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BioForward Leadership Breakfast series
             Elias Zerhouni


             Wisconsin, January 22, 2013
THE CORE ISSUE
A spectacular drop in productivity
     Clinical timelines
     Clinical timelines                                         NME11approvals by
                                                                NME approvals by
         increasing
          increasing                                             FDA decreasing
                                                                  FDA decreasing                                                 Rising R&D costs
                                                                                                                                 Rising R&D costs
Mean clinical                                              Number of NCEs2 and                                             R&D expenditure
development time (years)                                   NBEs3 approved                                                  per drug ($M)
12                                                         400                                                             2000
                                                                                                                                                                  1778

10
                                     9.2
                                                                                                                          1.500                    +11%
                                                           300
                     +20%                   Approval                                                                                                           1318
 8                            7.7                                                                                                                           1250
                                                                              241
                      6.7                                                              -26%
                                                                     210
                                                                               54
 6             5.6                                         200                                                            1.000                           880
                                                                     84                 162
       4.5
                                                                                         42       133
 4                                          Clinical                                                                                                  608
                                                                                                   24    NBE
                                                           100                187                                           500               359 400
 2                                                                                                                                         230
                                                                     126                120       109    NCE                            125
                                                                                                                                   54
 0                                                            0                                                                0
     82-89 90-94 95-99 00-04 05-06                                 90-94 95-99 00-04 05-10                                         76 82 87 90 94 96 01 03 07 104


1. NME: New molecular entity 2. NCE: New chemical entity 3. NBE: New biological entity 4. 2010 data is from Paul et al Nature Feb-10, rest of data from Tufts
Source: FDA; EvaluatePharma; Tufts CSDD 2007; Parexel; CMR; Paul et al, 2010, BCG analysis


                                                                                                                                                                         |   2
Why?
Major drivers of change

●   Patient needs                     ●   Regulation
     ● Acute to chronic                    ●   Regulatory burden
     ● Personalized                        ●   Safety thresholds
     ● Generics                            ●   Postmarketing requirement
                                           ●   Longer R&D cycles



●   Payer driven market               ●   Science
     ●   Differential medical value        ●   Low predictability in Humans
     ●   Rise of formularies               ●   Too concentrated on a few targets
     ●   Payment restrictions              ●   Low success rates
     ●   Price controls                    ●   Low overall efficiency




                                                                                   |   3
What went wrong?
●   The INNOVATION model
    ● Belief that advances in basic sciences could be easily translated to human disease
    ● A linear process from discovery to development to market with little interactions
      throughout the innovation cycle
    ● Concentration of research on « ME-TOO » drugs
    ● Too many novel but not validated targets in humans
    ● A strategy of « MANY SHOTS ON GOAL »


●   The ORGANIZATIONAL model
    ● Large complex organizations inherited from successive mergers
    ● All research focused on internal research without much interactions with larger world
      of external innovation
    ● Resource allocations driven by functions rather than specific projects and programs
    ● A disconnect between R&D strategies and the rapid changes in the Scientific, Medical
      and Market environments




                                                                                              |   4
Future of Healthcare is Dramatically Changing




                                                5
Unsustainable growth in Healthcare Costs


Index                                               Index                                                       Index
(2000 = 100)                                        (2000 = 100)                                                (2000 = 100)

300   Historic      Forecast                        300     Historic          Forecast                           300     Historic         Forecast

                                      HC cost
                                                                                               HC cost                                                      HC cost
200                                   GDP           200                                                          200
                                                                                               GDP                                                          GDP

100                                                 100                                                          100
  2000    2005   2010   2015     2020                  2000              2010             2020                      2000              2010               2020




Index                                               Index                                                       Index
(2000 = 100)                                        (2000 = 100)                                                (2000 = 100)
                                                                                               HC cost                                                      HC cost
300   Historic      Forecast          HC cost       300     Historic          Forecast                           300     Historic         Forecast

                                                                                               GDP                                                          GDP
                                      GDP
200                                                 200                                                          200


100                                                 100                                                          100
  2000           2010            2020                  2000              2010             2020                      2000              2010               2020




                                                                                                                                                                      6
                  Note: Index GDP on basis of local currency. GDP forecast by EIU while HC cost forecast by EIU (2010-2015) and BCG / OECD (2015-2020)
                  Source: EIU forecast (2011), OECD, Espicom, WHO, BCG estimates (2011)
We Need to Rethink Innovation




                                7
What Will it Take to Be?




Translational Medicine                  Open Innovation
Because strengthening cooperation       Because we recognize that inside
between laboratory researchers,         and outside our walls, there is
clinical trial directors and clinical   astounding scientific discovery
researchers whose work focuses          going on and that it is through
on patients and populations, is of      collaboration that we will deliver the
paramount importance to make our        best, the most innovative and the
science available to those who          most awaited solutions patients are
need it                                 hoping for



                                                                                 8
Our Focus
We Are Where Diseases & Needs Are

Priority Areas of Research




                                    |   9
Sanofi R&D Profile




                     |   10
Our Way of Working
Leveraging Local Innovative Ecosystems

Our ambition is to create integrated R&D Hubs

   To make the best of the opportunities, science, talents and resources
   available in local innovative ecosystems




                                                                           |   11
Flexible, responsive, adapted toolbox to
extend the reach of R&D making the Open
Innovation a reality




      Maximize Synergies in Everything We Do
      Maximize Synergies in Everything We Do
                                               12

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Elias Zerhouni - January 22, BioForward Breakfast Event Presentation

  • 1. BioForward Leadership Breakfast series Elias Zerhouni Wisconsin, January 22, 2013
  • 2. THE CORE ISSUE A spectacular drop in productivity Clinical timelines Clinical timelines NME11approvals by NME approvals by increasing increasing FDA decreasing FDA decreasing Rising R&D costs Rising R&D costs Mean clinical Number of NCEs2 and R&D expenditure development time (years) NBEs3 approved per drug ($M) 12 400 2000 1778 10 9.2 1.500 +11% 300 +20% Approval 1318 8 7.7 1250 241 6.7 -26% 210 54 6 5.6 200 1.000 880 84 162 4.5 42 133 4 Clinical 608 24 NBE 100 187 500 359 400 2 230 126 120 109 NCE 125 54 0 0 0 82-89 90-94 95-99 00-04 05-06 90-94 95-99 00-04 05-10 76 82 87 90 94 96 01 03 07 104 1. NME: New molecular entity 2. NCE: New chemical entity 3. NBE: New biological entity 4. 2010 data is from Paul et al Nature Feb-10, rest of data from Tufts Source: FDA; EvaluatePharma; Tufts CSDD 2007; Parexel; CMR; Paul et al, 2010, BCG analysis | 2
  • 3. Why? Major drivers of change ● Patient needs ● Regulation ● Acute to chronic ● Regulatory burden ● Personalized ● Safety thresholds ● Generics ● Postmarketing requirement ● Longer R&D cycles ● Payer driven market ● Science ● Differential medical value ● Low predictability in Humans ● Rise of formularies ● Too concentrated on a few targets ● Payment restrictions ● Low success rates ● Price controls ● Low overall efficiency | 3
  • 4. What went wrong? ● The INNOVATION model ● Belief that advances in basic sciences could be easily translated to human disease ● A linear process from discovery to development to market with little interactions throughout the innovation cycle ● Concentration of research on « ME-TOO » drugs ● Too many novel but not validated targets in humans ● A strategy of « MANY SHOTS ON GOAL » ● The ORGANIZATIONAL model ● Large complex organizations inherited from successive mergers ● All research focused on internal research without much interactions with larger world of external innovation ● Resource allocations driven by functions rather than specific projects and programs ● A disconnect between R&D strategies and the rapid changes in the Scientific, Medical and Market environments | 4
  • 5. Future of Healthcare is Dramatically Changing 5
  • 6. Unsustainable growth in Healthcare Costs Index Index Index (2000 = 100) (2000 = 100) (2000 = 100) 300 Historic Forecast 300 Historic Forecast 300 Historic Forecast HC cost HC cost HC cost 200 GDP 200 200 GDP GDP 100 100 100 2000 2005 2010 2015 2020 2000 2010 2020 2000 2010 2020 Index Index Index (2000 = 100) (2000 = 100) (2000 = 100) HC cost HC cost 300 Historic Forecast HC cost 300 Historic Forecast 300 Historic Forecast GDP GDP GDP 200 200 200 100 100 100 2000 2010 2020 2000 2010 2020 2000 2010 2020 6 Note: Index GDP on basis of local currency. GDP forecast by EIU while HC cost forecast by EIU (2010-2015) and BCG / OECD (2015-2020) Source: EIU forecast (2011), OECD, Espicom, WHO, BCG estimates (2011)
  • 7. We Need to Rethink Innovation 7
  • 8. What Will it Take to Be? Translational Medicine Open Innovation Because strengthening cooperation Because we recognize that inside between laboratory researchers, and outside our walls, there is clinical trial directors and clinical astounding scientific discovery researchers whose work focuses going on and that it is through on patients and populations, is of collaboration that we will deliver the paramount importance to make our best, the most innovative and the science available to those who most awaited solutions patients are need it hoping for 8
  • 9. Our Focus We Are Where Diseases & Needs Are Priority Areas of Research | 9
  • 11. Our Way of Working Leveraging Local Innovative Ecosystems Our ambition is to create integrated R&D Hubs To make the best of the opportunities, science, talents and resources available in local innovative ecosystems | 11
  • 12. Flexible, responsive, adapted toolbox to extend the reach of R&D making the Open Innovation a reality Maximize Synergies in Everything We Do Maximize Synergies in Everything We Do 12

Hinweis der Redaktion

  1. The context: the entire Pharma industry has been facing significant challenges in the recent years. 1) Clinical timelines are increasing : the average clinical development time more than doubled since the 80's, from 4.5 years to more than 9 years 2) NME (New Molecular Entities) approvals by FDA are decreasing : the number of NME decreased by 50% since the 90's, from an average of 50 per year to less than 25 a year in recent years. 3) R&D expenses are growing exponentially : the increase in costs to bring a successful NME to market increased from less than $100 million in the 70's to more than $1.7 billion recently. This is due to the increased costs and duration of clinical trials, a more difficult regulatory environment, the genericization of many drugs which requires that new drugs be better differentiated, much more efficacious against existing standards of care and payers who have raised the bar for reimbursement. In addition the overall success rate for research projects decreased due to increased complexity of science.   Consequently, the R&D investment which had a very high return and led to enormous expansion of companies and their R&D departments began to show negative returns. Today, estimates for the top Pharma companies indicate that 1 dollar of R&D investment returns about 70 cents in value on average. Clearly a new strategy is needed!
  2. The major drivers of these significant changes are the following: Patient Unmet Needs, Payers Strategies, Regulatory Pressures, and New Science Trends   Evolution of Patient Unmet Needs With the success of the past 50 years in Pharma R&D, many then prevalent unmet needs can now be addressed with genericized drugs . Examples: coronary heart disease and stroke; chronic diseases and the diseases of aging; - to name only the dominant causes of rising costs and disease burden.   In parallel there is a growing realization that a more precise so called "Personalized" Medicine approach focusing on well characterized subgroups of patients with well understood mechanisms of disease as exemplified by rare diseases is the most likely path to the development of more effective therapies . These changes need to be reflected in any future strategy.   New Payer Driven Environment Today, health care costs have become the N°1 priority for many governments and although pharmaceuticals represent about 10% of all costs they have become prime and popular targets for price reductions. Payers increasingly only reimburse for real and demonstrated medical value above and beyond that already available in the market and not against placebo.   The comparative effectiveness movement started in the UK with the National Institute for Clinical Effectiveness (NICE) to control national drug formulary and prices is predicted to continue to spread around the world . Example: recently NICE declined to provide coverage for Jevtana claiming insufficient incremental benefit over the less costly predecessor molecule.   Physicians are less and less the ultimate decision makers given the development of more rigid clinical protocols defined by institutional committees at the instigation of insurance companies along with more directive formulary committees. Therefore the optimal product profiling for R&D has rapidly changed and needs to be fundamentally redefined for our strategy by focusing on high value added projects that address unmet needs but also with the potential to reduce healthcare costs.   These payer policy changes have occurred at a pace that caught many companies, including Sanofi, unprepared with many products without sufficient differential values in their pipeline. Many of these were removed from our portfolio over the past 2 years but it is difficult to realign the entire portfolio as the time needed for original R&D is quite long. Hence the need to continue to look at external innovation in search of programs with a shorter development timeline.   Regulatory Pressures The persistently high attrition rate between discovery research and development as well as more stringent regulatory requirements leading to more expensive clinical trials have exploded the costs of successfully developing a molecule from less than a 100 million a few decades ago to nearly $1.7 Billion according to external studies. Moreover, R&D budgets are not solely dedicated to discovering new therapies but need to support all therapies existing in the portfolio for follow on trials, risk management programs as well as worldwide regulatory and pharmacovigilance activities all of which have to be continued while R&D budgets are under pressure.   Also important is the fact that after a long period of expansion across the many sites acquired through mergers and acquisition and a tendency at Sanofi for many years to do all things internally, the resultant cost structure of R&D is quite rigid with a large percentage of fixed costs relative to variable costs in an activity that requires rapid adaptation and changes because of the unpredictable ups and down of R&D . An important goal of our strategy is therefore an effort at reshaping our operating model to be more flexible and adaptive.   New Trends in Science Most experts recognize that advances in basic science over the past 20 years have been extraordinary but that the translation of these advances to real therapies has actually slowed with less and less new molecular entities being approved. Many believe that our scientific approaches are flawed because they rely too much on technologies and methodologies derived from molecular biology and genomics that are heavily reliant on in vitro, cell or transgenic animal models that have simply been unable to account for the complexity of human biology and unreliably predict either safety or efficacy in humans hence the high number of late stage failures in development. To achieve success, we need to refocus efforts on a better understanding of disease in humans as early as possible in the R&D process with early studies on well characterized patient populations and samples using a set of new methodologies to define as early as possible if a new therapy is effective in humans. This "translational Medicine" approach is considered to be critical to any new strategy and we are in the early stages of its implementation.   Lastly, the innovation process in Pharma has become so scripted, linear and process oriented that the necessary interactions and creative iterations from concept to early implementation, clinical development and marketing have become too fragmented. Insufficient insights are provided at all stages of the innovation cycle. This is why our strategy will focus on fully integrated research and development teams and programs with continuous internal and external input and iterations across the full cycle to avoid the all too frequent phenomenon of projects that continue to be supported without a clearly defined path to market success. In our experience successful R&D organization have mechanisms to constantly allocate and re-allocate resources across a diversity of teams and projects base on objective experimental results. This dynamic management of science operations enhances the ability of the organization to avoid dispersing its resources across too many projects without well defined milestones and reduces unproductive use of resources.
  3. In this specific environment, Sanofi was facing challenges of its own When Chris Viehbacher undertook a profound re-evaluation of all aspects of the company in early 2009, the following observations could be made:   1. Following successive mergers, there was the need to rethink the overall infrastructure and operations footprint. The R&D organization had been inherited from the many predecessor entities without a real effort at rationalizing the footprint and functions of the many different sites and programs making the organization unwieldy and less productive. A phenomenon experienced by many other companies that grew through multiple acquisitions but not addressed due to growing blockbuster revenues and good balance sheets leading to a certain level of complacency.   2. Organization also needed to open up to external innovation and new fields of opportunity (vaccines, biologics…) so as to feed and strengthen the pipeline. It became clear that previous policies focused on exclusively internal research without much interactions with the larger world of external innovation led to a situation where most programs were either an extension of older programs along the lines of "Me-Too“ drugs, many novel targets with weak validation and often late entries into already advanced programs by other companies. This led to a weak pipeline with impending loss of several leadership positions with no equivalent replacement products. In addition, despite strengths in biologics through Vaccines, Insulins and Heparin products, Sanofi relied heavily on traditional small molecule chemistry approaches and did not enter the field of first in class biologics until late in the game.
  4. The aim of Sanofi R&D is to respond to patients’ real needs and to provide them with adapted therapeutic solutions . To best answer these challenges, R&D has evolved towards an integrated R&D organization encompassing a wide range of therapeutics areas that are in line with public health issues, trends and the most pressing health needs. These form our priorities. Why are those areas our priority? – Selected facts & figures Chronic diseases such as diabetes, hypertension, heart disease, stroke and cancers are a large and growing burden on the populations and healthcare systems. 2 out of 3 patients admitted as medical emergencies have exacerbations of chronic disease and 60% of deaths are as a result of a chronic disease. Chronic diseases can be disabling and reduce a person’s quality of life, especially if left undiagnosed or untreated. For example, every 30 seconds, somewhere in the world a lower limb is amputated as a consequence of diabetes. Cancer is a leading cause of death worldwide, accounting for 7.6 million deaths (around 13% of all deaths) in 2008. Lung, stomach, liver, colon and breast cancer cause the most cancer deaths each year. 346 million people worldwide have diabetes . In 2004, an estimated 3.4 million people died from consequences of high blood sugar. Cardiovascular diseases ( CVDs) are the number one cause of death globally: more people die annually from CVDs than from any other cause. The increasing proportion of older people in the global population is contributing to the increase of age-associated chronic diseases. This has implications for the healthcare system , if the current trends continue, bed requirements in hospitals will increase by 50-60% over the next 15 years. Care-givers, health systems and societies need to be ready to cope with the growing needs of the elderly in every part of the world. Infectious Diseases are linked to significant and critical unmet medical needs both in the developed and developing worlds. In low-income countries, people predominantly die of infectious diseases : lung infections, diarrhoeal diseases, HIV/AIDS, tuberculosis, and malaria. Less than one in five of all people reach the age of 70 and more than a third of all deaths are among children under 15. Dengue Fever threatens nearly half the world’s population, i.e., at least 2.5 billion people , in almost one hundred countries located in tropical and subtropical regions. Hospital-acquired infections are a major concern for public health in many industrialized countries and cause significant annual costs to the healthcare systems . Every year in the US, 1.7 million people (4.5% of total hospital admissions) fall victim to hospital-acquired bacterial infections, leading to 99,000 deaths. Approximately 7,000 rare disorders are known to exist and new ones are discovered each year. Rare disease affects between 25-30 million people in the US and approximately 30 million people in the European Union. Sources: WHO website - Rare Project website
  5. We are evolving our R&D approach to be able to access the best science and people in research . Our ambition is to create geographically-focused integrated research hubs in four areas: North America and the Boston area Germany France Asia Why? Because in research, things don’t happen globally. Things happen locally, within networks that are as barrier-free, empowered and connected as possible. By locating our R&D hubs in regions known for innovation, we have the ambition to act as part of a creative and varied scientific community. By gathering in hubs, our R&D itself will become a network of communities, each at a scale that facilitates the development of relationships across areas of expertise, expanding opportunities to share ideas, resources and information for the benefit of our projects – and ultimately of patients. This way of working, combined with our global high quality development capabilities, is key to deliver the innovative health solutions patients need.