Insights

Artificial intelligence (AI) and machine learning (ML) have become ubiquitous across industries, and the pharmaceutical industry is no exception. AI and ML are already influencing drug development and manufacturing, but these innovations present unique regulatory challenges. For example, if a ML algorithm can change a CGMP-compliant manufacturing process on its own to increase efficiency, how does the drug manufacturer ensure that the updated, machine-created process is CGMP-compliant? If researchers use AI to identify ideal candidates to participate in a drug trial, how do they account for biases in the data underlying the AI’s decision-making? FDA recently released a discussion paper[1] requesting input from pharmaceutical industry stakeholders on how to tackle such issues. Stakeholders should seize this opportunity to provide input to FDA as the agency develops the applicable regulatory landscape.

In March, 2020, the U.S. Food and Drug Administration (“FDA”) announced that the Agency would temporarily halt domestic facility inspections not deemed “mission-critical,” citing health concerns related to the COVID-19 pandemic. On July 10th, FDA announced its plans to resume domestic on-site facility inspections during the week of July 20th. 

On May 8, 2020 the U.S. Food and Drug Administration (“FDA”) shared a checklist of best practices for re-opening retail food establishments (including restaurants) during the COVID-19 pandemic. According to FDA, this checklist establishes key food safety practices, but is not an exhaustive list. FDA recommends that retail food establishments work with local health and regulatory authorities to discuss requirements for safely re-opening.