Annex C

The financial ecosystem
of pharmaceutical R&D
Future scenarios for the financial
ecosystem of pharmaceutical R&D

Cambridge, December 2021
Sarah Parkinson
Robert J Romanelli
William Philips
Samiha Alom
Sonja Marjanovic

Annex C

Table of contents
1

2

3

Introduction and methods

2

1.1

Readers’ guide

2

1.2

Methodology

3

1.3

Limitations and caveats

12

Description of future scenarios

13

2.1

Scenario 1: Golden global age for pharmaceutical R&D

13

2.2

Scenario 2: Incremental improvements in the pharmaceutical R&D sector

17

2.3

Scenario 3: Pharmaceutical R&D stagnation

21

Key learning points from the stakeholder workshop

25

3.1

Scientific and technological advances

26

3.2

The role of data and digital innovation in pharmaceutical R&D

28

3.3

Financing the pharmaceutical R&D sector: creating sustainable landscapes

30

3.4

Global collaboration and competition

32

3.5

Concluding thoughts

35

Appendix A: Tools for scenario development

38

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Annex C

1 Introduction and methods
1.1 Readers’ guide
Annex C describes a work package for this study which developed three future scenarios for the
pharmaceutical R&D sector based on insights from prior work, the research team’s critical
reflection and consultation with the study’s Scientific Advisory Committee (SAC). The scenarios
aimed to represent a mix of more likely and extreme possibilities for the future. As such, they
provided a research tool enabling stakeholder discussion about current issues where actions may
be needed to prepare for the future and optimise the future financial ecosystem of pharmaceutical
R&D. The scenarios helped stakeholders reflect on ways to maximise opportunities, minimise risks
and manage the challenges ahead.
These scenarios were explored in a workshop of international stakeholders from various sectors,
as described in more detail in Section 1.2. Stakeholders in the workshop considered each
scenario’s challenges and opportunities reflecting on important themes and implications for
measures diverse societal stakeholders currently need to consider to prepare for the future.
This report is organised in the following sections:
• Section 1.2 describes the methodology used to develop future scenarios, conduct the
stakeholder workshop and arrive at results from the workshop
• Section 1.3 identifies limitations and caveats for the reader to bear in mind when interpreting
the insights presented in this progress report
• Section 2 describes the future scenarios developed and used in the stakeholder workshop.
• Section 3 summarises key insights from the workshop, organised by theme.
RAND Europe led Annex C and the associated work package.
The overall scope and focus of the research study should be borne in mind when interpreting the
findings of this work package. The workshop's scenarios aimed to identify key themes, challenges
and potential stakeholder actions to optimise R&D's future financial ecosystem. This included
identifying and reflecting on themes related to the wider healthcare and innovation landscape,
extending beyond directly implicated factors such as the availability of capital, R&D costs and
success rates. This study and work package did not aim to consider specific actions and
implementation requirements or attribute specific actions to distinct stakeholders. Instead, the
commissioned research was for a predominantly descriptive study characterising pharmaceutical
R&D financing, stakeholder motivations and actions, and value creation and transactions.
Exploring how broader system-level factors have influenced financial aspects in the past and how
they might do so in the future complements the overall study’s core focus.
Future research could build on this work package’s insights into the current actions that may make
the pharmaceutical R&D financing system fitter for the future, as discussed in the following
contents. A future research agenda could include analyses of the progress already made in specific

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areas where action may be needed to optimise the financial ecosystem of pharmaceutical R&D and
identify critical gaps and how these may differ across geographies. Such future research could
provide value in supporting the exchange of learning between different stakeholders and
geographies about what works in creating supportive health and innovation landscapes, what
actions are in the domain of national efforts, and which are dependent on international cooperation
and coordination.

1.2 Methodology
Although previous work packages inform this report’s findings, this Annex focuses primarily on
establishing future scenarios for how the pharmaceutical R&D sector may develop over the next
decade and an associated stakeholder workshop to discuss them. The aim was not to predict the
future or determine the most likely scenario but to help explore various possible futures and use
them to facilitate reflection and critical thinking about the implications of possible futures on the
present challenges and risks needing management and opportunities to harness. As with all
scenario work, multiple scenarios are possible. The research team selected sufficiently different
scenarios – both more likely and more extreme – to stimulate discussion and reflection among
stakeholders involved in pharmaceutical R&D.
The methodology for developing future scenarios and details about the stakeholder workshop are
described below.
1.2.1 Developing scenarios
The development of future scenarios involved the following stages, each described in further detail
later in this section:
• Identifying a longlist of key factors that may influence the pharmaceutical R&D landscape in
the next decade based on insights from prior work packages and consultation with this
study’s SAC
• Conducting an influence analysis to determine the most important and influential factors in
the future pharmaceutical R&D system
• Shortlisting the key influencing factors
• Developing projections for how each factor in the future scenarios may develop over the next
ten years
• Performing a consistency analysis to evaluate how consistent it would be for combinations of
projections for different influencing factors to appear in the same future scenario
• Performing a cluster analysis to identify plausible future scenarios based on consistency
analysis, by (i) using the help of specialised software to complete this task and (ii)
triangulating software outputs with the research team’s qualitative expertise and integrating
learning from the SAC’s expert views throughout the project
• Developing distinct, clear and easy-to-engage-with narratives for three future scenarios.
RAND Europe undertook this process in close collaboration with the L.E.K Consulting and SiRM
project teams, incorporating key advice and feedback from the SAC. Scenario Manager ScMI

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software package1 was used to inform the research team discussions and analysis that led to
selecting three scenarios as workshop aids.
Identifying a longlist of influencing factors
Based on insights from this study’s previous work packages, the research team identified a list of
25 potential factors2 influencing the future pharmaceutical R&D ecosystem (
Table 1). Th project’s SAC advised on this list’s comprehensiveness via email. This exercise
resulted in a longlist of potential factors for inclusion in future scenarios and a basis for prioritising
key influencing factors.
Table 1. Longlist of influencing factors.

Influencing area
Availability of capital/funding
Costs of pharmaceutical R&D
Scientific and technological developments

Drug pricing /affordability

Factors

1 Overall availability of funding for pharmaceutical R&D
2 Pharmaceutical R&D costs
3 The scale and pace of scientific and technological

advances and how they are incorporated into
pharmaceutical R&D
4 Data science and digital innovation advances, and
how these are incorporated into pharmaceutical R&D
5 Therapeutic and clinical focus areas within
pharmaceutical R&D
6 Major drug failure events once a drug is on the market
7 Success rates in pharmaceutical R&D

8 Costs of new and innovative drugs
9 Decisions around drug prices in key global markets
10 New financial models for reimbursement and
pricing

Collaboration

Nature of investors and investment
landscape

11

Pharmaceutical-sector reliance on external sources
of early-stage R&D
12 Biotech/SMEs entering later-stage R&D
(independently conducting later-stage R&D before
being acquired or selling assets to Pharma)
13 Collaborator diversity in pharmaceutical R&D

14

Public and not-for-profit investors/investment in
pharmaceutical R&D
15 Private-sector investment in pharmaceutical R&D
16 The public and-not-for-profit sectors’ commercial
attitudes around investing
17 Venture-capital (VC) sector consolidation or
diversification*
18 New financial models for investing in
pharmaceutical R&D
19 Indirect public-sector instruments and incentives*

Scenario Management International AG, Germany, Klingenderstr. 10-14, 33100 Paderborn. Email: info@scmi.de, Web:
https://www.scmi.de/en/
2
Two of these factors were discarded before progressing to the influence analysis stage, which is why only 23 factors
were included in the influence analysis exercise.
1

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Geography
Regulation
Unforeseeable macro-level events

Patient and public voice and attitudes

20

Global dynamics in pharmaceutical R&D and the
rise of emerging markets

21
22
23

Regulatory innovation
Government attitudes to intellectual property

Macro-level events (e.g. conflicts, wars and
pandemics)
24 Maintaining and applying learning from Covid-19
pandemic to improve pharmaceutical R&D

25

Patient attitudes towards and influences on R&D
agendas

*Factors were discarded from the long list before progressing to the influence-analysis stage of shortlisting.

Influence analysis
After identifying the longlist of potentially relevant factors for the future pharmaceutical R&D
landscape, the research team explored interrelations between different factors to identify mutual
influences. We aimed to rank each longlist factor’s impact on every other factor and score their
impact on one another. For example, we scored how much the availability of future pharmaceutical
R&D funding will influence the supply of scientific and technological advances, and vice versa.
Every factor pairing was scored from 0–3 to indicate how much a single factor impacts or
‘influences’ another (where ‘0’ indicates no impact and ‘3’ indicates a strong and direct impact).
It is vital to note that the ranking process entailed a degree of subjectivity inherent in all
quantitative approaches to scenario development. Influence analysis is only a tool, with no clear
‘right’ or ‘wrong’ ranking. Experts build on assumptions about the future in all scenariodevelopment processes, and the influence matrix aims only to stimulate discussion about the
system’s interrelationships. Influence analysis helps tease out the most direct and influential
relationships from less pivotal ones. Thus, the ranking itself is not the exercises’ purpose or output
but a tool to facilitate reflective discussion in the research team to identify the most important and
closely related variables to consider in scenario narratives.
The research team organised an internal workshop to agree on influence-analysis scores,
undertaken on an Excel-based matrix (see Figure 5 in Appendix A).
The outcome of this analysis is displayed in Figure 1, which shows the ‘activity’ and ‘passivity’
scores for each factor. A factor’s ‘activity’ score measures the magnitude of its influence on all
other factors in the system. The ‘passivity’ score measures the opposite – the magnitude of all
other factors’ influence on the single factor of interest. Factors with a high activity score and a high
passivity score are shown in the top-right of the figure (e.g. investment in pharmaceutical R&D).
These factors are strongly interconnected, significantly influencing and influenced by other factors.
Factors with a high activity score but a relatively low passivity score are shown in the top-left of
the graph. These factors are likely to influence other factors but are less likely to be influenced by
them. Despite a lower passivity score than many other factors in the system, these factors are still
very influential and may be important in developing future scenarios. Similarly, factors with a high
passivity score but a low activity score (seen in the bottom-right of the graph) are determined by
many other factors within the system, justifying their importance in future scenarios. Note that the
graph below is based on rankings rather than absolute scores; thus, there will always be items in
each quadrant of the graph based on each factor’s relative passivity and activity.

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Annex C

Figure 1. Activity-Passivity graph for the longlist of influencing factors. Note: All 23 factors are ranked in order of highest
activity/passivity (1) to lowest activity/passivity (23). Dot colours group factors by influencing area – see Table 1.

Shortlisting factors and creating projections
Developing scenarios requires focusing on a set of key factors to build a narrative around. Given
this, the next step was to create a shortlist from the initial longlist, deciding which factors should
be central to the scenario narratives. The main aim was to create three sufficiently different
scenario narratives for use in the workshop , ensuring a manageable number of factors guided the
overarching scenario narrative.
We considered a range of factors in this decision-making process. These included:
• The results of the influence analysis, providing insights into the strength of each factor’s
relationship with others in the pharmaceutical R&D ecosystem
• The need to consider both highly active and highly passive factors (i.e. those that strongly
influence other factors and are strongly influenced by them) and some active factors with
lower passivity scores that could nevertheless raise important considerations for stakeholders
(e.g. that may strongly influence other factors but not be strongly influenced by other factors)
• The need to ensure a diverse range of topic areas in each scenario that reflect the overall
project’s aims, e.g. present scenario ‘curveballs’ that create sufficiently complex and nuanced
‘worlds’ to encourage creative reflection in the workshop.

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These considerations guided the study team to ensure that shortlisted factors met the work
package and broader study’s needs.
Narrowing down a longlist of factors is essential to develop meaningful future scenarios that
stakeholders can easily consider and engage with. However, this process necessarily simplifies the
pharmaceutical R&D ecosystem’s complexity to identify a manageable number of variables guiding
scenario construction. While some scenario aspects are linear (e.g. more funding will likely go into
the pharmaceutical R&D system as science and success rates improve), there are also important
non-linear relationships where the pharmaceutical R&D system reacts in unexpected ways to
specific factors, since it is a complex adaptive system. To help capture this non-linearity
manageably, the research team included some ‘curveballs’ in each scenario alongside the core
factors included in the shortlist (see below). For example, one scenario involved pricing discussions
in key markets causing global profitability concerns, while another included a major drug failure
impacting an entire therapeutic sector’s financing. Although it was necessary to simplify some of
the pharmaceutical R&D system’s complexity in the future scenarios presented to stakeholders,
the scenarios were simply a tool that facilitated rich discussions during the workshop. Discussions
covered many of the broader influences impacting pharmaceutical R&D’s complex financial
landscape. Annex B provides a more detailed discussion of the influences, certainties and
uncertainties society faces regarding the pharmaceutical R&D’s financial ecosystem, discussing
insights from in-depth stakeholder interviews and exploring the additional factors involved.
The key factors selected for informing the next stage of scenario development are listed in Table 2.
We then created projections for each factor, representing the diverse ways each factor may
develop over the next ten years. Projections included likely and more-extreme/less-likely
projections that could have significant consequences if they unfolded. Projections for each factor
and initial ideas around which factors to consider shortlisting were checked with the SAC to
ensure no key factors were omitted.
Table 2. Shortlist of factors and their projections.

Factor
Overall funding availability for
pharmaceutical R&D
Costs of pharmaceutical R&D (trends
related to unit costs to develop one
medicine)

Scale, pace and nature of scientific and
technological advances

Therapeutic and clinical areas pursued

Projections
• Increases
• Remains the same as today
• Decreases
• Increase
• Remain relatively stable, do not increase further
• Decrease
• Change unevenly (R&D costs increase for some drugs
and decrease for others)
• Accelerate and creates new opportunities
• Continue at a rate similar to today (not an accelerating
pace)
• Stagnate and fail to deliver on initial promises
• New areas emerge
• Some current therapeutic areas become less
important, narrowing global portfolios
• New areas do not emerge

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Annex C

Public and not-for-profit investment in
pharmaceutical R&D
Private-sector investment in
pharmaceutical R&D

Success rates in pharmaceutical R&D

Global dynamics in pharmaceutical R&D
and the rise of emerging markets

•
•
•
•
•
•
•
•
•
•

•

Regulatory innovation (e.g. supporting
smarter trials and better use of R&D data)

•
•
•

Increases relative to other funding sources
Remains stable relative to other funding sources
Declines relative to other funding sources
Increases relative to other funding sources
Remains stable relative to other funding sources
funding
Declines relative to other funding sources
Increase
Remain broadly unchanged
Decrease
Emerging markets such as China and other countries
in the APAC region grow and become more linked to
European markets
Emerging markets grow but remain separate from
other global markets
Emerging markets do not grow and mature
Evolves to facilitate smarter, quicker and cheaper trials
Does not evolve to facilitate smarter, quicker and
cheaper trials

Consistency analysis
The next step was to conduct a consistency analysis to evaluate how likely a projection for one
factor can co-exist with a specific projection for another factor. We scored each pairwise
combination of projections to evaluate how plausible it is that two projections appear in the same
future scenario together (see Figure 6 in Appendix for the Excel-based template used for this
process). Projections deemed highly consistent were assigned a ‘5’, those deemed highly
inconsistent were assigned a ‘1’, those deemed neither consistent nor inconsistent were assigned
a ‘3’. To illustrate, an increase in available funding might be highly consistent with an increased
pace of scientific and technological development in pharmaceutical R&D. However, both
projections might be less consistent with a future scenario with no new therapeutic and clinical
areas pursued.
The project team conducted this scoring in an internal workshop. Again, the scores were not
designed as outputs but facilitated discussion about the relationships between different
projections.
Cluster analysis and qualitative expertise triangulation
The consistency-analysis data was subjected to cluster analysis to identify plausible and
consistent projection bundles (a list of projections with one projection per factor3) to select three
sufficiently distinct clusters to inform the development of scenario narratives. We used ScMI
software to conduct the cluster analysis, which involved grouping alternative projection bundles
with similar and overlapping themes. This stage’s primary outcome was a final set of three
different factor projections outlining three very different futures. We agreed on three scenarios as
the optimal number ensuring sufficient variation and detail without compromising workshop
manageability. Expertise from the research team (from RAND Europe, LEK and SiRM) and insights

The analysis sometimes indicated that two or more projections were equally valid. In these instances, the research team
judged which projection to select.
3

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Annex C

from Scientific Advisors in previous project phases complemented the cluster analysis approach,
incorporating broad and deep qualitative expertise into the final scenarios.
Developing scenario narratives
Finally, we developed titles, narrative descriptions and summaries of each scenario to facilitate
engagement by workshop participants. Along with the outputs of the above exercises, we added
additional detail and context to create a more vivid picture of the future pharmaceutical R&D
environment. We present these scenarios and summarise key themes and influencing factors for
each one in Section 2.
1.2.2 Future scenarios workshop
We designed, coordinated and facilitated a workshop for international stakeholders to reflect on
future scenarios for the pharmaceutical R&D sector. The workshop aimed to engage workshop
participants by inviting them to reflect on possible future scenarios. In particular, participants
considered the challenges, risks and opportunities each scenario presents and the implications for
possible stakeholder actions to prepare for the future and increase pharmaceutical R&D sector
resilience.
Workshop participants spanned a variety of sectors, including pharmaceutical companies,
Biotech/SMEs, policymaking representatives, standalone and corporate VCs, not-for-profits,
academics, consultants and other innovation experts. Invitees were chosen to represent a diversity
of perspectives from different professions, stakeholder groups and geographies. Although
internationally focused, the study is also particularly interested in the financial ecosystem of
pharmaceutical R&D in Europe. Participants included those who contributed to in-depth
stakeholder interviews in earlier project phases. Others were identified based on desk research,
recommendations of experts in the pharmaceutical R&D space and RAND Europe’s professional
networks.
All workshop participants gave informed consent to participate. Representatives from L.E.K.
Consulting, SiRM, VWS and the sounding board for the study 4 also joined the workshop as
observers. Please see below for a list of participants (Table 3) and observers (Table 4) present in
the workshop, along with RAND Europe facilitators and note-takers.
Table 3. Workshop participants.

Name

Organisation

Role

Country

Adrian Towse

Office of Health
Economics

Emeritus Director &
Senior Research Fellow

United Kingdom

Ameet Sarpatwari

Harvard Medical School

Assistant Professor of
Medicine

United States of
America

Anonymous

Novartis

Anonymous

International

This is a group of organisational representatives VWS interacts with about various aspects of the study. The research
team did not interact with this group aside from their role observing the workshop.
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Annex C

Antonios Rodiadis

DG SANTE

Policy Officer

Europe

Boris Azais

MSD

Director of Public Policy
Europe & Canada

International (Belgium
based)

Catriona Manville

Association of Medical
Research Charities

Director of Policy and
Public Affairs

United Kingdom

Chris Molloy5

Medicines Discovery
Catapult

Chief Executive Officer

United Kingdom

Colin Terry

Deloitte UK

Head of Life Sciences
and Healthcare
Consulting

United Kingdom

Daniel Chain

TauC3 Biologics Limited

President and Chief
Executive Officer

United Kingdom

Florian Schmidt

DG SANTE

Deputy Head of Unit
(Pharmaceutical)

Europe

Jeroen Bakker

Novo Holdings

Principal

Denmark

Martin Wenzl

OECD

Health Policy Analyst

International (France
based)

Mathieu Uhart

Sanofi

Director Corporate
Public Affairs Europe

International (France
based)

Neil Bertelsen

Health Technology
Assessment
International (HTAi)

Steering Committee
Member

International (Germany
based)

Susan Kohlhaas

Alzheimer’s Research
UK

Director of Research

United Kingdom

Vijay Karwal

CBC Group/Affamed
Therapeutics

Operating Partner/Chief
Financial Officer

Hong Kong

Table 4. Workshop observers.

5

Name

Organisation

Group (Study team, client or sounding
board)

Leah Ralph

L.E.K.

Study Team

Simon Middleton

L.E.K.

Study Team

Michiel Slag

SiRM

Study Team

Saskia van der Erf

SiRM

Study Team

Marit Heblij

HollandBIO

Sounding Board

Peter Bertens

Vereniging Innovatieve
Geneesmiddelen

Sounding Board

Present for the first half of the workshop.

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Annex C

Wim de Haart

Vereniging Innovatieve
Geneesmiddelen

Sounding Board

David Rappange

VWS

Client

Evert Jan van Asselt

VWS

Client

Wiro Stam

VWS

Client

Prior to the workshop, participants received an agenda for the workshop and a document with a
detailed description and summary of each scenario to familiarise themselves with the scenario
contents (see Chapter 2 of this report).
Workshop conduct
The workshop was conducted on 8 November 2021 using Microsoft Teams and lasted
approximately two hours. The workshop covered the following agenda:
• Welcome and introductions (15 minutes)
• Overview of the project and workshop aims (20 minutes)
• Future scenarios: Interactive facilitated discussion to consider the opportunities and risks
presented by the future scenarios (50 minutes)
• Break (5 minutes)
• Plenary discussion (25 minutes)
• Next steps and close (5 minutes).
Members of the study team introduced the study and the workshop and gave an overview of the
futures scenarios and their development.
The majority of the workshop focused on an interactive discussion about the three future scenarios
for how the pharmaceutical R&D landscape may evolve in the next decade. This discussion
occurred in three breakout groups and centred on the following questions:
1 What are the key challenges and risks in each scenario, and what are their implications for
financing pharmaceutical R&D?
2 What are the key opportunities in terms of potential actions that could be taken now to
maximise the opportunities presented by each scenario and manage potential risks?
Following small group discussions, we asked participants to reflect on common themes across the
scenarios and key takeaways for making the financial ecosystem fitter for the future as part of a
reflective plenary session.
1.2.3 Analysis and reporting
Detailed notes were taken during the workshop, capturing overall reflections on future scenarios,
the challenges and risks presented by each scenario and areas of opportunity for potential action
now. The study team met to discuss the workshop results, as reported in the following chapter.

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1.3 Limitations and caveats
As with all workshops, there is a trade-off between the number of participants and the depth of
discussion. To manage this trade-off, RAND Europe invited representatives of diverse stakeholder
groups and facilitated in-depth breakout discussions in smaller mixed-stakeholder groups and
collective feedback in the plenary session. Although the workshop attracted renowned experts
from diverse stakeholder groups, other individuals who did not attend may have had valuable
contributions. However, many common themes emerged in the workshops and stakeholder
interviews conducted in the previous work package (reported in Annex B) regardless of whether
individuals were from public, not-for-profit or industry stakeholder groups. There may be diverse
cross-sector implementation requirements to make the financial ecosystem for pharmaceutical
R&D fitter for the future, and further research could explore these differences in more detail.
However, this was outside the current study’s scope and focus. In addition, future research could
consider how specific actions needed to optimise the financial ecosystem of pharmaceutical R&D
may differ across clinical areas, e.g. between rare diseases and one-time cures on the one hand
and chronic conditions (such as hypertensives or oncology-related innovation) on the other.
As with all future-focused methods, the choice of scenarios entails a degree of subjective
judgement. The research team sought to use quantitative and qualitative approaches to scenario
development, integrate expertise from across the project team, consult the SAC, and use the
outputs of previous project phases to inform scenario development. This combination of
approaches supports the robustness of the selected scenarios. In addition, and as previously
mentioned, scenarios were framed as a tool for enabling reflection and discussion rather than a
rigid set of predictions.
Scenario selection also occurs in the context of project and workshop aims. Therefore, it is
plausible that researchers might select different scenarios for other projects with different aims,
even given the same input variables and projections. For example, if a project had an explicit
primary focus on drug affordability, variables such as patient and public advocacy and those
related to innovative pricing models might plausibly be selected as more prominent than others.
Given the current study’s primary focus on the financing of pharmaceutical R&D, variables such as
patient and public advocacy and affordability pressures are included in specific scenarios but not
the primary variable of focus.

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2 Description of future scenarios
Each future scenario used in the workshop is described below and assumes we are in the year
2031. As mentioned above, the scenarios do not predict the future or determine which futures are
more likely but encourage reflection and critical thinking about the implications of various possible
futures in terms of challenges, risks and areas of opportunity.

2.1 Scenario 1: Golden global age for pharmaceutical R&D
It is 2031, and the pharmaceutical R&D sector is thriving. The past few years have seen
significant scientific and technological breakthroughs, increased success rates and a new focus
on therapeutic areas that suffered historical underinvestment.
Artificial intelligence (AI), machine learning and other data-driven advancements have improved
R&D efficiency, especially in the early stages of drug discovery. Although it took some time for ‘big
data’ to embed into the R&D process, companies have become more comfortable working with
greater amounts of diverse types of data by 2031. A healthy supply of highly skilled researchers
from diverse disciplines and a flow of innovation between academia/research institutes,
biotech/SMEs and pharmaceutical companies have contributed to a vibrant R&D landscape.
Building on prior advances in genetics, genomics, proteomics and bioinformatics, the 2020s saw a
more decisive shift towards personalised drugs and a closer coupling between diagnostics and
pharmaceutical sectors. R&D success rates have also significantly improved, and prospects
unlikely to succeed are identified earlier than in the past. There is also growth in genetic therapies
reaching the market. Immunotherapy and oncology breakthroughs have made cancer treatments
more effective than before. As cancer has become a more curable and manageable disease, public
and private investments have shifted towards new therapeutic areas enabled by scientific and
technological developments. Examples include rare diseases, gastroenterology and the
microbiome, pulmonology, psychiatry, neurodegeneration and regenerative medicine. Cell and
gene therapies are attracting significant investments, as the concerns stifling progress have been
overcome.
Advances in science and technology have led to a surge in funding as investors eagerly enter
the attractive and lucrative pharmaceutical R&D space.
Government budgets in most developed economies have recovered from the impact of the Covid19 pandemic through smart fiscal policies and a growing emphasis on health as a determinant of
prosperous societies. Many OECD countries and non-members (e.g. China, India) have raised
investment in health as a percentage of total government expenditure by 2-4% compared to the
early 2020s. Public investment in early discovery research and previously neglected areas and
efforts to improve data and clinical-trial infrastructure have paid off, and private-sector investment
appetite is high. Not-for-profits have also recovered from the impact of Covid-19 and have
managed to raise funds in innovative ways. Many not-for-profits have adopted more commercial

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approaches to investing (e.g. taking equity or expecting royalties to support sustainability and
provide returns to channel into future investments).
Seeing opportunities in new therapeutic areas, investors are willing to take a chance on an
increasingly diverse supply of biotech/SMEs working in new and some established areas. Existing
investment funds have grown, and the start-up space is thriving, with a more abundant supply of
growth and scale-up capital than in the past. Although the US still leads globally in biotechnology
companies, initial public offering (IPO) markets and funding, Europe has also scaled up
investments and activity levels and now has a more attractive IPO market. There is a fair bit of
competition between different investors for the best investment opportunities, so innovators are in
a good position to secure favourable investment terms. A diversity of compounds progressing to
later stages of the R&D pathway have also helped boost investor confidence and contributed to
attractive valuations in the sector.
As pharmaceutical R&D yields good returns and has become even more attractive compared to
other sectors, new types of investors have entered the pharmaceutical space, and new types of
collaborations between public and private partners have emerged. Furthermore, new actors from
the data and technology space have become involved in the R&D process by creating dataenabled solutions for pharmaceutical R&D. Public and private partnerships are vibrant across
many areas, including major challenges like antimicrobial resistance (AMR) and rare diseases, and
other fields.
Some innovative financing mechanisms have become more popular over the past decade. Megafunds have gained momentum for tackling high-cost, high-risk R&D (e.g. for some rare and
infectious diseases), and pooling funding for several high-risk projects under a single fund has
enabled easier risk-reduction and capital raising. Access to debt financing in addition to equity has
become important in enabling access to a larger pool of capital. Innovative R&D and product
financing mechanisms have gained scale and traction for some infectious diseases (e.g. TB, AMR)
and chronic conditions (e.g. related to neurodegeneration and pulmonology) that needed
innovation. Examples include subscription-based models where R&D companies are paid a
monthly fee, usually by healthcare authorities, in exchange for securing access to innovations with
pre-agreed pricing and volume commitments.
Major shifts in the pharmaceutical R&D landscape have changed the dynamics of global
collaboration. Innovators and investors in emerging markets such as China, India and Brazil
increasingly collaborate with European and US counterparts.
China and other emerging markets have experienced the same pharmaceutical R&D boom that
Europe and the US have enjoyed. Furthermore, regulatory reform in China has increased trust in
pharmaceutical R&D quality and its resulting products, increasing investors’ ease and
collaborations between Europe, the US and the Asia-Pacific (APAC) region. In 2031, it is much
more common for biotech/SMEs and pharmaceutical companies to seek approval for products in
multiple global regions and receive a mix of funding from global investors. The increased global
mobility of labour and global competition for talent and investment has led to pressures on Europe

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to maintain competitiveness (including vis a vis increasingly competitive APAC countries),
providing further impetus for an improved European R&D funding environment.
Reform in clinical trial regulation has created fertile ground to help decrease R&D costs, but
affordability and unequal access to new and innovative treatments remain problematic.
Governments in Europe and the US have adjusted clinical-trial regulation to allow for smarter trial
design and reduce the bureaucracy associated with trial design amendments, with adaptive
pathways where companies can engage regulators throughout the R&D process to ensure they
are on the right path. Trials for personalised drugs with smaller patient populations require fewer
patients, and the types of data collected have evolved to include wider societal and economic
outcomes. More data can be collected remotely from patients, and there are fewer bureaucratic
hurdles without major concerns around safety or efficacy. This process has been a learning curve
for all involved in selecting appropriate trial endpoints and therapeutic areas that can benefit from
smarter trial design.
Although regulatory reform has decreased clinical trial and approval costs for some indications
(e.g. rare diseases, genetic therapies), scientific and technological advancements have had an
uneven impact on R&D costs. R&D in some therapeutic areas remains very expensive (e.g. chronic
conditions such as cardiology and respiratory). Affordability and access to highly innovative drugs
are still a challenge, and concerns about inequitable access are high on the global policy agenda.
Drugs offering incremental improvements are somewhat more affordable than in the past. In the
US, lobbying by the pharmaceutical industry has prevented any movement towards cost
containment, and drug prices remain particularly high. The creation of one-time therapies that save
lives or significantly improve quality of life has raised critical questions around affordability and
access; governments struggle to enable access while ensuring continued innovation. However,
some progress has been made in more flexible and adaptive pricing arrangements (e.g. outcomebased pricing, adaptive pricing and various price-volume agreements).

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Figure 2. Summary of Scenario 1 (Global golden age for pharmaceutical R&D).

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2.2 Scenario 2: Incremental improvements in the pharmaceutical
R&D sector
It’s 2031, and the pharmaceutical R&D sector has made modest advances since 2021. There
has been a steady stream of scientific and technological developments, but few major
breakthroughs. R&D success rates and the major therapeutic areas that attract investment
have remained relatively stable.
After an initial flurry of excitement around the possibilities that advances in AI, genetics and
genomics, and the microbiome would bring to pharmaceutical R&D, scientific and technological
advancements levelled off. There continue to be modest scientific and technological developments,
although by and large, the pharmaceutical R&D space has not seen major breakthroughs in the
past decade. Oncology and immunology still dominate the innovation space, although there is an
increased focus on infectious diseases, partly due to the Covid-19 pandemic. Other historically
neglected innovation areas, including pulmonology, ophthalmology, psychiatry and many rare
diseases, have not significantly progressed in scientific advances and innovation. Exceptions are
gastroenterology and the microbiome, which have seen some progress in the past decade.
A small number of innovative biotechnology companies have championed activity in innovative
areas such as gene therapies, cell therapies and some rare diseases (e.g. in neurology and
haematology) and microbiome-related R&D in gastroenterology. However, investments in these
therapeutic areas are still seen as high risk, only pursued by a limited number of companies and
investors. Several failures and complexities in gene and cell therapies and new safety-related
concerns diminished investor appetite after a period of increased investment in the early 2020s.
AI, machine learning and other data-driven techniques are used to some degree in drug discovery.
However, they have not been integrated in a way that has led to major industry transformations in
R&D processes, nor have they had a significant impact on success rates, which remain broadly
consistent with those of the early 2020s across therapeutic areas. Although the vast amounts of
generated data could potentially improve pharmaceutical R&D, the capacity to use these data to
their full potential is limited by a lack of infrastructure for quality control, data curation and
integration.
Pharmaceutical R&D funding has remained stable, and biomedicine remains an attractive area
for investment. However, it faces increasingly competitive investment pressures from areas
such as Greentech and Fintech.
Biomedicine remains an attractive investment area but has not surpassed other similarly attractive
sectors such as Greentech and Fintech, which continue to present competition for investor
interest. Compared to the early 2020s, available pharmaceutical R&D funding has remained
relatively stable, with only very modest growth driven mainly by private-sector investors and a
small number of therapeutic areas. There is somewhat more growth capital available for
biotechnology companies than in the past. However, competition for this funding means it tends to
target the most attractive clinical and therapeutic areas.

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The mix of public, private and not-for-profit sector investors in pharmaceutical R&D has remained
relatively stable relative to the 2020s, with limited new entrants into the pharmaceutical R&D
financial ecosystem. Despite an initial period of austerity after the Covid-19 pandemic in the early
2020s, public-sector funding for biomedical research rebounded quickly due to the importance of
health on national agendas. However, investment in health as a percentage of GDP has only
modestly increased relative to the early 2020s (i.e. by 1–2% in most OECD countries, and slightly
more in some emerging markets such as China actively bolstering the biomedical and health
sector). Governments continued to fund early biomedical research over the past decade, helping
pump-prime additional funding from the private sector. Governments have also supported
collaborative R&D efforts, focusing on market-failure areas (including rare diseases and
antimicrobial resistance) and technologically novel and uncertain areas (such as the microbiome).
The not-for-profit sector saw major post-pandemic declines in resources but gradually recovered.
Most not-for-profits still support grant-based funding. However, some – particularly those who
struggled most to recover costs or focus on high-risk areas or orphan diseases – have adopted
more commercial mindsets regarding royalties or pursuing equity from their investments.
However, in 2031, this is still the exception rather than the norm.
With few exceptions, R&D costs have continued to increase for most therapeutic areas, and
affordability and access to innovative drugs remain major challenges. While there are several
innovative pilots for new pricing arrangements, these have not achieved scale.
Although regulatory agencies have made some gradual adjustments in clinical trial regulation
related to bureaucracy in trial protocol amendments, smarter trials are not implemented at scale
(with some rare diseases and orphan-drug R&D the exceptions). Clinical trials remain one of the
costliest elements of pharmaceutical R&D. Adaptive pathways that allow companies to engage
with regulators throughout the R&D process have not materialised in practice at scale, despite
efforts to establish them. Overall, costs continued to rise throughout the 2020s, without major
scientific or technological breakthroughs or regulatory reform to combat rising costs. R&D success
rates have not changed relative to the 2020s.
However, global recognition of the affordability challenge and publicly funded healthcare systems’
inability to tolerate rising R&D costs have supported an increasing number of innovative pilots
exploring new pricing arrangements for a limited number of clinical areas (including flexible
pricing, price-volume agreement, adaptive and outcome-based pricing). How much these pilots
will impact pricing negotiations at scale remains to be seen. Some innovative financing models
linking R&D funding with price and volume product commitments (e.g. subscription models) have
gained slightly more traction than in the early 2020s – especially for areas with challenging market
conditions such as antimicrobial resistance and some infectious disease, and for areas like
hypertensives where a strong stimulus for innovation was needed. There are moves towards
pharmaceutical cost-containment in the US, although this is currently limited to drugs without
good pricing benchmarks (e.g. those without existing pharmaceutical standards of care). However,
such limited progress leaves the possibility of more substantial future change.

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China and some other emerging markets have continued growing their pharmaceutical R&D
sector over the past decade, increasing competition with European and US markets.
China and some other emerging markets such as India, Brazil and South-East Asia have
experienced moderate growth in the biomedical sector over the past decade. Such markets are
closing the gap with Europe and the US. Furthermore, regulation in emerging economies has
improved, contributing to higher quality pharmaceutical R&D being taken more seriously in the
global ecosystem. Whereas collaboration between the US, Europe and some emerging economies
has increased somewhat, geopolitical tensions are still at play between some parts of the world,
limiting collaboration. The competitive dynamics that have unfolded led to different innovation
blocs and consumer markets emerging. With few exceptions, there has been little movement of
innovators or investors between these innovation blocs. However, individual blocs have modestly
strengthened their biomedical sectors to serve their own respective markets.

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Figure 3. Summary of Scenario 2 (Incremental improvements in the pharmaceutical R&D sector).

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2.3 Scenario 3: Pharmaceutical R&D stagnation
It’s 2031, and the pharmaceutical R&D sector has stagnated. Scientific and technological
developments of the early 21st century have failed to deliver significant progress, and R&D
success rates have dropped to the lowest point of the last decade.
The initial promise of data-driven pharmaceutical R&D created more questions than answers.
Although AI, machine learning and other data-driven technologies showed early promise, much
proved too complex to implement at scale. This can be attributed, in part, to organisational inertia,
a lack of industry infrastructure and capabilities, and regulatory and policy challenges that limited
opportunities to effectively collect and utilise large amounts of data. Societal movements, a lack of
public trust and fear also limited how much ‘big data’ could be implemented in practice, and the
extent industry could use diverse healthcare data.
Without significant scientific and technological developments in most biomedical research fields,
and with declining public-sector investment in early R&D (driven by broader macroeconomic
pressures and austerity), pharmaceutical R&D failed to advance significantly over the past decade.
Government funding was put under significant pressure after the Covid-19 pandemic and has not
recovered. Due to limited funding for early discovery research, there are fewer spin-outs from
academia in 2031 than in the 2010s and 2020s, further limiting the supply of innovation feeding
pharma pipelines. R&D focuses mainly on improving existing drugs or repurposing rather than
major breakthroughs.
R&D success rates have reached their lowest rate in the past decade and are lower than in 2021.
Globally, there has been a narrowing of R&D portfolios towards fewer therapeutic areas (oncology
and immunology still dominate) – partly due to the necessity for both public and private sector
actors to stringently prioritise investments. Some highly publicised failures in gene therapy in the
early 2020s and increased scepticism towards opportunities related to the microbiome (in part
related to the complexity of science and limited advances) led investors and innovators to retreat
from these areas; early investors felt let down. Furthermore, historically underinvested areas such
as infectious diseases, neurodegeneration and pulmonology remain underfunded and have
experienced very little progress. An exception is a small number of rare diseases already wellserved since the late 2010s, which have made incremental advancements and modest increases in
success rates thanks to patient advocacy and not-for-profit and government investment. Society is
facing an increased risk of existing antibiotics becoming ineffective, and unattractive market
conditions have led to a reduction in industry involvement in this space.
Funding for pharmaceutical R&D is scarce, and public-sector funding is no longer effective in
encouraging further private-sector investment.
The availability of capital for pharmaceutical R&D has dropped to historic lows. Public-sector
funding declined throughout the 2020s as purse strings tightened after increased public spending
for the Covid-19 pandemic. Despite the need for public-sector investment in early research,
austerity and pressures from other sectors have stalled progress. The supply of research talent has

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also stagnated. Given that success rates have declined compared to the past, with few exceptions,
private-sector funding has declined at an even faster rate than public-sector funding. Not-forprofit funding has also become more limited and narrowly focused. Given substantial resource
constraints, some not-for-profits are experimenting with more commercial approaches to their
investments (expecting royalties or taking equity). However, relatively low success rates mean
these strategies have not boosted their financial positions. Private-sector investors have looked to
more commercially attractive areas experiencing a boom, such as Greentech and Fintech.
Today’s biotech/SMEs struggle to secure growth and scale-up capital. Given the scarcity of
available funding, biotechs are often bought by pharmaceutical companies early, before they have
had a chance to fully mature and develop. Failures increasingly happen on commercial and not
only scientific grounds, as SMEs run out of capital to mature R&D portfolios. Limited progression of
drug candidates through R&D phases has reduced investor confidence and contributed to less
attractive valuations and exit opportunities. As a result, patients continue to suffer from a high
disease burden in many chronic conditions (e.g. oncology, respiratory, cardiac) and historically
under-funded areas (e.g. infectious diseases). Pressures on healthcare services are increasing due
to greater demand for care, resulting in higher total healthcare costs.
The R&D collaboration landscape looks similar to 2020 with some consolidation, given few
entrants to the pharmaceutical R&D space. Public-private partnerships are limited to areas of key
market and scientific uncertainty but struggle from under-investment.
R&D costs have continued rising to the point that pharmaceutical R&D is facing imminent
sustainability concerns. Its role as a driver of innovation economies and economic
competitiveness is also increasingly under threat.
Pharmaceutical R&D costs continued to rise throughout the 2020s, exacerbated by low success
rates, stagnation in science and technology and insufficient investment. Clinical trials have not
seen any significant reform. Costs and regulatory demands have continued to balloon to a point
where some drugs fail to get through clinical trials and regulatory approval due to insufficient
funding. Thus scientific, commercial and regulatory challenges all impact failure rates.
There are serious concerns about developing new drugs for the future, with societal movements
and patient advocacy putting pressure on governments to find urgently needed solutions.
Advocacy groups warn of infectious disease and chronic condition pandemics, and there is public
dissatisfaction with rising inequalities. Without a reinvigorated investment landscape and a
decrease in R&D costs, the ecosystem will soon collapse to a point where returns are nearly
impossible without sky-high prices that most payers will not be able to afford. This issue is high on
the government agendas, who fear that only high-income countries and individuals will have
access to even mainstream medications. Affordability is also much higher on US decision-makers’
agenda than in the past, with cost-containment reducing differences in pricing between the US
and some other markets and supporting affordability. However, it is also causing serious concerns
for investors and the healthcare industry about returns, profitability and the ability to take risks and
pursue radically innovative R&D. Despite widespread global agreement on the scale of the
affordability challenge, there is no consensus on the best way to decrease R&D costs or

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reinvigorate the sector. Discussions about novel financing models and risk-sharing practices are
still in the early stages.
Stagnation in pharmaceutical R&D is global, as China and other emerging markets have
experienced similar innovation challenges and wider economic pressures to Europe and the US.
China and other emerging markets (e.g. India and Brazil) face similar scientific and technologicalinnovation challenges, funding scarcity and low R&D success rates as other global regions.
However, the Chinese regulatory environment has advanced compared to the past (concerning
quality control and ability to access and use patient data - although the latter is due to less patient
choice in data use than in some other countries). Regulatory developments have helped China and
some other APAC countries develop a more competitive edge in a small number of therapeutic
areas (e.g. gene therapy and, to a lesser degree, cell therapies and cardiology). However, there are
still significant scientific and technological obstacles to breakthroughs. However, emerging
economies focus more on generics, repurposing existing drugs and incremental innovation rather
than breakthroughs. Compared to the early 2020s, the biomedical sector has seen global
stagnation. In 2031, the emerging powerhouses of the early 2020s, such as China, are not major
competitive threats or key collaborators for European and US innovators.

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Figure 4. Summary of Scenario 3 (pharmaceutical R&D stagnation).

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3 Key learning points from the
stakeholder workshop
The scenarios presented in the previous chapter were used as a vehicle to facilitate exploration of
the main challenges, risks and opportunities presented by plausible futures and encourage
stakeholders to reflect on the critical issues that may require present action to prepare for the
future – regardless of how it unfolds. Given the workshop’s time pressures, scenarios were
individually discussed in breakout groups, with each group discussing a different scenario to
ensure all scenarios were covered collectively. The core themes for consideration to prepare for the
future were common across all scenarios. Given that the key influencing factors are consistent
across scenarios, this is expected. However, the projections are different, encouraging workshop
participants to consider theme-based actions that could enable preparedness across different
futures. Therefore, this chapter is organised by theme, highlighting scenario-specific insights
where relevant.
The core themes that emerged during the workshop and from participant reflections relate to the
challenges society faces and their implications for potential opportunities for action to optimise
pharmaceutical R&D’s financial ecosystem. These themes relate to the following areas:
• Scientific and technological advances
• The role of data and digital innovation in pharmaceutical R&D
• Pharmaceutical R&D financing
• Global collaboration and competition.
Several cross-cutting themes relating to each of the core themes above were also discussed
during the workshop:
• Pricing, affordability and reimbursement
• Regulation.
It is important to flag that the areas of opportunity for potential action to improve the financial
ecosystem for pharmaceutical R&D would need to include many stakeholders in the public, private
and not-for-profit sectors. Although policymaking and political choices can influence
pharmaceutical R&D’s financial ecosystem, how this system evolves and its ability to establish
informed and implementable policies requires the collective efforts of many stakeholders.
Finally, it must be noted that the themes below reflect broad areas for consideration rather than
prescriptive actions. Additional evidence would be required to determine specific actions
addressing issues in the financial ecosystem pharmaceutical R&D, explore implementation
requirements in different contexts and evaluate learning from past interventions. This is outside
the scope of the current study.

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3.1 Scientific and technological advances
3.1.1 Challenges
The pace and nature of scientific advances will influence the supply of medical innovation and
the private sector’s willingness to invest in higher-risk therapeutic areas.
Several key challenges relating to scientific and technological advances emerged from the
workshop discussions. Stakeholders noted that the pace and nature of scientific and technological
advances would influence the challenges and risks that need to be addressed. Both a slow and
fast pace of scientific and technological advancement could present future challenges and risks.
Slow-paced advancement in scientific and technological innovation (such as in Scenario 3 and
within specific therapeutic areas in Scenario 2) would likely decrease investor appetite for
pharmaceutical R&D and impede radical innovation. For example, slow progress could lead to an
insufficient innovation supply in the pharmaceutical space, influencing investor appetite for higherrisk and radical innovation. Without breakthroughs in science and technology, pharmaceutical
R&D would likely focus more on lower-risk clinical innovation, leading to drugs that only offer
incremental improvements in care. Such medicines would influence the private sector’s position in
pricing negotiations, as they would lead to modest gains in value compared to existing standards
of care.
However, rapid major scientific advances (such as in Scenario 1 and within specific therapeutic
areas in Scenario 2) would also raise challenges, most notably regarding societal ability to pay for
innovative treatments and industry’s ability to absorb and integrate novel science and technology
into R&D processes. Scientific and technological advancement may outpace society’s ability to
absorb innovation. For example, health systems may lack the capabilities to deliver innovative new
treatments if the skills or facilities are lacking in healthcare delivery settings. Industry may also lack
the skills to fully integrate novel technologies (e.g. AI) into R&D processes in ways that improve
efficiency. If R&D leads to major breakthroughs such as one-time genetic cures or other highly
innovative drugs, there will likely be significant challenges to healthcare systems’ ability to pay for
such treatments, exacerbating the risk of inequitable drug access.
3.1.2 Opportunities to address the challenges
Stakeholders identified a series of important considerations and potential action areas that
could help mitigate risks and challenges related to scientific and technological progress. These
span themes such as public-sector investment, skills and capability building, translational
research capacity, the R&D workforce’s labour mobility and connectedness, and advances and
innovations pricing models.
These include:
• Ensuring appropriate levels of public sector investment in basic science and research
infrastructure – a pre-requisite for downstream innovation and leveraging private-sector
investment. Public-sector funding is important for ensuring sufficient scientific and
technological advancement levels to feed later-stage pharmaceutical R&D and innovation

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pipelines and mobilise downstream investment by private-sector funders such as venture
capital, corporate investors, pension funds and other institutional investors. The absolute
financial amounts of public and not-for-profit sector investment versus private-sector
investment do not reflect the relative importance of different investment sources. This is
because public and not-for-profit investment to ensure a supply of science is often a
necessary pre-requisite for more downstream private-sector investment and because
different R&D phases are associated with different costs. It is important to consider health
and biomedical R&D specifically when considering public-spending levels rather than the
broader health-expenditure category that encompasses other non-R&D expenses.
• Ensuring that the private sector invests in R&D not only in the most profitable areas, but
also in diverse areas addressing unmet societal need – including those which may not
command the largest profits. This requires appropriate push-and-pull incentives to align
societal needs with industry’s commercial structures. It also requires innovative risk-sharing
agreements between industry and public-sector investors and payers. There may be scope to
learn from the innovation experiences in response to the Covid-19 pandemic and areas with
market viability challenges (such as antimicrobial resistance) to inform sustainable and
scalable business models for pharmaceutical R&D in areas of unmet societal need.
• Building healthcare systems’ skills and capabilities to absorb the innovation supply and
support the implementation of novel drugs in healthcare pathways (and the deimplementation of incumbent practices). This requires an information-and-communication
infrastructure and strategy to raise awareness about the medical innovations available and
how they compare to existing standards of care in cost-effectiveness. It also requires training
healthcare professionals as prescribers and deliverers of care to implement new drugs
regimes effectively and developing conducive healthcare-delivery pathways for innovations.
• Building translational research and innovation capacity by supporting a mobile labour
market for pharmaceutical R&D and a well-connected, skilled workforce. Educating and
training the pharmaceutical R&D labour force to apply new scientific developments in the
R&D process involves nurturing porous interfaces between academia, industry and the
healthcare service (which houses clinical entrepreneurs) to support appropriate labour
mobility. Encouraging the back-and-forth movement of talent can help foster transferable
skills. Partnerships and collaborations can help foster mobility between these sectors, as can
a better understanding of the cultural barriers that may present career-related challenges to
people moving between sectors, e.g. academia and industry. Fostering labour mobility is
likely to require industry and public-sector actions. Future research could examine the relative
degree of labour mobility in different geographical and cultural contexts and its impact on
investment attractiveness and functioning of the pharmaceutical R&D system. It could also
explore the mechanisms that might support appropriate mobility in the pharmaceutical R&D
labour markets (e.g. exchange programmes between industry and academia, secondments
and shared posts).
• Managing societal ability to afford innovative drugs and keep up with scientific and
technological development. Payers will need to balance affordability concerns with
rewarding innovation and encouraging investment across diverse therapeutic areas. As one
example of more innovative pricing approaches, value-based pricing models may be useful in

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future pricing debates. However, there is a need for greater stakeholder dialogue and
decisions on applying them to breakthrough treatments in practice (i.e. what constitutes
value, how it will be measured, how incremental gains in value influence pricing decisions).
Conversations about innovative and flexible pricing models and risk-sharing arrangements
between innovators and payers will need to tackle pricing and affordability, one of the most
challenging issues facing the future of the pharmaceutical R&D ecosystem that ultimately
impacts R&D financing as well. Affordability discussions will need to acknowledge that
unique considerations may apply to innovations representing one-time cures versus more
longer-term treatments and those for chronic conditions.

3.2 The role of data and digital innovation in pharmaceutical R&D
3.2.1 Challenges
R&D systems’ ability to leverage data and digital technology advances will influence the pace
and nature of pharmaceutical R&D, but there are several challenges to integrate them into R&D
practice.
Many scientific and technological advances will depend on companies’ ability to effectively collect
and use high-quality data in the R&D process and their access to data (both proprietary and from
the wider healthcare system). The current pharmaceutical R&D sector is not fully prepared to
integrate increasing amounts of data and digital advances into R&D processes at scale, although
some companies are making investments towards that end. Challenges relate to data access
issues, data infrastructure, the skills and capabilities to use data and harness digital innovation in
the pharmaceutical R&D process, and a limited capacity to effectively collect, analyse or share
high-quality data. Such challenges separate the rapid progress in Scenario 1 – partly enabled by
the capacity to use data and digital innovations – from the relatively slow progress of Scenario 2
and the challenges harnessing new developments’ potential in Scenario 3.
Greater use of data from electronic health records, for example, could play a key role in designing
innovative and potentially more efficient clinical trials and inform post-market value assessments.
However, data-access challenges are significant, both technological (e.g. related to the existence
of platforms that can link diverse data sets, data quality) and social (e.g. diverse public attitudes
and trust in data sharing and how industry uses data). Public trust in data and data-driven
technologies and debate about data security and privacy are also persistent challenges in some
geographies and cultures. How much this will escalate or decrease in the future remains to be
seen.
There are also challenges in the current data infrastructure, including data-quality standards,
interoperability, efficient data flows and data-sharing in healthcare innovation systems. There are
also skills challenges, highlighting the need to bolster data-science capabilities and the capacity to
collect, process and analyse vast amounts of patient data. These skills are in limited supply.
Although improved integration of data and digital advances in pharmaceutical R&D may contribute
to smarter and more efficient R&D, a greater focus on integrating data and digital advances into
the R&D process can also introduce additional demands on companies to build the capacity and

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infrastructure for more significant amounts of data in the future. This would necessitate additional
near-term investment. Such investment may be difficult to secure if the expected investment
returns are longer-term or heavily dependent on developments in the external landscape (e.g. how
data access will be regulated).
3.2.2 Opportunities to tackle these challenges
Stakeholders highlighted potential areas of action that society needs to consider to prepare for
the greater integration of data and digital approaches to pharmaceutical R&D. These include
improving the data infrastructure, mobilising public support, advancing regulatory and legal
frameworks, building skills and capability for data collection, interpretation and use,
understanding levers that could enable greater data sharing between innovating companies,
and understanding the capacities and capabilities needed in the healthcare system for more
diverse data types to feasibly inform drug-pricing discussions.
More specifically, workshop participants discussed the following themes:
• Industry and public-sector investments in improving data infrastructure (e.g. standards,
interoperability and data-linkage architecture to support effective data flows). This will likely
require engagement from the public and private sectors. Industry needs to invest in internal
infrastructure to ensure high-quality data curation and safe and secure use with appropriate
safeguards. Similarly, the public sector also needs to invest in high-quality data collection in
safe and secure ways. Stakeholders noted that improving data systems and data
infrastructure will be vital in supporting innovation and ensuring that R&D and health
systems can incorporate the insights from large amounts of data and data-driven
technologies.
• Tackling public hesitancy to share data and address concerns about data security and
privacy. This could be achieved through dialogue and engagement about the potential
benefits of greater data sharing for medical innovation and societal needs and transparency
about risks and safeguards. While conceding their necessity in debates about regulation,
some workshop participants felt data security and privacy concerns should be balanced with
data’s benefits to innovation. The public should be engaged in discussions around data,
which can help foster public trust. Patient groups may be able to define the circumstances
they are willing to share data in and health data use for innovation and post-market research.
Industry would need to develop appropriate levels of transparency in what data is used for
and how and the safeguards in place.
• Advancing regulatory and legal frameworks for pharmaceutical R&D data use to support
safe and secure data use. Though particularly important, this is a challenging ask for the EU
given the culturally and politically diverse EU landscape and different public attitudes and
policy responses to industry’s data use and re-use. The need for solutions that transcend any
one country’s borders adds to the challenge. Decisions and arrangements related to financial
aspects of data access (who will pay, for what, in what ways) also raise difficulties.
• Strengthening skills and capabilities for data collection, curation and use. This includes
bolstering data science capacities in the pharmaceutical R&D workforce in industry, the public
sector and the healthcare workforce.

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• Examining what is needed to increase future data sharing between companies involved in
pharmaceutical R&D. Depending on data availability the capacity to utilise it in R&D
processes effectively, data-sharing may increase between companies in the future,
contributing to more efficient R&D processes and reducing unnecessary duplication of effort.
There is a need for further discussion about what types of incentives, capabilities, policies and
infrastructure could support increased data-sharing (e.g. how to share data while protecting
commercial sensitivities). Increased data sharing between companies may be more likely in
areas where returns are especially difficult to secure and future scenarios with lower
innovation levels.
• Considering how increased data use and more diverse data types can inform innovative
pricing approaches. The ability to use data in decision-making about value depends on the
right kinds of data being available to measure relevant patient outcomes and the ability to
share, use and interpret such data. This may include building capacities and capabilities for
HTA agencies, regulators and payers to engage with more diverse types of outcomes data
and the wider healthcare system’s capacity to collect such data (including amongst
healthcare providers and organisations conducting traditional and real-world phase IV trials).

3.3 Financing the pharmaceutical R&D sector: creating
sustainable landscapes
3.3.1 Challenges
The pharmaceutical R&D sector’s ability to attract investment from the private sector will
depend on diverse factors. Critical factors identified during the workshop include the relative
attractiveness of other sectors of the economy, the supply of scientific and technological
advances, the nurture of the R&D workforce, success rates and societal ability to pay for
innovative drugs. Current investment challenges largely relate to resource constraints in the
public and not-for-profit sectors, partly due to the impact of the Covid-19 pandemic.
The pharmaceutical R&D sector’s ability to attract funding will partly depend on its attractiveness
to investors compared to other sectors of economic activity (e.g. cleantech, fintech), partially
determined by broader economic factors (as demonstrated in the scenarios). The pharmaceutical
R&D sector’s attractiveness to investors will partly depend on the supply of science and innovation
and investors’ ability to secure good returns on investments (for example, in Scenario 1). A lack of
investment would pose significant risks for society and likely result in fewer products reaching the
market and, ultimately, fewer advancements to benefit patients (for example, in Scenario 3 and in
many therapeutic areas in Scenario 2).
Some stakeholders felt that insufficient clarity about healthcare-innovation priorities could also
present challenges ensuring investment in underfunded areas of unmet societal need. High-risk
therapeutic and clinical areas with potentially significant benefits for society (or for at least some
underserved segments of society) may struggle to secure investment if other areas are seen as
more attractive and lower risk in potential success rates and returns. Private-sector R&D
investment will move towards what is profitable, which the public sector can impact by influencing
supply, demand and reimbursement. This potential misalignment between investment areas and

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unmet needs applied to all scenarios, even those with greater investment in pharmaceutical R&D
and a relatively attractive market.
Innovations in pharmaceutical R&D will only improve health if somebody pays for them, and
investment will only occur if investors are confident in the willingness to pay for innovation. There
may be future challenges in ensuring a balance between affordability, access and rewarding
innovation. Existing challenges related to societal ability to pay for drugs, especially for highly
innovative treatments and one-time cures, exist are likely to present one of the trickiest challenges
to address. Unequal access to drugs and innovative treatments within and across countries may
also need tackling, depending on healthcare systems and payers. Affordability issues and unequal
treatment access risk reputational damage to the pharmaceutical R&D industry and may enhance
public pressure regarding affordability concerns. Pressures around affordability can interact in
non-linear ways, such as in Scenario 3 where discussions around affordable pricing in the US
caused debates around profitability and the sector’s viability.
3.3.2 Opportunities to address challenges
Stakeholders noted opportunities for action related to the pharmaceutical R&D sector’s longerterm financing and competitiveness. They highlighted themes related to the importance of
public and not-for-profit investment for ensuring a sustainable pipeline of research talent and
scientific and technological advances, tackling affordability challenges through innovative
payment and risk-sharing arrangements, research prioritisation, and ensuring clear signalling in
the healthcare system about areas of demand and what will be paid for.
Stakeholders reiterated the importance of the following themes:
• Sustaining required public-sector and not-for-profit investment levels in basic and applied
science to ensure a sufficient supply of research talent and a healthy supply of science and
technology for downstream innovation to build on. This is also key for tackling potential
workforce sustainability issues. The sustainability of the pharmaceutical R&D workforce
merits attention, especially given public and not-for-profit sector resource constraints in
diverse clinical areas’ diverse R&D funding and their impacts on the future supply of talent.
This is particularly true given the prioritisation of Covid-19 research and the general impact of
the pandemic on available funds for other types of R&D.
• Supporting innovative healthcare systems and tackling affordability challenges, including
ensuring demand for innovation in the healthcare system. This matters as the demand for
innovation (i.e. creating a viable market) influences the willingness of private-sector investors
to channel resources into R&D. The public sector can support the demand side of innovation
by creating feasible pathways within healthcare services to adopt and uptake new or
improved classes of treatment. Industry would need to engage in ways to support affordable
access and workforce training on the safe and effective use of novel drugs in wider
healthcare pathways.
• Implementing innovative and flexible risk-sharing and payment models through collective
efforts of public sector decision-makers, payers and industry actors. Returns on investment
will always be critical considerations for private-sector innovators. However, there are limits

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on societal ability to pay that need to be considered in negotiations and discussions about
new financial incentives and reimbursement models. Value-based pricing models could be
applied to local economic situations and priorities in context-sensitive ways. Any
considerations around value-based pricing models should include discussions around
determining value for highly innovative drugs and one-time cures. Post-market value
assessments could also inform reimbursement negotiations. Such assessments require
collecting patient-outcome data and potentially other types of administrative data (e.g.
impact on healthcare-service utilisation) from the healthcare system. Coordination between
payers, the public sector and the healthcare sector would be needed to help ensure that the
right data is accessible to support value-based pricing models. Subscription models were also
identified as a potentially underexplored vehicle for incentivising and rewarding/reimbursing
innovation. Using subscription models, health authorities help de-risk R&D through upfront
payments to support R&D in exchange for guaranteed volumes and prices of potentially
successful products.
• Reflecting on how to prioritise R&D to address unmet needs most effectively. When
prioritising pharmaceutical R&D financing, it is critical not to lose sight of the end goal and
identify clear areas of unmet need and demand. Pharmaceutical R&D is a tool that helps
towards healthier populations. Research prioritisation needs to balance diverse therapeutic
areas and patient populations, and highly innovative R&D versus repurposing and more
incremental innovation. These considerations should ensure a balance between investing in
unlikely areas with high payoffs and more certain areas with modest gains in societal value.
Using data more effectively can also assist with prioritisation, although healthcare systems
will need support in collecting useful data for prioritisation. Prioritisation exercises should
include consultations across stakeholders to engage patients and the public.
• Clear signalling from payers about areas of demand and what will be paid for and how.
Clear communication about what will be paid for and how value will be determined will be
important in boosting investor confidence in pharmaceutical R&D and incentivising
innovators. Private-sector stakeholders noted that, from their perspective, policymakers and
payers need to clearly communicate priorities, budgeting (including timeframes covered by
budgets) and procurement arrangements.

3.4 Global collaboration and competition
3.4.1 Challenges
While changes in the global landscape present opportunities for new collaborations between
established actors in pharmaceutical R&D (e.g. in Europe and the US) and emerging economies
(e.g. China), they also raise challenges. These include potentially increased competition for
investment and research talent between different geographies and uncertainty related to how
innovative pharmaceutical markets may influence companies’ locations and global pricing
dynamics.
The competitiveness of the life sciences sector in different parts of the world and collaboration
dynamics can influence where investment into pharmaceutical R&D goes and how it flows.

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Collaboration between different types of stakeholders (e.g. biotech/SMEs, large pharma,
diagnostics companies, academic collaborators) also influences the flow of funds into
pharmaceutical R&D and value transactions.
Workshop participants discussed several key challenges related to global collaboration and
competition. Global dynamics in pharmaceutical R&D are evolving and are likely to continue doing
so. Workshop participants focused their discussion primarily on collaboration and competition
dynamics between Europe, the US and emerging markets such as China. Some of the latter have
prioritised building their pharmaceutical R&D sector’s competitiveness and may continue investing
in advancing the regulatory landscape governing pharmaceutical R&D, as described in Scenario 1.
There has also been some progress in these markets on establishing attractive ways for
companies to obtain reimbursement while reducing inequalities in access and controlling profits.
Europe may face opportunities in these emerging markets as a potential collaborator and supplier
of skills and capabilities in pharmaceutical R&D, but also as a competitor for investment (such as in
Scenario 2) and as a potentially attractive and sizeable new market for innovators. Geopolitical
dynamics and policies related to cooperation are likely to influence how the landscape evolves.
At present, decisions on pricing made in key global markets (e.g. the US) significantly impact
global innovation landscapes and investment behaviours. If the composition, configuration or
pricing strategies of key global markets change, this could potentially impact global pricing
behaviours, although how remains to be seen.
While there is a good supply of science and free movement of innovation communities in Europe,
there may be challenges in the future related to access to capital compared to the US or emerging
markets such as China. For example, workshop participants flagged challenges related to the state
of the IPO market in Europe that could potentially detract investors and make it more challenging
to attract and retain companies and talent in Europe.
Europe’s fragmented regulation in aspects such as the classification of new drugs and
technologies and different requirements governing data and cost-effectiveness thresholds for
reimbursement can decrease the region’s attractiveness for pharmaceutical R&D investors
compared to regions with more harmonised regulations. The diversity of regulations within Europe
can make it cumbersome for innovators to navigate the fragmented landscape.
3.4.2 Opportunities to address challenges
Workshop participants flagged opportunities for Europe to secure its longer-term
competitiveness vis a vis changing global landscapes for pharmaceutical R&D by building
learning healthcare innovation ecosystems, tackling the long-standing challenge of regulatory
fragmentation in some areas, and reflecting on interventions that can strengthen the
attractiveness of the European IPO markets.
More specifically, this includes themes such as:
• Ensuring learning in healthcare innovation systems:

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– Learning from what is working in other geographies: There is an opportunity to learn
across geographies about supporting innovation in pharmaceutical R&D, including
looking at how emerging economies support innovation.
– Learning from innovation experiences in response to Covid-19 and learning how to
support rapid and efficient innovation in times of crisis: For example, how to sustain
practices that enabled faster innovation in response to Covid-19. The pandemic
challenged the health and innovation system, with lessons to be learned from global
responses to Covid-19 in terms of rapid innovation, flexible and accelerated ways of
conducting remote trials at scale, reduced bureaucracy related to regulatory processes
and substantial public-private sector collaboration. The critical role of governments and
the public sector in creating conducive clinical-trial infrastructure, mobilising and
orchestrating investments and encouraging data-sharing and collaboration between
different companies and between the public and private sectors was highlighted
through Covid-19, particularly in geographies such as the US. What industry, publicsector, government and regulatory actions will be taken to sustain the efficient
innovation enabled in response to Covid-19 remains to be seen, as does the appropriate
safeguards that should be in place. Lessons about the potential benefits and united
consequences of unfolding innovation in response to the pandemic are still being
learned. Further research will be needed to fully understand the implications of Covid-19
on pharmaceutical R&D financing.
– Learning about how innovation happens in different spaces (academia, industry,
healthcare services) to sustain and further reinforce a connected European healthcare
innovation landscape and prevent organisational siloes and inertia.
• Tackling fragmented regulation and policies in some areas across Europe: European
countries can work together to reduce fragmentation and improve regulatory cooperation.
This requires dialogue and prioritising areas where regulatory harmonisation may be most
feasible in practice. Dealing with fragmented decision-making across different member states
(e.g. regarding reimbursement, regulation of new technologies, intellectual property policies,
approvals for drug repurposing, rules related to data use and re-use by industry) matters for
the attractiveness of Europe to investors. However, it is politically and operationally
challenging to address – though not impossible, as exemplified by the European Medicines
Agency’s (EMA’s) work on other regulatory fronts. European policymakers may also need to
tackle challenges related to differing regulations between the US Food and Drug
Administration (FDA) and EMA concerning where trials need to be conducted geographically,
as this can have a significant impact on R&D costs.
• Bridging siloes between research policy, industrial policy and healthcare policy: Some
workshop participants emphasised the importance of ensuring that policy affecting
pharmaceutical R&D is informed by research-policy, industrial-policy, and health-policy
priorities. Closer interaction between these policy domains is needed to ensure a competitive
sector that attracts funding and an innovation supply to improve health and prioritise areas of
need in alignment with commercial realities. Less siloed policymaking is important for aligning
supply with demand.

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• Continuing to support and sustain international cooperation, building on existing efforts
and further expanding on them: International cooperation will be vital for maintaining
Europe’s competitiveness in pharmaceutical R&D given changing global dynamics.
• Strengthen economic incentives and opportunities: Considerations for Europe may include
supporting capital markets, enabling a more globally competitive IPO market and furthering
the dialogue about the provision of tax incentives for innovation to attract investors and
innovators to the region and retain them long term.

3.5 Concluding thoughts
Workshop participants’ engagement with the future scenarios highlighted that the financial
ecosystem of pharmaceutical R&D functions as a complex and interrelated system. Decisions and
developments about financing connect inextricably with other parts of the system, including the
availability of capital, R&D phases and clinical areas that will attract funding, science and
technology supply, pricing and affordability, regulation, and policy governing collaboration and
competition.
The diversity of actors in this broader ecosystem highlights the need for joined-up approaches to
policymaking to support sustainable financial ecosystems for pharmaceutical R&D. A considerable
range of actors have a stake in pharmaceutical R&D: Researchers in the public sector; innovators in
biotechs, SMEs and the pharma industry, government and not-for-profit investors, venture
capitalists (standalone and corporate), other industry and institutional investors such as pension
funds and debt-finance providers, regulators, payers, and the healthcare systems and patients that
adopt and use innovations. Furthermore, the pharmaceutical R&D space is influenced by different
policy spheres: research, innovation, industrial strategy and healthcare policies. Therefore, the
collaboration between decision-makers in these policymaking spheres is critical for ensuring
coordinated approaches supporting a sustainable financial ecosystem for pharmaceutical R&D.
Many of the opportunities and areas for consideration highlighted in the workshop are not novel in
themselves. Stakeholders have been seeking to address some of them for a considerable time
already. For example, decision-makers across the European Union have been working on healthdata and data-access infrastructure. The importance of public-sector investment in fuelling
biomedical R&D is also widely recognised and prominent in both national and international R&D
strategies, with Horizon 2020 being one example. Similarly, the need for innovative payment
models for highly innovative drugs is not new, although not yet implemented at scale. The
challenges fragmented-regulation challenges across the European Union (e.g. in classifications of
some new technologies and health-technology assessments) present to innovators and investors
are also well known, influencing clinical-trial designs, clinical-evidence requirements and
associated R&D costs. However, existing recognition of the themes discussed above makes them
no less important to highlight, given their challenges and impact on pharmaceutical R&D’s financial
ecosystem. In addition, a future research agenda may benefit from ‘deeper dives’ into individual
themes. This will help assess progress in addressing challenges, making the most of future
opportunities in different geographical contexts, identifying areas that require coordinated
international action that extends beyond national borders, and considering detailed
implementation and success criteria.

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Some of the opportunities for potential action identified through the future-scenarios workshop
may be, in relative terms, less prominent in current debates than the data, public-sector
investment, innovative-payment models and fragmented-regulation themes discussed above. For
example, many discussions related to innovation uptake focus primarily on affordability; however,
uptake also depends on broader factors such as incentives, accountabilities, available skills for
implementing new care pathways and de-implementing incumbent practices, and public buy-in.
The workshop also flagged the potential merits of closer collaboration between research, industrial
and healthcare policies, currently seen in pockets but not at scale in many parts of the world.
Similarly, there is potential scope for more established markets learning from successful innovation
experiences in pharmaceutical R&D work in some emerging economies that have rapidly improved
their pharmaceutical R&D sector’s competitiveness (or parts of it) in recent times. Moreover,
despite considerable discourse about the importance of learning from the Covid-19 crisis, a deeper
understanding of how applying and adapting some of the ways innovation happened in response
to Covid-19 in the future might influence the financial ecosystem for pharmaceutical R&D in other
areas is needed. There are also knowledge gaps about how sustainable the pace and nature of
innovation in response to Covid-19 will be.
Although the multiple factors influencing pharmaceutical R&D were already clear, our work has
highlighted their intimate links with pharmaceutical R&D financing – including through investor
appetite and confidence, the product progression through the R&D pathway, and R&D costs. Our
findings emphasise that multiple forces shape pharmaceutical R&D financing within a complex
system.
Finally, the opportunities in areas where action may be needed are multiple and interrelated and
often not straightforward to address. Inevitably, decision-makers will need to prioritise actions that
may be taken and consider their feasibility. Such prioritisation will likely require identifying shorterterm actions that can make a difference (i.e. identifying ‘low-hanging fruits’) and longer-term
interventions that may require more complex and fundamental changes in the pharmaceutical R&D
system. Identifying which actions may be tractable is outside the scope of this study; however,
some efforts may be more tractable to shorter-term actions than others, which will be critical for
policymakers and other stakeholders to consider. Future studies could explore the areas of
opportunity our research has identified and support prioritisation and implementation efforts.
Any potential prioritisation will partly be influenced by how the challenges and opportunities
ahead are framed. This requires reflecting on whether and how much the key challenges to
optimising pharmaceutical R&D’s financial ecosystem are related to innovation’s supply end,
demand end, or both.
More specifically, given that pharmaceutical R&D financing and the supply of innovation are so
closely related to the ability to ensure demand and adoption, decision-makers face three options
for framing the challenge ahead and prioritising potential stakeholder actions:
• One is to ask: ‘If we tackle challenges related to ensuring affordability and ensuring viable
markets first (e.g. tackling the demand side through clear demand signalling, innovative
payment models, innovative and flexible risk-sharing agreements between the public and
private sectors, and innovating in procurement models), what else would we need to do on

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the supply end (e.g. nurturing collaboration, tackling regulation and ensuring a supply of R&D
capital) to optimise the financial ecosystem of pharmaceutical R&D?’ Such a framing
prioritises the ‘securing demand, adoption and affordability’ challenge.
• The alternative framing asks: ‘What do we need to do on the supply-side to make the
demand-side challenges easier to tackle?’ Such a framing assumes addressing matters such
as the availability of capital for R&D, public and not-for-profit sector investment in early R&D
and infrastructure and other interventions to de-risk R&D, innovating in regulation, and
nurturing needed collaborations can impact R&D costs in a way that minimises the
affordability and demand-side challenge. It may also assume significant spill-over benefits
related to prioritising supply-side interventions (e.g. employment and tax-revenue benefits
from vibrant pharmaceutical R&D ecosystems). However, further research is needed on how
much a reduction in R&D costs would impact pricing decisions and affordability in the
absence of government pricing regulation.
• The third framing approaches both ends of the challenge simultaneously, asking: ‘What are
the key demand-side interventions that can help support affordability and secure demand,
and what supply-side interventions need supporting in parallel to ensure a sustainable supply
of pharmaceutical R&D and optimise R&D costs?’
Ultimately, the framing that could guide stakeholder action and policymaking in Europe will depend on how decision-makers prioritise the resources, time and investments at their disposal to
channel into building sustainable and resilient financial ecosystems for pharmaceutical R&D and
future sector competitiveness.

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Appendix A: Tools for scenario development

Figure 5. Influence matrix.

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Figure 6. Consistency matrix.

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