Case Study: Artificial Intelligence for Environmental Monitoring

Abstract: This presentation discusses the application of artificial intelligence for environmental monitoring during pharmaceutical manufacturing. The APAS Independence is a laboratory automation device that uses advanced imaging and machine learning algorithms to interpret microbial growth on culture plates. The device has achieved global regulatory approvals in the United States, Europe and Australia.

The presentation discusses the validation and testing requirements to achieve regulatory clearance as a Class II medical device in the United States and how the testing approach compares to the validation requirements for use within pharmaceutical manufacturing processes. It also considers the maturity levels of different AI models and how this can impact the validation and ongoing controls required when implementing new technologies.

LBT Quality and Regulatory Director, Mrs Julie Winson said:
“We have led the way in the application of artificial intelligence technology for clinical microbiology and remain one of only five devices using artificial intelligence to obtain clearance by the US FDA in this field.1 The systems and processes we have developed for our clinical product are a key differentiator for our technology and enable us to collect the data we require to demonstrate the performance of APAS PharmaQC in pharmaceutical environmental monitoring.”

Oral Presentation by LBT Innovations

Conference: 2023 PDA Asia Pacific Regulatory Conference

Date: November 2023

Authors: Mrs Julie Winson

Citation: Julie Winson. Case Study: Artificial Intelligence for Environmental Monitoring

1. U.S. Food & Drug Administration Website, Artificial Intelligence and Machine Learning (AI/ML)-Enabled Medical Devices,