Secrets and semiconductors

'Bordering Secrecy: An Empirical Study on Cross-Border Trade Secret Misappropriation in the Semiconductor Sector' by Tzu-I Lee in (2024) 39(2) Connecticut Journal of International Law 166-237 comments 

Nation-states take steps to prevent the theft of domestic entities’ trade secrets and other intellectual property (“IP”). The United States has issued complaints, passed laws, and implemented initiatives and sanctions targeting China’s unfair and illegal economic practices, which include trade-secret theft. Although China has responded by amending its civil, criminal, and administrative trade-secret regime, foreign companies still routinely struggle with thefts connected to China. The semiconductor industry– essential to daily-life, commercial, and military needs–is one of the most brutal battlegrounds of today’s IP and tech wars. A leader in the industry is the Taiwanese semiconductor sector, which, along with the Taiwanese government and like-minded democracies, must confront a particularly complex set of economic, security, and geopolitical challenges from China. Currently, poor grasp of cross-border trade secret thefts has greatly weakened sincere efforts to deal with the grave threat posed by China. In this Article, I cross-analyze empirical quantitative and qualitative data regarding U.S. and Taiwanese semiconductor trade-secret litigation to better understand the dynamics of Chinese trade-secret theft. I propose that individuals, companies, governments, and international organizations should respond to trade-secret threats by restoring trust within a geopolitical economic framework, rather than by pursuing purely legalistic IP approaches.

AI, Patent Reading and Patent Disclosure

'Misleading AI: Regulatory Strategies for Transparency in Information Intermediary Tools for Consumer Decision-Making' by Jeannie Marie Paterson in (2023) Loyola Consumer Law Review comments

Increasingly, consumers’ decisions about what to buy are mediated through digital tools promoted as using “AI”, “data” or “algorithms” to assist consumers in making decisions. These kinds of digital information intermediaries include such diverse technologies as recommender systems, comparison sites, virtual voice assistants, and chatbots. They are promoted as effective and efficient ways of assisting consumers making decisions in the face of otherwise insurmountable volumes of information. But such tools also hold the potential to mislead consumers, amongst other possible harms, including about their capacity, efficacy, and identity. Most consumer protection regimes contain broad and flexible prohibitions on misleading conduct that are, in principle, fit to tackle the harms of misleading AI in consumer tools. This article argues that, in practice, the challenge may lie in establishing that a contravention has occurred at all. The key characteristics that define AI informed consumer decision-making support tools ––opacity, adaptivity, scale, and personalization –– may make contraventions of the law hard to detect. The paper considers whether insights from proposed frameworks for ethical or responsible AI, which emphasise the value of transparency and explanations in data driven models, may be useful in supplementing consumer protection law in responding to concerns of misleading AI, as well as the role of regulators in making transparency initiatives effective.

'Linguistic metrics for patent disclosure: Evidence from university versus corporate patents' by Nancy Kong, Uwe Dulleck, Adam B Jaffe, Shupeng Sun and Sowmya Vajjala in (2023) 52(2) Research Policy comments 

 Encouraging disclosure is important for the patent system, yet the technical information in patent applications is often inadequate. We use algorithms from computational linguistics to quantify the effectiveness of disclosure in patent applications. Relying on the expectation that universities have more ability and incentive to disclose their inventions than corporations, we analyze 64 linguistic measures of patent applications, and show that university patents are more readable by 0.4 SD of a synthetic measure of readability. Results are robust to controlling for non-disclosure-related invention heterogeneity. The linguistic metrics are evaluated by a panel of “expert” student engineers and further examined by USPTO 112(a) – lack of disclosure – rejection. The ability to quantify disclosure opens new research paths and potentially facilitates improvement of disclosure. ... 

The patent system serves two purposes: “encouraging new inventions” and “adding knowledge to the public domain”. The former incentivizes creation, development, and commercialization by protecting inventors’ exclusive ownership for a limited period of time. The latter encourages disclosure of new technologies by requiring “full, clear, concise, and exact terms” in describing inventions.2 Sufficient disclosure in patents has three major benefits: (1) fostering later inventions (Jaffe and Trajtenberg, 2002, Scotchmer and Green, 1990, Denicolò and Franzoni, 2003); (2) reducing resources wasted on duplicate inventions (Hegde et al., 2022); and (3) inducing more informed investment in innovation (Roin, 2005). 

Despite a large body of literature on the patent incentivizing function (Cornelli and Schankerman, 1999, Kitch, 1977, Tauman and Weng, 2012, Cohen et al., 2002), patent disclosure receives limited attention. This raises concerns; as Roin (2005), Devlin (2009), Sampat (2018), Arinas (2012) and Ouellette (2011) document, the technical information contained in patent documents is often inadequate and unclear. Important questions, such as how to measure disclosure, potential incentives behind disclosure, heterogeneous levels of disclosure by entities, and the tactic of avoiding the disclosure requirement, have not been directly investigated. A major barrier to such empirical research has been the lack of broadly applicable, reproducible quantitative measures of the extent of disclosure or information accessibility. We propose and demonstrate that extant metrics developed in computational linguistics can help to fill this gap. 

In using computational linguistic metrics to compare the readability of documents, we follow researchers in the finance and accounting literature, who have used readability metrics to gauge whether readers are able to extract information efficiently from financial reports (Li, 2008, Miller, 2010, You and Zhang, 2009, Lawrence, 2013). This literature posits that more complex texts increase the information processing cost for investors (Grossman and Stiglitz, 1980, Bloomfield, 2002) and finds, for example, that companies are likely to hide negative performance in complicated text to obfuscate that information (You and Zhang, 2009). 

Although patent applications differ from corporate annual reports, the research question regarding strategic obfuscation is similar: Documents are created subject to regulation, in which the purpose of the regulation is to compel disclosure, but the party completing the document may have incentives to obscure information. Our proposed linguistic measures are likely to serve as an informative proxy for the explicitly or implicitly chosen level of disclosure. The goal of this article is simply to demonstrate that these measures do appear to capture meaningful differences in accessibility or disclosure, and thereby opening up the possibility of research on the causes and effects of variations in disclosure. 

Our strategy for demonstrating the relevance of linguistic readability metrics is to identify a situation in which we have a strong a priori expectation of a systematic difference in disclosure across two groups of patents. If the proposed metrics show the expected difference, we see this as an indication to treat them as potentially useful. We compare patent applications from universities with those of corporations. Both strategic reasons and the costs of revealing information inform our expectations. From a strategic perspective, universities, with their focus on licensing of patents have an interest in making their patents more accessible. In contrast, corporations (particularly practicing corporations) may benefit from limiting the accessibility of information. From a cost perspective, drafting patents is usually informed by documentation of the relevant research or process of innovation. Given university researchers’ primary interest in accessible publications and the relevant standards of documentation, the source material available to an attorney drafting a patent may be much better than in the case of the same attorney drafting a patent for a corporation, in which the need for such documentation is much less. The literature also supports this expectation (Trajtenberg et al., 1997, Henderson et al., 1998, Cockburn et al., 2002). 

Universities and corporations follow different business models for patenting: technology transfer versus in-house commercialization. Patents applied for by universities, with a focus on generating income from the licensing of inventions, should have a higher level of disclosure because transparent information makes it easier to signal the technology contained in the patent and attract potential investors. As a result, they are more readable than corporate patents. The readability difference could be further magnified by the moral requirements of university research as well as the rigor of academic writing, which could further affect the level of disclosure. 

Corporations, particularly those with a focus on in-house production, on the other hand, have a greater incentive to obfuscate crucial technical information to deter competitors from understanding, using, and building on their inventions. The profit-maximizing motive, as well as a lack of incentive to thoroughly document the invention, could also contribute to the low level of disclosure. Together, it is reasonable to assume that universities may strategically (or unconsciously) choose a higher disclosure level in patent applications than corporations. We emphasize that we do not see this analysis as testing the hypothesis that universities engage in more disclosure than corporations for a particular reason. Rather, we take this as a maintained hypothesis and show – conditional on that maintained hypothesis – that the linguistic measures meaningfully capture differences in disclosure across patents, which indicates the value of further research and the need to reconsider patent examination with respect to the accessibility and disclosure of information contained in patents. 

Similar to the finance literature, we use a computational linguistic program designed to assess the reading difficulty of texts using 64 measures from second language acquisition research. The indicators cover the lexical, syntactic, and discourse aspects of language along with traditional readability formulae. We apply them to a full set of U.S. patent application texts in three cutting-edge industries from the past 20 years. Our baseline OLS estimations reveal significant differences between university and corporate patents. Using principal component analysis (PCA) to combine the 64 indicators and create synthetic readability measures, we show that composite indices detect strong differences between university and corporate patents, which lends support to the validity of our measures. 

The key empirical challenge is that the nature of corporate and university inventions might differ; thus, the textual communication required for corporate inventions could differ. To address this concern, our identification strategy employs the following. First, to account for the unobserved heterogeneity in linguistic characteristics intrinsic to technical fields, our econometric method controls for U.S. patent subclass fixed effects. This enables us to measure disclosure as the degree of readability relative to other technologically similar patents. Second, we use patent attorney fixed effects to control for systematic disclosure effects from the drafting agents. This compares the university and corporate patents drafted by the same patent attorney. Third, we employ cited-patent fixed effects with a data compression technique, least absolute shrinkage and selection operator (LASSO), to further control for the nature of inventions. This is because university and corporate patents that cite the same previous patents build on the same prior knowledge, and are therefore likely to be technologically similar inventions. Fourth, to deal with any selection bias from observables, we use a doubly robust estimation that combines propensity score matching and regression adjustment. This enables us to compare university and corporate patents with similar attributes. 

Our results show that corporate patents are 0.4 SD more difficult to read and require 1.1–1.6 years more education to comprehend than university patents. We find that the difference is more prominent for more experienced patent applicants, and that licensing corporate patents disclose more than other corporate patents, which we believe supports the idea that the differences in readability are at least somewhat intentional. We also show that a potential channel for obfuscation lies in the provision of many examples in order to conceal the “best mode” of inventions. 

This paper is one of the first to specifically use textual analysis to examine patent disclosure (with exception of Dyer et al. (2020) who focus on patent examiners’ leniency) and validate the measure. We obtain the whole set of full text patent applications in categories related to nanotechnology, batteries, and electricity from 2000 to 2019, totaling 40,949, and apply our linguistic analysis model to the technical descriptions of these patents. We expand readability studies in related literature that rely heavily on traditional readability indices such as Gunning Fog, Kincaid, and Flesch Reading Ease by including lexical richness, syntactic complexity, and discourse features. We use the best non-commercial readability software (Vajjala and Meurers, 2014b) to capture the multidimensional linguistic features of 64 indicators, and perform a more in-depth linguistic analysis (Loughran and McDonald, 2016) than previous studies. We also use principal components analysis to construct synthetic overall measures of readability. 

Having developed this rich set of readability measures, we validate them as indicators of effective patent disclosure by testing whether the lexical measures show patents to be more readable in several real-world contexts. Our primary comparison is between university and corporate patents. The licensing aims of universities and absence of market driven competitive motives mean that they have greater incentive to disclose – less incentive to conceal – key information relative to corporations. Through analyses that control for sources of variation in readability, we find that university patents are, indeed, more readable. We support this main analysis with several other comparisons. Intellectual Ventures – a corporation that, akin to universities, seeks to license its patents over competing in the market – also holds patents with above average readability. Several large corporations known to be active patent licensors (IBM, Qualcomm, and HP) similarly exhibit higher readability. Additionally, a set of patents that can be presumed to have been reassigned also exhibit higher readability than otherwise similar patents. Finally, we compared the computational readability measures to subjective evaluations of readability and disclosure for a small number of patents, and assessed the readability of patents rejected by the USPTO for reasons that include failure to adequately disclose the technology. 

We see the role of this paper as analogous to Trajtenberg et al. (1997), who first introduced metrics of patent “importance”, “generality” and “originality” based on patent citation data. We imitate their strategy to test whether our proposed new measures reveal the contrast we expect between university and corporate patents, and argue that the finding – that they display the predicted pattern – can be taken as initial evidence that they capture meaningful variation in unobservable patent disclosure quality. The introduction and initial validation of these measures open up the possibility of quantitative treatment of extent of disclosure in patents, both for social science research on the sources and effects of better or worse disclosure, and potentially for use in more systematic treatment of the disclosure obligation in the patent examination process. 

The rest of the paper proceeds as follows. Section 3 explains the linguistic measures used in the study. In Section 2, we review the relevant literature and lay out our hypothesis of differences in disclosure between university and corporate patent applications. Section 4 presents our data and baseline estimation, followed by our main results in Section 5. We examine attorney fixed effects and cited-patent fixed effects in Section 6, and one channel that corporations could use to obscure patent applications in Section 7. We show heterogeneous effects in Section 8 and usefulness tests in Section 9, and conclude in Section 10.

Health Data Opacity

'The Big Data Regulator, Rebooted: Why and How the FDA Can and Should Disclose Confidential Data on Prescription Drugs and Vaccines' by Amy Kapczynski and Christopher J. Morten in (2021) 109(2) California Law Review 493 comments 

Medicines and vaccines are complex products, and it is often extraordinarily difficult to know whether they help or hurt. The Food and Drug Administration (FDA) holds an enormous reservoir of data that sheds light on that precise question, yet currently releases only a trickle to researchers, doctors, and patients. Recent examples show that data secrecy can be deadly, and existing laws such as the Freedom of Information Act (FOIA) cannot solve the problem. We present here a wealth of new evidence about the urgency of the problem and argue that the FDA must “reboot” its rules to proactively disclose all safety and efficacy data for drugs and vaccines with minimal redactions, deploying data use agreements to ensure the most sensitive data is handled appropriately. In line with the literature that has been critical of simplistic calls for “transparency,” we urge a more contextual form of “data publicity.” We also show that clinical trial data publicity can be achieved without legislative reform, while respecting privacy, protecting any legitimate trade secrets, and maintaining or improving incentives to innovate. The FDA must adapt to protect and expand structural accountability and to protect the public and its trust. The model we offer here could guide similar action at other regulatory agencies as well, enabling better oversight of information-intensive industries and helping safeguard the agencies themselves. 

The authors argue 

Few issues are more important to the American public than the quality and safety of our medicines. About half of all Americans take one or more prescription drugs, and medicines represent a startling 2% of total U.S. gross domestic product (GDP) each year. Life as we know it relies on vaccines that prevent dangerous diseases. But there is a structural problem at the heart of our system for the development and assessment of therapeutics and vaccines: a problem of secrecy in the age of big data. 

The problem of data secrecy is especially visible in the shadow of the COVID-19 pandemic. As we complete this in the summer of 2020, governments around the world are taking unprecedented measures to promote the development of a COVID-19 vaccine. Billions of dollars of public money are being invested, with dozens of potential vaccines in development. But researchers have raised an outcry, pointing out that they have no access to some of the most basic and important information about the design and outcomes of the most promising COVID-19 vaccine trials. Access to this information could enable scientists to understand key clinical trial decisions in time to influence them, to evaluate the quality of the evidence as it emerges, and to protect against mistakes and misconduct, such as changes in trial endpoints that produce spurious results. Researchers could also make novel uses of the data collected, advancing our understanding of COVID-19 at a critical time. Under pressure, several companies (as of this writing) have begun to release some such data voluntarily.  This is a positive step and a proof of concept. But there are important gaps in what has been provided and no systems in place to be sure that they will be remedied, despite the extraordinary stakes. 

The inability to access data related to COVID-19 vaccine development sheds light on the problems caused by systemic data secrecy in clinical trials. Therapeutics and vaccines are complex products. We cannot know whether they hurt or help without rigorous clinical trials, whose conduct and interpretation are highly complicated. Today these trials, particularly at later stages, are typically conducted by companies with strong financial interests in the outcomes. This is a key justification for our drug regulatory system: independent experts are needed to protect the public by examining and validating data about the effects of medicines. But our drug regulatory bodies are under-resourced, and recent examples show that outside expert analysis can reveal concealed risks of medicines. 

The rise and fall of the painkiller rofecoxib (Vioxx) offers a stark example of the harms of data secrecy. The drug was promoted as being safer than aspirin and became a blockbuster. It earned $2 billion each year for Merck before it was abruptly removed from the market because it caused heart attacks, strokes, and heart failures. The evidence only became known to outside experts through litigation. Later independent research showed that signals of these risks were present in data held by the FDA nearly 3.5 years before the drug was withdrawn from the market. That evidence did not reach doctors or patients because the data was not made available to the scientific community. An FDA official later estimated that tens of thousands of people died as a result. 

Data secrecy also causes harm by undermining our health care system. Secrecy prevents us from making the best allocation of scarce resources and obscures avenues for systematic reforms at the FDA and in the pharmaceutical industry. Data secrecy may also undermine trust. The American public, for example, expressed widespread hesitancy about any COVID-19 vaccine that was to be rushed to market before the November 2020 U.S. election. Sharing safety and efficacy data on drugs and vaccines—including COVID-19 vaccines—would help to secure public trust in the FDA review process and in the products that emerge from it and would help to protect the scientific integrity of the FDA review process from political pressure.  

There is, accordingly, an emerging consensus that independent researchers need better access to clinical trial data to keep both the industry and regulators honest and accountable. Yet existing tools for an independent assessment of clinical trial data are inadequate. What remains missing is an effective legal and regulatory framework for the release of this data within the United States. For several years, working closely with medical researchers and a legal team, we have worked to maximize the potential of existing strategies for clinical trial data disclosure. This Article sets out a key lesson of that work: existing tools are inadequate for the task. If researchers are to have systematic access to the clinical trial data needed to help spot unsafe and ineffective medicines, the FDA will have to make clinical trial data available proactively. 

We show that the agency can, consistent with existing law, make clinical trial data available proactively. We describe how the FDA can do so while navigating the two main challenges of data sharing: protecting the privacy of individuals who participate in trials and addressing claims that company data should remain confidential. Drawing on examples of successful data sharing in other countries and at other agencies, we also show that the process can be done effectively and manageably. Our central contribution is a wealth of new evidence about the significance of the problem and an updated argument for proactive disclosure that can be achieved without legislative reform. We reveal the flaws in arguments that comprehensive proactive disclosure is prohibited under U.S. federal statutes  or, if permitted, will require expensive compensation to the industry for intellectual property violations. 

This Article is centrally aimed at solving an important public health problem, but it also contributes to two broader literatures. The first is the literature on transparency and the implications of freedom of information laws. Transparency as an ideal has been rightly criticized recently as having taken on a formalistic, decontextualized quality. As an ideal, transparency does not appropriately recognize that “freedom” at times requires more than unfettered, standardless exchange and does not appreciate how freedom of information laws can be weaponized to undermine public interests. We show here that the implications of data sharing turn on and should be sensitive to a broader political-economic context. Data sharing can serve public interests because of a wider ecology that provides researchers with the necessary resources to analyze the data and includes publications and norms (of the “open science” tradition in academic medicine, for example) that help generate and validate important new insights and challenge false claims. Data itself does not produce these insights, and a context that enables trustworthy analysis is essential if data sharing is to work well. 

To this end, we argue that data use agreements will be an important component of data disclosures in our “big data” age. They provide a means to navigate issues of privacy and commercial interest—issues that can otherwise shut down data sharing, rightly or wrongly—and a mechanism to develop and impose other publicly minded conditions. The role of these agreements here illustrates the importance of contract as a tool to facilitate information exchange and innovation. Decontextualized demands for “openness” have gained traction in recent decades and might suggest that in every instance we need unfettered data exchange that treats all parties equally, including companies. We argue instead that the FDA should prioritize health researchers over industry actors and that it should use data use agreements to ensure those researchers protect legitimate public interests. These contracts are possible only with proactive disclosure and are inconsistent with reactive FOIA requests. 

We join other scholars in suggesting that the future of freedom of information, if it is to achieve its aims, lies in the development of robust proactive disclosure systems. In part to mark these distinctions, we call what we seek here not data transparency, but data “publicity.” The term as we use it, which draws upon early progressive traditions, marks the need for attention to context, power, and resources if data sharing is to serve the public. We also seek to contribute to the broader literature on the future of the regulatory state and the conditions of democracy broadly understood. Today, we live in an extraordinarily information-intensive age. Decades of dramatic advances in technologies for information processing have transformed the core of the modern economy and enabled the emergence of massively complex new industries and firms. This means that not only pharmaceuticals but also products like cars, insurance, airplanes, and phones are far more informationally intensive today than they were twenty years ago. Informationally intensive products and systems are complex, opaque, and dynamic. Systems that are improperly or fraudulently designed — think here about Volkswagen’s deceptive “defeat device” to evade emissions testing, or Boeing’s defective automated flight software for the 737 Max — generate serious social and individual harms. Regulators face growing challenges in this environment, and we need structures to allow the public to hold both regulators and the industry accountable. Yet the same barriers that appear in this context—issues of privacy, corporate claims to trade secrecy and confidentiality, and difficulties with reactive data release models (FOIA especially)—will reappear throughout the administrative state. Our Article thus can help inform a wide variety of regulators who face related issues, whether in the area of consumer products, environmental protection, or artificial intelligence. Data publicity will have plausible benefits elsewhere, and regulators can learn from how it can be achieved at the FDA. But they must also learn from the fertile conditions in the pharmaceutical and medical context that allow clinical trial data publicity to inform the public. It is not open data alone, but data publicity in a context where resources and expertise exist to enable intelligible uses of such data, that furthers democratic accountability. 

 We begin in Part I by describing the need for proactive disclosure of safety and efficacy data  and why existing legal avenues, such as FOIA, fail to create adequate data publicity. In Part II, we show that, contrary to the conventional wisdom and the (usual) view of the FDA itself, federal law does not prohibit the FDA from disclosing such data, even from the moment of drug or vaccine approval. Consistent proactive disclosure, however, will require revisions to the FDA’s current regulations, corrections to its interpretations of certain statutes, and, for the most sensitive data, data use agreements. We also show that the move should not hurt and may improve innovation, nor should it require compensation under the Takings Clause. If the agency does not act, Congress can and should, as we describe in Part III. 

Trade Secrets

'Trade Secrecy, Factual Secrecy and the Hype Surrounding AI' by  Sharon K. Sandeen and Tanya Aplin, in Ryan Abott (ed) Research Handbook on Intellectual Property and Artificial Intelligence (Edward Elgar, forthcoming) comments

Access to and sharing of anonymized machine-generated data and the transparency of data analysis techniques has taken on vital importance in a world characterized by artificial intelligence, particularly machine learning'. In short, this chapter interrogates the extent to which such data and algorithms may qualify as 'trade secrets' under US and EU trade secrets law, focusing in particular on whether the definition of a ‘trade secret’ is met. We show through the use of two case studies – involving autonomous vehicles and credit scoring – and a close analysis of the trade secrets definition that the claim of trade secrets protection is overstated. The greater risk relates to factual secrecy rather than legally protected trade secrets and the policy debate needs to shift to assess what regulation, if any, there should be of data that is simply kept secret. 

AI and EU Intellectual Property Policy

The European Commission report Trends and Developments in Artificial Intelligence: Challenges to the IPR Framework by Christian Hartmann, Jacqueline Allan, P. Bernt Hugenholtz, Joao Pedro Quintais and Daniel Gervais states

This Report examines the state of the art of copyright and patent protection in Europe for AI- assisted outputs in general and in three priority domains: science (in particular meteorology), media (journalism), and pharmaceutical research. “AI-assisted outputs” are meant as including productions or applications generated by or with the assistance of AI systems, tools or techniques. 

As the state of the art reviewed demonstrates, the use of AI systems in the realms of culture, innovation and science has grown spectacularly in recent years and will continue to do so. AI systems have become almost ubiquitous in meteorology and in pharmaceutical research and are making deep inroads into media and journalism. Outside these distinct domains, AI systems are being used to generate diverse literary and artistic content, including translations, poems, scripts, novels, photos, paintings, etc. Likewise, a wide variety of innovative and inventive activity relies on AI systems for its development and deployment, from facial recognition to autonomous driving. 

While AI systems have become – and will become – increasingly sophisticated and autonomous, this Report nonetheless assumes that fully autonomous creation or invention by AI does not exist, and will not exist for the foreseeable future. We therefore view AI systems primarily as tools in the hands of human operators. For this reason, we do not enquire whether AI systems should one day be accorded authorship or inventorship status under future IP Law. We also do not examine the IP protection of AI systems per se; legal issues concerning the input of protected subject matter into AI systems (e.g. for text-and-data mining); nor algorithmic moderation or enforcement of IP subject matter, as these topics are beyond the scope of this analysis. Analysis of legal protection regimes beyond copyright and patent law (e.g. trade secrets, unfair competition and contract law) is also outside the terms of reference. An important trend that does emerge from the state of the art review is that more and more AI capability is being offered “as a service” rather than as “bespoke” (tailored) AI systems. Consequently, the emphasis of our analysis is on the users (operators) of AI systems, rather than on their developers. 

This Report provides an assessment of the state of the art of uses of AI in the three priority domains and a legal analysis of how IP laws currently apply to AI-assisted creative and innovative outputs. The Report concludes with recommendations regarding possible revision of IP law at the European level. 

State of the Art in Uses of AI 

There is no universally accepted definition of AI. At a high level, it can be defined as “computer- based systems that are developed to mimic human behaviour” or a “discipline of computer science that is aimed at developing machines and systems that can carry out tasks considered to require human intelligence, with limited or no human intervention.” 

In pharmaceutical research, AI is finding patterns within large data sets and helping to automate the search process. Based mostly on machine learning, AI is assisting in disease diagnoses, predictions of drug efficacy and identification of drug characteristics (e.g. toxicity). Neural networks enable compound discovery, personalised medicine and drug repurposing. AI is being applied in finding molecular drug targets (e.g. proteins, nucleic acids) by searching through libraries of candidates, accelerating the high throughput screening needed to find a candidate substance for further investigation in drug development. It is helping in repurposing of drugs to meet new or different need, in polypharmacology (where a disease is due to multiple malfunctions of the body) and to find and accelerate the development of vaccines (by both gene sequencing and simulations of vaccines). In these processes, some measure of human intervention is usually required, either at the start or throughout the entire process, with human feedback optimising the steps. 

In recent years, there has been increasing cooperation between the pharmaceutical industry and AI companies. Some companies pursue an active IP strategy and file patents in both the domains of pharmaceutical and AI technology while others sell services confidentially to pharmaceutic companies. 

In the area of science, the Report examines meteorology as one of the main application areas where AI is already routinely used. Meteorology predicts the state of the atmosphere, at a certain time in a certain place or over a specific area, based on historical data and knowledge of climate and the atmosphere. Automated tasks include post-processing of weather data; predictive analytics for future forecasts; bias correction of meteorological observations; parameterisation of models to correct for radiation, turbulence, cloud microphysics, etc.; data assimilation; and local downscaling of model outputs to improve predictions. 

Weather forecasts rely on vast quantities of data. The ability of machine learning to extract knowledge from complex and extensive databases makes it particularly suitable for numerical weather forecasting. Some companies support media companies in weather reporting and forecasting, providing high-precision, precise weather forecasts in multiple formats daily, including recordings, to suit the various reporting media. 

In journalism, AI enables automated aggregation, production and distribution of content (data, text, images, audio or video). Assistive technologies support journalists in the creation of media content, including speech recognition, information extraction, clustering, summarising, and machine translation capabilities for multi-lingual access to sources. Generative technologies produce media content with human intervention limited to inputting the data set, defining output specifications, and quality control. Distributing technologies encompass the publication or other forms of communication (e.g. through chat bots) of automatically created content with the help of algorithms.  

Several companies currently offer technologies for automated content creation for uses in diverse areas including describing product, summarising patient notes in hospitals, reporting on sports events, reporting share prices and customising local information on property markets. Other companies have in-house capabilities for automated news generation. Know-how is commonly protected through licensing models, rather than asserting ownership of IP. It also relies on the tacit knowledge within a company, with the knowledge on how to develop customer-specific systems acting as a high barrier to competitors looking to enter the market. 

Legal Analysis under EU Copyright and Patent Laws 

The legal analysis examines whether, and to what extent, AI-assisted outputs are protected by European copyright law, related rights or patent law. For copyright, the analysis is concentrated on the so-called EU copyright acquis and its interpretation by the Court of Justice of the EU (CJEU). The patent analysis concentrates on the European Patent Convention (EPC).

EU Copyright Law 

As our inquiry into EU copyright law reveals, four interrelated criteria are to be met for an AI- assisted output to qualify as a protected “work”: the output is (1) a “production in the literary, scientific or artistic domain”; (2) the product of human intellectual effort; and (3) the result of creative choices that are (4) “expressed” in the output. Whether the first step is established EU law is however uncertain. Since most AI artefacts belong to the “literary, scientific or artistic domain” anyway, and are the result of at least some “human intellectual effort” (however remote), in practice the focus of the copyright analysis is on steps 3 and 4. 

Based on a thorough analysis of the CJEU’s case law, and in light of the findings of two experts workshops, we conclude that the core issue is whether the AI-assisted output is the result of human creative choices that are “expressed” in the output. In line with the CJEU’s reasoning in the Painer case, we distinguish three distinct phases of the creative process in AI-assisted production: “conception” (design and specifications), “execution” (producing draft versions) and “redaction” (editing, finalisation). While AI systems play a dominant role at the execution phase, the role of human authors at the conception stage often remains essential. Moreover, in many instances, human beings will also be in charge of the redaction stage. Depending on the facts of the case, this will allow human beings sufficient creative choice. Assuming these choices are expressed in the final AI-assisted output, the output will then qualify as a copyright- protected work. By contrast, if an AI system is programmed to automatically execute content without the output being conceived or redacted by a person exercising creative choices, there will be no work. 

Due to the “black box” nature of some AI systems, persons in charge of the conception phase will sometimes not be able to precisely predict or explain the outcome of the execution phase. This however need not present an obstacle to the “work” status of the final output, assuming that such output stays within the ambit of the person’s general authorial intent. 

Authorship status will be accorded to the person or persons that have creatively contributed to the output. In most cases, this will be the user of the AI system, not the AI system developer, unless collaboration between the developer and user on a specific AI production indicates co- authorship. If “off-the-shelf” AI systems are used to create content, co-authorship claims by AI developers will also be unlikely for commercial reasons, since AI developers will normally not want to burden customers with downstream copyright claims. 

A problem that might arise is the possibility of falsely claiming authorship in respect of AI productions that do not qualify as “works” for lack of human creativity. Producers or publishers might be tempted to falsely attribute authorship in such productions in order to benefit from the authorship presumptions granted under EU law, which allow the person whose name is mentioned as an author to initiate infringement procedures. 

British and Irish copyright law accord authorship statu s to persons undertaking the arrangements necessary for creating computer-generated works in cases where no (human) author can be identified. These provisions have been criticised as being incompatible with EU copyright standards, since “authorless” works do not meet the EU standard of “the author’s own intellectual creation”. Perhaps, they are therefore better understood as a species of related rights. 

The related rights harmonised under the EU acquis offer various possibilities for protecting AI- assisted outputs that do not qualify for copyright protection. In light of the general absence in related rights’ law of a requirement of human authorship or originality, and its rationale of rewarding economic or entrepreneurial activity, related rights will accommodate AI-assisted output in cases of insufficient human creative input. 

While AI-assisted outputs in the form of aural signals (audio data) may benefit from the phonographic right, audio-visual outputs will qualify for protection under the film producer’s right. Moreover, AI-assisted broadcasts may find protection under the related rights of broadcasters. None of these related rights provide for a threshold requirement, making these regimes available for AI-assisted outputs that are generated without any creative human involvement – even absent significant economic investment. In most cases the user, not the developer, of the AI system will be deemed the owner of the related right, since it is the user that triggers the acts that give rise to these rights through his use of the AI system and output generation. 

Additionally, AI-generated databases will qualify for sui generis protection under the EU Database Directive if the databases are the result of substantive investment. This includes investment in AI technology and know-how applied in producing the database. In light of the broad legal notion of “database”, the sui generis right potentially offers protection to a wide range of AI-assisted productions. However, it is currently uncertain whether investment in machine-generating data – for example, the generation of weather data with the aid of AI – may be factored in. In any case, the prerequisite of a “database” rules out protection of raw data. 

Illustrated via case studies in the Report, it is impossible to make general assessments of the copyright status of AI-assisted outputs in individual cases. In some cases, where the creative role of human beings is evident at various stages of the creative process, such as The Next Rembrandt project, the output will most likely be copyright protected. In other cases, where it is difficult or even impossible to identify creative choices, such as automatically-generated sports reports or AI-assisted weather forecasts, copyright protection will be less likely. Note however that this is the same for sports reports and weather forecasts produced without machine assistance. Nevertheless, producers of “authorless” AI-assisted outputs might still find recourse in related (neighbouring) rights. 

“Authorless” AI-assisted outputs will remain completely unprotected only in cases where no related right or sui generis right is available. Since such rights attach primarily to aural and audio-visual signals, as well as to databases, such cases are most likely to occur if the AI- assisted output is in alphanumerical form. Whether this absence of IP protection might justify regulatory intervention, is primarily an economic question that cannot be addressed in the context of this Report. Such intervention is justified only if no alternative protection (e.g., under trade secret protection, unfair competition or contract law) is available, and solid empirical economic analysis reveals that the absence of protection harms overall economic welfare in the EU. 

Our analysis for EU copyright law and AI leads to the following conclusions and recommendations:  

• Current EU copyright rules are generally sufficiently flexible to deal with the challenges posed by AI-assisted outputs. 

• The absence of (fully) harmonised rules of authorship and copyright ownership has led to divergent solutions in national law of distinct Member States in respect of AI-assisted works, which might justify a harmonisation initiative. 

• Further research into the risks of false authorship attributions by publishers of “work-like” but “authorless” AI productions, seen in the light of the general authorship presumption in art. 5 of the Enforcement Directive, should be considered. 

• Related rights regimes in the EU potentially extend to “authorless” AI productions in a variety of sectors: audio recording, broadcasting, audivisual recording, and news. In addition, the sui generis database right may offer protection to AI-produced databases that are the result of substantial investment. 

• The creation/obtaining distinction in the sui generis right is a cause of legal uncertainty regarding the status of machine-generated data that could justify revision or clarification of the EU Database Directive. 

EU Patent Law 

Our analysis of European patent law – and in particular the EPC – demonstrates that the requirement that an inventor be named on a patent application means that one or several human inventors must be identified. Under the EPC regime, this is essentially a formal requirement. The EPO does not resolve disputes regarding substantive entitlement, which is an issue that is governed by national law. Following this approach, the EPO decided two cases in 2020 (currently under appeal) where it considered that, because AI systems do not have legal personality, they cannot be named inventors on a patent application. 

A human inventor typically has the right to be named on the application. Beyond this, inventorship and co-ownership are mostly a matter for national law. It should be noted, however, that as AI technology stands today, the possibility that an AI system would invent in a way that is not causally related to one or more human inventors (e.g. the programmer, the trainer, the user, or a combination thereof) seems remote. As technology stands, no immediate action appears to be required on the issue of inventorship at EPC level. 

As regards ownership, there are at least three possible (sets of) claimants to an AI-assisted invention: the programmer or developer of the AI system; the owner of the system; and the authorised user of the system (who provided it with training data or otherwise supervised its training). Neither international law nor the EPC provide clear rules on how ownership of patents may be affected by this new type of AI-assisted inventive activity. It is therefore a matter for national laws. However, that might not require harmonisation as there does not seem to be a problem in establishing a sufficient connection between an AI-assisted invention and a patent applicant. 

The granting of a patent requires that, as of the date of filing, the invention must be new (novel) and involve an inventive step. While the increasing use of AI systems for inventive purposes does not require material changes to these core concepts, it may have practical consequences for patent offices. AI systems enable qualitatively or quantitively different novelty (prior art) searches, and the practical application of inventiveness may change as certain claimed inventions may be “obvious” to a person of ordinary skill in the art (“POSITA”) due to the increasing use of AI systems. Any future changes will likely emerge in legal decisions at European (EPO Boards of Appeal) or national levels where patents will either be upheld or not. 

A patent application must also sufficiently disclose the invention. The “black box” nature of some AI systems may present challenges to this requirement. In that regard, it has been suggested that a mechanism to deposit AI algorithms be established, akin to that for microorganisms (the Budapest Treaty). Although it is as yet unclear that a deposit system for AI algorithms would be useful, it seems advisable to at least consider the possibility of requiring applicants to provide this type of information, while maintaining sufficient safeguards to protect all confidential information to the extent it is required under EU or international rules. 

Finally, inventions that might otherwise be patentable might be protectable as trade secrets under the 2016 Trade Secrets Directive, a topic for future study as it is outside the scope of the current work. 

Our analysis for EU patent law and AI leads to the following conclusions and recommendations:

• The EPC is currently suitable to address the challenges posed by AI technologies in the context of AI-assisted inventions or outputs. 

• When assessing novelty, IPOs and the EPO should consider investing in maintaining a level of technical capability that matches the technology available to sophisticated patent applicants. 

• When assessing the inventive step, it may be advisable to update the EPO examination guidelines to adjust the definition of the POSITA and secondary indicia as to track developments in AI-assisted inventions or outputs. 

• When assessing sufficiency of disclosure, it would be useful to study the feasibility and usefulness of a deposit system for AI algorithms and/or training data and models that would require applicants in appropriate cases to provide information that is relevant to meet this legal requirement. 

• For the remaining potential challenges identified in this report arising out of AI-assisted inventions or outputs it may be good policy to wait for cases to emerge to identify actual issues that require a regulatory response, if any. 

• Further study on the role of alternative IP regimes to protect AI-assisted outputs, such as trade secret protection, unfair competition and contract law, should be encouraged.

Medicines Access and global trade

The Directors-General of the World Trade Organisation, World Health Organization and World Intellectual Property Organization have released a new edition of the Trilateral Study on Access to Medical Technologies and Innovation which 

seeks to strengthen the understanding of the interplay between the distinct policy domains of health, trade and intellectual property (IP), and how they affect innovation and access to medical technologies, such as medicines, vaccines and medical devices. The second edition provides an improved, evidence-based foundation for policy debate and informed decision-making at a critical time for global health. 

The Study

  

discusses key factors determining access to medical technologies and innovation, including regarding medicines, vaccines and other medical technologies, such as medical devices and diagnostics. The second edition draws practical lessons from experiences regarding the intersections between public health, IP and trade within the broader perspectives established by the human rights dimension of health and the Sustainable Development Goals (SDGs). The study records numerous significant developments since 2013 when the first edition was launched. Among the new topics covered are antimicrobial resistance and cutting-edge health technologies. The revised edition provides updated data on health, innovation trends in the pharmaceutical sector, and trade and tariffs regarding medical products. It also includes an updated overview of access to medical technologies globally and key provisions in regional trade agreements. In addition, it takes account of developments in IP legislation and jurisprudence.

 

A COVID-19 section at the start of the publication provides a factual overview of the developments and measures taken to address this extraordinary public health crisis, which began after the work on the second edition of the study had been completed. The section guides the reader to parts of the study that are of direct relevance to the issues that have been raised during the pandemic.

It states 

Public health is inherently a global challenge and thus assumes high priority for international cooperation. The World Health Organization (WHO) is the directing and coordinating authority for health, but the interaction between health issues and other policy domains – human rights, development policy, intellectual property (IP) and international trade – creates a strong rationale for cooperation and coordination between the WHO and other international organizations, in particular the World Intellectual Property Organization (WIPO) and the World Trade Organization (WTO). This study and its updated and reviewed second edition have emerged from an ongoing programme of trilateral cooperation among these agencies. It responds to an increasing demand, particularly in developing countries, for strengthened capacity for informed policy-making in areas of intersection between health, trade and IP, focusing on access to and innovation of medicines and other medical technologies. The need for cooperation and coherence at the international level has intensified over the past decades, as successive multilateral decisions have confirmed. 

 The study is set in an evolving health policy context. An integrated approach can reinforce a dynamic, positive interplay between the measures that promote innovation and those that ensure access to vital medical technologies. The aim of the technical cooperation activities of the WHO, WIPO and the WTO is to facilitate understanding of the full range of options and their operational context. This study draws together the materials used in technical cooperation and addresses needs for information in an accessible, systematic format to support ongoing collaborative efforts. 

 

Navigating the study 

 The study has been prepared as a capacity-building resource for policy-makers. The study is structured so as to enable users to grasp the policy essentials, and then to look more deeply into areas of particular interest. After explaining the need for policy coherence and the role of each of the cooperating agencies to address the global disease burden and health risks (see Chapter I), the study lays out a general panorama of the policy landscape (see Chapter II), so that all interrelated elements can be seen in context. It then provides more detailed accounts of issues specifically connected with innovation (see Chapter III) and access (see Chapter IV). The contents reflect the multilateral policy debate over the past two decades, recognizing that innovation and access are inevitably intertwined – both are indispensable ingredients to meeting an evolving global disease burden. 

 ƒƒChapter I presents the general background to health policy relating to medical technologies and to international cooperation in this field, sets out the distinct roles and mandates of the three cooperating agencies, and outlines the global disease burden that defines the essential challenge for health policy.

 

ƒƒChapter II outlines the essential elements of the international framework – health policy, IP and trade policy, including regulatory issues, as well as technical barriers to trade, sanitary and phytosanitary measures, health services and procurement rules. It lays the basis for the following, more detailed analysis of the innovation and access dimensions in Chapters III and IV. It outlines the key insights of economics for medical technology innovation and access. A final section reviews the policy issues associated with traditional medical knowledge and access to genetic resources, in view of its significance for national health systems and as an input to medical research. 

 ƒƒChapter III provides a more detailed overview of policy issues concerning the innovation dimension of medical technologies. The historical pattern of medical research and development (R&D) provides a backdrop for analysing the current R&D landscape. The chapter looks at challenges with overcoming market failures in medical product R&D in areas such as neglected diseases and antimicrobial resistance. It then outlines alternative and complementary instruments to incentivizing and financing R&D. It outlines the role of IP rights in the innovation cycle, including issues relating to IP management in health research and selected pre- and post-grant patent issues. A final section looks at influenza vaccines as a distinct example of innovation management and product development to address a specific global health need. 

ƒƒChapter IV deals with key aspects of the access dimension, describing the context for access to health technologies, with more detailed case studies on access in respect of HIV/AIDS, hepatitis C, tuberculosis (TB), non-communicable diseases (NCDs), and vaccines. It sets out the key determinants of access related to health systems, IP and trade, and it analyses access to health products in specific areas. It reviews in particular pricing policies, transparency across the value chain of medicines and health products, taxes and mark-ups, and procurement mechanisms, as well as regulatory aspects and initiatives to transfer technology and boost local production, patent quality and review procedures, compulsory and voluntary licences, free trade agreements and international investment agreements, tariffs and competition policy. 

 As access and innovation issues are increasingly considered across a broader range of policy areas, a more diverse set of stakeholders, values, experience, expertise and empirical data now shapes and informs policy debates, through: ƒƒgreater diversity of policy voices, creating opportunities for cross-fertilization between traditionally distinct policy domains ƒƒenhanced possibilities for harvesting the practical lessons of a far wider range of innovation and access initiatives ƒƒimproved global inclusiveness, quality and availability of empirical data on a range of interconnected factors, including the global health burden, access and pricing of medicines, regulatory and trade policy settings, and national IP systems. 

 The cross-cutting character of these policy domains means that some themes are introduced in Chapter II, in the course of sketching out the general policy framework, and are later elaborated in Chapter III and/or Chapter IV, which look in more detail at how these elements have bearing on innovation and access, respectively. For example, the general elements and principles of IP policy are set out in Chapter II, while Chapter III elaborates aspects of IP policy, law and practice that bear particularly on innovation of medical technologies, and Chapter IV considers how specific aspects of IP impact access to technologies. Similarly, the broad rationale for regulation of medical technologies is set out in Chapter II, and Chapters III and IV deal with the implications of product regulation, respectively, for the innovation process and for access to medical technologies. Regarding trade policy, Chapter II sets out the main elements, and Chapter IV considers the impact of trade and trade policy settings on access to medicines and other medical technologies.

 

The global burden of disease necessitates dynamic responses

 

The global burden of disease is in transition. Populations are ageing due to progress in preventing and treating infectious diseases. But the burden of NCDs in low- and middle-income countries (LMICs) is rising, leadingtoadoubleburdenofdisease(seeChapterI, section C). While preventive measures with respect to lifestyle, physical inactivity, tobacco use and harmful use of alcohol, nutrition and environmental factors are key, the innovation system has to adjust to these changes in the global disease burden. The focus on access to medicines – which, in the past, has been on communicable diseases such as HIV/AIDS, TB and malaria – has broadened. Access to treatments for NCDs, including expensive cancer treatments in middle- income countries, will be the challenge of the future and the focus of the access debate (see Chapter IV, section B.4)

 

Access to medicines and the right to health

 

Access to medicines and health services is an element of the fulfilment of the right of everyone to the enjoyment of the highest attainable standard of health. Furthering access to medicines is also part of the United Nations Sustainable Development Goals (SDGs) (see Chapter II, section A.1–3). Lack of access to health technologies is rarely due to a single factor. The “value chain” of medicines and health products (see Figure 4.3) includes R&D, regulation, selection, procurement and supply, distribution, prescribing of medicines and diagnostics, dispensing, and responsible use (see Chapter IV, section A.2). Selection of the medications requires a health system to identify which medicines are most important to address the national burden of disease. This selection can be guided by the WHO Model List of Essential Medicines. Political commitment to adequate and sustainable funding is a basic condition for effective and sustainable access. Universal health coverage (UHC) has crystallized as a key aim of the SDGs (see Chapter IV, section A.1). Affordable prices are a critical determinant of access to medicines, especially in countries where the public health sector is weak and a large part of the population pays for medicines out of pocket. Generic medicine policies are key interventions to control health budgets and make medicines and other health products and services more affordable. Yet even generic medicines can still be unaffordable to health systems. A substantial part of the global population cannot access even the most basic medicines (see Chapter IV, section A.3). The overarching condition for providing access to needed medical technologies and health services is a functioning national health-care system (see Chapter IV, section A.4–12.).

 

Efforts to scale up treatment coverage for HIV/AIDS have become a major focus for policy-makers since the turn of the millennium. Low prices for generic antiretroviral treatments have helped governments and donor agencies strive to end the AIDS epidemic by 2030, as set out in target 3.3 of the SDGs (see Chapter IV, section B.1). In the area of antimicrobial resistance (AMR), there is a need to simultaneously secure wide availability of core antimicrobials, while also ensuring good stewardship (appropriate antimicrobial use to improve patient outcomes and minimize the development and spread of resistance) and the research in, and development of, new antimicrobials (see Chapter II, section A.5, Chapter III, section C.2 and Chapter IV, section B.2).

 

While most cases of TB can be successfully treated with medicines that have been available for many decades and are low cost, there has been growing concern about drug-resistant TB. Three new medicines were approved between 2012 and 2019 to treat drug-resistant TB, but access to them has been limited for reasons including limited clinical data, lack of national registration, high prices and a lag in implementing new treatment guidelines (see Chapter IV, section B.3).

 

NCDs put an enormous and continuous financial strain on household budgets, and major gaps in access to both originator and generic medicines for NCDs persist. Shortcomings in access have been highlighted, for example, for newer cancer treatments and insulin for diabetes. For all countries, the cost of inaction far outweighs the cost of taking action on NCDs (see Chapter IV, section B.4). Health systems, including in high-income countries, face rising launch prices, in particular for cancer and “orphan” medicines.

 

Hepatitis C has seen treatment breakthroughs, but these new treatments entered the market at very high prices, leading to treatment being unavailable, rationed or delayed in numerous countries. Thanks to the conclusion of licensing agreements for some of the treatments, generics are available at relatively low prices in most LMICs (see Chapter IV, section B.5). National immunization programmes are a highly effective public health tool for the prevention of illness and the spread of infectious diseases. Distinct market conditions and know-how requirements create a different landscape for the development and dissemination of vaccines (see Chapter III, section B.4(e) and Chapter IV, section B.7; see also Chapter III, section E). Other areas addressed by the study are access to paediatric formulations and medical devices (see Chapter IV, sections B.6 and B.8).

 

Measures to contain costs and increase access

 

Governments employ many different means to contain costs for medical technologies. Policies aimed at increasing access concern areas such as procurement, pricing and IP (see Chapter IV, sections A and C), and they increasingly use health technology assessments to control costs (see Chapter IV, section A.4). Import tariffs (see Chapter IV, section D.1), various taxes (see Chapter IV, section A.5) and mark-ups along the supply chain (see Chapter IV, section A.6) can increase consumer prices and constrain access, and can also be targeted by cost- containment policies, which must, however, ensure sustainable margins for commercial suppliers in order to be economically viable.

 

Differential pricing applied by companies can be a complementary tool to increase access. Price differentials may exist across different geographical areas or according to differences in purchasing power and socio- economic segments (see Chapter IV, section A.4(g)). Another strategy for enhanced access to medicines is to promote the development of local production capacity and leverage technology transfer. Policy coherence associated with local production is crucial to achieving sustainable public health and industrial development benefits (see Chapter IV, section A.10).

 

The WTO Agreement on Trade-Related Aspects of Intellectual Property Rights (TRIPS Agreement) makes available to WTO members flexibilities in implementing access policies, such as patentability criteria and patent review procedures, and regulatory review exceptions (see inter alia Chapter II, section B.1 and Chapter IV, section C.3). With regard to access to patented products, these flexibilities include the use of compulsory or government-use licensing, wherein generic versions of the patented product can be locally manufactured or imported without the authorization of the patent holder.

 

Regulation of health technologies

 

Regulation of health technologies addresses essential health policy objectives: products must be safe, efficacious and of adequate quality. It also shapes the landscape for access and innovation. Regulatory review processes affect the time and cost it takes to bring new products to market and may delay market entry of new products (see Chapter II, section A.6).

 

Clinical trials are research studies in which groups of human participants are enrolled to evaluate the safety and/or effectiveness of new health technologies. The registration and publication of clinical trials are important for public health. The WHO considers registration of clinical trials a scientific and ethical responsibility and maintains the International Clinical Trials Registry Platform. From the perspective of public health policy, clinical trial results should be publicly available, so that researchers and other interested groups can assess the efficacy and potential side effects of new products (see Chapter III, section B.7). The emergence of biotherapeutic medicines has raised challenges for regulatory systems, notably with regard to regulating similar biotherapeutic (also termed biosimilar) products (see Chapter II, section A.6). Another challenge for regulatory systems is posed by substandard and falsified (SF) medical products, which are found in all parts of the world but are typically a much greater problem in regions where the regulatory and enforcement systems are weak. To effectively combat SF medical products, regulatory intervention may be required, whereastheapproachtofalsifiedorcounterfeitmedical products may involve criminal investigation (see Chapter II, section B.1(f) and Chapter IV, sections A.12 and C.3(h)). WHO prequalification has contributed substantially to improving access to quality medical products in developing countries through ensuring compliance with quality standards (see Chapter IV, section A.11(a)).

 

Innovation in medical technologies: the evolving policy landscape

 

Innovation in medical technologies requires a complex mix of private- and public-sector inputs. It differs from innovation more generally due to the ethical dimension of health research, a rigorous regulatory framework, liability questions and the high cost and high risk of failure. Economic, commercial, technological and regulatory factors have precipitated rapid change in the current landscape for R&D, involving more diverse innovation models and a wider range of active players. Providing adequate incentives to absorb the high cost and associated risks and liabilities is a central policy challenge; this has been the historic role of the patent system, in particular as applied to pharmaceuticals. While estimates vary of the actual cost of medical research and product development, innovation is undoubtedly costly and time consuming. The risk and uncertainty of innovation increases R&D costs in this sector, which include the development costs of the vast majority of inventions that fail before reaching the market (see Chapter III, section B.3). Rising expenditure for medical research has not been matched by a proportionate increase in new products entering the market, sparking a debate about research productivity and a quest for new models of innovation and for financing R&D. Many initiatives are exploring new strategies for product development, thus informing a rich debate about how to improve and diversify innovation structures to address unmet health needs. Current policy discussions have identified possibilities for open innovation structures, and a range of “push and pull” incentives, including schemes such as prize funds that would delink the price of products from the cost of R&D (see Chapter III, section C.5). The WHO Consultative Expert Working Group on Research and Development: Financing and Coordination recommended some of these options, including beginning negotiations on a globally binding convention or treaty on R&D (see Chapter III, sections C.4 and C.5(i)).

 

New thinking on industry’s role and structure and the public/ private divide

 

The evolving innovation landscape is driving change in the pharmaceutical industry. Driving factors include rising global spending on prescription drugs, increasing payer scrutiny of prescription drug prices in high-income markets, the progress of non-profit initiatives engaged in medical research and product development, new research tools and platform technologies, increased industry focus on personalized medicines, and the greater share of global demand from large middle- income-country markets. The historic industry model of vertically integrated in-house R&D is opening up to more diverse and collaborative structures, with major industry players developing products by integrating technologies that are licensed in or acquired through mergers and integration of smaller firms. Originator firms have also invested in generic production capacity. An increasing proportion of new medicines are for orphan indications. At the same time, most large pharmaceutical companies have withdrawn from antimicrobial research in light of the poor potential for investment returns.

 

The role of public research and academic institutions, increasingly, also in developing countries, has come under the spotlight as those institutions seek to reconcile public-interest responsibilities with the capital and product development capacity offered by private-sector partnerships (see Chapter II, section C; Chapter III, sections A and B; and Chapter IV, section D.5(d)).

 

Research and innovation gaps in neglected diseases and other areas: a policy challenge generating practical initiatives

 

For diseases that predominantly affect people living in poorer countries, the innovation cycle is not self-sustaining and fails to address their health needs, due to low potential for revenue, underfunded health services and generally weak upstream research capacity. A similar situation arises where sales are likely to be low, for example, in antibiotics and treatments or vaccines for emerging pathogens. In this type of environment, market-based incentives, such as patent protection, cannot by themselves address the health needs of developing countries. The landscape of health research for these diseases has evolved. Product development partnerships (PDPs) have been a significant development over the past decade, drawing together not-for-profit entities and industry players, with major philanthropic funding, significantly increasing the number of products in development for neglected diseases, and identifying pathways regarding existing research gaps (see Chapter III, section C.6). Originator pharmaceutical companies also engage increasingly in philanthropic research. Several companies have established dedicated research institutes to research diseases disproportionately affecting developing countries or participated in cooperative projects to share assets and knowledge, such as WIPO Re:Search, which has been developed to make better use of IP-protected assets and improve access (see Chapter III, section C.6–8). However, much more needs to be done by the international community in this area. AMR has been recognized as a global threat, and is addressed by many countries in national action plans and by a WHO Global Action Plan on Antimicrobial Resistance. Private investments are insufficient to fill current R&D gaps. New non-profit initiatives have been established by a range of actors to reinvigorate the pipeline of drug candidates.

 

The IP system at the centre of debate on innovation and access

 

Apart from the patent system and test data protection, other relevant IP rights include trademarks, for example, the relationship with international non-proprietary names (INNs), and copyright, for example, covering the package insert of medicines (see Chapter II, section B.1(d)–(e)). The patent system has been widely used for health technologies, especially by the pharmaceutical sector. Indeed, the pharmaceutical sector stands out in terms of its dependence on patents to capture returns to R&D, but its role in innovation and how to enhance its effectiveness are matters of continuing debate (see Chapter III, section B). The rationale for having patents is to make investment in innovation attractive and to offer a mechanism that ensures that the knowledge contained in the patent documents is accessible. Patents can function to structure, define and build innovation partnerships. The role of intellectual property rights (IPRs) in the innovation cycle is addressed in Chapter III, section D. The impact of patents on access is complex and an area of particular focus. IP policy, the laws that embody the policy, and the administration and enforcement of those laws each aim to balance and accommodate a range of legitimate interests in a way that promotes overall public welfare (see Chapter II, section B.1).

 

The global IP framework is defined in particular by the treaties administered by WIPO and the TRIPS Agreement, which forms part of the WTO legal system and in turn incorporates the substantive provisions of several WIPO treaties, including the Paris Convention. The TRIPS Agreement sets minimum standards for IP protection and enforcement. For example, patents must be available for any innovation in all fields of technology, provided they are new, involve an inventive step (or are non-obvious) and are capable of industrial application (or are useful). Substantive patent examination leads to a higher degree of legal certainty regarding the validity of granted patents. Where search and examination are of low quality, this can have an adverse effect because it may raise false expectations in respect of the patent’s validity. Review procedures allow courts and other review bodies to correct erroneous grant of patents and give relief where necessary, in order to ensure that the patent system, as a whole, functions as a public-interest policy tool. Strict patentability criteria and strict patent examination supported by patenting examination guidelines contribute to preventing strategies employed to delay the entry of generic competition, such as “evergreening” (see Chapter III, section D.4(b) and Chapter IV, section C.1).

 

Integral to the patent system is the requirement to disclose the innovation described in patent documents, thus creating an extensive knowledge base. The resultant patent information serves as a tool for charting freedom to operate, potential technology partnerships, and procurement options, as well as giving policy-makers insights into patterns of innovation (see Chapter II, section B.1(b)(viii)–(xi)). While patent information has become more accessible, coverage of data for many LMICs remains a challenge. Recent trends show a growth in patent applications on health technologies from key upper-middle-income economies (see Chapter III, section A.5).

 

The protection of clinical trial data also illustrates the complex relationship between the IP system and innovation and access. Protecting these data against unfair commercial use is important given the considerable efforts made to generate these data, which are needed to bring new medicines to the market. For this purpose, in some jurisdictions, newly approved medicines are protected by periods of regulatory exclusivity, such as data exclusivity and market exclusivity, during which the medicines regulatory authority may not accept a submission for approval of a generic and/or may not approve a generic for marketing. The TRIPS Agreement requires protection of test data but does not specify the exact form it should take, and national authorities have taken diverse approaches (see Chapter II, section B.1(c)).

 

How IP is managed can determine its impact on public health

 

Appropriate licensing of patents can help build partnerships and enable innovation through cooperation to bring new health technologies to fruition. Private- sector licensing strategies typically aim at commercial objectives, but public-sector entities can use patents to leverage public health outcomes. New models of socially responsible licensing protect IP while ensuring that new health technologies are available and affordable. Public– private partnerships have resulted in creative licensing agreements that forgo profit maximization in favour of providing essential technologies to poorer countries at affordable prices. Voluntary licences also form part of corporate social responsibility programmes, especially for HIV/AIDS treatments.

 

The Medicines Patent Pool has reinforced the trend towards voluntary licensing programmes that increase access to medicines by enabling new formulations and enhancing provision of cheaper generic medicines for developing countries (see Chapter IV, section C.3(b)).

 

Policy options and IP flexibilities also impact on public health

 

A wide range of policy options and flexibilities are built into the international IP regime and can be used to pursue public health objectives. Action is needed at the regional and domestic levels to determine how best to implement such flexibilities, so that the IP regime responds to each country’s individual needs and policy objectives. Key options include transition periods for least-developed countries (LDCs) (see Chapter II, section B.1), differing IP exhaustion regimes, refining the criteria for grant of a patent, making available pre-grant and post- grant review procedures, exclusions from patentability and exceptions and limitations to patent rights once granted, including regulatory review exception (“Bolar” exception) to facilitate market entry of generics, as well as compulsory licences and government-use licences. Countries have used one or more of these instruments to improve access to medicines for both communicable and noncommunicable diseases (see Chapter IV, section C.1–3). WTO members amended the TRIPS Agreement to permit wider use of compulsory licensing. The additional flexibility enables members that need to import medicines because of insufficient or no local manufacturing capacity to seek supply from generic manufacturers in other countries where the medicines are patent protected. For this purpose, potential exporting members can grant special compulsory licences exclusively for export under what is termed the “Special Compulsory Licensing System” (see Chapter IV, section C.3 and Annex III). While the legal scope for flexibilities is now clearer, thanks also to the Doha Declaration, and some flexibilities are widely implemented (such as “Bolar” exceptions), policy debate continues on the use of measures such as compulsory licensing.

 

International trade is an essential avenue to access

 

International trade is vital for access to medicines and other medical technologies, markedly so for smaller and less-resourced countries. Trade stimulates competition, which, in turn, reduces prices and offers a wider range of suppliers, improving security and predictability of supply. Trade policy settings – such as tariffs on medicines, pharmaceutical ingredients and medical technologies – therefore directly affect the accessibility of such products (see Chapter II, section B.3–5 and Chapter IV, section D). Trade policy and the economics of global production systems are also key factors in strategic plans to build domestic production capacity in medical products. Non- discriminatory domestic regulations founded on sound health policy principles are also important for a stable supply of quality health products. Access to foreign trade opportunities can create economies of scale to support the costs and uncertainties of medical research and product development processes. Developed countries have dominated trade in health- related products, but India and China have emerged as leading global exporters of pharmaceutical and chemical inputs and, in the case of China, of medical devices, and some other developing countries have shown strong export growth recently. Countries’ imports of health-related products differ considerably according to their level of development, illustrating substantial and widening gaps in access: in 2016, a small number of countries (China, European Union member states, Japan and the United States) accounted for the majority of imports. Some new players are emerging from developing countries, while LDC imports have grown least, starting from a low base.

 

Import tariffs on health-related products can affect access: since they increase cost early in the value chain, their impact on price may be magnified. Developed countries have largely eliminated such tariffs, in line with the WTO Pharmaceutical Agreement of 1994. Other countries have reduced tariffs significantly, but the picture is still mixed: some developing countries structure tariffs to promote local production, while LDCs apply lower tariffs (see Chapter IV, section D.1).

 

Competition policy promotes effective innovation and supports access

 

Competition policy is relevant to all stages in the process of supplying health technologies to patients, from their development to their sale and delivery. The creation of sound, competitive market structures through competition law and enforcement thus has an important role to play in both enhancing access to health technologies and fostering innovation in the pharmaceutical sector. It can serve as a corrective tool if IP rights hinder competition and thus constitute a potential barrier to innovation and access. Competition authorities in several jurisdictions have taken action to address anti-competitive practices in the pharmaceutical sector, including some patent settlements, certain licensing practices and pricing policies. Competition policy also has an important role to play in preventing collusion among suppliers of medical technology participating in procurement processes (see Chapter II, section B.2 and Chapter IV, section D.2).

 

Access to medical technologies through more effective government procurement

 

In many countries, access to medical technologies largely results from government procurement, with pharmaceuticals made available through public funds or subsidies. Procurement systems aim to obtain medicines and other medical products of good quality, at the right time, in the required quantities and at favourable costs. These principles are particularly important in the health sector, given the large expenditures, health impact of value for money and quality issues, with some programmes reportedly paying considerably more than necessary for medicines (see Chapter IV, section A.8).

 

Procurement policies favouring open and competitive tendering, coupled with the rational use of medicines, become all the more important in ensuring continued access in a fiscal climate in which national budgets are under pressure and philanthropic programmes face funding constraints. Good governance in procurement is consistent with increasing access to medical technologies through lower prices and uninterrupted supply. The WTO’s plurilateral Agreement on Government Procurement provides an international framework of rules to promote efficiency and good governance in public procurement, with particular application to procurement of medicines, promoting transparency, fair competition and improved value for public expenditure (see Chapter II, section B.4).

 

Free trade agreements have increasing relevance to access

 

The international policy and legal framework has been made more complex by the growth of free trade agreements (FTAs) and international investment agreements, outside the established multilateral fora (see Chapter II, section B.5 and Chapter IV, section C.5). Policy debate in this context has focused on IP, such as patent term extensions, regulatory exclusivities and other measures, such as patent linkage, as well as pharmaceutical regulation provisions n these agreements, and their impact on access to medicines. The later generation of FTAs often includes side letters or provisions confirming the Doha Declaration and, in particular, the right of WTO members to take measures to protect public health. These agreements also set standards in other policy areas with implications for access, notably, standards established on government procurement and competition policy, as well as preferential tariffs on pharmaceuticals, inputs and other health products. FTAs usually require implementation in domestic laws, which, in turn, can directly affect access to, and innovation in, medicines and medical technologies.