Publication date: February 23, 2026
Labor law, as it regulates one of the key aspects of life, which is performing work in order to obtain funds ensuring a decent living, is one of the most important branches of law. As such, it must be constantly amended to adapt to the dynamically changing reality of life.
Publication date: February 16, 2026
Notarial deposit is one of the most important institutions of notarial law, serving as an instrument to protect the interests of parties to legal transactions that, due to their nature, value, or complexity, require a higher level of security. Its primary role is to create a mechanism enabling the safekeeping of specific items—most often cash—by a notary until strictly defined conditions are met.
The importance of notarial deposits extends far beyond traditional real estate transactions. Today, this institution is increasingly used in professional transactions, particularly in commercial, corporate, investment, and restructuring transactions, where it is essential to ensure the neutrality of the intermediary and full transparency in the execution of obligations.
Publication date: February 16, 2026
The European Green Deal has been the subject of much discussion in public debate since its announcement. As part of this ambitious project, the European Commission aimed to achieve, among other things, climate neutrality for the entire European Union by 2050. One of the key aspects of this economic transformation was to focus on more sustainable products and, in particular, a transition to a circular economy. Sustainable products were considered a prerequisite for implementing such an economic model.
Publication date: February 12, 2026
The EU Chips Act is a major European legislative package launched to boost the EU’s semiconductor industry, aiming to double its global market share to 20% by 2030, enhance supply chain resilience, and reduce reliance on external chipmakers. The EU Chips Act 2.0 is a proposed follow-up to the 2023 Chips Act, driven by a coalition of EU member states (including Germany, France, Netherlands) in late 2025 to shift from crisis management to long-term industrial strategy. It aims to secure supply chains, boost competitiveness, and accelerate investment by simplifying regulations and targeting R&D.
Publication date: February 12, 2026
In recent years, the importance of artificial intelligence (AI) in drug development, evaluation, and monitoring has grown significantly. AI technologies have the potential to accelerate research, improve predictions of drug efficacy and safety, and reduce the need for animal testing. At the same time, their use presents new challenges. AI models can make errors, be susceptible to unforeseen risks, or use data in a non-transparent manner. To fully realize the benefits of AI while minimizing risks, it is essential to establish clear and common principles for the use of these technologies. In response to these challenges, the European Medicines Agency (EMA) and the US Food and Drug Administration (FDA) have jointly developed ten principles of good practice for the use of AI in the drug lifecycle. This document is fundamental and a framework, not a binding legal regulation – it provides general directions and guidelines that should guide drug manufacturers, applicants, and regulators. These principles indicate how AI should be designed and used to ensure it is ethical, safe, transparent, and based on reliable data. The ten principles also identify areas where international regulators, standards-setting organizations, and other collaborating entities can work together to promote good practice in drug development. These areas of collaboration include: conducting scientific research, creating educational tools and resources for market participants, international harmonization, and developing consensus standards. To facilitate initial analysis, these principles can be grouped into three logical pillars. Principles 1-3 address organizational foundations and people, focusing on interdisciplinary team expertise and ensuring that AI remains under human control within specific, established governance processes. Principles 4-7 address technical quality and model integrity, addressing the “heart” of the technology. Principles 8-10 address accountability and lifecycle, defining standards for documentation, clear communication with users, and continuous monitoring of the model after its implementation. Below is a detailed summary of the 10 principles of good practice for AI in the drug lifecycle:
