A Study on the Multi-Compartment Linear Circulation Pharmacokinetic Model for the Targeting Drug Delivery System

By analyzing the observed phenomena and the data collected in the study, a multi-compartment linear circulation model for targeting drug delivery system was developed and the function formulas of the drug concentration-time in blood and target organ by computing were figured out. The drug concentration-time curve for target organ can be plotted with reference to the data of drug concentration in blood according to the model. The pharmacokinetic parameters of the drug in target organ could also be obtained. The practicability of the model was further checked by the curves of drug concentration-time in blood and target organ(liver) of liver-targeting nanoparticles in animal tests. Based on the liver drug concentration-time curves calculated by the function formula of the drug in target organ, the pharmacokinetic behavior of the drug in target organ(liver) was analyzed by statistical moment, and its pharmacokinetic parameters in liver were obtained. It is suggested that the (relative targeting index( can be used for quantitative evaluation of the targeting drug delivery systems.

Non-human primate models in drug addiction deserve more attention

Dear Editor, The process of relapse involves firm or aberrant memories of environmental cues associated with drug craving or addiction. To date, it is not known where these memories are stored in the brain, what kinds of regulatory biological factors or molecules are involved, nor why it is so difficult to stop addiction psychologically. Currently, rodent animal models, such as the self-administration and conditioning place preference / aversion paradigm are still widely used in the studies of drug withdrawal syndromes or drug-associate memories. However, the differences between humans and rodents--particularly in terms of genetics, and pathology and pharmacology--have significantly limited the application of further studies on this topic. Essentially, rodents lack the longterm or life-time memories humans possess and lose their drug-associated memory only after a few weeks of withdrawal.

Application of Modeling Drugs in Animal Models of Chemical Phlebitis: Review

Objective: This review aims to determine the impact of different drugs and methods on the successful establishment of an animal model for chemical phlebitis (CP). Design: Search the Cochrane Library, ProQuest Academic Journal Library, PubMed, Web of Science, Ovid, Embase, CINAHL complete (EESCO) and other related databases to determine the literature. Screen out articles consistent with this review and summarize them. Results: Since the establishment of the database, a total of 1463 articles have been retrieved. After reading the title, abstract and full text, and excluding non-related and duplicate articles, 22 reports were finally included. Among them, there are 8 articles using different medication methods to compare the effects of establishing a CP model. The included articles explored the effects of different animal models, drug types, and their dose, concentration, speed, and time on the CP model. Conclusion: The factors of dose, concentration and time were positively correlated with the incidence of CP. The effect of speed factors on CP and the results of different animal models are inconsistent. It requires further research in the future.

The potential role of the three-dimensional-bioprinting model in screening and developing drugs

Recently,we have read with great interest the original article used different spatial configuration models of colorectal cancer(CRC)for validating the antitumor efficacy with Diiminoquinone.We feel obliged to provide new insight into the drug screening models by integrating and analyzing the original method and result.These comments may provide comprehensive insights into threedimensional drug screening models and the difference between pathologic subtypes in CRC.

Modelling two different therapy strategies for drug T-20 on HIV-1 patients

A mathematical model describing the antiretroviral therapy of Enfuvirtide on HIV-1 patients is developed. The effect of Enfuvirtide （formerly called T-20） by impulsive differential equations is modeled by two different drug elimination kinetics, the first-order elimination kinetics and the Michaelis-Menten elimination kinetics. The model is a non-autonomous system of differential equations. For a time-dependent system, the disease-free equilibrium is mainly studied. Its stability, when the therapy is taken with perfect adherence, is obtained. To ensure the disease-free equilibrium remains stable, the analytical thresholds for dosage and dosing intervals are determined. The effects of super- vised treatment interruption are also explored. It is shown that the supervised treatment interruption can be worse than no therapy at all.

The Presence of Phases and the Inability of the Classical Compartment Models to Provide Pharmacokinetic Parameters of Physiological Significance for Lipophilic Drugs

The first biphasic open one-compartment pharmacokinetic model is described. Its analytical solutions to drug concentration were developed from parameters of an open two-compartment pharmacokinetic model. The model is used to explain the unusually large compartment volumes and apparent volumes of distribution of lipophilic drugs, as well as to identify which of the pharmacokinetic parameters of the classical compartment models are biologically relevant.

AN ANALYTICAL SOLUTION FOR THE MODEL OF DRUG DISTRIBUTION AND ABSORPTION IN SMALL INTESTINE

According to the physiological and anatomical characteristics of small intestine,neglecting the effect of its motility on the distribution and absorption of drug and nutrient,Y.Miyamoto et al.proposed a model of two-dimensional laminar flow in a circular porous tube with permeable wall and calculated the concentration profile of drugby numerical analysis.In this paper,we give a steady-state analytical solution of the above model including deactivationterm.The obtained results are in agreement with the results of their numerical analysis. Moreover the analytical solution presented in this paper reveals the relation among the physiological parameters of the model and describes the basic absorption rule of drug and nutrient through the intestinal wall and hence pro- vides a theoretical basis for determining the permeability and reflection coefficient through in situ experiments.

Evaluation of the Effect of Chemotherapeutic Drug Training on Mobile Terminal for Neuro-Oncology Nurses Based on Kirkpatrick’s Model

Background: Since there has been training, there has been discussion about the effect of training. But training evaluation is not systematic until Kirkpatrick came up with the training evaluation model in 1959. At present, the prevailing model in the systematic summary of training evaluation is still The Kirkpatrick’s model. This model was further improved in 1994, more responsive to contemporary needs, and thus widely used all over the world. At the beginning, it was widely used in human resource management of enterprises. In recent years, this model has been gradually used in the medical field to evaluate the effect of medical training. The Kirkpatrick’s model has a systematic, integrated and persuasive evaluation system for trainees. It has good effects in the pre-service nurse training, the professional image and code of conduct nurses training, and the geriatric nurse training. At present, there are few studies on the chemotherapeutic drug training of neurologist nurses in China. In clinical work, nurses’ cognitive and practical behaviors of chemotherapeutic drug protection and drug extravasation prevention and treatment are insufficient. It directly harms the health of nursing staff and increases the complications of chemotherapy, increases pain of tumor patients, delays or interrupts chemotherapy, and aggravates the economic burden of patients. Especially, Chemotherapeutic drugs for neuro-oncology have particularity and necessity of urgent training. Objective: To investigate the effect of chemotherapeutic drug training through mobile terminal for neuro-oncology nurses based on the Kirkpatrick’s model. Methods: The training content and evaluation questionnaire for chemotherapeutic drugs were designed by nursing management personnel and senior nurses in our department according to the guidelines and common diseases requiring chemotherapy in the department. The content includes the basic knowledge of neuro-oncology chemotherapy, pharmacological knowledge, toxic and side effect of chemotherapy, etc., which are regularly pushed through the mobile terminal-WeChat. Forty nurses participated in the training and the effect is evaluated by Kirkpatrick’s model. Result: After the training, 100% of nurses were satisfied with the training content and 97.5% with the training form. The scores of nurses in learning level such as basic pharmacological knowledge, drug configuration and exposure, drug treatment and infusion, observation of toxic and side effects, and treatment of drug extravasation were significantly higher than those before the training (P < 0.01). The scores of nurses in the behavior level such as drug allocation, health education, toxic and side effect observation and prediction, treatment of exosmosis, occupational protection were significantly higher than those before the training. After the training, the satisfaction of managers, chemotherapy physicians and chemotherapy patients on the behavior of nurses was significantly higher than that before the training (P < 0.01). Conclusion: The chemotherapeutic drug training through mobile terminal based on Kirkpatrick’s model can improve the ability of neuro-oncology nurses, so as to improve the satisfaction of physicians and patients.

Mixture Models for Estimating the Number of Drug Users in Thailand 2005-2007

It is difficult to measure the sizes of illegal drug user populations directly by using the survey method because of many “hidden drug addicts” and the difficulty of receiving a true response. Systematic and routine information on treatment episodes of drug users is adopted to estimate the population size in this study. Mixture models of zero-truncated Poisson distributions using the nonparametric maximum likelihood estimators (NPMLE) by means of capture-recapture repeated count data were used to project the number of drug users. The method was applied to surveillance data of drug users identified by treatment episodes in over 1140 health treatment centers in Thailand from the Bureau of Health Service System Development, Ministry of Public Health. We presented how this mixture model could be utilized to construct the unobserved frequency of drug users with no treatment episode and further estimated the total population size of drug users in the country from 2005 to 2007. The result of simulation was confirmed that mixture model is suitable when population is large. By means of mixture models, the estimations for the number of drug users were fitted with excellent goodness-of-fit values and we were also compared to the conventional Chao estimates. The NPMLE for the total number of drug users in Thailand 2005, 2006, and 2007 were 184,045 (95% CI: 181,297-86,793), 230,665 (95% CI: 226,611-234,719), 299,670 (95% CI: 294,217-305,123), respectively, also 125,265 (95% CI: 123,092-127,142), 166,287 (95% CI: 163,222-169,352), 228,898 (95% CI: 224,766 - 233,030) for the number of methamphetamine (Yaba) users, and 11,559 (95% CI: 10,234-12,884), 11,333 (95% CI: 9276-13,390), 8953 (95% CI: 7878-10,028) for the number of heroin users, respectively. The numbers of marijuana, kratom-plant, opium, and inhalant users were underestimated because their symptoms were mild and not severe enough to remedy in health treatment centers which led to the smaller size of the total number of drug users. The well-estimated sizes of heroin and methamphetamine addicts are high reliable because they are based on clearly evident count with a severe addiction problem to health treatment centers. The estimation by means of mixture models can be recommended to monitor drug demand trend and drug health service routinely;it is easy to calculate via the available programs MIXTP based on request.

Hydrodynamic modeling of ferrofluid flow in magnetic targeting drug delivery

Among the proposed techniques for delivering drugs to specific locations within human body, magnetic drug targeting prevails due to its non-invasive character and its high targeting efficiency. Magnetic targeting drug delivery is a method of carrying drug-loaded magnetic nanoparticles to a target tissue target under the applied magnetic field. This method increases the drug concentration in the target while reducing the adverse side-effects. Although there have been some theoretical analyses for magnetic drug targeting, very few researchers have addressed the hydrodynamic models of magnetic fluids in the blood vessel. A mathematical model is presented to describe the hydrodynamics of ferrofiuids as drug carriers flowing in a blood vessel under the applied magnetic field. In this model, magnetic force and asymmetrical force are added, and an angular momentum equation of magnetic nanoparticles in the applied magnetic field is modeled. Engineering approximations are achieved by retaining the physically most significant items in the model due to the mathematical complexity of the motion equations. Numerical simulations are performed to obtain better insight into the theoretical model with computational fluid dynamics. Simulation results demonstrate the important parameters leading to adequate drug delivery to the target site depending on the magnetic field intensity, which coincident with those of animal experiments. Results of the analysis provide important information and suggest strategies for improving delivery in clinical application.

高级别浆液性卵巢癌类器官模型的建立及鉴定

目的目的建立并鉴定高级别浆液性卵巢癌类器官模型。方法方法选取行卵巢癌细胞减灭术的10例高级别浆液性卵巢癌患者的卵巢癌组织,将卵巢癌组织消化成单细胞,在基质胶中培养7天,构建高级别浆液性卵巢癌类器官模型。比较类器官与原发肿瘤的形态学特征、免疫组化特征和苏木精-伊红(HE)染色结果。结果结果10例患者的高级别浆液性卵巢癌类器官模型均成功构建。光学显微镜显示类器官数量可观,形态呈类圆形3D立体结构。HE染色显示,在高倍镜下,类器官细胞核异型性明显,局部区域形成微乳头状结构。免疫组化显示黏蛋白16(MUC16)强阳性,p53弥漫性强阳性,类器官与原发肿瘤的免疫组化染色情况一致。结论结论体外成功构建的高级别浆液性卵巢癌类器官模型具有明显的上皮性特征,与原发肿瘤高度相似,可用于卵巢癌的药物筛选和基础研究建模。

头孢哌酮/舒巴坦致血小板减少列线图预测模型的建立与验证

目的探讨头孢哌酮/舒巴坦致成人住院患者血小板减少的预测因子,建立列线图预测模型并进行验证。方法回顾性收集西安市中心医院2021年6月30日至2023年6月30日使用头孢哌酮/舒巴坦治疗的成人住院患者资料,按7∶3随机分为训练集和内部验证集。采用单因素/多因素Logistic回归分析筛选头孢哌酮/舒巴坦致血小板减少的独立预测因子,通过R4.0.3软件“RMS”包绘制列线图;采用受试者工作特征曲线及C-index值评估模型的预测效能;采用Hosmer-Lemeshow拟合优度检验评价模型的校正度。以相同标准,收集西安市第一医院同期使用头孢哌酮/舒巴坦治疗的成人住院患者的临床资料,对列线图预测模型进行外部验证。结果共纳入西安市中心医院患者1045例,其中头孢哌酮/舒巴坦致血小板减少患者67例,发生率为6.41%。排除假阳性患者后,最终纳入患者473例,其中训练集331例、内部验证集142例。多因素Logistic回归分析结果显示,患者年龄[OR=1.043,95%CI(1.017,1.070)]、估算的肾小球滤过率(eGFR)[OR=0.988,95%CI(0.977,0.998)]、基线血小板[OR=0.989,95%CI(0.982,0.996)]、营养风险[OR=3.863,95%CI(1.884,7.921)]和累计限定日剂量数(DDDs)[OR=1.082,95%CI(1.020,1.147)]是头孢哌酮/舒巴坦致血小板减少的独立预测因子(P<0.05)。训练集和内部验证集的C-index值分别为0.824[95%CI(0.759,0.890)]和0.828[95%CI(0.749,0.933)],Hosmer-Lemeshow检验的χ^(2)值分别为0.441、1.804(P值分别为0.802、0.406)。外部验证集中,C-index值为0.808[95%CI(0.672,0.945)],Hosmer-Lemeshow检验的χ^(2)值为0.899(P值为0.638)。结论患者年龄、基线血小板、eGFR、营养风险和累计DDDs是头孢哌酮/舒巴坦致血小板减少的独立预测因子;所建列线图预测模型具有良好的预测效能和外推性,有助于临床快速、准确地识别头孢哌酮/舒巴坦致血小板减少的潜在风险。

利用计算模拟技术建立头孢呋辛酯片体内、外相关性溶出度评价方法

目的利用计算模拟技术,探索建立前体药物头孢呋辛酯片的体内外相关性预测模型,用于仿制药生物等效性评估。方法参考文献中头孢呋辛酯片口服给药后的PK数据,结合参比制剂的血药浓度数据,利用GastroPlus TM软件搭建头孢呋辛酯片药代动力学模型;结合原研制剂在不同溶出条件、4种溶出介质(pH1.2盐酸溶液、pH4.0醋酸盐缓冲溶液、pH6.8磷酸盐缓冲溶液和水)中的体外溶出行为,筛选适宜的溶出条件;将在不同溶出介质中得到的溶出曲线作为体内释放曲线,预测头孢呋辛酯片在体内PK参数并与参比制剂的临床实测数据进行比较,探讨头孢呋辛酯片体内外相关的溶出度方法。结果成功建立了头孢呋辛酯片体内外相关的溶出度方法:桨法,转速为55 r/min,以pH4.0醋酸盐缓冲液900 mL为溶出介质。结论所建立的头孢呋辛酯片药代动力学预测模型,可用于仿制药的生物等效性虚拟评估,为该药物的质量与疗效一致性评价提供了新思路。

基于不同群体药动学分析工具建立真实世界丙戊酸群体药代动力学模型

目的:基于NONMEM和MONOLIX 2种不同群体药动学分析工具建立真实世界丙戊酸群体药动学模型(PPK),探索可能影响丙戊酸血药浓度的潜在协变量,为癫痫患者使用丙戊酸提供科学依据。方法:回顾性收集2021年1月—2022年12月南京医科大学第二附属医院收治的167例癫痫患者239个丙戊酸稳态血药浓度数据资料,按随机数字表法将其分为模型组(n=111)与验证组(n=56)。2种群体药动学分析工具同时建立适合真实世界的群体药动学模型,采用拟合度优度诊断、可视化预测检验对所得的模型进行内部验证和外部验证,评估模型的预测能力。结果:该群体药动学为一室模型,在使用NONMEM软件建立的最终模型中纳入了联合用药(DDI)-美罗培南和给药方式(ROUTE)作为协变量;而在使用MONOLIX软件建立的最终模型中纳入了联合用药(DDI)-美罗培南和体质量(BW)作为协变量。与此同时,与NONMEM相比较,MONOLIX软件所得到的最终模型具有更好的精密度和准确度。结论:本研究初步构建了适用于癫痫患者给予丙戊酸剂量指导的群体药动学模型。

基于大数据挖掘下多重耐药菌风险评估的研究价值

目的 基于大数据构建多重耐药菌感染的风险预测模型,并对其应用价值进行评估。方法 收集2018年1月至2022年12月于新疆医科大学第五附属医院诊治的405例患者,根据是否发生多重耐药菌(multidrug-resistant organisms,MDRO)感染分为非MDRO组(n=324)和MDRO组(n=81),比较并分析各指标与MDRO发生风险的相关性。构建大数据风险预测模型,分析各指标重要性,验证其准确性。结果 MDRO组合并糖尿病、原发肺部感染的患者比例,机械通气、广谱抗菌药物使用时间及降钙素原水平显著高于非MDRO组,而血红蛋白、白蛋白水平显著低于非MDRO组(均P <0.05);相关性分析显示,合并糖尿病、原发肺部感染等因素与MDRO风险的相关性较高,且合并糖尿病与原发肺部感染及联合使用抗生素等指标间相关性较高;大数据模型示抗生素使用时间、吞咽功能障碍等因素重要性较高,而血红蛋白及白蛋白重要性较低;大数据模型预测MDRO发生风险的AUC显著高于Logistic回归模型(Z=2.415,P=0.016),两种预测模型的训练集预测准确率差异无统计学意义(P>0.05);但测试集大数据模型预测准确率、敏感度及特异度均显著高于Logistic回归模型(χ^(2)=9.062,5.385,4.267;均P<0.05)。结论 合并糖尿病、原发肺部感染及联合使用抗生素等因素与MDRO发生风险具有一定相关性,基于MDRO危险因素指标的大数据模型对MDRO发生风险具有较高预测价值。

Process Modeling of Ferrofluids Flow for Magnetic Targeting Drug Delivery

Among the proposed techniques for delivering drugs to specific sites within the human body, magnetic targeting drug delivery surpasses due to its non-invasive character and its high targeting efficiency. Although there have been some analyses theoretically for magnetic drug targeting, very few researchers have addressed the hydrodynamic models of magnetic fluids in the blood vessel of human body. This paper presents a mathematical model to describe the hydrodynamics of ferrofluids as drug carriers flowing in a blood vessel under the applied magnetic field. A 3D flow field of magnetic particles in a blood vessel model is numerically simulated in order to further understand clinical application of magnetic targeting drug delivery. Simulation results show that magnetic nanoparticles can be enriched in a target region depending on the applied magnetic field intensity. Magnetic resonance imaging confirms the enrichment of ferrofluids in a desired body tissue of Sprague-Dawley rats. The simulation results coincide with those animal experiments. Results of the analysis provide the important information and can suggest strategies for improving delivery in favor of the clinical application.

基于知识图谱嵌入与深度学习的药物不良反应预测

识别药物潜在的不良反应,有助于辅助医生进行临床用药决策。针对以往研究的特征高维稀疏、需要为每种不良反应构建独立预测模型且预测精度较低的问题,本文开发一种基于知识图谱嵌入和深度学习的药物不良反应预测模型,能够对实验所覆盖的不良反应进行统一预测。一方面,知识图谱及其嵌入技术能够融合药物之间的关联信息,缓解特征矩阵高维稀疏的不足;另一方面,深度学习的高效训练能力能够提升模型的预测精度。本文使用药物特征数据构建药物不良反应知识图谱;通过分析不同嵌入策略下知识图谱的嵌入效果,选择最佳嵌入策略以获得样本向量;然后构建卷积神经网络模型对不良反应进行预测。结果表明,在DistMult嵌入模型和400维嵌入策略下,卷积神经网络模型预测效果最佳;重复实验的准确率、F_1分数、召回率和曲线下面积的平均值分别为0.887、0.890、0.913和0.957,优于文献报道中的方法。所得预测模型具有较好的预测精度和稳定性,可以为安全用药提供有效参考。

基于生物三维打印的体外药筛模型构建

以生物三维打印技术为基础,构建了一种体外三维模型药物筛选模型,并采用双向温控喷头挤出式的打印方式完成模型打印,将构成血脑屏障的两种细胞与天然水凝胶混合后层层打印,从而得到体外药筛模型。通过检测模型的弹性模量、微观结构及细胞特异性蛋白的表达,在功能上与空白对照组及二维细胞组进行对比。结果表明,相较于空白组及二维细胞培养组,打印完成的体外药筛模型弹性模量稳定,内部形成适合细胞生长的多孔结构,证明具有较好的生物相容性与结构稳定性,对于胰岛素分子的筛选中有着显著优势。

一体化视角下涉毒类社区矫正对象矫正工作的实践难点及破解路径——兼论社区矫正与戒毒模式之间的协作

涉毒类社区矫正对象是社区矫正对象中的特殊群体,具有身患疾病多、毒瘾戒断难、再犯风险高、社会排斥大等特点,需要予以特别关注。我国现行社区矫正法律规范并未专门规定涉毒类社区矫正对象及特别的矫正措施,社区矫正制度与不同戒毒模式之间存在适用界限,加之现有社区矫正工作人员数量有限及戒毒专业知识不足,导致实践中矫正此类群体工作难度大,增加了监管压力与社会风险。立法机关适时完善法律规范,增加针对涉毒类社区矫正对象的特殊条款及相应的矫正措施,为矫正特殊群体提供指导与保障;同时,从一体化视角出发,社区矫正机构整合不同戒毒模式的优势资源,促进社区矫正与戒毒模式间的协作,以提高教育矫正质量与刑事执行效果。

长爪沙鼠不同感音神经性耳聋模型的建立及比较

目的利用不同的耳毒性药物建立长爪沙鼠感音神经性耳聋模型,并对3种模型进行比较分析,为感音神经性耳聋的研究提供精准的动物模型。方法选择长爪沙鼠,建立硫酸卡那霉素和呋塞米联用(KM+Fur)、新霉素(Neo)及哇巴因(Oua)3种耳毒性药物的感音神经性耳聋模型,通过听性脑干反应(ABR)和耳蜗组织形态学检测,比较分析不同耳毒性药物的损伤特点。结果KM+Fur造模后,与对照组(14.00±1.80)相比,该组(71.00±5.26)长爪沙鼠的听力阈值显著上升,耳蜗HCs大量损伤,而SGNs无明显损伤;Neo造模后,与对照组相比,40 mmol·L^(-1) Neo仅影响沙鼠高频32 kHz时听力阈值(60.00±8.66),无明显的组织学改变;而100 mmol·L^(-1) Neo组的沙鼠各频率听力阈值均显著上升,且耳蜗HCs及SGNs均严重受损;Oua造模后,1 mmol·L^(-1) Oua和10 mmol·L^(-1) Oua均可引起沙鼠各频率听力阈值显著上升,但损伤范围不同,10 mmol·L^(-1) Oua使HCs和SGNs均严重受损,而1 mmol·L^(-1) Oua仅造成耳蜗SGNs损伤。结论利用KM+Fur可建立长爪沙鼠HCs特异性受损的感音神经性耳聋模型;40 mmol·L^(-1) Neo可建立高频区听功能损伤的感音神经性耳聋模型;利用100 mmol·L^(-1) Neo和10 mmol·L^(-1) Oua可以建立长爪沙鼠HCs和SGNs均受损的感音神经性耳聋模型;利用1 mmol·L^(-1) Oua可以建立长爪沙鼠耳蜗SGNs特异性受损的耳聋模型。