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Abstract
Despite promising results, the adoption of machine learning in the pharma and biotech industries is limited due to data accessibility, deployment complexity, and application-specific challenges. We present an anomaly detection platform that uses state-of-the-art MLOps technologies for easy deployment and maintenance. This low-code platform supports various algorithms, including deep learning, reinforcement learning, and statistical methods, and integrates human-in-the-loop for continuous model improvement.