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PACKING IT UP WITH AI

From the macro view of production to the more micro packaging

Currently, the zeitgeist is all about Artificial Intelligence (AI). While it may be arguable if we are truly in the age of AI or still witnessing rapidly advancing machine learning, we’re going to leave the semantics to philosophers and focus on the very real and practical shift in pharmaceutical manufacturing and packaging propelled by AI. As an industry driven by immense amounts of data, the pharmaceutical industry is perfectly poised to make use of rapid and intelligent processing. 

One of the largest areas where we’re seeing the inclusion of AI is in design and manufacturing. Starting with drug discovery, which is already predicted to grow to $3.74 billion in 2027 at a CAGR of 28.4%. This alone could overhaul the market, as it improves ROI on research. Machine learning and advanced pattern recognition are already being used to identify gaps and errors in processes and equipment. Early adopters are already seeing improved efficiency and yield while gaining insight and minimizing risk in their assembly lines. Being able to simulate and assess all possible scenarios quickly may be tedious and slow for even the most skilled experts, but is a simple task when performed by AI. While we might still be in the early stages of large-scale use of the technology, we are already seeing tangible improvements.  

From the macro view of production to the more micro packaging, researchers are covering all the bases. Companies have been using machine vision in their packaging lines for some time to detect defects in pills and their packaging. They are now adding automated artificial inspection systems to the process. Early detection increases production efficiency while also minimizing losses.  

AI can also be used after the product has left the factory. The global market for smart packaging is expected to reach $26.7 billion by next year. Currently, it mostly consists of embedded sensor technology that can provide consumers with vital information such as freshness, viability, and even dose reminders. Drugmakers and tech startups are already making use of Internet of Things (IoT)-enabled products to link to phones and help patients achieve more precise control of monitoring and administering doses. This has already proven life-changing for diabetes patients. While this is a more complex solution, we are also seeing a rise in combining more conventional solutions with newer smart AI-enabled solutions, such as the use of Quick Response (QR) codes and Radio Frequency Identifier (RFID) that can be scanned and used together with apps. It is inevitable that we will see smarter AI-enabled packaging and manufacturing in the pharmaceutical industry as time goes on and the barriers to implementation fall faster.