Active Materials & Manufacturing Computing & AI

AI-Driven Digital Twin for Enhancing Productivity and Resource Efficiency in 3D-Printed Personalised Pharmaceuticals (3DDTBPRE)

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AI plain-English summary

A single 3D printer could soon produce a custom-shaped, precisely dosed tablet for a child in seconds, replacing the current practice of crushing adult pills and guessing the dose. This matters because children and other patients needing personalised medicines are poorly served by mass-production methods. Crushing tablets introduces dosing errors, reduces drug effectiveness, and wastes expensive active ingredients. Traditional manufacturing cannot economically produce the small, varied batches that personalised medicine requires. If this project succeeds, the AI-powered digital twin will continuously monitor and optimise every printing parameter—temperature, speed, nozzle size, material flow—in real time. This would eliminate the costly trial-and-error process currently needed to develop stable drug-loaded filaments. The result: faster production of tablets in any shape or size, significant cost reductions for small-batch drugs, less material waste, lower energy consumption, and higher manufacturing yields. For healthcare systems, this means age-appropriate, accurate doses become practical and affordable. For manufacturers, it means producing personalised medicines becomes economically viable, not a niche luxury.

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The demand for personalised medicine is rapidly increasing, driven by the high costs of advanced therapies and the need for flexible drug delivery methods. This is especially crucial in paediatric medicine, where medications are often crushed or weighed per dose, leading to errors, inaccuracies, and reduced effectiveness. Organisations like the National Institutes of Health (NIH), European Medicines Agency (EMA), and World Health Organisation (WHO) have all emphasised the need for age-appropriate formulations. However, traditional manufacturing methods are not equipped to meet the scale and precision required for personalised medicines. 3D printing (3DP), or additive manufacturing, is emerging as a revolutionary solution for personalised medicine production. FabRx, the lead partner in this project, developed the world's first pharmaceutical 3D printer, the M3DIMAKER, a GMP-compliant extrusion-based printer. Despite this innovation, challenges remain in developing stable drug-loaded filaments due to issues with formulation, rheology, mechanical, and thermal properties. Printing parameters such as temperature, speed, direction, and object geometry significantly impact drug quality, while machine settings like nozzle size and extrusion are difficult to optimise, particularly with sensitive or costly materials. These parameters across materials, operations, and machine settings are interdependent, making their optimisation a critical challenge for productivity, waste reduction, emissions control, energy efficiency, and resource optimisation. To overcome these challenges, FabRx Ltd, the global leader in FDM drug printing, is partnering with Teesside University to develop a digital twin for pharmaceutical 3D printing. This AI-powered digital twin will analyse and monitor large datasets in real time to optimise every aspect of the process, from material formulation to machine and operational parameters. Key innovations of this project include: * Faster and more reliable implementation of 3D printing technologies in pharmaceutical manufacturing. * The ability to print tablets of any shape and size within seconds. * Significant cost reductions in the production of personalised medicines by addressing material and machine inefficiencies. * Reduced waste by eliminating excessive physical trials and manual adjustments, driven by AI-based optimisation. * Customised dosage settings tailored to individual patients, improving treatment outcomes. * Enhanced resource efficiency, including reduced energy consumption, higher yield, and increased productivity. * The ability to produce small, cost-effective batches of drugs, substantially lowering production and testing costs compared to traditional methods. This breakthrough technology will lead to more efficient, cost-effective, and precise production of personalised medicines, enabling significant advancements in healthcare and improving patient outcomes across various medical fields.

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Collaborative R&D

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