From “drug candidates” to “algorithms and data”: AI drug development is reshaping the IP landscape

[Financial News] As artificial intelligence (AI) is used throughout the drug development process, from identifying drug candidates to clinical trials and regulatory approval, the pharmaceutical and biotech industries’ core competitive assets are rapidly expanding beyond candidate compounds to include AI platforms, algorithms and data.
The Korea Institute of Intellectual Property published on the 3rd a report analyzing policies in major countries, including the United States, the European Union (EU), China and Japan, as well as the intellectual property (IP) strategies of domestic and overseas companies. The report is titled “Analysis of AI Drug Development Policies and IP Trends for Building an AI Bio Ecosystem.”
The report says that major countries are all seeking to develop AI drug development into a strategic national industry, but differ in their support policies and regulatory and IP strategies. The United States is expanding research infrastructure and computing resources to promote private-sector-led innovation while establishing a risk-based regulatory framework. Under such a framework, regulatory and verification requirements are applied at different levels according to the degree of risk that may arise from the use of AI. The U.S. Food and Drug Administration (FDA) is establishing a system to verify and manage the use of AI on a risk-based basis throughout the drug development lifecycle.
The European Union (EU) is pursuing AI risk regulation alongside a framework for using health data. This approach advances AI drug development while also protecting safety, transparency and fundamental rights. The European Medicines Agency (EMA) has set out principles for using AI from drug discovery through post-approval safety monitoring.
China is pursuing the digital and intelligent transformation of its pharmaceutical industry under state leadership while also seeking to secure data sovereignty and protect IP. It is expanding the domestic use of medical and genomic data while regulating their transfer abroad. Japan is focused on building a foundation for industry-academia-research collaboration, including by opening up biobanks and medical data and introducing AI drug development platforms and autonomous laboratories. Through its “AI Bio National Strategy,” South Korea is supporting the expansion of AI models, data and research infrastructure, as well as the acquisition of global IP.
In December last year, the government approved the “AI Bio National Strategy,” deciding to develop AI bio models in five key areas: drug development, brain and reverse aging, medical devices, biomanufacturing, and agri-food. The plan also calls for expanding “AI Bio Innovation Research Hubs,” where researchers, AI developers and data scientists work together. It will begin with one pilot hub in synthetic drug development this year and expand to at least two fields starting next year.
The analysis of company cases found that major overseas companies such as Insilico Medicine and BenevolentAI use their own AI platforms to identify drug candidates and broaden their business through platform provision, co-development and technology transfers. In South Korea, established pharmaceutical companies focus on securing patents centered on candidate compounds and therapeutic uses, while specialized AI drug development companies build differentiated patent portfolios centered on platforms and algorithms or on candidate compounds, depending on their business models.
Ko Yu-heum, a senior researcher at the Korea Institute of Intellectual Property who conducted the study, said, “As competition in AI drug development expands beyond candidate compounds to platforms and data, a multilayered IP strategy combining patents, trade secrets and contracts is essential.” He added, “Policy support should be strengthened to help domestic companies secure overseas IP and commercialize it so they can take the lead in global markets.”
[email protected] Kim Won-jun Reporter