Elsevier

Research Policy

Volume 36, Issue 4, May 2007, Pages 566-589
Research Policy

The myth of the biotech revolution: An assessment of technological, clinical and organisational change

https://doi.org/10.1016/j.respol.2007.02.013Get rights and content

Abstract

This paper argues that despite being widely promoted by academics and consultants, the empirical evidence does not support the existence of a biotech revolution. Nor does the data support the widely held expectations that biotechnology is having a revolutionary impact on healthcare or economic development. The revolutionary model is therefore a misleading basis for policy making as it over-estimates the speed and extent of any changes in productivity or the quality of therapeutics. Instead, the evidence suggests biotechnology is following a well-established incremental pattern of technological change and ‘creative accumulation’ that builds upon, rather than disrupts, previous drug development heuristics.

Introduction

The aim of this paper is to inform policy by extending previous critiques of the revolutionary model of technological change currently used to understand medicinal biotechnology (e.g. Arundel and Mintzes, 2004, Nightingale and Martin, 2004, Hopkins et al., 2006a).1 It suggests that a more appropriate framework for policymaking is needed that is more realistic about the incremental nature of major technological changes.

Such a rethink is required because academics, policy makers, consultants and industrialists have promoted a model of technological change in which drug innovation is being revolutionised by biotechnology.2 The diffusion of this revolutionary model into public thinking has generated widespread, but also very diverse, expectations of biotechnology's impact. These include expectations that biotechnology is transforming pharmaceutical innovation by increasing the number and the effectiveness of drugs and diagnostics, and expectations that it is shifting traditional reactive medicine towards more preventative interventions involving increasingly personalised therapies (Bell, 1998, Collins et al., 1998, Lenaghan, 1998, Lindpaintner, 2002, Department of Health, 2003). The biotech revolution is also supposed to be generating significant wealth by improving the productivity of pharmaceutical innovation, and driving a related shift in industrial structure as networks of biotechnology firms, often agglomerated in regional clusters, displace the large drug companies that have previously dominated the sector (DTI, 1999, Enriquez and Goldberg, 2000, Tollman et al., 2001).

These expectations have led to annual investments of tens of billions of dollars of private investment in biotechnology (Ernst and Young, 2004, Gassmann et al., 2004) together with substantial public investment as government agencies at the regional, national and supra-national levels attempt to establish a foothold in what is seen as a key part of the Knowledge Economy (DTI, 2001, Dohse, 2000, Giesecke, 2000, Senker et al., 2000). As a result, all OECD members’ national and regional development plans and science and technology policies involve biotechnology.3

These initiatives take a number of forms, including dedicated research funding programmes, fostering knowledge/technology transfer and networking between university researchers and industry, financial and technical support for start-up firms and regional clusters, R&D tax credits, lower regulatory hurdles, a focus on funding directly applicable research, and changes to the relationship between health services and industry to allow easier clinical trials and earlier access to advanced drugs (DTI, 2001, Senker et al., 2000, Dohse, 2000, Giesecke, 2000, BIGT, 2003).

The questions this paper addresses are: Is there evidence for the revolutionary model of technological change underpinning this transformation of policy? Is the biotech revolution real or is it a myth? And, if it is real, what form is it taking?

The reason that these questions need to be raised is that there are contradictions and inconsistencies in the various expectations of the revolutionary model's impact. While the revolutionary model is widely accepted by social scientists and policy-makers, those in the pharmaceutical industry, in the financial community, and some regulators see a more complex and troubling picture. The FDA, for example, has noted that:

Today's revolution in biomedical science has raised new hope for the prevention, treatment, and cure of serious illnesses. However, there is growing concern that many of the new basic science discoveries that have been made in recent years may not quickly yield more effective, more affordable, and safe medical products for patients. This is because the current medical product development path is becoming increasingly challenging, inefficient, and costly. During the last several years, the number of new drug and biologic applications submitted to FDA has declined significantly; the number of innovative medical device applications has also decreased. The costs of product development have soared over the last decade. (FDA, 2004: i).

In this paper, we present a detailed examination of the evidence for a biotechnology-driven revolution in drug innovation by updating and contextualising previous sceptical accounts.4 In summary, the evidence shows that in moving from the sciences towards the clinic, evidence for a biotechnology revolution rapidly diminishes and the technology increasingly follows a well-established historical pattern of slow and incremental change. The translation of advances in bioscience into new technology is far more difficult, costly and time-consuming than many policy-makers believe. Our analysis will hopefully alert the reader to the deficiencies of the revolutionary model and induce some of its more evangelical proponents to reconsider their positions.

To explore the diverse expectations of biotechnology outlined above, this paper examines evidence from a range of biomedical settings. We begin in Section 2 by placing biotechnology in its historical context. In the following sections, we assess the evidence for a biotechnology revolution in three areas where discussion of revolutionary change has been prevalent. Section 3 analyses advances in drug discovery. Section 4 focuses on changes in drug development. Section 5 surveys changes further downstream, brought about in the clinic as a result of the diffusion of biotechnology-derived drugs. In each section, we explore the empirical evidence for a biotechnology-driven revolution, using both quantitative and qualitative indicators of change, and examine the scope (how different?), scale (how much? how widespread?) and, where relevant, the speed (how rapid?) of change. In Section 6, we briefly reflect on structural changes within the industry and the co-evolution of biotechnology and pharmaceutical firms in a period of declining pharmaceutical productivity. In Section 7, we critically assess the evidence and discuss policy implications.

Section snippets

Biotechnology: the historical context

New drugs are generated within path-dependent socio-technical systems based on high-level heuristics and hierarchies of interconnected operational principles that structure the way problems are solved (Martin, 1998, Nightingale, 2000). The pharmaceutical industry has relied on a series of heuristics that have been associated with different waves of products over the past two centuries, with each one leading to the development of new social networks (ibid; Galambos and Sewell, 1995, Galambos and

The scope of change in drug discovery

Drug discovery is the process of creating chemical or biological molecules that have the potential to be developed as therapeutic agents, typically because they generate a desired biological effect in an appropriate testing or assay system against a particular molecular (drug) target. Biotechnology has had a profound effect on drug discovery through the development of increasing numbers of research tools for both small-molecule drugs and new biopharmaceuticals. This is depicted in Fig. 1, which

The scope of change in drug development

Drug development is the period of R&D from when a drug prototype enters pre-clinical testing to the time when it is approved by the regulatory authorities (FDA, 2004).18

The scope of change in clinical practice

So far, we have established that while biotechnology has substantially increased the number of drug targets, for the most part these are still being assessed in clinical trials or preclinical testing. Biotechnology, particularly the HGP and Genomics, also promised the rapid development of genetic tests to predict and prevent disease by supporting early interventions, and more optimal or targeted use of therapies (pharmacogenetics) (Cantor, 1992, Gilbert, 1992, Hood, 1992, Department of Health,

The impact of biotechnology on industrial structure

Since the early 1980s a very large and well-financed global biotechnology sector has developed, growing from just a few dozen pioneers in 1980 to nearly 300 biotech firms in the US alone by 1988 (OTA, 1991, Robbins-Roth, 2000). Investor enthusiasm has lead this population to grow to an estimated 4000–5000 businesses globally (Ernst and Young, 2004). The sector raised an estimated $80 billion in the five years to 2004, with $18 billion invested during 2003 in North America and Europe alone (

Assessing the impact of biotechnology

Having reviewed the data we are now in a position to assess the impact of biotechnology on drug discovery, drug development and clinical practice. The substantial impact of biotechnology on drug discovery has to be understood in the context of a number of important industry trends, including changing heuristics, the shift towards blockbuster products, and the ongoing decline in R&D productivity. Molecular biology techniques were initially applied to further extend the existing synthetic

Acknowledgements

The research in this paper was supported by the UK's Economic and Social Research Council and Medical Research Council under the Innovative Health Technologies Programme (Grant L218 25 2087) and the joint ESRC/MRC fellowship initiative (Grant PTA-037-27-0029). We are grateful for very insightful comments from anonymous referees, Anthony Arundel, Michael O’Neill, and Research Policy editors. Any remaining errors are our own.

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