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相关概念视频

Quality Assurance01:19

Quality Assurance

Quality assurance is the overarching term used to describe the activities employed to ensure the proper performance of a system. These activities can be classified into three categories: quality control, quality assessment, and internal corrective measures. Typically, these activities work cyclically: quality control is performed before and during the analysis, while quality assessment occurs during and after the investigation. Internal corrective measures are implemented based on the findings...
Bioreactor Controls-I01:28

Bioreactor Controls-I

Maintaining optimal conditions within fermenters is essential for maximizing microbial productivity and ensuring process efficiency. This lesson focuses on key parameters—temperature, foam, pH, carbon dioxide, oxygen, and pressure—and their precise measurement and control strategies in fermentation systems.Temperature ControlTemperature regulation is critical due to the exothermic nature of many fermentation processes. In small laboratory fermenters, temperature is commonly monitored using...
Bioreactor Controls-III01:22

Bioreactor Controls-III

Strain improvement is a foundational strategy in industrial microbiology aimed at maximizing microbial productivity, particularly because natural isolates typically yield commercially valuable products in very low concentrations. Although optimizing the culture medium and environmental conditions can improve yields, these adjustments are inherently limited by the organism’s genetic potential. As a result, the focus shifts toward genetic modifications to enhance biosynthetic capacity. The...

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相关实验视频

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Automated Robotic Dispensing Technique for Surface Guidance and Bioprinting of Cells
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通过机器学习加强生物打印的质量控制.

Amedeo Franco Bonatti1, Giovanni Vozzi1, Carmelo De Maria1

  • 1Department of Information Engineering and Research Center 'E. Piaggio', University of Pisa, Pisa, Italy.

Biofabrication
|January 23, 2024
PubMed
概括

机器学习 (ML) 为生物打印提供自动化质量控制 (QC) 解决方案,解决技术和监管障碍. 这加速了生物打印组织的临床转化,用于再生医学.

科学领域:

  • 生物打印是一种生物打印技术.
  • 组织工程是组织工程.
  • 再生医学是一种再生医学.

背景情况:

  • 生物打印在组织工程方面得到了广泛的研究,但临床转化有限.
  • 技术挑战包括复制复杂性,打印时间和生物材料选择.
  • 监管障碍和缺乏明确的产品分类阻碍了临床使用.

研究的目的:

  • 审查生物打印质量控制 (QC) 中的机器学习 (ML) 应用.
  • 从技术角度分析生物打印中QC的ML模型.
  • 提供关于生物打印QC中的ML挑战和未来方向的见解.

主要方法:

  • 在生物打印中基于ML的QC解决方案的全面文献分析.
  • 基于使用的数据,算法和性能指标评估ML模型.
  • 评估ML在加工前,加工中和加工后的质量控制中的作用.

主要成果:

  • 机器学习算法显示出自动化生物打印QC的前景.
  • ML可以减少批次间的变化,提高产品的一致性.
  • 确定了各种ML模型及其在生物打印QC中的技术性能.
关键词:
生物打印是一种生物打印技术.临床翻译 临床翻译机器学习是机器学习.质量控制质量控制质量控制

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Author Spotlight: Quantitative Characterization of Liquid Photosensitive Bioink Properties for Continuous Digital Light Processing Based Printing
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结论:

  • 机器学习是推动生物打印QC的关键技术.
  • 通过ML自动化QC可以加速临床翻译和商业化.
  • 需要进一步的研究来克服ML驱动生物打印QC的当前挑战.