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Research progress of artificial intelligence in 3D printed drugs
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Xiao-lu HAN1, Shan-shan WANG1, Jing PENG2, Xiao-xuan HONG1, Zeng-ming WANG1, *, Na WANG2, *, Ai-ping ZHENG1
Acta Pharmaceutica Sinica | 2023, 58(6) : 1577 - 1585
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Acta Pharmaceutica Sinica | 2023, 58(6): 1577-1585
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Research progress of artificial intelligence in 3D printed drugs
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Xiao-lu HAN1, Shan-shan WANG1, Jing PENG2, Xiao-xuan HONG1, Zeng-ming WANG1, *, Na WANG2, *, Ai-ping ZHENG1
Affiliations
  • 1. Institute of Pharmacology and Toxicology, Academy of Military Medical Sciences, Academy of Military Sciences, Beijing 100850, China
  • 2. National Biomedical Analysis Center, Beijing 100850, China
Published: 2023-06-12 doi: 10.16438/j.0513-4870.2022-1259
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In 2015, the United States put forward the concept of precision medicine, which changed medical treatment from "one size fits all" to personalization, and paid more attention to personalization and drug customization. In the same year, Spritam®, the world's first 3D printed tablet, was in the market, marking the emerging pharmaceutical 3D printing technology was recognized by regulatory authorities, and it also provided a new way for drug customization. 3D printing technology has strong interdisciplinary and high flexibility, which puts forward higher requirements for pharmaceutical staffs. With the development of artificial intelligence (AI), modern society can perform various tasks, such as disease diagnosis and robotic surgery, with superhuman speed and intelligence. As a major AI technology, machine learning (ML) has been widely used in many aspects of 3D printing drug, accelerating the research and development, production, and clinical application, and promoting the new process of global personalized medicine and industry 4.0. This paper introduces the basic concepts and main classifications of 3D printing drug, non-AI drug optimization technology and ML. It focuses on the analysis of the research progress of ML in 3D printing drug, and elucidates how AI can empower the intelligent level of 3D printing drug in pre-processing, printing, and post-processing process. It provides a new idea for accelerating the development of 3D printed drug.

3D printing  /  artificial intelligence  /  machine learning  /  design of experiment  /  finite element analysis
Xiao-lu HAN, Shan-shan WANG, Jing PENG, Xiao-xuan HONG, Zeng-ming WANG, Na WANG, Ai-ping ZHENG. Research progress of artificial intelligence in 3D printed drugs[J]. Acta Pharmaceutica Sinica, 2023 , 58 (6) : 1577 -1585 . DOI: 10.16438/j.0513-4870.2022-1259
Year 2023 volume 58 Issue 6
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Article Info
doi: 10.16438/j.0513-4870.2022-1259
  • Receive Date:2022-11-23
  • Online Date:2025-11-21
  • Published:2023-06-12
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  • Received:2022-11-23
  • Revised:2022-12-22
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    1. Institute of Pharmacology and Toxicology, Academy of Military Medical Sciences, Academy of Military Sciences, Beijing 100850, China
    2. National Biomedical Analysis Center, Beijing 100850, China
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表12种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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