The Dawning of a Digital Revolution in Pharma Manufacturing
Dr. Loubna Bouarfa, CEO of OKRA.ai, and Stephan Rosenberger, Lonza's Head of Digital Transformation, discuss how AI is currently transforming the pharma industry.
Machine learning is an essential subset of the vast field of Artificial Intelligence, in which computer programs aim to mimic human intelligence. Machine learning is at work in many of the algorithms that impact our daily lives, from suggesting new songs we might like to targeting ads. These algorithms learn from large data sets similarly to how a child learns during the early stages of development. As the algorithm matures from child to teenager to adult, it refines its own functioning by learning from its errors and through help from humans, much like we do.
This powerful way of programming is making tsunamis across nearly all industries. It notably transforms the pharmaceutical world from drug discovery to production and even sales. Whether it is creating AI brains for companies to build digital workers to help their human employees or streamlining the factory with ultra-reliable predictive maintenance, the machine learning and artificial intelligence revolution is well underway.
Curious to Know More?
Listen to the conversation between A View On host Martina Hestericová and two world specialists about the present and future applications of AI and Machine Learning in the pharmaceutical industry.
Artificial Intelligence is a field of computer science where simulations of human intelligence by computer processes are used to improve the performance of machines.
Machine Learning is a subset within the field of AI that is inspired by the way humans learn. Computational programs in the form of algorithms continually evolve by "learning" or processing information through trial and error, often with the help of human intervention. The goal of machine learning is to create machines that are independent learners capable of solving problems without human involvement.
An AI brain, or digital brain is the term used by OKRA CEO Dr. Lubna Bouarfa to describe a form of AI that learns from several data sets to create a company-specific intelligence to aid decision-making and predictions. For Bouarfa, the company's product can be employed to solve many of the current bottlenecks and problems in Life Sciences and pharma.
Synthetic route optimization is used to map out the best way that a scientist can synthesize a compound. With the help of machine learning and AI, this route can be even further optimized by harnessing vast data sets and predicting outcomes. It is only one of many avenues where AI can greatly improve the efficiency of existing technologies in pharma manufacturing.
In edge computing the computational work happens outside of the cloud and closer to the actual data event, which allows for real-time processing. With bigger data sets needed to feed in-house AI systems, edge computing architecture holds many advantages for companies looking to harness the power of AI for functions such as automation and safety.