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Review
. 2021 Aug:175:113805.
doi: 10.1016/j.addr.2021.05.015. Epub 2021 May 18.

Harnessing artificial intelligence for the next generation of 3D printed medicines

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Review

Harnessing artificial intelligence for the next generation of 3D printed medicines

Moe Elbadawi et al. Adv Drug Deliv Rev. 2021 Aug.

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.

Keywords: 4D printed personalized pharmaceuticals and medical devices; Additive manufacturing; Computational modeling and finite element analysis; Computer aided design of printlets; Digital therapeutics and healthcare; Drug product design and development; Fabricating gastrointestinal drug delivery systems and dosage forms; Falsified and counterfeit oral pharmaceutical products; Mass customization and machine learning; Translational pharmaceutics and pharmaceutical sciences.

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