Quality & Compliance
Safety & Vigilance
10 july 2023
Artificial intelligence (AI) has increased in various sectors, including the pharmaceutical industry. Artificial intelligence is the simulation of human intelligence processes by machines, especially computer systems. Machine learning is a branch of artificial intelligence (AI) and computer science that focuses on using data and algorithms to imitate how humans learn, gradually improving its accuracy. Thus, Artificial Intelligence (AI) and Machine Learning (ML) is a branch of computer science, statistics, and engineering that uses algorithms or models to perform tasks and exhibit behaviors such as learning, making decisions, and making predictions. ML is considered a subset of AI that allows models to be developed by training algorithms through the analysis of data without models being explicitly programmed.
Artificial intelligence can aid in drug designing, target detection, drug/target interaction, decision making; personalizing medicines; and management of the clinical data for future clinical drug development. One of the most used of AI is predicting lead compounds that might pass clinical trials. The US Food and Drug Administration (USFDA) has seen a significant increase in drug and biologic application submissions using AI/ML components over the past few years, with more than 100 submissions reported in 2021.
AI/ML creates opportunities and new and unique challenges. USFDA has accelerated its efforts to create an agile regulatory ecosystem to facilitate innovation while safeguarding public health. So the US Food and Drug Administration (USFDA) issued a discussion paper, “Using Artificial Intelligence and Machine Learning in the Development of Drug and Biological Products.” The discussion paper aims to communicate artificial intelligence and machine learning (AI/ML) with stakeholders, including industry and academia, to promote mutual learning and discussion.
FDA is soliciting feedback on the opportunities and challenges of utilizing AI/ML in drug development and medical device development for drugs. USFDA expects this discussion paper to complement and help prepare future guidance on AI/ML in drug development. In this discussion paper, three main topics are discussed:
USFDA solicit feedback on three key areas in the context of AI/ML in drug development. These areas are:
Thus, it shall be prudent to see suggestions and guidance documents on AI/ML by USFDA in the coming months.
As we all wait for the next steps in forming the AI/ML guidance from the FDA, ProductLife Group reminds you to check out our Pre-Clinical and Clinical Services.
Feel free to contact us at [email protected] to learn more about these services and the many others we support our global clients with.
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