AI-Driven Pharmaceutical Manufacturing: Leveraging Datarobot and GenAI / Agentic AI For Predictive Modeling and Process Optimization

Nivedha Sampath

Abstract: Objectives: To analyze the application of artificial intelligence technologies-DataRobot, Generative AI, and Agentic AI-for predictive modeling and process optimization in pharmaceutical manufacturing, with a focus on enhancing quality stability and reducing costs. Study Design: A comprehensive applied study involving the systematization of practical case studies and an analytical comparison of manufacturing solutions within the context of the industry's transition to the "Pharma 4.0" model. Setting and Duration: The work is based on a synthesis of industrial and academic sources covering the period from 2022 to 2025, focused on the implementation of digital factories and intelligent platforms. Methodology: The methodology included a review of publications, thematic coding of AI application examples, reconstruction of production chains, and classification of tasks by cycle stages (biotechnological processes, quality control, logistics). Results: The study systematized areas of predictive analytics, identified use cases for generative models for synthetic data and formulations, and described the architecture of agentic systems for monitoring, Corrective and Preventive Action (CAPA), and resource planning. The findings confirm accelerated technology development, improved process stability, and reductions in product defects and unplanned downtime. Conclusion: The combined use of predictive, generative, and agentic solutions forms the foundation of the digital factories of the future and ensures a sustainable increase in the efficiency of pharmaceutical manufacturing.

Keywords: pharmaceutical manufacturing, DataRobot, predictive modeling, Generative AI, Agentic AI, Quality by Design, digital factory, quality control, synthetic data, manufacturing analytics

How to Cite?: Nivedha Sampath, "AI-Driven Pharmaceutical Manufacturing: Leveraging Datarobot and GenAI / Agentic AI For Predictive Modeling and Process Optimization", Volume 14 Issue 11, November 2025, International Journal of Science and Research (IJSR), Pages: 521-525, https://www.ijsr.net/getabstract.php?paperid=SR251106170925, DOI: https://dx.doi.org/10.21275/SR251106170925