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相关概念视频

Factors Affecting Dissolution: Drug pKa, Lipophilicity and GI pH01:21

Factors Affecting Dissolution: Drug pKa, Lipophilicity and GI pH

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Drug absorption within the gastrointestinal (GI) tract is a complex process influenced by several critical factors, including the site pH, the drug's dissociation constant (pKa), and the drug's lipophilicity. The GI tract exhibits a pH gradient, with an acidic environment in the stomach and a more alkaline environment in the small intestine. This pH variation directly affects the ionization state of drugs.
A drug's pKa and the pH of the gastrointestinal (GI) tract play crucial roles...
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Extraction: Partition and Distribution Coefficients01:14

Extraction: Partition and Distribution Coefficients

2.5K
The distribution law or Nernst's distribution law is the law that governs the distribution of a solute between two immiscible solvents. This law, also known as the partition law, states that if a solute is added to the mixture of two immiscible solvents at a constant temperature, the solute is distributed between the two solvents in such a way that the ratio of solute concentrations in the solvents remains constant at equilibrium.
For extracting a solute from an aqueous phase into an...
2.5K
Extraction: Effects of pH00:53

Extraction: Effects of pH

535
Consider a neutral form of an amine, B, with a partition coefficient, K, in a liquid mixture containing organic and aqueous phases. The pH of the aqueous phase affects the charge on acidic and basic solutes, and the charged form is usually more soluble in the aqueous phase. Suppose the conjugate acid form of the amine is soluble only in the aqueous phase while the base form is soluble in both phases. Then the distribution coefficient, D, can be given as the ratio of amine concentration in the...
535
One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation01:24

One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation

573
This lesson introduces two critical methods in pharmacokinetics, the Wagner-Nelson and Loo-Riegelman methods, used for estimating the absorption rate constant (ka) for drugs administered via non-intravenous routes. The Wagner-Nelson method relates ka to the plasma concentration derived from the slope of a semilog percent unabsorbed time plot. However, it is limited to drugs with one-compartment kinetics and can be impacted by factors like gastrointestinal motility or enzymatic degradation.
On...
573
Quantitative Aspects of Drug-Receptor Interaction01:30

Quantitative Aspects of Drug-Receptor Interaction

1.0K
The receptor occupancy theory connects a drug's response to the number of occupied receptors. With higher drug concentrations, more receptors are occupied, leading to increased responses. The formation of drug-receptor complexes involves association and dissociation rates, which reach equilibrium when the forward and backward reactions are equal. The equilibrium association constant (Ka) and its inverse, the equilibrium dissociation constant (Kd), indicate drug affinity. Higher Ka and lower...
1.0K
Thermodynamics: Activity Coefficient01:24

Thermodynamics: Activity Coefficient

1.5K
Activity is the measure of the effective concentration of the species in solution. It can be expressed as the product of the molar concentration of the species and its activity coefficient. The activity coefficient is a dimensionless quantity and depends on the total ionic strength of the solution.
The activity coefficient is a measure of the deviation from ideal behavior. When the ionic strength of the solution is minimal, the activity coefficient of an ionic species is close to unity, making...
1.5K

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相关实验视频

Updated: Jul 21, 2025

A New Straightforward Method for Lipophilicity logP Measurement using 19F NMR Spectroscopy
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可解释的归因分配对八醇-水分区系数的分配.

Daisuke Yokogawa1, Kayo Suda1

  • 1Graduate School of Arts and Sciences, The University of Tokyo, 3-8-1 Komaba Meguro-ku, Tokyo 153-8902, Japan.

The journal of physical chemistry. B
|July 27, 2023
PubMed
概括

本研究引入了一个可靠的图形神经网络模型,用于化学归因分配. 我们的可解释方法确保了分子设计和模型调试的可靠预测.

科学领域:

  • 化学 化学 化学
  • 机器学习 机器学习
  • 计算化学计算化学

背景情况:

  • 机器学习模型的可信度至关重要,特别是在分子设计和调试的化学中.
  • 目前的归因方法侧重于原子重要性,但缺乏归因合理性的验证.

研究的目的:

  • 为化学应用开发一个可信和可解释的归因模型.
  • 提高机器学习模型在化学研究中的可靠性.

主要方法:

  • 开发了一个图形神经网络 (GNN) 模型,用于化学中的可解释归因.
  • 修改了集成梯度方法以评估归因合理性.
  • 预测了八醇-水分区系数 (logP) 来验证模型.

主要成果:

  • 开发的GNN模型在归因分配方面表现出了很高的可信度.
  • 评估指标包括准确性,一致性和稳定性证实了该方法的可靠性.
  • 该模型成功预测了logP,展示了它的实际应用性.

结论:

  • 拟议的可解释归因模型提高了机器学习在化学中的可信度.
  • 这项工作为验证化学机器学习中的归因提供了一个强大的框架.

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  • 这些发现支持使用可靠的归因方法来进行分子设计和模型调试.