Legal Risks in Artificial Intelligence and Drug Development Processes
According to a report published by Crowell & Moring, there are five key legal and regulatory risks associated with the use of artificial intelligence in drug discovery.
In the life sciences sector, the reliability of artificial intelligence-generated evidence in drug development processes brings significant risks such as hallucinations, biases stemming from inefficient data, a lack of transparency in artificial intelligence reasoning, and data manipulation.
A client bulletin published by Crowell & Moring highlights five core legal and regulatory risks introduced by the use of artificial intelligence in drug discovery and development phases. To address these risks, it is stated that human oversight and experimental validation are essential in order to comply with the standards of the US Food and Drug Administration and the European Union.
While international regulations such as the FDA and EMA Joint Guidelines and ICH M15 impose strict rules on data source and model validation, the EU Product Liability Directive, which will enter into force on December 9, 2026, links the explainability of artificial intelligence to product liability. Legal experts point out that for artificial intelligence analyses to be admissible within frameworks such as Federal Rule of Evidence 702, they must be validated by qualified experts.
Sources
- crowell.com · Link