This article uses data from several publicly available databases to show that the distribution of intellectual property for frontier technologies, including those useful for sustainable development, is very highly skewed in favor of a handful of developed countries. The intellectual property rights (IPR) regime as it exists does not optimize the global flow of technology and know-how for the attainment of the sustainable development goals and is in need of updating. Some features of the Fourth Industrial Revolution imply that the current system of patents is even more in need of reform than before. COVID-19 vaccines and therapies and the vast inequality in access to these has highlighted the costs of inaction. We recommend several policy changes for the international IPR regime. Broadly, these fall into three categories: allowing greater flexibility for developing countries, reassessing the appropriateness of patents for technologies that may be considered public goods, and closing loopholes that allow for unreasonable intellectual property protections.

There is an increasing gap between the policy cycle’s speed and that of technological and social change. This gap is becoming broader and more prominent in robotics, that is, movable machines that perform tasks either automatically or with a degree of autonomy. This is because current legislation was unprepared for machine learning and autonomous agents. As a result, the law often lags behind and does not adequately frame robot technologies. This state of affairs inevitably increases legal uncertainty. It is unclear what regulatory frameworks developers have to follow to comply, often resulting in technology that does not perform well in the wild, is unsafe, and can exacerbate biases and lead to discrimination. This paper explores these issues and considers the background, key findings, and lessons learned of the LIAISON project, which stands for “Liaising robot development and policymaking,” and aims to ideate an alignment model for robots’ legal appraisal channeling robot policy development from a hybrid top-down/bottom-up perspective to solve this mismatch. As such, LIAISON seeks to uncover to what extent compliance tools could be used as data generators for robot policy purposes to unravel an optimal regulatory framing for existing and emerging robot technologies.

The inclusion of antimicrobial resistance (AMR) and increased research and development (R&D) capabilities in the most recent outline of the World Health Organization’s (WHO’s) international pandemic instrument signals an opportunity to reshape pharmaceutical R&D system in favour of antimicrobial product development. This article explains why the current innovation ecosystem has disadvantaged the creation of antimicrobial products for human use. It also highlights how the COVID-19 pandemic experience can inform and stimulate international cooperation to implement innovative R&D incentives to bring new, life-saving antimicrobial products to the market.

From exoskeletons to lightweight robotic suits, wearable robots are changing dynamically and rapidly, challenging the timeliness of laws and regulatory standards that were not prepared for robots that would help wheelchair users walk again. In this context, equipping regulators with technical knowledge on technologies could solve information asymmetries among developers and policymakers and avoid the problem of regulatory disconnection. This article introduces pushing robot development for lawmaking (PROPELLING), an financial support to third parties from the Horizon 2020 EUROBENCH project that explores how robot testing facilities could generate policy-relevant knowledge and support optimized regulations for robot technologies. With ISO 13482:2014 as a case study, PROPELLING investigates how robot testbeds could be used as data generators to improve the regulation for lower-limb exoskeletons. Specifically, the article discusses how robot testbeds could help regulators tackle hazards like fear of falling, instability in collisions, or define the safe scenarios for avoiding any adverse consequences generated by abrupt protective stops. The article’s central point is that testbeds offer a promising setting to bring policymakers closer to research and development to make policies more attuned to societal needs. In this way, these approximations can be harnessed to unravel an optimal regulatory framework for emerging technologies, such as robots and artificial intelligence, based on science and evidence.

This article explores the role of interoperability in the development of digital public services in Europe, analyzing the effects of an European Union (EU)-level initiative (the European interoperability framework, EIF) and the development of e-Government services on how citizens interact online with public administrations. The EIF is a common EU framework providing guidance on public sector interoperability. EU countries are not mandated to follow the EIF, but they are encouraged to take up its guidance in their respective national interoperability frameworks (NIFs). Against this background, this article tests two hypotheses: (a) the introduction of NIFs facilitates the online interaction between citizens and public administrations and (b) better e-Government services encourage citizens to interact online with public administrations. Both hypotheses are confirmed by a panel data analysis covering 26 European countries over the period 2012–2019. The analysis relies on a dummy variable reflecting the adoption of NIFs, built by carefully examining official documents of the countries in the scope of the analysis. Based on the empirical results, this article puts forward two main policy recommendations. First, efforts to improve e-Government services across Europe should be intensified in order to support the overarching digital agenda of the EU and increase benefits for European citizens. Second, interoperability should become a central element when designing new digital public services. Therefore, the European Commission could foster a common approach to interoperability of digital public services across the EU by strengthening the governance of interoperability initiatives and encouraging the adoption of specific interoperability requirements.

The COVID-19 pandemic has underscored emerging vulnerabilities in the US research and development (R&D) ecosystem. While an open and collaborative environment has been essential for advancing R&D, this approach exposes university-based R&D to a variety of security threats including state-supported efforts, attacks by malicious actors, and insufficient internal mitigation. As the pandemic led to more remote work and online collaboration, the incidence of exploitation has expanded. Increased security measures are needed to insulate and protect the R&D ecosystem, and US innovation more broadly, while maintaining the fundamental qualities that have contributed to its historical success. In this article, we present the Research Integrity Security Certification (RISC) framework. This concept preserves the autonomy of the US higher education system while also suggesting a mechanism whose effect would be a general enhancement of the security of the US university R&D enterprise with minimal additional state involvement. Much of the work in the proposed model is done by market mechanisms and self-interested microeconomic calculations that generate beneficial aggregate effects. The RISC framework modernizes the university R&D enterprise while strengthening it to operate in this evolving security environment.

The combination of advances in knowledge, technology, changes in consumer preference and low cost of manufacturing is accelerating the next technology revolution in crop, livestock and fish production systems. This will have major implications for how, where and by whom food will be produced in the future. This next technology revolution could benefit the producer through substantial improvements in resource use and profitability, but also the environment through reduced externalities. The consumer will ultimately benefit through more nutritious, safe and affordable food diversity, which in turn will also contribute to the acceleration of the next technology. It will create new opportunities in achieving progress towards many of the Sustainable Development Goals, but it will require early recognition of trends and impact, public research and policy guidance to avoid negative trade-offs. Unfortunately, the quantitative predictability of future impacts will remain low and uncertain, while new chocks with unexpected consequences will continue to interrupt current and future outcomes. However, there is a continuing need for improving the predictability of shocks to future food systems especially for ex-ante assessment for policy and planning.

The Internet of Things (IoT) is currently developing fast and its potential as driver of innovative solutions is increasing, pushed by technologies, networks, communication, and computing power, and has the potential to drive the development of technological ecosystems, such as innovation clusters. Innovation clusters are agglomeration of enterprises and research organizations, which cooperate, interact and compete, generating innovation and driving the growth of ecosystems. The narrative around innovation clusters has been developing since many years and policy-makers seek to use such clusters as a policy instrument to support the growth of technology on the one hand and regional and sectoral development on the other hand. This policy paper expands an empirical study on IoT innovation clusters in Europe and places it within the current debate around clusters and innovation clusters to provide evidence-based advice to policy-makers on what may and may not work as public policy measures. The paper highlights the findings of the interaction with several hundred European IoT innovation clusters and points out their points of view on their own creation factors, operational characteristics, and success stories, as well as their expectations in respect to policy interventions for IoT and for clusters. Suggestions for IoT policy-making are provided. The paper has also undertaken an extensive review of up-to date research on innovation cluster creation and performance, thoroughly analyzing the real possibility to define causal relationships between clusters, productivity and economic growth, and business performance, and providing suggestions for policy-makers on the approach to cluster policy.

Health technology assessment conducted to inform decisions during technology development (development-focused or DF-HTA) has a number of distinct features compared with HTA conducted to inform reimbursement and usage decisions. In particular, there are a broad range of decisions to be informed related to the development of a technology; multiple markets and decision makers to be considered; a limited (and developing) evidence base; and constrained resources for analysis. These features impact upon methods adopted by analysts. In this paper, we (i) set out methods of DF-HTA against a timeline of technology development; (ii) provide examples of the methods’ use; and (iii) explain how they have been adapted as a result of the features of DF-HTA. We present a toolkit of methods for analysts working with developers of medical technologies. Three categories of methods are described: literature review, stakeholder consultation, and decision analytic modeling. Literature review and stakeholder consultation are often used to fill evidence gaps. Decision analytic modeling is used to synthesize available evidence alongside plausible assumptions to inform developers about price or performance requirements. Methods increase in formality and complexity as the development and evidence base progresses and more resources are available for assessment. We hope this toolkit will be used in conjunction with the framework of features of DF-HTA presented in our earlier article in order to improve the clarity and appropriateness of methods of HTA used in DF-HTA. We also seek to contribute to a continuing dialogue about the nature of, and the best approach to, DF-HTA.

Target Product Profiles (TPPs) outline the characteristics that new health technologies require to address an unmet clinical need. To date, published TPPs for medical tests have focused on infectious diseases, mostly in the context of low- and middle-income countries. Recently, there have been calls for a broader use of TPPs as a mechanism to ensure that diagnostic innovation is aligned with clinical needs, yet the methodology underpinning TPP development remains suboptimal. Here, we propose that early economic evaluation (EEE) should be integrated within the TPP methodology to create a more rigorous framework for the development of “fit-for-purpose” tests. We discuss the potential benefits that EEE could bring to the core activities underpinning TPP development—scoping, drafting, consensus building, and updating—and argue that using EEE to help inform TPPs provides a more objective, evidence-based, and transparent approach to defining test specifications.