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

【Author】 Elbadawi, Moe; McCoubrey, Laura E.; Gavins, Francesca K. H.; Ong, Jun Jie; Goyanes, Alvaro; Gaisford, Simon; Basit, Abdul W.

【Source】ADVANCED DRUG DELIVERY REVIEWS

【影响因子】17.873

【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. (c) 2021 Published by Elsevier B.V.

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

【发表时间】2021 AUG

【收录时间】2022-04-07

【文献类型】综述

【主题类别】

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