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Managing Biotechnology: From Science to Market in the Digital Age

Managing Biotechnology: From Science to Market in the Digital Age PDF

Author: Francoise Simon and Glen Giovannetti

Publisher: Wiley


Publish Date: October 2, 2017

ISBN-10: 1119216176

Pages: 296

File Type: Epub

Language: English

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Book 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.

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