期刊
AAPS PHARMSCITECH
卷 22, 期 1, 页码 -出版社
SPRINGER
DOI: 10.1208/s12249-020-01905-8
关键词
3D printing; personalized medicine; dosage forms; polypill; clinical practice
资金
- Manipal Academy of Higher Education, Manipal
Personalized medicine aims to tailor medication to individuals based on their physiology, drug response, and genetic profile. One major technology emerging to enable personalized medicine is 3D printing, which can create a variety of pharmaceutical dosage forms. The future application of this technology may include dispensing prescriptions based on individual needs in a clinical setting.
Personalized medicine has the potential to revolutionize the healthcare sector, its goal being to tailor medication to a particular individual by taking into consideration the physiology, drug response, and genetic profile of that individual. There are many technologies emerging to cause this paradigm shift from the conventional one size fits all to personalized medicine, the major one being three-dimensional (3D) printing. 3D printing involves the establishment of a three-dimensional object, in a layer upon layer manner using various computer software. 3D printing can be used to construct a wide variety of pharmaceutical dosage forms varying in shape, release profile, and drug combination. The major technological platforms of 3D printing researched on in the pharmaceutical sector include inkjet printing, binder jetting, fused filament fabrication, selective laser sintering, stereolithography, and pressure-assisted microsyringe. A possible future application of this technology could be in a clinical setting, where prescriptions could be dispensed based on individual needs. This manuscript points out the various 3D printing technologies and their applications in research for fabricating pharmaceutical products, along with their pros and cons. It also presents its potential in personalized medicine by individualizing the dose, release profiles, and incorporating multiple drugs in a polypill. An insight on how it tends to various populations is also provided. An approach of how it can be used in a clinical setting is also highlighted. Also, various challenges faced are pointed out, which must be overcome for the success of this technology in personalized medicine.
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