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Safeguards for accelerated market authorization of vaccines in Europe
Safeguards for accelerated market authorization of vaccines in Europe

by Suzan Slijpen & Mauritz Kop

This article has been published by the Stanford Law School ‘Center for Law and the Biosciences’, Stanford University, 15 March 2021. link to the full text: https://law.stanford.edu/2021/03/15/safeguards-for-accelerated-market-authorization-of-vaccines-in-europe/

The first COVID-19 vaccines have been approved

People around the globe are concerned about safety issues encircling the accelerated introduction of corona vaccines. In this article, we discuss the regulatory safeguards for fast-track market authorization of vaccines in Europe. In addition, we explain how the transmission of European Union law into national Member State legislation works. We then clarify what happens before a drug can be introduced into the European market. We conclude that governments should build bridges of mutual understanding between communities and increase trust in the safety of authorized vaccines across all population groups, using the right messengers.

Drug development normally takes several years

Drug development normally takes several years. The fact that it has been a few months now seems ridiculously short. How is the quality and integrity of the vaccine ensured? That people - on both sides of the Atlantic - are concerned about this is entirely understandable. How does one prevent citizens from being harmed by vaccines and medicines that do not work for everyone, because the admission procedures have been simplified too much?

The purpose of this article is to shed a little light upon the accelerated market authorization procedures on the European continent, with a focus on the situation in the Netherlands.

How a vaccine is introduced into the market

In June 2020, the Dutch government, in close cooperation with Germany, France and Italy, formed a Joint Negotiation Team which, under the watchful eye of the European Commission, has been negotiating with vaccine developers. Its objective: to conclude agreements with drug manufacturers at an early stage about the availability of vaccines for European countries. In case these manufacturers are to succeed in developing a successful vaccine for which the so-called Market Authorization (MA) is granted by EMA or CBG, this could lead to the availability of about 50 million vaccines (for the Netherlands alone).

Who is allowed to produce these vaccines?

Who is allowed to produce these vaccines? The Dutch Medicines Act is very clear about this. Only "market authorization holders" are allowed to manufacture medicines, including vaccines. These are parties that have gone through an extensive application procedure, who demonstrably have a solid pharmaceutical quality management system in place and have obtained a pharmaceutical manufacturing license (the MIA, short for Manufacturing and Importation Authorisation). This license is granted after assessment by the Health and Youth Care Inspectorate of the Ministry of Health, Welfare & Sport (IGJ) – by Farmatec. Farmatec is part of the CIBG, an implementing body of the Ministry of Health, Welfare and Sport (VWS). The M-license is mandatory for parties who prepare, or import medicines.

Read more at the Stanford Center for Law and the Biosciences!

Read more on manufacturing licenses, fast track procedures and market authorization by the European Medicines Agency (EMA) and the EC, harmonisation and unification of EU law, CE-markings, antigenic testing kits, mutations, reinfection, multivalent vaccines, mucosal immunity, Good Manufacturing Practices (GMP), pharmacovigilance, the HERA Incubator, clinical trials, compulsory vaccination regimes and continuous quality control at Stanford!

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Biomedische wetenschappen, eHealth, EU-wetgeving, Geneesmiddelenrecht, Geneesmiddelenwet, Gezondheidsrecht, Medicine, Vergunningen, Wetgeving, VaccinsMauritz KopSlijpen LegalVaccines, Corona, COVID-19, SARS-CoV-2, Medication, Law and Biosciences, Stanford Law School, Suzan Slijpen, Mauritz Kop, Stanford University, Marked Authorization, RIVM, Europe, USA, Pharmaceutical Manufacturing License, Dutch Medicines Act, Slijpen Legal, AIRecht, CIBG, Farmatec, EudraGMDP, IGJ, CBG, EMA, FDA, Warp Speed, EUA, fast-track, herd immunity, CHMP, GMP, quality management system, pharmacovigilance, Healthcare, Intellectual Property, Artificial Intelligence, clinical trials, innovation, democracy, ethics, fundamental rights, technology transfer, HERA Incubator, harmonisation, unification, reception, EU law, compulsory vaccination regimes, multivalent vaccines, CE-marking, mutations, reinfection, antigenic testing kits, nasal spray, mucosal immunity
Regulating Transformative Technology in The Quantum Age: Intellectual Property, Standardization & Sustainable Innovation
Regulating Transformative Technology in The Quantum Age: Intellectual Property, Standardization & Sustainable Innovation

Stanford - Vienna Transatlantic Technology Law Forum, Transatlantic Antitrust and IPR Developments, Stanford University, Issue No. 2/2020 (Forthcoming)

New Stanford cutting edge tech law research: “Regulating Transformative Technology in The Quantum Age: Intellectual Property, Standardization & Sustainable Innovation”.

Quantum technology has many legal aspects

The behavior of nature at the smallest scale can be strange and counterintuitive. In addition to unique physical characteristics, quantum technology has many legal aspects. In this article, we first explain what quantum technology entails. Next, we discuss implementation and areas of application, including quantum computing, quantum sensing and the quantum internet. Through an interdisciplinary lens, we then focus on intellectual property (IP), standardization, ethical, legal & social aspects (ELSA) as well as horizontal & industry-specific regulation of this transformative technology.

The Quantum Age raises many legal questions

The Quantum Age raises many legal questions. For example, which existing legislation applies to quantum technology? What types of IP rights can be vested in the components of a scalable quantum computer? Are there sufficient market-set innovation incentives for the development and dissemination of quantum software and hardware structures? Or is there a need for open source ecosystems, enrichment of the public domain and even democratization of quantum technology? Should we create global quantum safety, security and interoperability standards and make them mandatory in each area of application? In what way can quantum technology enhance artificial intelligence (AI) that is legal, ethical and technically robust?

Regulating quantum computing, quantum sensing & the quantum internet

How can policy makers realize these objectives and regulate quantum computing, quantum sensing and the quantum internet in a socially responsible manner? Regulation that addresses risks in a proportional manner, whilst optimizing the benefits of this cutting edge technology? Without hindering sustainable innovation, including the apportionment of rights, responsibilities and duties of care? What are the effects of standardization and certification on innovation, intellectual property, competition and market-entrance of quantum-startups?

The article explores possible answers to these tantalizing questions.

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QuantumMauritz KopSlijpen LegalQuantum Technology, Machine Learning, AI & Quantum Computing Hybrids, Software, Intellectual Property, Patents, Database Rights, Copyright, Trade Secrets, Public Domain, Standardisation, Regulation, Technology, Certification, Ethics, ELSA, Competition Law, Democracy, Human Rights, Innovation Policy, Mauritz Kop, Stanford-Vienna Transatlantic Technology Law Forum, Stanford Law School
The Right to Process Data for Machine Learning Purposes in the EU
The Right to Process Data for Machine Learning Purposes in the EU

Harvard Law School, Harvard Journal of Law & Technology (JOLT) Online Digest 2020, Forthcoming

New interdisciplinary Stanford University AI & Law research article: “The Right to Process Data for Machine Learning Purposes in the EU”.

Data Act & European data-driven economy

Europe is now at a crucial juncture in deciding how to deploy data driven technologies in ways that encourage democracy, prosperity and the well-being of European citizens. The upcoming European Data Act provides a major window of opportunity to change the story. In this respect, it is key that the European Commission takes firm action, removes overbearing policy and regulatory obstacles, strenuously harmonizes relevant legislation and provides concrete incentives and mechanisms for access, sharing and re-use of data. The article argues that to ensure an efficiently functioning European data-driven economy, a new and as yet unused term must be introduced to the field of AI & law: the right to process data for machine learning purposes.

The state can implement new modalities of property

Data has become a primary resource that should not be enclosed or commodified per se, but used for the common good. Commons based production and data for social good initiatives should be stimulated by the state. We need not to think in terms of exclusive, private property on data, but in terms of rights and freedoms to use, (modalities of) access, process and share data. If necessary and desirable for the progress of society, the state can implement new forms of property. Against this background the article explores normative justifications for open innovation and shifts in the (intellectual) property paradigm, drawing inspiration from the works of canonical thinkers such as Locke, Marx, Kant and Hegel.

Ius utendi et fruendi for primary resource data

The article maintains that there should be exceptions to (de facto, economic or legal) ownership claims on data that provide user rights and freedom to operate in the setting of AI model training. It concludes that this exception is conceivable as a legal concept analogous to a quasi, imperfect usufruct in the form of a right to process data for machine learning purposes. A combination of usus and fructus (ius utendi et fruendi), not for land but for primary resource data. A right to process data that works within the context of AI and the Internet of Things (IoT), and that fits in the EU acquis communautaire. Such a right makes access, sharing and re-use of data possible, and helps to fulfil the European Strategy for Data’s desiderata.

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Artificial Intelligence, Intellectual PropertyMauritz KopSlijpen LegalRight to Process Data, Data Sharing Access and Re-Use, Ius Utendi (usus) et Fruendi (fructus), Quasi Usufruct, Locke, Kant, Machine Learning, AI, Intellectual Property, European Data Act, Training Datasets, Database Rights, Copyright, Trade Secrets, Property Paradigm, Public Domain, Open Innovation, Mauritz Kop, Stanford University, Harvard Law School, Harvard Journal of Law & Technology
Machine Learning & EU Data Sharing Practices
Machine Learning & EU Data Sharing Practices

Stanford - Vienna Transatlantic Technology Law Forum, Transatlantic Antitrust and IPR Developments, Stanford University, Issue No. 1/2020

New multidisciplinary research article: ‘Machine Learning & EU Data Sharing Practices’.

In short, the article connects the dots between intellectual property (IP) on data, data ownership and data protection (GDPR and FFD), in an easy to understand manner. It also provides AI and Data policy and regulatory recommendations to the EU legislature.

As we all know, machine learning & data science can help accelerate many aspects of the development of drugs, antibody prophylaxis, serology tests and vaccines.

Supervised machine learning needs annotated training datasets

Data sharing is a prerequisite for a successful Transatlantic AI ecosystem. Hand-labelled, annotated training datasets (corpora) are a sine qua non for supervised machine learning. But what about intellectual property (IP) and data protection?

Data that represent IP subject matter are protected by IP rights. Unlicensed (or uncleared) use of machine learning input data potentially results in an avalanche of copyright (reproduction right) and database right (extraction right) infringements. The article offers three solutions that address the input (training) data copyright clearance problem and create breathing room for AI developers.

The article contends that introducing an absolute data property right or a (neighbouring) data producer right for augmented machine learning training corpora or other classes of data is not opportune.

Legal reform and data-driven economy

In an era of exponential innovation, it is urgent and opportune that both the TSD, the CDSM and the DD shall be reformed by the EU Commission with the data-driven economy in mind.

Freedom of expression and information, public domain, competition law

Implementing a sui generis system of protection for AI-generated Creations & Inventions is -in most industrial sectors- not necessary since machines do not need incentives to create or invent. Where incentives are needed, IP alternatives exist. Autonomously generated non-personal data should fall into the public domain. The article argues that strengthening and articulation of competition law is more opportune than extending IP rights.

Data protection and privacy

More and more datasets consist of both personal and non-personal machine generated data. Both the General Data Protection Regulation (GDPR) and the Regulation on the free flow of non-personal data (FFD) apply to these ‘mixed datasets’.

Besides the legal dimensions, the article describes the technical dimensions of data in machine learning and federated learning.

Modalities of future AI-regulation

Society should actively shape technology for good. The alternative is that other societies, with different social norms and democratic standards, impose their values on us through the design of their technology. With built-in public values, including Privacy by Design that safeguards data protection, data security and data access rights, the federated learning model is consistent with Human-Centered AI and the European Trustworthy AI paradigm.

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Artificial Intelligence, Data, EU-wetgeving, Europees recht, PrivacyMauritz KopSlijpen LegalData Sharing, Machine Learning, Artificial Intelligence, Intellectual Property, Training Corpora, Mixed Dataset, Sui Generis Database Right, Copyright, Patent, Trade Secret, Data Ownership, Property Law, Public Domain, Res Publicae ex Machina, Policy, AI-Regulation, Technology, Data Protection, Privacy, GDPR, FFD, Data-Driven Economy, Machine Legibility, Federated Learning, Future, Vision, Design, Values, Trustworthy AI, Human-Centered AI, Open Data, Legal Reform, Trade Secret Directive, Database Directive, EU Copyright Directive, Antitrust, Competition Law, Stanford University