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相关概念视频

Mass Spectrometry: Overview01:19

Mass Spectrometry: Overview

5.0K
Mass spectrometry is an analytical technique used to determine the molecular mass and molecular formula of a compound. The basic principle of mass spectrometry is to generate ions from the analyte molecule and measure these ion abundances against their molecular mass.  One common type of ionization, known as electrospray ionization or EI, bombards the analyte molecules in the gas phase with high-energy electron beams. The electron beams displace an electron from the molecule and leave...
5.0K
Mass Spectrum: Interpretation01:24

Mass Spectrum: Interpretation

1.2K
An unknown compound can be established by identifying the molecular ion peak in the mass spectrum. The molecular ion peak is often weak or absent due to the predominance of fragmentation in high-energy electron beams. In such cases, a low-energy electron beam can be used to scan the spectrum to enhance the intensity of the molecular ion peak. Additionally, chemical ionization, field ionization, and desorption ionization spectra are used to obtain a relatively intense molecular ion peak.
To...
1.2K
Mass Spectrum01:23

Mass Spectrum

1.9K
A mass spectrum is the graphical representation of the relative abundance of the charged fragments in an analyte plotted against their mass-to-charge ratio (m/z). The plot's x axis represents the ratio of the mass of the charged fragment to the elementary charge it carries. The y axis of the plot represents the relative abundance of each charged species. The relative abundance is calculated from the signal intensity of each charged species recorded at the detector. The most intense signal...
1.9K
High-Resolution Mass Spectrometry (HRMS)01:15

High-Resolution Mass Spectrometry (HRMS)

1.3K
The resolution of a mass spectrometer depends on the efficiency of separating ions with different ion masses. The mass of an atom is approximated to the sum of the masses of protons and neutrons inside, considering the masses of protons and neutrons as equal. However, the masses of the proton (1.6726 × 10−24 g) and neutron (1.6749 × 10−24 g) are not truly equal. There is a minor error in the expression of atomic masses relative to the simplest atom of hydrogen. For...
1.3K
Mass Spectrometry: Complex Analysis01:21

Mass Spectrometry: Complex Analysis

740
Mass spectrometry is an important technique for the identification of pure compounds. However, it has some limitations for the analysis of complex mixtures, often due to excessive fragmentation making the spectrum too complicated to decipher. Mass spectrometry can be combined with suitable separation methods in sequence, forming hyphenated methods, which are useful in the analysis of complex mixtures.
GC–MS is a powerful hyphenated method commonly used in forensics and environmental...
740
Mass Analyzers: Overview01:13

Mass Analyzers: Overview

630
The mass analyzer is a crucial component of the mass spectrometer. In the ionization chamber, the vaporized sample is bombarded with a high-energy electron beam to generate a radical cation and further fragment into neutral molecules, radicals, and cations. A series of negatively charged accelerator plates accelerate the cations into the mass analyzer. The mass analyzer separates ions according to their mass-to-charge (m/z) ratios and then directs them to the detector. The common types of mass...
630

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Author Spotlight: Advancing Biotherapeutic Mass Calculation by Introducing mAbScale, a Python-Based Desktop Application
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用开源机器学习方法评估分子复杂性,以预测过程质量强度.

Nicole Tin1, Mandeep Chauhan2, Kennedy Agwamba1

  • 1Analytical Sciences, Gilead Sciences Inc, Foster City, California 94404-1147, United States.

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概括
此摘要是机器生成的。

制药制造中的绿色化学得到了新的开源工具的推进,该工具可以预测工艺质量强度 (PMI) 目标. 该工具使用分子复杂性来优化资源效率并推动可持续实践.

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科学领域:

  • 制药制造业 制药制造业 制药制造业
  • 绿色化学 绿色化学
  • 计算化学计算化学

背景情况:

  • 过程质量强度 (PMI) 是制药制造业资源效率的一个关键指标.
  • 准确的PMI目标设定对于可持续实践来说具有挑战性和关键性.
  • 现有的机器学习工具显示出潜力,但需要进一步开发以获得更广泛的应用.

研究的目的:

  • 将SMART-PMI工具改进和扩展为一个开源模型和应用程序.
  • 提高用于设定PMI目标的分子复杂性的预测.
  • 在制药工艺开发中促进可解释性和知情决策.

主要方法:

  • 开发了一个基于四个分子描述符的开源机器学习模型:异原子数,立体中心数,独特的拓扭曲和连接指数chi4n.
  • 与分子复杂性相关的分子特征,以预测PMI目标.
  • 创建了一个用户友好的应用程序,接受SDF文件,以快速量化复杂性和生成PMI目标.

主要成果:

  • 改进后的模型实现了82.6%的预测准确度和0.349RMSE的分子复杂性.
  • 开发的应用程序提供了可访问的PMI目标,以指导流程开发.
  • 该模型强调可解释性和节性,以更好地理解和决策.

结论:

  • 开源的SMART-PMI工具提供了一种灵活和可解释的方法来优化制药制造流程.
  • 这一进步支持绿色化学原则和可持续实践的采用.
  • 综合工具促进了数据驱动的流程开发,以提高资源效率.