abstract. Pharmaceuticals is the sector most widely thought to be in need of strong patent protection in order to sustain a robust level of innovative activity. This Feature comprehensively seeks to revise that assessment. It argues that a proper understanding of the actual informational resources at play in drugs reveals that pharmaceutical innovation can, significantly does, and entirely should proceed without any role played by patents.

The foundational plank of the argument is that innovation in pharmaceuticals consists of not one but two distinct information goods: (1) knowledge of a chemical or biological compound (the “compound information good”), and (2) knowledge of a compound’s safety and efficacy for use in humans, as validated by clinical-trial data (the “data information good”). It is the latter information good, not the former, that is both the driver of the economics in this sector and the apt focal point of innovation-policy rules. Indeed, a close examination of how the doctrines of patent law map onto the pipeline of pharmaceutical innovation reveals a set of radically sector-specific doctrines that confer little protection during the preclinical research that generates the compound information good, contrary to a common view. Meanwhile, for the clinical testing that generates the data information good, revised regulatory-exclusivity rules can and entirely should suffice. Indeed, the protection presently afforded this good by patents is indirect, incomplete, and—owing to a basic misalignment between the patent system’s focus and sensible aims for innovation policy in this sector—haphazard and highly costly.

Consequently, simply by phasing out patent protection for drugs and replacing it with a revised form of regulatory exclusivity, we would reap large gains in social welfare: better-tailored incentives, reduced access and duplication costs, and significantly curbed wastes from gaming of the present system. Many of these costs stem from “evergreening” practices and “me-too” drugs, which have both been the subject of sharp criticism. The present analysis offers a deeper diagnosis of the causes and extent of these problems, and it proposes more effective, better-tailored solutions.

This same analysis should also reorient broader debates in patent theory and innovation policy more generally by revising our understanding of the special case posed by drugs for innovation-policy support. The conventional view that pharma presents an especially strong case for patent protection turns out to be triply wrong. First, the innovation taking pride of place in judicial and scholarly attention—the compound information good—presents no special case for patents. Second, the innovation that does present a strong case for innovation-policy support—the data information good—is both sidelined by the patent system and in any case ill-suited for patent protection. Thus, the special case presented by pharma is not for patents but for an alternative innovation-policy intervention. Finally, the basis of that special case for innovation-policy support lies in a regulatory regime rather than in any generalizable economic or technological features of drugs.

author. Lecturer, University of California, Berkeley, School of Law. Thanks to Yochai Benkler, Oren Bracha, and Terry Fisher for invaluable comments on an earlier draft, and to Ken Ayotte, Colleen Chien, Seth Davis, Dhammika Dharmapala, Aaron Edlin, Mark Gergen, Katerina Linos, Peter Menell, Rob Merges, and Jonathan Simon for helpful discussion. For excellent research assistance, I thank Garreth McCrudden, Caressa Tsai, and Will Kirkland. I also wish to thank the editorial staff of the Yale Law Journal, in particular Deniz Arıtürk and Fred Halbhuber, for terrific comments that significantly improved the Feature. Research for this Feature was partly funded by a grant from the Institute for New Economic Thinking (INET), for which I am grateful.

Introduction

Does pharma need patents? The consensus view among scholars is a resounding “yes.” The pharmaceutical industry is widely agreed to be the sector most in need of strong patent protection to sustain a robust level of innovative activity.1 Study after study of the effects of patents on innovation—be they empirical surveys asking firms in different industries what they rely on to appropriate the benefits of innovation, historical studies of long-term patterns of innovation and patent protection, or synthetic theoretical-empirical treatments of the aggregate costs and benefits of the patent system as a whole—agree that, whatever other conclusions may be reached regarding the overall case for patent protection across the economy, such protection is crucial for innovation in drugs.2 This conviction holds not only for those most strongly endorsing the patent system as a whole,3 but also for those more uncertain about the overall merits of patents.4 Indeed, even the staunchest critics of the patent system in general accept that pharma remains a crucial exception.5

This Feature seeks to revisit that assessment comprehensively.6 It argues that a proper understanding of the actual informational resources at play in drugs reveals that pharmaceutical innovation can, considerably does, and entirely should proceed without any significant role played by patent protection.7 The foundational plank of the argument is to underline how innovation in pharmaceuticals consists of not one but two separate information goods: (1) knowledge of a new chemical or biological compound, and (2) knowledge of the safety and efficacy of that compound for use in humans, as validated by clinical trials.8 Moreover, not only is the latter information good a separate innovation from the former; it is one very distinct in its risk-cost profile, diverging sharply in those technical and economic features that are relevant to innovation-policy analysis. What these features reveal is that the first information good likely poses no stronger case for patent protection than innovation in most other sectors, while fitting quite well a model of decentralized, competitive development. Meanwhile, the second information good does require strong innovation-policy support, while fitting better a model of centrally coordinated development.

Two fundamental implications follow from this theoretical distinction. First, the distinction reveals a new understanding of existing patent practice in the pharmaceutical industry. Applying the insight of two information goods discloses a dramatically new picture of how patent and related laws map onto the pipeline of pharmaceutical innovation, including by revealing a set of highly sector-specific patent doctrines applicable only to pharma. The upshot of this picture is that patents provide only partial—and largely unnecessary—protection over the first information good, and indirect—and highly misaligned—protection over the second. Second, these explanatory implications of the distinction justify a deep reform of pharmaceutical innovation policy. A better innovation policy for this sector would be to phase out patents altogether and replace them with an alternative innovation-policy intervention, one better suited to the distinctive technological and economic features of the second information good: a revised system of “regulatory exclusivity.”9

At the heart of pharmaceutical innovation lie two information goods. The first is knowledge of a new drug product, which we may call the “compound information good.”10 The second is knowledge of that drug’s safety and efficacy for humans as evinced by clinical-trial data, which we may call the “data information good.”11 Generating the compound information good involves the exploration of a highly uncertain possibility frontier: each step involves many risks—only about one in a thousand candidate compounds make it through the drug-discovery phases of “search, synthesis, and screening” to enter clinical trials12—so as to warrant comparatively low expenditures per step.13 By contrast, generating the clinical information good is a comparatively low-risk, high-cost endeavor: roughly one out of five to ten drugs that enter clinical trials successfully navigate the process of testing and refinement to receive Food and Drug Administration (FDA) approval,14 while the costs of phase 1, 2, and 3 trials dwarf those of each step of preclinical drug discovery.15 This sharp divergence in the risk-cost profiles of these information goods carries two sets of crucial implications for their apt innovation-policy treatment.

First, from a purely economic point of view, it is the data information good—not the compound information good—that is the driver of the industry’s innovation costs. While the cost of drug development remains a topic of fierce controversy,16 what is not controversial is that clinical-trial expenditures comprise the lion’s share of the costs, running around 70% according to the industry’s own preferred studies,17 and even higher for others.18 Indeed, a 2021 metareview of twenty-two studies of drug-development costs conducted over the past four decades found that over half (thirteen) of the studies reviewed did not even consider preclinical drug-discovery expenditures significant enough to factor in as a part of total costs.19

In addition to their very different economic significance for pharmaceutical innovation, these information goods also sharply differ in the technological features of the respective innovation processes that generate them. Preclinical drug discovery, with its high risks and lower costs, is well suited for a decentralized search, where “many minds” are given free rein to explore various different avenues, even at the risk of a fair bit of overlapping, duplicative activity.20 Clinical trials, on the other hand, with their lower risks and high costs, are better suited for coordinated development to curb duplicative efforts that would be highly wasteful at this stage.21 In other words, preclinical research should be a nonexclusionary zone, to enable many-minded exploration unencumbered by proprietary barriers. Meanwhile, for clinical trials, some mechanism is needed to call off the innovation race at their outset.

Integrating these distinct economic and technological features of the two innovations leads to the following pair of conclusions. First, the compound information good—generation of new knowledge of a chemical or biological product or process—poses no special incentive case for patent protection. Its share of overall industry innovation costs is relatively modest. Further, what is the really relevant focus for innovation-policy analysis is the differential between its average innovation costs and risks and its average imitation costs and speed (i.e., the cost and time involved in reverse engineering and being ready to manufacture a new or improved drug product or process). And that differential is likely no greater than in many other sectors where a combination of first-mover advantages and secrecy suffice to ensure a relatively robust level of innovative activity.22 In addition, patents also serve no useful “coordinating” function during the research phase leading to the generation of the compound information good: its comparatively high risks and low costs make that phase suitable for a competitive, decentralized search.

Second, the data information good—generation of new clinical results on a drug—does present a strong case for an innovation-policy intervention, but it is one for which patents are a highly unsuitable instrument. That strong case stems not only from the large share of overall industry innovation costs taken up by this activity but also from—what is again the relevant focus—the large difference between its average costs and risks of generation and its average costs and speed of replication (with the latter massively reduced by regulatory permission of imitator piggybacking on innovator data).23 Yet the patent system provides little to no direct protection over this information good, as its doctrines center on the results of preclinical research, not clinical testing.24 And it is not only that patents currently sideline the protection of clinical data; they also cannot effectively provide such protection. Given the technological features of this innovation, it would be untenable to try to reform the patent system to protect it; inquiries into its desirability and validity are simply not ones that the patent system is well suited to carry out.25

Consequently, patents serve their two primary functions in pharmaceutical innovation—coordinating innovation races and incentivizing innovative activity—only indirectly, with respect to an information good, clinical data, that they do not directly protect.26 Meanwhile, for the information good that patents do directly cover—knowledge of the compound—they play little to no coordinating role and only a secondary incentive role.27 A sounder innovation policy would be to replace the primary, yet indirect, role played by patents over data information with a form of regulatory exclusivity that specifically attends to the distinctive features of this innovation, while at the same time phasing out the direct but secondary role patents play over compound information.

The point of doing so is to bring our system of innovation-policy rules into better alignment with the underlying innovations that they seek to generate. This alignment would ensure that the rules directly attend to the relevant features of the information goods they govern and that they are better equipped to make the various tradeoffs facing any innovation policy. In particular, such a reform would significantly improve the performance of our innovation policy for drugs in tackling the two key tradeoffs facing any incentive system that uses exclusionary rights (such as patents or data exclusivity). First, it would reduce undue barriers to access that exclusionary rights erect over those innovations that would have been generated at lower levels of protection. Second, it would curb undue rent dissipation—that is, wastefully duplicative innovative activity—that exclusionary rights may incur for innovations that would have been incentivized by a lower level of protection.28 Specific versions of each of these concerns have been prominently voiced in the critical literature on pharma, the first under the heading of “evergreening” practices29 and the second under that of “me-too” drugs.30 In both cases, analysis of the distinct information goods—and of how existing rules fail to align with their relevant features—immeasurably improves both our diagnosis of the precise causes and extent of the problems and our prospects for prescribing effective solutions.

In the case of evergreening and related practices such as “reverse settlement agreements” (RSAs), this analysis identifies the generative cause of such practices: the specific industry structure of pharma that stems from the regulatory treatment of the data information good.31 This information-good analysis fills a gap in the literature by explaining why such practices are, indeed, pharma-specific. The Feature then specifies better ways of evaluating the extent of the social costs of such practices, anchored in the distinction between the compound and data information goods.32 Finally, this same information-goods analysis also points the way to reforms that attack the problem at its root—the basic misalignment between patents and data information—as opposed to proposals that seek only to remedy surface ills with how patents currently operate.33 And similarly for the duplication wastes incurred by me-too drugs, an analysis focused on the distinction between generating new compounds and generating new clinical data is better able to specify both the extent to which such drugs do incur such wastes and how to tailor remedies for effectively curbing them.34

In sum, an assessment of pharmaceutical innovation policy that trains its attention on the data information good lying at its heart leads to the following conclusions. The actual protection provided by patents over the key information goods in pharmaceuticals is partial, indirect, and—owing to a misalignment between what the patent system focuses on (the compound information good) and what sensible innovation policy would center (the data information good)—haphazard and highly costly. This protection would be radically improved by replacing patents’ exclusionary rights with those of a revised—streamlined and tailored—form of data exclusivity. Such exclusivity should be streamlined to curb the gaming and administrative costs associated with misaligned patents, and tailored to realign the system’s focus on the incentives that matter—those pertaining to the costs, risks, and desirability of generating different types of clinical data on drugs.

This analysis has major implications for lowering both the prices and the cost of drugs, and for improving both access to and incentives for pharmaceutical innovation. In 2022, the United States spent $406 billion on retail prescription drugs.35 One source of this high price tag, on which critics of the industry have rightly focused their attention, is how RSAs and related evergreening abuses of patents unduly drive up drug prices, with estimates of their effects ranging between $3.5 billion to $6.2 billion in higher prices annually.36 In response, the Federal Trade Commission (FTC) has called for reforms such as the “delisting” of over 100 drug patents from the “Orange Book”—to remove one evergreening obstacle to generic entry—as well as changing the antitrust burden for establishing the legality of RSAs, to remove another.37 The present analysis not only provides a firmer basis for such reforms than has so far existed, but it also shows why they do not go far enough: not only should some patents be delisted from the Orange Book, but all such Orange Book linkage should be
abolished,38 and similarly for RSAs—they should be deemed per se, rather than merely presumptively, anticompetitive.39 Doing so would dramatically reduce barriers to access from trivial or modest secondary drug patents and products.

At the same time, however, the foregoing estimates of the costs of evergreening practices are incomplete because they do not factor in possible incentive benefits from extended patent protection to be weighed against its access costs. And these estimates do not factor in the wastes associated with gaming the patent system to obtain such (indirect) incentives.40 In addition, a focus on the role of evergreening—or trivial or modest secondary drug patents or productions—in driving up industry prices and costs needs to be supplemented with an analysis of the role of me-too—or duplicative primary drug patents and products—in doing the same. For both, the best metric of their costs is to step back from specific cases, take a comprehensive view of the industry’s output, and analyze the types and extent of innovation they represent. Such a review, carried out here, reveals that, of the 2,872 new drugs approved in the years 1990 to 2023,41 almost 70% were secondary products, and 86% of these were rated by FDA not to hold out a significant advance. In other words, 60% of the industry’s output consists of secondary products securing patent protection that is likely incommensurate with the modest innovation they hold out. Moreover, of the roughly 30% of output that consisted of primary products, over half (51%) were similarly rated as standard—that is, held to be somewhat to highly duplicative of already-available treatments.

Both the high access and duplication costs incurred by evergreening practices and me-too drugs stem from the misaligned incentives of the present system of innovation-policy rules in place for pharmaceuticals. In each case, the cause lies in different aspects of how the central innovation in pharmaceuticals, the data information good, is handled by the present system of regulatory requirements, permissions, and data exclusivity. And for both, the solution lies in the same domain: to replace patent protection with a tailored system of regulatory exclusivity, one that retains strong incentives for truly socially valuable forms of drug innovations while curtailing them for others.

Turning from pharmaceutical innovation policy to broader debates in patent theory, this analysis also provides a distinct explanation for the consensus view that patents are especially important for pharmaceuticals. The special case for protection presented by pharma, this analysis reveals, is a regulatory artifact rather than, as is commonly thought, the result of any generalizable technological or economic features of the pharmaceutical industry. That is, this case stems from the gap between innovation and imitation costs with respect to the second, data information good, and not the first, compound information good.42 More specifically, it is due to the combined effect of two distinct regulatory features with respect to data information: how regulatorily mandated clinical trials massively drive up innovation costs, and how regulatorily permitted piggybacking on clinical data massively drives down imitation costs.43 Absent this combination, there is little reason to believe that pharma would be very different—that is, with respect to the compound information good—from other sectors in terms of the ability of first-mover advantages and secrecy to sustain a robust level of innovative activity. None of this is to query the regime of regulatory requirements and permissions. Far from it. Rather, it is to just underline that it is this regime that makes pharma special, putting it in need of special innovation-policy support.

This point has crucial import for general debates in patent theory. In those debates, pharma has long cast a shadow over the standard conclusion that the overall case for patents—across the economy as a whole—is uneasy,44 and likely at its best for modest protection for small inventors at the margins.45 Pharma has long operated as the key exception to that general rule, one that, so long as it remained unexplained, gnawed away at confidence in the rule. Showing that this exception can be not only explained, but explained away, reinforces the broader conclusion that for most sectors, strong patents are likely not needed for robust innovation, a conclusion that may now be retained in its original force, without qualification.

The rest of the Feature proceeds as follows. Part I lays the theoretical foundations by setting out a framework for the analysis of innovation policy, clarifying why all innovations need to be conceived as information goods, identifying the two distinct (compound and data) information goods at issue in pharmaceutical innovation, and specifying their divergent technological and economic features as relevant to innovation policy in theory. Part II then turns to analyzing how the two information goods are presently treated by pharmaceutical innovation policy in practice. It begins with a sketch of the technological and institutional pipeline of pharmaceutical innovation, and the roles played by patents, FDA regulatory requirements, and data exclusivity. It then details the coordination and incentive functions that patents and data exclusivity do (or do not) play with respect to each of the two information goods along the innovation pipeline. It shows that patents play only a modest role in directly protecting the compound information good. Meanwhile, patents serve more significant functions for the data information good, but they do so only indirectly.

Part III then evaluates how well this system of indirect—and thus misaligned—protection performs. It finds that for each of the two main tradeoffs raised by exclusionary incentives—access costs and rent dissipation—the system performs quite badly indeed. The undue access (and gaming) costs incurred by “evergreening” practices and the duplication wastes associated with “me-too” drugs are very high, and in each case they stem from the basic underlying misalignment between patents and data information. The most effective way to curb these costs, then, is not so much to improve how drug patents work but rather to attack the problem at its root and eliminate the basic misalignment by replacing pharma patents with a revised system of tailored regulatory exclusivity. Finally, Part IV briefly canvasses three issues broached by the present analysis that merit future investigation: how to determine the precise duration and scope of regulatory-exclusivity protection; whether and how to supplement such an improved system of regulatory-exclusivity incentives on the “supply” side with better pricing (signals) on the “demand” side; and whether the role of nonexclusionary innovation policies should be expanded in this area.