Abstract

Artificial intelligence (AI) is redefining how we exist in the world. In almost every sector of society, AI is performing tasks with super-human speed and intellect; from the prediction of stock market trends to driverless vehicles, diagnosis of disease, and robotic surgery. Despite this growing success, the pharmaceutical field is yet to truly harness AI. Development and manufacture of medicines remains largely in a 'one size fits all' paradigm, in which mass-produced, identical formulations are expected to meet individual patient needs. Recently, 3D printing (3DP) has illuminated a path for on-demand production of fully customisable medicines. Due to its flexibility, pharmaceutical 3DP presents innumerable options during formulation development that generally require expert navigation. Leveraging AI within pharmaceutical 3DP removes the need for human expertise, as optimal process parameters can be accurately predicted by machine learning. AI can also be incorporated into a pharmaceutical 3DP 'Internet of Things', moving the personalised production of medicines into an intelligent, streamlined, and autonomous pipeline. Supportive infrastructure, such as The Cloud and blockchain, will also play a vital role. Crucially, these technologies will expedite the use of pharmaceutical 3DP in clinical settings and drive the global movement towards personalised medicine and Industry 4.0.

Highlights

  • The last 25 years have experienced a digital revolution: from the naissance of wireless internet access to 3 global smart phone uptake, widespread use of cloud storage, and the permeation of social media into 4 everyday life

  • We find that technology is being hardwired for intelligence far beyond human 6 capacity; allowing it to entertain us, highlight lucrative financial investments, and maintain our health, to 7 name just a few applications [1,2,3,4,5]

  • The development and supply of pharmaceuticals sits behind the forefront of modern technology, who employ in silico tools to expedite discoveries

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Summary

Intelligent 3D Printing of Personalised Medicines

The last 25 years have experienced a digital revolution: from the naissance of wireless internet access to 3 global smart phone uptake, widespread use of cloud storage, and the permeation of social media into 4 everyday life. The FDA approval of Spritam, and the more investigation new drug (IND) clearance for Triastek’s T19 – indicated for rheumatoid arthritis [28] – has set the precedence for 3DP as a viable manufacturing technology, demonstrating that they are viable fabrication technologies Both these examples do not capitalise on 3DP ability to produce personalised dose. An advanced goal of pharmaceutical 3DP is to achieve a fully autonomous and intelligent pipeline of personalised medicines supply in the healthcare setting. IoT-based technology can realise this vision: a network of robots will be connected to 3D printers to support formulation compounding, post-processing, quality control (QC), and packaging. An overview of IoT and an evaluation of the trajectory of the pharmaceutical 3DP field will be provided

The Modern Catalogue of Pharmaceutical 3D Printing Technologies
Material Extrusion
Alternative Optimisation Techniques to Machine Learning in 3D
Design of Experiment
Finite Element Analysis and Computational Fluid Dynamics
Mechanistic Modelling
Artificial Intelligence and Fundamentals of Machine Learning
Machine Learning Techniques
Applications of ML in Pharmaceutical 3D Printing
Machine Learning in the Pre-Printing Stage
Automated 3D Printing of Medicines
Machine Learning in the Post-Printing Stage
Limitations
Internet of Things for Pharmaceutical 3D Printing
Pharmaceutical 3D Printing’s Intelligent Trajectory
Findings
Conclusion
Full Text
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