 50 high prescribers/country is guaranteed

>15 questions ▪ At least 15 closed questions

▪ Further (open) questions may be asked with marginal
price increase

… with rapid, 5-day turnaround

Steps Deadlines
Questionnaire ▪ Team hands over questionnaire and sample
Monday morning
parameters – quick quality check

Programming ▪ Questionnaire is programmed and tested,

Tuesday
launched the next day

Fieldwork ▪ Physicians fill out questionnaire – McKinsey Thursday/Friday

ensures completion based on predefined sample
parameters

Database ▪ McKinsey checks and filters data and completes

Friday/next Monday
check final database for analysis

17
Cancer data and AA – data aggregation
and analytics platform for advanced
analytics and insights generation

Broad and exclusive oncology data sources

McKinsey common data model Key benefits
▪ Integration of disparate data into
centralized, flexible repository
Commercial ▪ Combination of medical,
secondary consumer, and behavioral data
data for patients and HCPs
▪ Holistic model development and
production through integrated
Academic commercial data sources.
institution Academic data to monitor
partnerships ongoing model robustness
▪ Late binding (“schema on read”)1
Public data ▪ Large processing power for
sources advanced analytics and signal
detection on proprietary
▪ CRM data through Veeva, SFA system cloud- based platform
Client- ▪ Patient hub data
▪ Specialty pharmacy partnership data
▪ Ease of portability to client
provided
▪ IQVIA, SHS environment for enterprisewide
data
▪ Social media/patient forum partnerships scale-out

Proprietary machine-learning platform

▪ Automated research engine and
machine- learning platform “Nerve”
▪ Extensive function library with feature discovery and optimization
▪ Machine learning with algorithm selection and model visualization

Multiple oncology use cases

▪ Patient segmentation refinement through analysis of 39m behavioral patterns to
double brand potential
▪ Trigger-based deployment for field team via type and frequency of lab reports linked
to anonymized patient data
▪ Segmentation-of-one for uro-genital oncology sales force via patterns in Rx behavior
▪ Real-world-evidence data-analysis-driven FDA application for data expansion

1 Schema on read refers to an innovative analysis strategy in new data-handling tools like Hadoop and other more involved
database technologies. In schema on read, data is applied to a plan or schema as it is pulled out of a stored location

18
Cancer access and outcomes – innovative
market access strategies and capability
building programs

Innovative market access strategies

▪ Population pathways by tumor type based ▪ Collection of >400 products and services
on international guidelines and literature pharmaceutical companies and healthcare
▪ Critical interventions along pathway and institutions offered beyond conventional
quantification of cost and outcome benefit drug-selling model
▪ Identification of opportunities for care ▪ Categories C include add-on products/
optimization, cost reallocation (“value services, training/education, support
pools”), and respective solutions for health services, care consulting services, care
systems and pharma/biotech/device delivery

Market access capability building academy

▪ Customized academy learning programs ▪ Field work tailored to and focused on key
teaching functional and business skills business deliverables for respective
▪ Multiformat nature reflecting best practices functional teams
of adult learning including ▪ Program size from 30 to over 100
in-person forums, fieldwork, coaching, and participants ranging from 4 months to over
digital courses via McKinsey Academy 1 year
▪ Balance of functional topics, business and ▪ Train-the-trainer concept for continuous
leadership skills, format and timing can be program delivery, renewal, and expansion
fully tailored to specific client needs as needed

19
Cancer strategy and go-to-market – growth
strategy simulation platform and innovative
GTM approaches

Cancer strategy – elements and use cases

Platform to develop winning growth strategies from R&D to commercialization
Elements Use cases
▪ Strategic growth frameworks and ▪ Oncology strategy refresh or de novo
approaches franchise launches
▪ Forecast engine for portfolio scenario ▪ Competitive scenario modeling
modeling ▪ Asset or portfolio lifecycle management
▪ BD&L contribution assessment assessments
▪ Pro-forma P&L output ▪ BD&L strategies and screens
▪ Portfolio asset balancing and resource
(re-)allocations
Growth can come from one of 4 directions, each requiring a different lens Growth scenarios based on identified opportunities can be assessed in a Disguised example – Illustrative output to assess sales potential of growth
to identify the right opportunities data-driven manner to trade off value potential and investment scenarios to address flattening top-line Externally licensed assets Internal pipeline

1 Apply a clinical development lens to

2 optimize indications to pursue, Net sales 2013-2030 Upfront cost 2015-2019
Scenarios2030
$ moutlook - Scenarios based$ on
m 8 compounds sourced 2014-2017 1
Current indications Other indications Input Analysis Output Key points for consideration
based on match between asset and Incorporate key inputs from several sources Assess top and bottom-line Assess NPV and sensitivity of
indications, competitive dynamics, to capture the context and lay out key impact over time across each scenario, compare against • Long time to market due to cycle times
1 Focus 2 Expand indications and indication value assumptions assets in each scenario investment to optimize solution 89 89 89 89 • Significant attrition risk
In-license
Core indications Non-core • Limited overall financial risk due to back-
pipeline 2,000
Asset 1 2 3 4 5 6 7 Risk-adjusted sales Risk-adjusted NPV loading of cost
Double down Explore current Scenarios, e.g., assets
contribution (Scenario A) 1,000 • Possible risk optimization (e.g., opt-in
Internal investment in current assets in tumor types A Ph 3 0
options)
▪ Invest in internal R&D of X assets US$ M 0
assets assets in the core outside of current B Ph 3
▪ In-license X “average” pipeline asset Scenario 300 300 300 300 • Long time to market due to cycle times
indications pillars Acquire /
• Front-loading of investment compared to
C Ph 3
▪ In-license X block-buster pipeline asset 3,500 A
C purchase 2,000
D ▪ Purchase X pipeline asset Asset 1 in-licensing option (no milestone
3,000 pipeline 1,000 payments & royalties)
E Preclin ▪ Co-promote X marketed assets Asset 2 D assets 0 • Higher overall risk (e.g., attrition)
▪ Acquire a company with X assets 2,500 Asset 3 0
3 Expand assets 4 Explore new F Ph 1 Ph 1
Asset 4 B E • Fast time to market/access to technology
2,000 Co- 400
horizons Information about potential assets • Limited risk as assets already marketed
promote 2,000
1,500 by partner
Externally source marketed
3 Apply a BD lens to identify MoA ▪ Indications (opportunity sizing) 1,000 • Least feasible option as few potential
External assets as Expand into non- assets 0 0 0 0
(e.g., kinase inhibitors, checkpoint ▪ Stage of assets 1,000 partners would offer an attractive deal
0
assets monotherapy or core indications with ▪ Available efficacy / safety data
modulation targets), and asset 500 • Fast time to market/access to technology
combination partner externally sourced types (e.g., mAbs, ADC, cell ▪ Competitive landscape 3’000 • Significant increase of sales potential
with internal assets in assets - • Requires large upfront investment (based
therapy) to supplement current M&A 2,000
2013
2015
2017
2019
2021
2023
2025
2027
2029

core indications Industry/company-specific benchmarks on the current market outlook upfront

portfolio Investment needed 1,000
cost could even be higher)
0 0 0 0
4 Assess longer-term strategic ▪ Development costs / timeline 0
▪ Payments for license, upfront, milestone,

2015
2017
2019
2021
2023
2025
2027
2029
2031

2015

2016

2017

2018

2019
partnership or M&A opportunities to
premium
move into new areas (e.g., co- Approach provides a clear fact base to support
▪ PTRS in given indication
development, co-promotion, recommendation, and clearly illustrates tradeoffs
▪ Discount rate / cost of capital 1 All scenarios based on licensing/acquiring 8 external assets in 2014-2017, except option “co-promote marketed assets” (2 marketed assets) and “M&A”
licensing, M&A) (1 marketed assets and 6 pipeline assets); cost assumptions for internal pipeline same as for externally sourced asset modeling

Cancer go to market – available modules

Launch excellence Go-to-market innovation Commercial resource
modeling
▪ Suite of launch ▪ Collection of innovative ▪ Modeling engine to
excellence modules go-to-market approaches predict field synergies
including launch to support field-based across tumor types
readiness framework and teams based on patient ▪ Quantification of
Web-based tracking tool, and physician journeys incremental field
organizational ▪ Digital and advanced resources required based
approaches, case analytics approaches, on prescriber overlap
example library, launch solutions beyond the pill,
uptake analytics innovative partnering

20
Cancer IO/MIOSS – comprehensive
deterministic scenario modeling engine
for IO assets and portfolios

Extremely rapid evolution of IO market MIOSS simulates market and portfolio

with nearly daily updates scenarios

Rapid market growth predicted until … with subsequent shift to competition

2022 … for share

MIOSS offers market forecasting and … as well as risk assessment and

portfolio simulation … functional strategy development

MIOSS – McKinsey Immuno-oncology Strategy Simulation

21
Cancer rapid DD – proven track record
serving clients in rapid DD from preclinical
to on-market assets

Stage of
asset Example client situation Scope

Preclinical/ ▪ In-licensing assessment for an ▪ Scientific diligence on MOA

discovery emerging technology platform ▪ Best-guess development pathway
in discovery phase in the ▪ Valuation model (analog based)
space of immuno-oncology

Pre-POC ▪ In-licensing assessment for ▪ Potential clinical differentiation from

a Phase I oncology asset standard of care and new pipeline
(with data room access) ▪ Scientific rationale for indication/line
expansion
▪ Valuation model (bottom-up, patient
based)

Post-POC ▪ In-licensing assessment for ▪ Phase III clinical data review and
a Phase III oncology asset differentiation from standard of care and
post data readout (with data new pipeline
room access) ▪ Assessment of new indications/lines of
therapy
▪ Valuation model (bottom-up, patient
based)

On-market ▪ M&A assessment for an ▪ Assessment of new competitive pipeline

on-market drug ▪ Pricing sustainability
▪ Threat from biosimilars
▪ Pressure testing lifecycle management
plan

Use cases for rapid DD are

not only in BD situations, but
also in major stage-up
decisions for internal pipeline

Analog drug database Valuation model solution Forecasting in a box

▪ Database of over 1,000 drug ▪ Drug valuation engine for ▪ Comprehensive playbook
launches systematically both pre-POC assets and and toolkit for drug
characterized by >20 variables post-POC assets forecasting

22
Cancer drug development/CAO – suite
of assets to optimize clinical development
strategies for single assets or asset portfolios

What does CAO do?

Archetypes Description Impact examples
Product ▪ Comprehensive program design for ▪ Complete program redesign for 2 pre-POC assets;
development commercial success USD150–250m savings, >3 years acceleration
strategy ▪ Applicable to all asset stages – from pre-POC ▪ Lifecycle management clinical trial strategy for lead
to market asset; USD300–500m additional peak sales
opportunity
Portfolio ▪ Portfolio strategy and investment decisions ▪ Oncology portfolio and asset strategies for several
decisions/ ▪ Organizational capability building top-10 pharmacos
capability – Expertise transfer ▪ Several NDAs filings for midsize pharmacos (all
building – Tools and processes approved)
– Operational acceleration
Investment ▪ Targeted decision support, e.g., asset ▪ Development strategy ahead of POC investment
due diligence acquisition or stage gate advancement decision for several oncology assets
– Objective, fact-based analysis ▪ Definition of POC stage gate criteria for 3 assets
– External validation across MOAs
– Framing and evaluation of business, ▪ Multiple asset evaluation projects
clinical, etc., trade-offs

Guiding principles for asset optimization

Identify ▪ Identify, De-risk ▪ Further stress- Maximize ▪ Shorten time to market and aim for the
risks disaggregate, early test prioritized value indication with the greatest market
and prioritize risks, prior to potential by optimizing indications,
risks inherent starting Phase III inclusion criteria, and end points
to the asset ▪ Stop projects ▪ Optimize TPP for a suite of indications
based on TPP early if success and LCM strategies, ensuring that the first
and research in Phase III is indication allows appropriate expansion
results questionable ▪ Broaden indication later to fully leverage
drug’s potential

Tool What it is
Asset strategy Cross-functional methodology for meeting commercial
optimizer differentiation goals while optimizing for speed, cost, and
feasibility
Risk Practical risk management methodology to assess, prioritize, ▪ Frame and quantify
optimizer and mitigate most important risks among strategic, operational, trade-offs among
and organizational ones cost, speed, PTS
▪ Focus on the
Cost Objective and independent evaluation and optimization of decisions that can
optimizer major trial design cost drivers (e.g., number of sites, monitoring change the course
visits, recruitment length) of a program
Trial design Strategic trial design and stats analysis planning to ensure
▪ Foster an internal
culture of cross-
optimizer trials support the achievement of a differentiated TPP
functional
collaboration and
Speed Comprehensive program for accelerating trials based on disciplined decision
optimizer analysis and optimization of most relevant subactivity in design, making
execution, and filing phases
Clinical program Industry-leading experts available at a short notice for
advisory board workshops and due-diligence-style inquiries

23
Our leadership team covers the Americas, Europe,
and Asia with over 150 years of experience

Europe North Americas

Bjorn Albrecht, PhD (Lead McKCC) Laura Furstenthal, PhD
Partner, London Senior Partner, San Francisco
(Post-)doctoral research in molecular oncology, Doctoral research in cancer biology, >20 years
Leukemia Society Fellow, 20 years of oncology of oncology experience
experience
Thomas Rudolph, MD Olivier Leclerc, MBA
Senior Partner, Stuttgart Senior Partner, Los Angeles
Medical training and specialization in oncology, Oncology strategy, launch, and commercial
>20 years of experience expertise, >15 years of experience

Philippe Menu, MD, PhD, MBA Paul Gurney, PhD

Associate Partner, Geneva Partner, San Francisco
Medical and research training in oncology, Commercial and go-to-market as well as value in
>10 years of experience oncology expertise, 10 years of experience
Sébastien Allard, MBA
Associate Partner, Geneva Kevin Webster, PhD
Oncology market access and outcomes expertise, Associate Partner, San Francisco
>5 years of experience Diagnostics and personalized medicine,
biomarkers, >5 years of experience
Stephan Wurzer, PhD
Engagement Manager, Munich Flora Yu, MBA
Oncology research in cancer stem cells, Associate Partner, Silicon Valley
5 years of experience Business development and strategy expertise,
>5 years of experience

Asia Lydia The, PhD

Engagement Manager, Silicon Valley
Minyoung Kim, MD, MBA Immuno-oncology, PD-1 and CAR T-cells, overall
Partner, Tokyo and R&D strategies, >5 years experience
Business unit and local oncology strategy and
commercial expertise, >10 years of experience Dmitriy Kolodin, PhD
Engagement Manager, Los Angeles
Tina Hou, MBA Commercial immuno-oncology expertise and
Partner, Shanghai business unit strategy experience, >3 years of
Local oncology strategy and regulatory expertise, experience
10 years of experience
Guang Yang, PhD
Gaobo Zhou, MS, MBA
Engagement Manager, Charlotte
Partner, Hong Kong
CAR T-cell, Immuno-oncology, asset-optimization
Local oncology strategy and commercial expertise
expertise, >5 years of experience
including health system, >5 years of experience
Yukako Yokota, PhD Sandra Andersen
Partner, Tokyo Engagement Manager, New York
Local business unit and product strategy, Oncology strategy, launch, and GTM innovation,
5 years of experience >3 years of experience

Dedicated experts
Daina Graybosch, PhD Jason Hichborn
Senior Expert, New York Specialist, New Jersey
Doctoral research in oncology, immuno-oncology, Commercial, market access, and digital expertise,
and clinical development expert, >15 years of 4 years of experience
experience
Keval Chauhan, MS, MEng Tiffany Kwok
Senior Analyst, London Advanced analytics Expert, Tokyo
Commercial, corporate finance, and strategy Clinical and commercial analytics expert, 5 years
expertise in oncology, 4 years of experience of experience

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