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- Herausgeber: John Wiley & Sons
- Kategorie: Fachliteratur
- Sprache: Englisch
A comprehensive overview of the new business context for biopharma companies, featuring numerous case studies and state-of-the-art marketing models Biotechnology has developed into a key innovation driver especially in the field of human healthcare. But as the biopharma industry continues to grow and expand its reach, development costs are colliding with aging demographics and cost-containment policies of private and public payers. Concurrently, the development and increased affordability of sophisticated digital technologies has fundamentally altered many industries including healthcare. The arrival of new information technology (infotech) companies on the healthcare scene presents both opportunities and challenges for the biopharma business model. To capitalize on new digital technologies from R&D through commercialization requires industry leaders to adopt new business models, develop new digital and data capabilities, and partner with innovators and payers worldwide. Written by two experts, both of whom have had decades of experience in the field, this book provides a comprehensive overview of the new business context and marketing models for biotech companies. Informed by extensive input by senior biotech executives and leading consultancies serving the industry, it analyzes the strategies and key success factors for the financing, development, and commercialization of novel therapeutic products, including strategies for engagement with patients, physicians and healthcare payers. Throughout case studies provide researchers, corporate marketers, senior managers, consultants, financial analysts, and other professionals involved in the biotech sector with insights, ideas, and models. JACQUALYN FOUSE, PhD, RETIRED PRESIDENT AND CHIEF OPERATING OFFICER, CELGENE "Biotech companies have long been innovators, using the latest technologies to enable cutting edge science to help patients with serious diseases. This book is essential to help biotech firms understand how they can-and must-apply the newest technologies including disruptive ones, alongside science, to innovate and bring new value to the healthcare system." BRUCE DARROW, MD, PhD, CHIEF MEDICAL INFORMATION OFFICER, MOUNT SINAI HEALTH SYSTEM "Simon and Giovannetti have written an essential user's manual explaining the complicated interplay of the patients who deserve cutting-edge medical care, the biotechnology companies (big and small) creating the breakthroughs, and the healthcare organizations and clinicians who bridge those worlds." EMMANUEL BLIN, FORMER CHIEF STRATEGY OFFICER AND SENIOR VICE PRESIDENT, BRISTOL-MYERS SQUIBB "If you want to know where biopharma is going, read this book! Our industry is facing unprecedented opportunities driven by major scientific breakthroughs, while transforming itself to address accelerated landscape changes driven by digital revolutions and the emergence of value-based healthcare worldwide. In this ever-changing context, we all need to focus everything we do on the patients. They are why we exist as an industry, and this is ultimately what this insightful essay is really about." JOHN MARAGANORE, PRESIDENT AND CHIEF EXECUTIVE OFFICER, ALNYLAM PHARMACEUTICALS "Since the mapping of the human genome was completed nearly 15 years ago, the biotechnology industry has led the rapid translation of raw science to today's innovative medicines. However, the work does not stop in the lab. Delivering these novel medicines to patients is a complex and multifaceted process, which is elegantly described in this new book."
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Contents
Cover
Title Page
Copyright
Dedication
Foreword
Preface
Acknowledgments
Praise for Managing Biotechnology: From Science to Market in the Digital Age
About the Authors
Part 1: New Models for Networked Innovation
Chapter 1: Digital Evolution of Biotechnology
Industry Applications
Impact of Megatrends
Digital Health Opportunities
Infotechnology Initiatives in Healthcare
Disruption Risk from Infotech
Technology Strategies
Big Infotech Strategies
Conclusion
Summary Points
Chapter 2: Biotechnology Financing Strategies
The Long Game
Strategic Decisions
Geographic Considerations
Sources of Financing
A Word About Mergers and Acquisitions
Summary Points
Chapter 3: Success Through Collaboration
Alliance Evolution: More Players and New Structures
Strategic Alliances: A Stalwart of the Biopharma Industry
Alliance Versus Acquisition
Structure Considerations to Maximize Value
Divesting for Focus
Doing the Deal
Summary Points
Part 2: New Business and Marketing Models
Chapter 4: Precision Medicine
What is Precision Medicine?
Targeted Medicines Multiply But Drug-Diagnostic Pairs are Rare
Precision Medicine is Happening at Several Levels
Multiple Forces, Beyond Science, are Driving Precision Medicine
Digital Precision Medicine
Precision Medicine in Practice: Lessons from Cancer
Challenges: Scientific, Infrastructural, Regulatory, and Commercial
Surmounting the Hurdles to Revolutionize Medicine
Biopharma Must Drive, not be Driven by, Precision Medicine
Precision Medicine's Future
Summary Points
Chapter 5: Precision Marketing
Introduction
Portfolio Shift to Specialty Products
Balancing Evidence and Experience
R & D and Commercial Coordination
Value of Experience: The Consumer Decision Journey
Marketing Beyond the Pill
Targeting New Consumer Segments
New Physician Segments
Dual Branding Models
New Launch Strategies
Companion Diagnostics
Global Organization
Multichannel Communications
Content Marketing
Salesforce Strategies
Sustainability Strategies: Beyond the Life Cycle
Summary Points
Chapter 6: Patient Centricity Strategies
Introduction
Patient Centricity Drivers and Barriers
Discovery: Understanding Unmet Needs
Designing Patient-Friendly Clinical Trials
Connecting the Points of Care
Understanding the Patient Journey
Organizing for Patient Centricity
Patient Engagement Metrics
Organization Models
Summary Points
Chapter 7: Drug Pricing in Context
Introduction
The Economics of Drug Pricing
Competing Definitions of Product Value Complicate Drug Pricing
Proving Efficacy in the Real World
Setting the Pricing Strategy
Analyzing New Pricing Models
Deployment of New Pricing Strategies
Experimental Pricing Strategies
Financing the Future: Affordability
New Tools for Outcomes-Data Capture
Conclusion
Summary Points
Chapter 8: Strategic Payer Engagement
Payers Are Not All Alike
New Market Forces Increase Payer Power
The Increasing Importance of the Consumerin the United States
European Payers: High-Level Unity, Low-Level Fragmentation
United States Adopts European-Stylecost-Effectiveness Hurdles
Payer Engagement Strategies Must be Tailored, Scalable, and Flexible
Changing Biopharma-Payer Relationships: From Transactional to Collaborative
New Biopharma Organizational Models Needed
Biopharma-Payer Engagement Must Move Beyond Experimentation
Strategic Payer Engagement Comes in Many Forms
Summary Points
Part 3: New Models for Digital Health
Chapter 9: Digital Health Strategies
Introduction
Biopharma Digital Strategies
Digital Impact on Supply Chain Management
Digital Transformation of Commercial Activities
Consumer-Centered Trends
Provider-Centered Strategies: Telehealth
Conclusion
Summary Points
Chapter 10: Creating Agility Through Data and Analytics
Introduction
Multiple Forces Converge to Create Data and Analytics Opportunities
Healthcare's Four Data Vectors: Volume, Velocity, Variety, and Veracity
Extracting Value from Data Requires New Tools
The Analytics Continuum: From Descriptive to Prescriptive
Data Analytics Across the Biopharma Value Chain
Data and Analytics Challenges
Building an Analytics-First Organization: Cultural not Technical Hurdles
Conclusion
Summary Points
Conclusion
References
Index
End User License Agreement
List of Illustrations
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Guide
Cover
Table of Contents
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Praise for Managing Biotechnology: From Science to Market in the Digital Age
“We can sometimes forget why technology matters beyond helping us do our work faster and cheaper; it is because technology tools help us connect with patients, our most important end customers. By including a discussion on patients and patient centricity in their book, Simon and Giovannetti remind us that technology is a powerful way to connect us with them. The recent emergence of patient engagement, sophistication and empowerment means that any healthcare leader must be prepared to genuinely understand the needs of patients, and be prepared to engage with them to improve their health outcomes. This book nicely maps out how technology can be used to meet those goals.”
Olivier Brandicourt, MD, Board Member, Pharmaceutical Research and Manufacturers of America
“Biotech innovation is rapidly embracing digital technologies in the discovery, validation, clinical and product commercialization phases. The Internet of Things is bringing forward the Internet of Medical Things and the opportunities to build value with combinations of molecules, software and devices have never been so evident. Personalization, precision, data analytics and elements of consumer convenience are making their way into product pipelines. Industry participants can use this book as a modern roadmap to innovation and commercialization.”
Donald Jones, Chief Digital Officer, Scripps Translational Science Institute and Chairman, Cardiff Ocean Group
“This is an unprecedented moment in the healthcare industry. Simon and Giovannetti have captured the tremendous potential of the period in this innovative and well-informed book, where they have brought to life the need to leverage digital technology and patient centricity to drive better health outcomes.”
Lynn O'Connor Vos, CEO Greyhealth Group
“If you want to know where biopharma is going, read this book! Our industry is facing unprecedented opportunities driven by major scientific breakthroughs, while transforming itself to address accelerated landscape changes driven by digital revolutions and the emergence of value-based healthcare worldwide. In this ever-changing context, we all need to focus everything we do on the patients. They are why we exist as an industry, and this is ultimately what this insightful essay is really about.”
Emmanuel Blin, former Chief Strategy Officer and Senior Vice President, Bristol-Myers Squibb
“This expert and thorough analysis of the journey from biomedical investigation to patient care presents an innovative blueprint for streamlining, redesigning, and amplifying the process. Specific examples of success stories support the recommendations for improved networking among the various players in the medical arena. Essentially, the authors predict a shift from emphasis on drug development to a broader collaborative system focused on the individual patient. The book is an interesting and important read for anyone involved in the prevention and treatment of disease.”
Marianne J. Legato, MD, PhD (hon. c.), FACP, Emerita Professor of Clinical Medicine, Columbia University Founder and President, Foundation for Gender-Based Medicine
“Precision Medicine, Patient Centricity, Digital Health, Value-Based Reimbursement, Risk-Sharing—these terms were virtually unused in biopharma even five years ago. This book provides essential grounding and concepts to consider for anyone interested in healthcare, drug development and patient access in the 21st Century.”
Ron Cohen, MD, Former Chairman, Biotechnology Innovation Organization
Managing Biotechnology
From Science to Market in the Digital Age
Françoise Simon, PhD
Professor Emerita, Columbia University and Senior Faculty, Icahn School of Medicine at Mount Sinai,New York, NY
Glen Giovannetti
EY Global Biotechnology LeaderCambridge, MA
This edition first published 2017
© 2017 John Wiley & Sons, Inc.
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Dedication
In memory of my parents, Yvonne David and Louis Simon
—Françoise Simon
To my wife Lisa, who has been a companion on the Life Sciences journey for over 30 years in multiple cities, with tremendous flexibility, support and patience, including with this project
—Glen Giovannetti
Foreword
The healthcare sector is undergoing unprecedented change. Aging populations and the rising incidence of chronic diseases have strained budgets, resulting in policy reforms that are changing the way healthcare is provided, consumed and paid for around the globe. The traditional contrast between the European universal payer system and the US freer market model is starting to fade, as more than half of US reimbursement now comes from public entities such as Medicare and Medicaid. In emerging markets, despite the rise of middle-class populations, challenges remain, from intellectual property to manufacturing quality, drug pricing. and patient access to health services.
Major players in the health ecosystem—patients, providers, manufacturers, and payers—are changing their behaviors in response by assuming more financial responsibility for improving health outcomes, adopting new technologies, and leveraging data to drive innovation and care delivery. In parallel, the confluence of radical advances in biotechnology and information technology is leading to a new model of precision medicine. It gives unprecedented power to individuals, and it allows the deep integration of the customer voice into innovation, from product co-creation to continuous monitoring.
As it has happened in many other industries, the entrance of nontraditional players is poised to disrupt the health industry and its incumbents, creating a cadre of new potential leaders. Some of these include consumer, telecom, and tech powerhouses; Apple, IBM, Google, Intel, and QualComm have all made major investments in health. A plethora of start-ups, particularly in the data analytics space, is also upending business as usual. Today, health data is fragmented and in silos.
While consumer data collected on smartphones and biosensors are still not connected to medical offices and electronic health records, there is great promise in eventually providing seamless care to patients, from research to the clinic, and moving from treatment of illness to prevention and prediction. Consumers have become accustomed to the convenience of personal technologies and will increasingly demand the same from their health providers, including more remote care and data sharing. With health budgets already under strain, the value generated by these insights may come at the expense of healthcare industry incumbents.
The global biopharmaceutical industry finds itself in the middle of this storm. In a world where payment will be based on demonstrating real value, the industry's traditional development and commercial strategies are no longer fit for purpose. Commercial-stage biopharma companies are beginning to adapt their strategies, reducing their dependence on large sales forces that promote undifferentiated products. They now seek to unlock value across their operations—from how they approach R & D (leveraging data and focusing on precision medicine and orphan diseases), to the evidence they collect to support value arguments, to providing “beyond-the-pill” solutions that may require partnerships with nontraditional entrants.
Emerging biotech companies working on exciting new science must also adapt their financing strategies to this new reality. No longer is it enough to sell investors on the promise of new scientific approaches. Biotechs must also articulate why their scientific advances will result in differentiation in a competitive global market. In Managing Biotechnology: From Science to Market in the Digital Age, Françoise Simon and Glen Giovannetti provide a comprehensive overview of the new business context and global strategies for biotechnology companies. The book is an important source of insight into critical topics such as networked innovation, alliances, commercialization, and digital communications. It serves as a roadmap to take concepts and products from science to market, and it captures the range of knowledge that students and managers need to leverage emerging technologies. It can also help interested policymakers aiming to grow and support biotech clusters worldwide to understand the risks, opportunities and challenges of the biotech industry.
This in-depth examination, based on the authors' broad experience, will be useful in teaching and inspiring current and future leaders across sectors driven by biotechnology. It will contribute high-value guidance for all stakeholders, from providers and payers to manufacturers. Most importantly, it may play a part in helping to bring new medicines to market and improving patients' lives and outcomes.
For biopharmaceutical firms, the future may hold an enabling scenario of optimized research, but it could also be a disruptive one, of disintermediation by infotechs of patient/provider communications. As the authors point out, success will depend on a melding of new cross-industry business models and of leading edge science, to improve the standard of patient care on a global scale.
By Philip Kotler
S.C. Johnson & Son Distinguished
Professor of International Marketing
Kellogg School of Management
Northwestern University
Preface
Since its founding four decades ago, the modern biotechnology industry has been a source of significant innovation across many parts of the economy, especially in the area of human health. Once-fatal diseases—ranging from HIV and hepatitis C to many cancers—are now chronic conditions or have been effectively cured, due to the introduction of innovative biotech medicines. Many of these medicines were discovered and developed by nimble entrepreneurial companies. New techniques and technology platforms under development by companies both large and small (and in academic, government, and private research labs) continue to create optimism that many more poorly treated, or untreated, conditions will soon be addressed, including many diseases prevalent in aging populations.
Over the same four decades, the rise of digital technologies has restructured the order of many industries, giving a majority of the global population access to enormous computing power and information, while simultaneously enabling previously unimaginable connectivity through social media platforms. These technologies have had an impact on the delivery and consumption of healthcare, although the pace of change in this industry has lagged many other parts of the global economy.
While scientific innovation remains at the core of the biopharma industry, the long-term trend of constrained health systems budgets and persistent public pressure on drug prices has put the traditional biopharma business model under tremendous strain. Biopharma companies understand that this new reality requires them to objectively demonstrate the real-world value of their products. They also realize that, to address significant unmet medical needs, they must expand their traditional focus on physicians to include engagement with patients and payers; in short, to think “beyond the pill.” Adoption of digital technologies and access to, and effective analysis of, data will be key enablers as proof of outcomes becomes the industry benchmark. At the same time, many information technology (infotech) companies view healthcare as an untapped growth area ripe for digital disruption, as was previously seen in the financial and retail sectors. As a result, they are committing significant resources to developing new health offerings. Biopharma companies will have to understand whether these relatively new entrants in healthcare represent collaborators, competitors, or both.
The convergence of these trends is altering the biopharma value chain and ultimately the industry's business model. Traditionally, that value chain was linear, starting with scientific inquiry, product identification, clinical development, and, for those drugs that successfully progressed through regulatory approval, commercialization. As development milestones were achieved, responsibility for the product was handed off from function to function, with little integration and information sharing (or one-way sharing at best). Strategic decisions, including budgets and capital allocation, often occurred within functional silos. This structure worked in a world in which “me-too” drugs that did not provide much, if any, incremental value could still generate a return on investment through effective sales and marketing.
This fundamentally product-centric view of biopharma drug development is outdated. It is no longer tenable for companies to invest in products that, even if proven safe and effective by regulators, do not provide measureable value to patients and health systems. Patient expectations, driven by growing reliance on digital technologies and the connectivity they provide, are also changing. As a consequence, the biopharma value chain has reoriented around a fundamental understanding of patient needs, with data and insights flowing not just in one direction from the lab to the market but also from the market back to the lab, as depicted in the figure.
Managing biotechnology—framework
The innovation end of this cycle begins with a deep understanding of disease, including both the biology and the care pathways that patients experience. These insights are informed by a company's own experiences in a disease area (again, from research and commercial perspectives). The need to develop this depth of expertise is a factor causing many larger companies to fundamentally rethink their portfolios in order to specialize in fewer areas, increasing the likelihood of true differentiation. This is also resulting in broader adoption of precision medicine strategies to target more precisely patient populations that can be segmented by genetic or other characteristics to identify those more likely to respond to a particular drug therapy. In addition, technological convergence will also be a source of insight. For instance, artificial intelligence technologies developed by infotech companies can assimilate and analyze a range of patient and health data to generate new drug development hypotheses.
Understanding the patient care pathway in the actual health setting is important for effective clinical trial designs that support not just a regulatory approval but also negotiations with payers. Patient input is also becoming essential at the clinical development stage where patient relevant endpoints can be considered as part of a strategy to demonstrate effectiveness to a regulator and value to a payer. Connectivity to patients and patient advocacy groups also has the potential to facilitate trial recruitment.
In commercialization, making the case for the value of a product to payers and marketing a drug to providers and patients will be based on a combination of clinical data and “real-world” data that takes into account actual patient experiences, co-morbidities, and care delivery models. In some sense, the innovation phase of the cycle never really ends, as payers put more focus on real-world data over that generated in randomized clinical trials with selective enrollment criteria. Companies entering into risk-based reimbursement models in which payment is based on the achievement of defined outcomes will especially need a deep understanding of the patient journey and what other lifestyle factors might impact those outcomes. In some circumstances, this will drive the need for education, monitoring or other “beyond-the-pill” solutions.
Digitally enabled strategies will result in new ways to connect with patients. They will provide both structured and unstructured data from electronic health records, wearables, monitoring of social media, and other channels for analysis. These data will inform interactions with payers, providers, and regulators and will also feedback into R & D, completing the cycle.
Book Structure
The structure of this book largely follows the above framework. We have left a detailed discussion of the scientific breakthroughs underpinning the biopharma sector to others. Our book follows the triple transformation of the biopharma sector: networked innovation, including the convergence of infotech and biotech; new digital strategies; and patient centricity through the value chain.
In Chapter 1, we address the impact of technology convergence and the strategies of big infotech players on the biopharma value chain, as well as the barriers to further convergence. As most of the industry's innovation comes from, or is advanced by, start-up biotechnology companies, in Chapters 2 and 3 we provide information for entrepreneurs around financing and connected innovation through alliances with large companies and other entities. Chapter 4 discusses the impact of an expanding view of precision medicine on drug development and commercialization strategies, including significant market and organizational barriers that must be overcome to promote more widespread adoption.
As a companion to precision medicine, in Chapter 5, we introduce the concept of precision marketing. As payers, physicians, and consumers increasingly expect clinical and economic data to support a medicine's use, biopharma companies can make their product profiles more compelling via evidence-based marketing. This chapter also discusses product launch strategies, multichannel marketing approaches, sales force deployment, and product sustainability. Complementing material in Chapter 5, Chapter 6 explores what patient-centricity means today, discussing in greater detail the concepts described above, as well as the challenges biopharma companies encounter as a result of regulations and a lack of trust by the public.
In Chapters 7 and 8, we discuss approaches to engage with payers on a more strategic (versus transactional) basis, including understanding the needs of various payers and the patient populations they serve. We also develop drug pricing concepts, including novel risk-sharing pricing structures that can be based either on financial or clinical outcomes.
Chapter 9 covers digital health trends among patients and physicians and how digital technologies are impacting the biopharma value chain as well as digital strategies being deployed by biopharma and health systems. Finally, Chapter 10 addresses the data analytic core competencies that companies will need to develop in order to access and extract value from the data that surrounds the product during both development and commercialization.
Leading the biopharmaceutical enterprise is becoming a more complex proposition because of changing market dynamics, including the growing power of the patient and the emergence of increasingly powerful and accessible digital technologies. This book is intended to highlight these changes and help students, prospective entrepreneurs, and management teams identify both the risks and the opportunities that come from operating in the Digital Age.
Research Methodology
The research material for this book was derived from a variety of public and private sources including peer-reviewed and industry journals, media reports, and financial databases. This research and analysis were supplemented though qualitative interviews conducted over a two-year period with over 150 industry and academic experts, biopharma and infotech executives across research and commercial functions, venture capitalists, and public and private payers.
Acknowledgments
This book is based on several years of research, and it is also a field study of biopharma strategy through the value chain, including many executive interviews and company case studies. We benefited as well from management seminars and academic executive programs that allowed us to test our models and concepts.
A global network of academic and industry leaders brought great value to our book. At the risk of overlooking several, we first note the experts and executives who contributed thoughtful comments and case studies: Philip Kotler, whose seminal work in healthcare strategy inspired us, and Charlotte Sibley (former SVP, Shire), who generously provided in-depth reviews and expert insights throughout our book; Olivier Brandicourt (Board Member, PhRMA), Roch Doliveux (former CEO, UCB), Wendy Gabel (former VP, Biogen), and Bernard Poussot (Board Member, Roche) also provided valuable comments.
John Maraganore (CEO Alnylam), Michael Pehl (President, Hematology and Oncology, Celgene), and Jacqualyn Fouse (Executive Chair, Dermavant and retired President and COO, Celgene), as well as Emmanuel Blin (former SVP, Bristol-Myers Squibb) contributed company case studies.
In Europe, we benefited from a case study from Maryvonne Hiance, Dominique Costantini, and Emile Loria at OSE Immunotherapeutics, and thoughtful reviews and insights from Philippe Latapie, François Meurgey, and Catherine Parisot.
Françoise Simon would also like to extend her appreciation to her academic colleagues: At the Icahn School of Medicine at Mount Sinai, Dean Dennis Charney; Annetine Gelijns, Professor and System Chair, Population Health Science and Policy; and Senior Associate Dean, Brian Nickerson, for their support, and Dr. Bruce Darrow, Mount Sinai Chief Medical Information Officer, for his technology expertise.
At Columbia, Françoise Simon would like to acknowledge Deans Linda Fried at the Mailman School of Public Health and Glenn Hubbard at the Business School, and she thanks Professors Kamel Jedidi, Don Lehmann, and Michael Sparer for their support, as well as Emerita Professor Marianne Legato for sharing her expertise in gender-based medicine; in Europe, she thanks Professors Nathalie Angelé-Halgand and Frantz Rowe at the Université de Nantes, Martine Bellanger at EHESP, Claire Champenois at Audencia, Pierre Lévy at Université Paris-Dauphine, and Christine Coisne and Loïc Menvielle at EDHEC for providing an academic testing ground for the book.
At INSEAD, Françoise Simon also thanks Professor Stephen Chick and Research Program Manager Ridhima Aggarwal for the use of the PatientsLikeMe case, which she co-wrote with them and excerpted in the book.
Both authors give a special acknowledgement to Ellen Licking, Senior Life Sciences Analyst at EY, for her insights, her network and for her research and editorial contributions. Ellen worked with great dedication to advance the research for the entire book, with particular emphasis on the following areas: precision medicine, data analytics, new pricing models, and strategic payer engagement.
In addition to Ellen, Glen Giovannetti would like to thank many colleagues at EY including Global Life Sciences Sector Leader Pamela Spence, Susan Garfield, Kristin Pothier, and Ryan Juntado for their contributed articles. EY Life Sciences specialists Jeff Greene, Scott Palmer, Mahala Burn, Alan Kalton, Todd Skrinar, Jamie Hintlian, and Adlai Goldberg also provided invaluable insights. Melanie Senior, a life sciences writer and analyst, provided support for the precision medicine and payer engagement sections of the book. Jason Hillenbach and Rajni Sadana ably led a research team who also provided support for many of the figures in the book, and Angela Kyn provided marketing support.
Finally, we would like to thank our publisher, John Wiley & Sons, and our editor, Bob Esposito, and Editorial Director, Justin Jeffryes, for their expert guidance through our book.
About the Authors
Françoise Simon
Françoise Simon is a Professor Emerita at Columbia University and Senior Faculty at the Icahn School of Medicine at Mount Sinai. She also manages her own international consulting group. Her teaching focuses on executive programs and won her the Chandler Award for Commitment to Excellence from the Columbia Business School.
Dr. Simon has more than thirty years of experience in consulting and marketing management in the Americas, Europe, Asia, and Africa. Her clients include many Fortune 500 companies as well as new venture firms, several governments, and the United Nations.
Prior to joining the Columbia faculty, Dr. Simon was a Director of Arthur D. Little, and developed a global strategy practice serving clients in the Americas, Europe, and Asia.
Previously, Dr. Simon was a Principal of Ernst & Young, where she led a strategy practice in the health and consumer industries in the United States and Europe. Her corporate experience includes an appointment as New Product Manager in International Diagnostics for Abbott (now Abbvie) in Chicago. Prior to that, she was a Marketing Development Manager for Novartis in Switzerland.
Dr. Simon holds an MBA from Northwestern University and a PhD from Yale University. She has held faculty positions at the University of Chicago and New York University, as well as Columbia University and the Icahn School of Medicine at Mount Sinai.
She has published more than twenty articles and conducted more than 200 management seminars in the Americas, Europe, Asia, and Africa. She is the co-author of Building Global Biobrands: Taking Biotechnology to Market, with Philip Kotler (Free Press, 2003), Winning Strategies for the New Latin Markets, with Fernando Robles and Jerry Haar (Prentice-Hall, 2002), and Europe and Latin America in the World Economy with Susan Kaufman Purcell (Rienner, 1995). She is a past Vice President and Director of the American Marketing Association, and has served on the International Council of the American Management Association.
Dr. Simon has also served as a member of the Council on Foreign Relations.
Glen Giovannetti
Glen Giovannetti is a Partner at Ernst & Young LLP and the EY Global Biotechnology Leader. He has more than 25 years of experience serving clients in the biopharmaceutical industry, primarily in Silicon Valley and Boston. He has extensive experience in assisting clients from start-ups to market leaders around issues of growth, global expansion, and strategic transactions including initial public offerings, R&D collaborations, and acquisitions.
Glen has led the development of the EY Biotechnology Annual Report, Beyond Borders, for more than a decade. He is a past member of the Board of Directors of the Biotechnology Innovation Organization and a member of the Board of Directors of Life Sciences Cures. Glen has a BA in Accounting from Linfield College, where he is also a member of the Board of Trustees, and is a Certified Public Accountant in California and Massachusetts.
Part 1New Models for Networked Innovation
Chapter 1Digital Evolution of Biotechnology
For nearly four decades, biotechnology has driven the transformation of many sectors, from healthcare to food and energy, and it has grown into a global industry. It is now being transformed itself by its convergence with information technology (infotech). Biotechnology has been defined as “the use of living systems or molecular engineering to create and manufacture biologic therapies and products for patient care” [1], but it can be more broadly seen as the application of molecular biology across industries.
From the start, biotechnology grew together with other sciences. A first inflection point, Watson and Crick's 1953 discovery of the structure of DNA, depended on the development of X-ray crystallography by Franklin and Wilkins. By 1986, the first automated gene sequencer by Hunkapiller at Applied Biosystems supported Venter's National Institutes of Health (NIH) research, and a later-generation ABI sequencer, introduced in 1998, further enabled his research at Celera. This led to a second inflection point, in 2000, with the draft of the human genome by Celera and the Human Genome Project. The synergy between computing and bioscience continued with the emergence of bioinformatics and the 2003 launch of IBM's Blue Gene supercomputer, with a focus on structural proteomics.
Another technology has evolved over the past three decades, supported by the optimization of gene sequencing: CRISPR (clustered regularly interspaced short palindromic repeats). This nucleotide sequence was first identified in Japan in 1987, but it took decades to define its function as a molecular scalpel and an RNA guide capable of editing genes. By 2007, it was shown that spacer DNA could alter microbial resistance, and by 2012, a team including Doudna and Charpentier showed that a simpler CRISPR system relying on the Cas9 protein could work as an editing tool in human cell culture. In 2014, Platt used a Cas9 mouse to model lung adenocarcinoma. CRISPR may be first developed for monogenic diseases such as beta thalassemia, but challenges include safety (avoiding activity in unintended parts of the genome), delivery (via methods such as lipid-based nanoparticles or virus-based particles) and manufacturing [2].
Unlike computing, bioscience has not progressed in linear fashion, due to the inherent risk of working with animal and human biology. After the 1953 discovery of the DNA structure, it took 29 years for the launch of the first recombinant human insulin, discovered by Genentech and licensed to Eli Lilly. Monoclonal antibodies, developed by Köhler and Milstein in 1975, were not marketed until the introduction of IDEC's Rituxan (rituximab) in 1998, after several failed attempts by firms such as Hybritech.
Similarly, the first genotype-specific oral therapy, Novartis's Gleevec (imatinib) for Philadelphia—positive chronic myeloid leukemia, was approved in the United States, Europe, and Japan in 2001, but it took decades to develop it; the abnormal Bcr-Abl gene coding for tyrosine kinase, stimulating leukemia cell growth, was identified in 1985, and the molecule was first synthesized in 1992 (Figure 1-1).
Figure 1-1 Biotechnology milestones
Industry Applications
Today, biotechnology has matured and is driving innovation across sectors, from medicine and food to agriculture and biomaterials (Figure 1-2):
In healthcare,
red biotech
has led to novel biologic therapeutics, including recombinant proteins such as insulin and growth hormone, monoclonal antibodies such as Genentech's Herceptin (trastuzumab) for HER2-positive breast cancer, vaccines, molecular diagnostics, gene and stem cell therapy, tissue engineering, and regenerative medicine.
In food and agriculture,
green biotech
has improved crop efficiency and used bioremediation for environmental reclamation. It has blurred the distinction between food and medicine, with the emergence of medical foods and innovations such as a strain of “golden rice” yielding provitamin A [3].
Marine biology has led to
blue biotech
, with food products and ingredients derived from algae, invertebrates, and fish; diagnostic agents such as fluorescent reporter protein; and marine extract additives in cosmetics.
In industrial processes,
white biotechnology
has produced biodegradable plastics, renewable chemicals, pollution-eating bacteria, and advanced biofuels [4].
Figure 1-2 Biotechnology across industries
The following chapters will focus on red biotech, including the transformational impact of digital technologies and the convergence with infotech. A new form of digital convergence has emerged, which presents both an opportunity and a threat for the biopharmaceutical sector. From mobile devices, such as the Fitbit wristband biosensor, to R & D analytics tools such as IBM's Watson, infotech companies are playing a key role in meeting consumer and researcher communication needs.
Impact of Megatrends
Multiple trends are disrupting business models and leading the industry to define value differently. For consumers, longer life spans are increasing the incidence of chronic conditions such as diabetes and heart disease, across developed and also emerging markets, driving demand as incomes rise. However, this is also placing manufacturers on a collision course with resource-constrained payers, who are increasingly defining value in terms of outcomes achieved by new therapies. For researchers, postgenomic science is driving precision medicine, which has already yielded a new wave of targeted therapies but is struggling to handle an explosion of data: at the individual level, “small data” from biosensors, monitors, smartphones, and smartwatches; at the population level, “big data” from genomic, clinical trial, and insurer databases. These conflicting trends have led to a disconnect within the biopharma space.
Consumer-generated health data need professional interpretation, which medical offices largely cannot provide online due to liability and reimbursement issues and which cannot be transmitted to most hospital electronic health records (EHRs). Researchers now access an overwhelming amount of health data, well beyond clinical trial databases, which has led to the entry of information technology leaders into healthcare. Apple is partnering with the Mayo Clinic with its HealthKit and ResearchKit software that links patients, physicians, and EHRs. IBM aims to streamline R & D with its Watson Health unit and has made significant acquisitions in data analytics, including Explorys, Phytel, and Merge. Alphabet is partnering through its Verily unit with Sanofi, Dexcom, and Medtronic in diabetes, and in 2013 it launched Calico, a biotech company focused on longevity. Qualcomm and Novartis have set up the dRx Capital joint venture to invest in digital startups and optimize clinical trials. The interaction of these transforming forces is summarized in Figure 1-3.
Figure 1-3 Transforming forces
Digital Health Opportunities
From research to postmarketing surveillance, digital health has the potential to greatly improve R & D and manufacturing efficiency, as well as product co-creation and communication with patients:
In R & D, digital health can optimize diagnostics through integrated biomarkers, increase speed to market, and streamline data analytics.
In manufacturing, digital technology can adapt processes to reduce costs.
From a regulatory and reimbursement standpoint, it can enable real-time drug monitoring and support health economics dossiers with real-world evidence.
At the commercial end, digital health can allow deep integration of the customer voice, from drug co-creation to postlaunch communications, and it can help collect real-world evidence to support economics dossiers (
Figure 1-4
).
Figure 1-4 Impact of digital solutions on the value chain
Infotechnology Initiatives in Healthcare
The health sector has been slower than other industries such as banking and retail to adopt digital technology, due to regulation, physician concerns about liability and reimbursement, and upfront costs and resistance to changing workflows, as well as consumer concerns about data security and privacy.
By contrast, infotechs have entered this space rapidly, for various reasons. Companies such as IBM may grow their businesses by addressing large database interpretation problems that require platform technologies such as Watson. Consumer-focused firms such as Apple are responding to market demand for online healthcare information by adding health apps on their mobile devices.
While infotech leaders are reluctant to become directly involved in healthcare due to the heavy burden of regulation and long development cycles, they still have the potential to disrupt the sector, for instance, if digital interventions prove more effective than some drug therapies. To support their healthcare penetration, infotechs have the added advantage of massive resources. Apple's market capitalization passed $800 billion by May 2017, well above that of Johnson & Johnson, which led biopharmas at nearly $346 billion at the same time. A key advantage for Apple is its brand value among consumers. Alphabet combines advertising revenue from Google with strong gains in mobile search, and infotech growth, in general, is driven by the rise of the cloud, that is, the shift of many computing operations to online services [5].
As mobile health (mHealth) comes to dominate the sector, through the fast growth of mobile devices versus PCs or laptops, infotechs play a key role in all of its aspects. As defined by the World Health Organization (WHO), mHealth is “medical and public health practice supported by mobile devices such as mobile phones, patient monitoring devices, personal digital assistants and other wireless devices” [6]. At the consumer end, infotech provides hardware and software from biosensors and smartphones and also enables real-time interactions via social media. At the research end, infotech aims to optimize predictive analytics to gain deeper insights into the origin of diseases, diagnostics, and treatments.
A hybrid category of mHealth includes Food and Drug Administration (FDA)-approved medical devices such as WellDoc's BlueStar to measure glucose levels and AliveCor's mobile electrocardiogram machine. More broadly, Apple's HealthKit and ResearchKit aim to address the current lack of interoperability by linking consumer biomarkers with medical offices and EHRs (Figure 1-5).
Figure 1-5 Digital health landscape
Disruption Risk from Infotech
In addition to opportunities, the rising dominance of infotechs in healthcare may pose significant risks for biopharmas. What makes their convergence uncertain is the significant variance between the business models of biopharmas, device companies, and technology firms:
R & D is profoundly different in the biology and engineering cultures, where biotech timeframes may span 10 years, in contrast to the rapid cycle times and iterations for technology products. Firms such as Apple may release new or upgraded products twice a year.
Success metrics also vary: in biopharma they are rigidly defined by FDA-validated safety and efficacy, whereas in technology they are driven by network effects and viral diffusion.
As patients manage more of their healthcare, companies such as Apple may be better positioned to own the consumer relationship. In addition, with the rising role of social media such as the PatientsLikeMe website, conducting member-driven observational trials, biopharmas may lose partial control of clinical data and cannot interactively join the online dialogue with product messages, due to regulatory restrictions.
Economic models are just as divergent, as drugs and devices depend on public or private payer reimbursement, with some consumer copays, whereas tech products rely on direct selling through app fees, licenses, or subscriptions, or indirect selling such as advertising revenue from search engines (Figure 1-6).
Figure 1-6 Business model variance
Another nontrivial barrier to the convergence trend is a different cultural attitude toward risk. Silicon Valley, unlike Big Pharma, has an inherent tolerance for risk. Risk itself is also increased by the digitization of healthcare. In addition to the extreme product attrition seen in biopharma R & D, the cloud-based diffusion of data may pose significant security problems. A study of 1,000 US consumers showed that 43 percent were not comfortable with sharing their personal data online [7], and this trend is reinforced by recurring media exposure of security breaches. In 2015, Anthem, the second-largest US health insurer, revealed that its records had been compromised by hackers, posing a potential risk for Social Security numbers and employment data for up to 80 million past and present members [8]. In addition, Silicon Valley has so far remained wary of health regulators. Devices such as the Apple Watch are not therapeutic and are therefore seen by the FDA as wellness-related and not subject to its regulation.
Because a convergent business model has yet to emerge, the following questions for infotech companies entering the health space are worth considering:
Product or service
: Is it a wellness support tool like the Fitbit wristband sensor, a medical device like the BlueStar glucose monitor, or a true therapeutic product?
Validation:
What is required, from randomized clinical trials to user acceptance?
Technology:
Does the product include hardware (smartphones), software (apps), and/or cloud-based analytics platforms? What information is transmitted, from small data (individual biomarkers) to big data (population-level genomics)?
Customer/end user:
Who is the customer? For wellness tools, it is primarily the consumer. For medical devices, there are hybrid targets (patients or physicians). For researchers, analytics platforms reflect the greatest need.
Economics:
Will revenue come from payer reimbursement, patient copays, or full out-of-pocket consumer expenditure [9]?
Technology Strategies
Rise and Limitations of Wearables
According to Forrester Research, the average US online adult uses more than four connected devices (from desktops to tablets and eBook readers), 70 percent use a smartphone, and this usage cuts across age groups, from Millennials (born 1981 to 1997) to Boomers (born 1945 to 1964). However, the generation gap is evident for wearables, with usage by 34 percent of Millennials versus only 7 to 11 percent of Boomers [10]. This may be linked to the limited functionality of apps: While their number exceeds 165,000, from Apple iTunes and Google Play (Android), most are only wellness tools, and less than a quarter focus on disease and treatment management. Over half of apps have low functionality, such as simply providing information.
A major barrier to true “scientific wellness,” including data analysis by healthcare professionals, remains the lack of interoperability, with only 2 percent of apps linking patients to physicians and healthcare systems. Other adoption barriers are a lack of scientific evidence, limited reimbursement, and privacy and security [11].
The mHealth sector is beginning to evolve from consumer gadgets to prescribed devices, but full integration into EHRs is so far confined to a few pilot programs (Figure 1-7). Despite these limitations, infotech-enabled innovations are being introduced by players of all sizes, from startups to multinationals.
Figure 1-7 Evolution of mHealth
New Entrants
WellDoc was first to launch an FDA-approved, physician-prescribed, and payer-reimbursed mobile medical device. Its BlueStar software for continuous glucose monitoring (CGM) was validated with a randomized trial of more than 150 patients, showing a capacity to reduce glycated hemoglobin, that was published in Diabetes Care in 2011. FDA clearance via a 510(k) submission supported reimbursement, and WellDoc was able to raise funding from sources such as Merck.
AliveCor, founded in 2010, adopted a hybrid model. While its mobile electrocardiogram (ECG) device was also FDA approved and validated by trials, including those of the Cleveland Clinic, it is marketed online directly to consumers, without a prescription. It can also be sold to physicians, with reimbursement for point-of-care use [12].
Proteus Digital Health innovated in a different way, as it gained in 2012 the first FDA clearance for a medication adherence function for its Ingestible Sensor, a capsule that records and sends to a smartphone the time of ingestion, activity, and heart rate. The adherence indication requires a new drug application filing, but its potential market is significant, as up to half of patients may not be compliant. The company is working with Otsuka to use its sensor with the psychiatric drug Abilify (aripiprazole). Proteus also plans to target common conditions such as cardiometabolic syndrome and high-value drugs such as those for hepatitis C [13].
On a larger scale, Dexcom competes with Medtronic in diabetes, a condition that affects a 29 million population in the United States alone, with estimated direct medical costs of $176 billion and indirect costs of $69 billion, according to the US Department of Health and Human Services. In April 2015, Dexcom announced that its Platinum glucose sensor would be linked to the Apple Watch, to be followed by an integration with Android platforms.
An advantage Medtronic has over Dexcom is that it is the only firm with both a CGM device and an insulin pump. Its MiniMed Connect device was cleared by the FDA in June 2015. Medtronic is also partnering with Samsung to allow CGM and pump data on Samsung devices [14].
Big Infotech Strategies
Technology leaders have entered healthcare with different strategies that reflect their core strengths. Apple remains focused on consumers, whereas Qualcomm and IBM are expanding within a business-to-business (B to B) perspective, and Alphabet may be seen as a holding company with a broad portfolio, from its core Google search engine to biotech Calico.
Apple: Building a Consumer Ecosystem
Apple has become the world's most valued company, with 2016 revenues of nearly $215.6 billion, gained through innovation-driven growth and a role as a category maker. In the same way that it redefined digital music with iTunes, it broke new ground in mobile devices, from the iPod to the iPhone and the iPad, while spending vastly less on R & D than biopharma companies. This is linked to Apple's talent for perfecting through superior design and bringing to the mainstream existing products: MP3 players before the iPod, smartphones before the iPhone, and tablet computers before the iPad.
The power of the brand is such that the “killer app” may be the Apple name itself; in the first 24 hours after the Apple Watch launch, sales reached 1 million devices, and within a few weeks, developers had introduced more than 3,500 apps for it [15].
Apple retains in healthcare its consistent overall strategy: focus on a limited number of products, target the high end of the market, and keep building the Apple brand equity.
As Michael O'Reilly at Apple mentions, “we are committed to making great consumer products with great user experience in the marketplace” [16]. Apple's consumer focus is also apparent in the fact that, after consultation with the FDA, the agency considered the Apple Watch as a wellness tool not subject to regulation. It may now move toward more medical applications, as it is increasingly used in clinical trials. In this context, infotech companies may need to play a future role in screening third-party apps, and data security remains key. Health data collected on Apple devices will not be stored on servers, but instead on IBM's Watson Health cloud, where it will be de-identified and stored for data mining and predictive analytics.
Together, the HealthKit, ResearchKit, and the Apple Watch are meant to constitute a continuous learning environment, linking individual data to health systems.
From Apple to Epic: The Road to Data Integration
HealthKit evolved as Apple realized that, with the proliferation of healthcare apps, different apps did not communicate with each other. For this iOS framework introduced as a wellness tool, Apple first formed a partnership with the Mayo Clinic, followed by other health systems, including integration with the Epic EHRs.
The follow-up ResearchKit aims to turn the iPhone into a medical tool helping physicians and scientists gather patient data more frequently and accurately. With it, trial participants can access an interactive consent process, complete active tasks, and submit survey responses. With user permission, researchers can access biomarkers and gain insights on mobility, motor impairment, speech, and memory.
GlucoSuccess, one of the five initial apps, prompts users to log their finger-stick blood glucose levels, and gives visual and text summaries. The app can determine a patient subset whose glucose is more responsive to exercise and can even track the impact of time of day for exercise. This has a potential for biopharma disruption, as exercise could bypass drugs for prediabetes cases, for instance.
Other projects include, in dermatology, a study at Oregon Health and Science University on iPhone images to measure moles over time and allow globally collected data to help create new detection algorithms.
The Apple Watch links to ResearchKit. The EpiWatch app from Johns Hopkins will test whether biosensors can detect the onset and duration of epileptic seizures, capture their digital signature through activity and heart rate data, and send an alert to caregivers. The app also aims to track medication adherence and side effects. In addition, the CareKit now allows developers to build apps to track symptoms and monitor treatment effectiveness, facilitate medical dosing, and permit patients to share data with family members and providers [17].
While ResearchKit is already used by leading health systems, some issues remain. Monetization is not one of them, however, as Apple views it largely in philanthropic terms and does not have proprietary claims to the related apps, because it was released as an open-source platform.
Portability to Android and other platforms will need to occur through third-party developers. Selection bias exists in two ways: the relatively upscale iOS demographics versus those of Android users (who are more numerous, especially outside of the United States) and the “active/take-charge” behavior profile of customers. While the Apple Watch may lead to higher user engagement, it still has a fairly limited worldwide market. Misrepresentation may also pose a problem, as is the case for all social media. ResearchKit participants may disguise their gender, age, or medical condition. This may be addressed through patient identification by physicians in clinical trials.
What remains to be seen is whether these mobile devices can actually impact outcomes, and whether there is enough user incentivization for them to graduate from niche to mainstream products. Will consumers worldwide want to diligently monitor their health, or will many wearables sit on shelves after novelty fatigue, information overload, privacy concerns, and lack of time prevail over health activism?
Qualcomm: From Chips to Health Ventures
Within an overall strategy of “end-to-end two-way connectivity,” Qualcomm Ventures has made investments in companies as diverse as Fitbit, AliveCor, AirStrip Technologies, Telcare (disease management), Sotera (wireless telemetry), and ClearCare (mobile platforms for home care providers).
In healthcare, Qualcomm is in three lines of business:
Venture investments:
Through the Life Fund and the dRx Capital Fund, a joint venture with Novartis with a capital commitment of up to $100 million, for early stage investments in companies including Omada Health (digital behavioral medicine), Science 37 (clinical research) and Cala Health (bioelectronics to develop therapies in neurology).
Platforms:
With its 2net system (acting as middleware between patient and claims data, and healthcare professionals), and the HealthyCircles care coordination platform, monitoring a patient's status at home and optimizing care management.
Licensing and acquisitions:
Among others, Qualcomm Life acquired Capsule Technologie, a French provider of medical integration, with more than 1,930 hospital clients in over 38 countries. This supports an extension into acute and ambulatory care, with the goal of leading to the Internet of Medical Things (IoMT) for the company (
Figure 1-8
).
Figure 1-8 Qualcomm Life ecosystem
While, in its core chip business, Qualcomm competes directly with Intel, its technology overlaps that of other players such as Samsung. The company can be seen as a technology enabler rather than a business-to-consumer (B to C) player [18].
IBM: From Hardware to Software and Cloud Services
IBM first formalized its healthcare involvement with the Life Sciences Solutions unit it formed in 2000 and its early partnerships with Spotfire and Agilent in data management and MDS in proteomics. These complemented IBM's long-term development of its Blue Gene computer and academic collaborations with universities including Duke, Georgia Tech, and Johns Hopkins [19].
Since then, IBM has continued to evolve from a horizontal technology company to one delivering comprehensive vertical solutions. This is shown by extensive acquisitions and partnerships, from Apple to Medtronic, and the introduction in April 2015 of its Watson Health unit, with its own budget and R & D.
Through the Watson ecosystem, IBM may provide B to B to C solutions, aggregating clinical and claims data at the population health level and from the medical literature, and combining them with individual genomic data to support precision medicine. Within IBM, distinct groups also cover health systems and biopharmaceuticals [20]. Watson Health leverages broad datasets, including 100 million electronic health records, 200 million claims records, and 30 billion medical images. Watson for Genomics absorbs 10,000 new medical articles and data from 100 trials every month, and it is available through Quest Diagnostics to oncologists in the United States.
Current strategic objectives are the management of data (which IBM views as the world's new “natural resource”), cloud computing, and customer engagement through mobile and social technologies. IBM has made multiple acquisitions to build its capacity in data analytics. This includes the acquisitions of Explorys (spun off in 2009 from the Cleveland Clinic), Phytel (with cloud software for hospital data), and Merge Healthcare in October 2015 for $1 billion (in radiology and imaging services), as well as Truven in 2016 (analytic solutions for healthcare utilization, quality, and cost data).
For cloud services, which IBM sees as a “catalyst for innovation,” the company has invested more than $8 billion to acquire 18 companies [21]. To expand its global footprint, the company has been partnering with many others across countries.
Apple and IBM in Japan
In April 2015, the two companies announced a collaboration with Japan Post group, the largest health and life insurer in Japan, to deliver iPads with IBM-developed apps to an intended target group of 4 to 5 million seniors by 2020. Japan has one of the world's fastest-aging populations, with 33 million seniors accounting for a quarter of the population, and a projected growth of 40 percent over the next 40 years. Custom-built IBM apps include exercise and medication reminders, access to community activities, and supporting services, with data stored by the cloud services of the IBM MobileFirst for iOS platform [22].
