ISPE Singapore Conference and Exhibition

Machine Learning in Pharmaceutical Process Development:

The State of the Art

21 - 23 August, Suntec Singapore

David Lovett - Perceptive Engineering

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International Society for Pharmaceutical Engineering is the world's largest not-for-profit association serving its Members by leading scientific, technical and regulatory advancement throughout the entire pharmaceutical lifecycle.

ISPE's Core Members are pharmaceutical professionals who use expert knowledge to create high-quality, cost-effective GMP solutions.

The organisation leads and facilitates the development of next generation process technologies and innovative technical solutions. On matters of regulation, our focus is on those requirements that impact — or will impact — the licensing of facilities, manufacturing processes and operations, and the sustainability of the supply chain over the product lifecycle. ISPE provides a neutral environment where individual Members and experts belonging to Regulatory Authorities can engage in open dialogue on issues that will ultimately benefit patients around the world.


Artificial Intelligence (AI) and Machine Learning (ML) have become ubiquitous terms in the past couple of years.  This presentation inspects and compares the current AI and ML approaches with alternative techniques which are already well established within the process industries, and now also in many of the innovative Pharmaceutical companies.
Advanced Process Control (APC) and Multi-Variate Analysis are data driven techniques to build models of the process that provide greater insight and understanding, then use those models to monitor for abnormal operational events and, more recently, directly adjust the process to achieve closed loop control of product CQAs. 
When we compare these “traditional” data-driven techniques with Machine Learning we see the same algorithms being applied and the common goal of improved decision making through data analysis, prediction and adjustment. There is a difference, however, and we’ll explore what it is within the talk.

Case studies from the Pharmaceutical and other industries will be used to demonstrate the application of several forms of Machine Learning for process control and optimisation. The case studies present applications for the rapid development of synthesis and crystallisation processes.

Our Clients & Partners

Selection of our clients and key partners we work with to improve process efficiency

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