Structure-Property Relationships and Models of Controlled Drug Delivery of Biodegradable Poly (D, L-lactic acid) Microspheres

An oil-in-water (O/W) solvent evaporation method was used to prepare biodegradable microspheresbased on poly(D,L-lactic acid) (PLA). Nifedipine, a hydrophobic drug, was chosen as a model molecule in the studyof drug entrapment and release. Effect of preparation conditions on the size, morphology, drug loading, and releaseprofiles of micropheres was investigated. Based on in vitro release experimental findings, a diffusion/dissolutionmodel was presented for quantitative description of the resulting release behaviors and drug release kinetics fromPLA microspheres analyzed. The mathematical models were used to predict the effect of microstructure on theresulting drug release. It provided an approach to determine the suitable structure parameters for microspheres toachieve desired drug release behaviors.

Quantitative Structure Activity Relationship Studies of Benzoxazinone Derivative Antithrombotic Drug Using New Three-dimensional Structure Descriptors

A novel three-dimensional holographic vector of atomic interaction field（3D-HoVAIF） was used to describe the chemical structures of 23 benzoxazinone derivatives as antithrombotic drugs.Here a quantitative structure activity relationship（QSAR） model was built by partial least-squares（PLS） regression.The estimation stability and prediction ability of the model were strictly analyzed by both internal and external validations.The correlation coefficients of established PLS model,leave-one-out（LOO） cross-validation,and predicted values versus experimental ones of external samples were R2=0.899,RCV2=0.854 and Qext2=0.868,respectively.These values indicated that the built PLS model had both favorable estimation stability and good prediction capabilities.Furthermore,the satisfactory results showed that 3D-HoVAIF could preferably express the information related to the biological activity of benzoxazinone derivatives.

Primary investigation of dose-effect relationship of ^(153)Sm-EDTMP in treating multiple bone metastases

Objective:To calculate the focus absorption dose of 153Sm-EDTMP with the Monte Carlo(MC)EGS4 method for treatment of bone metastases from nasopharyngeal carcinoma or breast cancer,and investigate the relationship between the focus absorption dose and painkilling effect of 153Sm-EDTMP.Methods:Four patients with multiple bone metastases from nasopharyngeal or breast carcinoma and suffered from grade IV bone pain were treated with radionuclide internal irradiation of 153Sm-EDTMP.The absorption dose and dose distribution of bone metastases and other targeted organs were calculated with MC EGS4 program based on the time-order SPECT/CT scanning and the measurement of the radioactivity in the urine accumulation.The release of bone pain and the improvement of life quality were observed.Results:Bone pain of the patients was significantly alleviated to grade II for 3–4 weeks after internal 153Sm-EDTMP irradiation.The 3-dimensional absorption dose distribution image of bone metastases and targeted organs showed that the dose distribution in bone metastases was not asymmetrical.After injection of 0.65×37 MBq/kg 153Sm-EDTMP,the highest absorption dose in bone lesions was about 4.9–5.9 Gy,and the dose in the lesion margin was about 2.0 Gy.Using the highest dose as reference dose point,the relative absorption dose values of bone marrow,vertebra and sex organ near lesions were 0.48–1.1 Gy,0.51–0.85 Gy,and 0.01–0.14 Gy,respectively.Conclusion:The absorption dose of bone metastases is significantly lower than treatment dose of 30 Gy after single irradiation of 153Sm-EDTMP.The painkilling effect is limited and in accordance with clinical observation.

Survey of dose-effect relationship in Chinese materia medica

The research on the dose-effect relationship in Chinese materia medica is delayed due to the complexity of its composition, multi-efficacy, multi-targeting and other factors. Many experts put forward relevant research ideas and methods and worked out more and more research results in literature, experimental and clinical categories because of the progress of statistical methods and scientific and technological means in recent years. In this paper, these results were preliminarily combed to show the basic situation of dose-effect relationship research in Chinese materia medica.

Analysis on Epidemiology Causality Relationship Theory under Food and Drug Safety Context

Violation of food and drug safety and other hazard crimes have the features of long latency and multiple factors. Traditional criminal law causality theory is no controversy to determine causality of criminal responsibility, thus it is necessary to introduce the epidemiology causality theory-it is a kind of causality theory based on epidemic diseases, and it is the high degree of probability in the determination of causality in criminal laws so as to solve the traditional attribution problem, but the theory also exists applicable restriction conditions in judicial practice.

Ionic liquids as the effective technology for enhancing transdermal drug delivery: Design principles, roles, mechanisms, and future challenges

Ionic liquids (ILs) have been proven to be an effective technology for enhancing drug transdermal absorption. However, due to the unique structural components of ILs, the design of efficient ILs and elucidation of action mechanisms remain to be explored. In this review, basic design principles of ideal ILs for transdermal drug delivery system (TDDS) are discussed considering melting point, skin permeability, and toxicity, which depend on the molar ratios, types, functional groups of ions and inter-ionic interactions. Secondly, the contributions of ILs to the development of TDDS through different roles are described: as novel skin penetration enhancers for enhancing transdermal absorption of drugs;as novel solvents for improving the solubility of drugs in carriers;as novel active pharmaceutical ingredients (API-ILs) for regulating skin permeability, solubility, release, and pharmacokinetic behaviors of drugs;and as novel polymers for the development of smart medical materials. Moreover, diverse action mechanisms, mainly including the interactions among ILs, drugs, polymers, and skin components, are summarized. Finally, future challenges related to ILs are discussed, including underlying quantitative structure-activity relationships, complex interaction forces between anions, drugs, polymers and skin microenvironment, long-term stability, and in vivo safety issues. In summary, this article will promote the development of TDDS based on ILs.

Prediction of Blood-to-Brain Barrier Partitioning of Drugs and Organic Compounds Using a QSPR Approach

The purpose of this study was to develop a quantitative structure–property relationship(QSPR) model based on the enhanced replacement method(ERM) and support vector machine(SVM) to predict the blood-to-brain barrier partitioning behavior(log BB) of various drugs and organic compounds. Different molecular descriptors were calculated using a dragon package to represent the molecular structures of the compounds studied. The enhanced replacement method(ERM) was used to select the variables and construct the SVM model. The correlation coefficient, R^2, between experimental results and predicted log BB was 0.878 and 0.986, respectively. The results obtained demonstrated that, for all compounds, the log BB values estimated by SVM agreed with the experimental data, demonstrating that SVM is an effective method for model development, and can be used as a powerful chemometric tool in QSPR studies.

The Impact of a Drug Safety Warning on Discussions between Doctors and Their Patients;the Case of Rosiglitazone

The goal of this study was to track the influence of a highly publicized report on discussions between doctors and their patients and prescribing decisions made in response to concerns about potential medication adverse side effects. This was a retrospective analysis of a primary care network’s electronic medical record database. From a diabetes registry of 12, 246 patients, 329 were identified as taking rosiglitazone prior to the June 14, 2007 release of an article in the New England Journal of Medicine;the article suggesting an increased risk of myocardial events. The entire content of all office visits, telephone messages, and medication lists for each patient were reviewed over a 2-year period subsequent to the article’s publication. Doctor/patient discussions regarding concerns for rosiglitazone were catalogued including the physician’s treatment recommendations. There were documented discussions on rosiglitazone’s potential adverse side effects for 64 patients;19.5 percent of this population. All of the discussions occurred between June 15 and October 30, 2007. Of the entire group, 59.3 percent (N = 195) remained on rosiglitazone. For those advised to continue rosiglitazone, the provider indicated that he/she wanted more data before determining if the drug was not safe or discounted the validity of the safety concerns. For those advised to discontinue rosiglitazone, 112 (83.6 percent) were placed on pioglitazone. An article suggesting potential adverse effects of rosiglitazone resulted in a documented discussion in 19.5 percent of patients on this medication. These findings suggest an awareness of this publication by patients, presumably derived from media reports. However, an awareness of this concern did not result in a substantial change in practice.The majority of patients remained on rosiglitazone. The content of these discussions suggest that most physicians’ recommended waiting for more published data before considering a change. While many factors influence physician’s prescribing behavior, this study demonstrates how a highly publicized report influences the doctor/ patient dialogue.

Chemoinformatic Resources for Organometallic Drug Discovery

Medicinal Organometallic Chemistry keeps contributing to drug discovery efforts including the development of diagnostic compounds. Despite the limiting issues of metal-based molecules, e.g., such as toxicity, there are drugs approved for clinical use and several others are under clinical and pre-clinical development. Indeed, several research groups continue working on organometallic compounds with potential therapeutic applications. For arguably historical reasons, chemoinformatic methods in drug discovery have been applied thus far mostly to organic compounds. Typically, metal-based molecules are excluded from compound data sets for analysis. Indeed, most software and algorithms for drug discovery applications are focused and parametrized for organic molecules. However, considering the emerging field of material informatics, the objective of this Commentary we emphasize the need to develop cheminformatic applications to further develop metallodrugs. For instance, one of the starting points would be developing a compound database of organometallic molecules annotated with biological activity. It is concluded that chemoinformatic methods can boost the research area of Medicinal Organometallic Chemistry.

Progress in the Research of Radix Astragali in Treating Chronic Heart Failure:Effective Ingredients,Dose-Effect Relationship and Adverse Reaction

Radix Astragali,a Chinese herbal medicine possessing important cardiovascular pharmacologic effects,is widely applied for the treatment of chronic heart failure（CHF） in clinical practice.This paper summarizes briefly the researches in the last 10 years on its chemical compositions,effective ingredients for improving cardiac function,dose-effect relationship in treating CHF,and adverse reactions that occurred in clinical practice.

Clinical Observations on the Dose-effect Relationship of Gegen Qin Lian Decoction (葛根芩连汤) on 54 Out-patients with Type 2 Diabetes

Objective: To observe the therapeutic effect of different dosages of Gegen Qin Lian Decoction (葛根芩连汤) on type 2 diabetic patients. Methods: Fifty-four type 2 diabetic patients from low dosage group (20 cases), medium dosage group (19 cases) and high dosage group (15 cases) were treated with different dosage of Gegen Qin Lian Decoction for 12 weeks. Fasting blood-glucose (FBG), postprandial blood sugar (PBG) and Hemoglobin A1c (HbAlc) were determined before and after treatment. Results: With the increase of dosage, the overall effective rate of glycaemic control increased, and FBG, PBG, HbAlc decreased. The overall effective rate of blood glucose control of high dosage, medium dosage and low dosage group were 80%, 47%, 30% respectively, and there were significant differences between high dosage group and low dosage group. The decrease of FBG, PBG and HbAlc of high dosage showed significant differences from low dosage too. These data was analyzed by trend χ2 test and covariance analysis. Conclusion: The result indicated that different dosage of Gegen Qin Lian Decoction has dose-effect relationship in reducing HbAlc and FBG.

Research ideas and strategies on the dose-effect relationship of traditional Chinese medicine prescriptions and herbs

We discuss here the complexity of the doses of traditional Chinese medicine(TCM) prescriptions and herbs from different viewpoints,including the heterogeneity of drug quality,the flexibility of prescriptions,and the diversity of drug effects.Then,the corresponding research ideas and strategies are proposed.We can reveal the actual situation of clinical doses based on in-depth "real-world study" of the safety and effectiveness of TCM prescriptions,create an analytical method for dose-effect relationships in accordance with the features of TCM,and reveal the correlated regular nature of the effectiveness and dosage of TCM prescriptions and herbs.

Machine Learning-Based Quantitative Structure-Activity Relationship and ADMET Prediction Models for ERα Activity of Anti-Breast Cancer Drug Candidates

Breast cancer is presently one of the most common malignancies worldwide,with a higher fatality rate.In this study,a quantitative structure-activity relationship(QSAR)model of compound biological activity and ADMET(Absorption,Distribution,Metabolism,Excretion,Toxicity)properties prediction model were performed using estrogen receptor alpha(ERα)antagonist information collected from compound samples.We first utilized grey relation analysis(GRA)in conjunction with the random forest(RF)algorithm to identify the top 20 molecular descriptor variables that have the greatest influence on biological activity,and then we used Spearman correlation analysis to identify 16 independent variables.Second,a QSAR model of the compound were developed based on BP neural network(BPNN),genetic algorithm optimized BP neural network(GA-BPNN),and support vector regression(SVR).The BPNN,the SVR,and the logistic regression(LR)models were then used to identify and predict the ADMET properties of substances,with the prediction impacts of each model compared and assessed.The results reveal that a SVR model was used in QSAR quantitative prediction,and in the classification prediction of ADMET properties:the SVR model predicts the Caco-2 and hERG(human Ether-a-go-go Related Gene)properties,the LR model predicts the cytochrome P450 enzyme 3A4 subtype(CYP3A4)and Micronucleus(MN)properties,and the BPNN model predicts the Human Oral Bioavailability(HOB)properties.Finally,information entropy theory is used to validate the rationality of variable screening,and sensitivity analysis of the model demonstrates that the constructed model has high accuracy and stability,which can be used as a reference for screening probable active compounds and drug discovery.

Why 90%of clinical drug development fails and how to improve it?

Ninety percent of clinical drug development fails despite implementation of many successful strategies,which raised the question whether certain aspects in target validation and drug optimization are overlooked?Current drug optimization overly emphasizes potency/specificity using structure-activityrelationship(SAR)but overlooks tissue exposure/selectivity in disease/normal tissues using structure-tissue exposure/selectivity—relationship(STR),which may mislead the drug candidate selection and impact the balance of clinical dose/efficacy/toxicity.We propose structure-tissue exposure/selectivity—activity relationship(STAR)to improve drug optimization,which classifies drug candidates based on drug’s potency/selectivity,tissue exposure/selectivity,and required dose for balancing clinical efficacy/toxicity.ClassⅠdrugs have high specificity/potency and high tissue exposure/selectivity,which needs low dose to achieve superior clinical efficacy/safety with high success rate.ClassⅡdrugs have high specificity/potency and low tissue exposure/selectivity,which requires high dose to achieve clinical efficacy with high toxicity and needs to be cautiously evaluated.ClassⅢdrugs have relatively low(adequate)specificity/potency but high tissue exposure/selectivity,which requires low dose to achieve clinical efficacy with manageable toxicity but are often overlooked.ClassⅣdrugs have low specificity/potency and low tissue exposure/selectivity,which achieves inadequate efficacy/safety,and should be terminated early.STAR may improve drug optimization and clinical studies for the success of clinical drug development.

A New Strategy in Drug Design of Chinese Medicine:Theory,Method and Techniques

The research and development （R＆D） process of Chinese medicine, with one notable feature, clinical application based, is significantly different from which of chemical and biological medicine, from laboratory research to clinics. Besides, compound prescription is another character. Therefore, according to different R＆D theories between Chinese and Western medicine, we put forward a new strategy in drug design of Chinese medicine, which focuses on ＂combination- activity relationship （CAR）＂, taking prescription discovery, component identification and formula optimization as three key points to identify the drugs of high efficacy and low toxicity. The method of drug design of Chinese medicine includes： new prescription discovery based on clinical data and literature information, component identification based on computing and experimental research, as well as formula optimization based on system modeling. This paper puts forward the concept,research framework and techniques of drug design of Chinese medicine, which embodies the R＆D model of Chinese medicine, hoping to support the drug design of Chinese medicine theoretically and technologically.

The relationship between antimicrobial consumption and the rates of resistance of Klebsiela pneumoniae in respiratory unit

Objective To investigate the relationship between the consumption of antibacterial agents and resistance rate of Klebsiela pneumoniae(KP)in the hospital respiratory unit for 3 consecutive years in 2005-2007.Methods The total antibacterial consumption expressed as defined DDDs/100BD,as well as resistance rate of total KP and producing ESBLs KP were collected,and their correlation was analyzed.Results The rate of resistance of KP to cefoperazone/sulbactam,Cefepime,Imipenem,Moxifloxacin was significantly positively associated with the consumption of Cefotaxime,Ceftazidime,Moxifloxacin,Amikacin respectively;A significant positive association was observed between the rate of resistance of KP to Piperacillin/Tazobactam,Ceftriaxone and the consumption of Imipenem;The rate of resistance of KP to Piperacillin,Cefotaxime,Ciprofloxacin was significantly positively associated with the consumption of Levofloxacin.ESBLs producing bacilli of KP were detected in 44 of 75 isolates(58.7%),The rate of resistance of producing ESBLs KP to Piperacillin/Tazobactam,Ceftriaxone was significantly positively associated with the consumption of Imipenem,Ceftazidime;A significant positive association was observed between the rate of resistance of producing ESBLs KP to Piperacillin,Imipenem and the consumption of Moxifloxacin.There was no significant correlation in other drugs.Conclusions A relationship existed between antimicrobial consumption and rates of resistance of KP in the hospital respiratory unit.We must use antibiotics carefully and with reason to control and lessen the drug resistance of bacterial.

A Strategy to Find Novel Candidate DKAs Inhibitors Using Modified QSAR Model with Favorable Druggability Properties

The study dealed with quantitative structure-activity relationship(QSAR)to explore the important features of diketo acid(DKA)derivatives for exerting potent HIV-1 integrase inhibitors activity.A three-step screening method was proposed to choose descriptors.Then,additional descriptors were used in the CoMFA and CoMSIA.Lastly,a modified CoMSIA m7 model,constructed by adding Csp^2_03_F descriptor,showed better predictive ability.Validation parameters(Q^2 and R^2)for the models were 0.722 and 0.925,respectively.In addition,external validation for the models using a test group revealed R^2pred=0.892.Contour maps analysis defined favored and disfavored regions of the compounds,and two new compounds with the descriptor structure were designed with better activities than Raltegravir(RAL),well drug-likeness and low toxicity.The research provides a base for further DKA development.

血浆蛋白与骨质疏松症的关系及潜在治疗靶点:基于国际UK Biobank数据库信息

背景:骨质疏松症是全球范围内增加疾病负担和致残率的重要因素。血浆蛋白参与体内复杂的生物过程,在揭示疾病机制和发现潜在治疗靶点方面起着关键作用。尽管已有研究显示血浆蛋白与骨质疏松症之间存在关联,但这些关联的因果性质尚未得到充分阐明。因此,利用大规模的血浆蛋白数据探究与骨质疏松症相关的因果蛋白并识别潜在的药物靶点,对于骨质疏松症的防治至关重要。目的:运用两样本孟德尔随机化分析,以国际UK Biobank数据库为来源信息,评估血浆蛋白与骨质疏松症之间的因果关联。方法:从UK Biobank数据库获取1001种血浆蛋白相关的全基因组显著性水平(P<5×10-8)的蛋白质数量性状位点作为工具变量,并排除连锁不平衡。骨质疏松症的汇总数据来自FinnGen数据库,共涉及438872名欧洲血统个体。研究采用逆方差加权、MR-Egger回归、加权中位数等方法进行分析,并进行多项敏感性分析以确保结果的稳健性。进一步构建蛋白-蛋白互作网络,结合基因本体富集分析和京都基因与基因组百科全书通路分析,探索血浆蛋白的功能相关性及潜在作用机制。结果与结论:①孟德尔随机化逆方差加权法结果显示有50种血浆蛋白与骨质疏松症存在因果关系(P<0.05),包括染色体19开放阅读框12(chromosome 19 open reading frame 12,C19orf12;OR=0.610,95%CI:0.483-0.769,P=2.967×10-5)、表皮生长因子(OR=0.877,95%CI:0.770-0.999,P=0.049)等20种血浆蛋白可能与骨质疏松症的风险降低相关,有CCL18(OR=1.091,95%CI:1.037-1.147,P=0.001)、CD209(OR=1.036,95%CI:1.003-1.070,P=0.034)等30种血浆蛋白可能增加骨质疏松症的风险,经Bonferroni校正后,只有C19orf12与骨质疏松症存在显著的因果关联。②多项敏感性分析显示研究不存在多效性和异质性,说明结果具有稳健性。③通过构建蛋白-蛋白互作网络明确了表皮生长因子、CCL5、CXCL13、CXCL5、血管内皮生长因子C、CCL18、CCL17、TEK受体酪氨酸激酶、含免疫球蛋白样和表皮生长因子样结构域的酪氨酸激酶1(TIE1)和CCL23为核心蛋白。④基因本体富集分析和京都基因与基因组百科全书通路分析表明这些血浆蛋白在免疫系统中具有重要作用,通过参与信号传导、细胞迁移和趋化等过程影响骨质疏松症。⑤文章结果揭示了1001种血浆蛋白与骨质疏松症的潜在因果关联,这种基于大规模数据驱动的分析方法有助于在中国人群中识别新的生物标志物和药物靶点;其次,文章结果表明,免疫系统信号传导、细胞迁移和趋化等过程在骨质疏松症发病机制中发挥重要作用,这为特定遗传背景和环境因素下的骨质疏松症研究提供了新的方向;最后,研究中识别的核心蛋白(如表皮生长因子、CCL5及CXCL13等)有望成为新的生物标志物或药物靶点,为骨质疏松症的精准防治提供新的依据。

中美禁毒合作的非传统安全向度——以芬太尼治理合作为例

由芬太尼泛滥引发的药物安全危机已成为当前中美两国共同面临的非传统安全问题。中美两国曾因芬太尼问题存在诸多争端,但在2023年又重新开展禁毒合作。中美关系影响下的合作意愿,以及两国对芬太尼问题的认知分歧共同塑造了两国对芬太尼治理的集体认同,进而影响两国的禁毒合作。中美关系在跌至历史性低点后回温,两国的禁毒合作意愿随之加深;两国选择搁置在芬太尼问题上的分歧,使得认知分歧得以弥合。中美两国各自的合作认同通过互动凝聚成高度的集体认同,最终促成两国在禁毒议题上从冲突转向合作。当前,中美两国在技术交流、执法协调、物质列管等多个方面开展合作,通过多种路径推进芬太尼治理。

A pathway profile-based method for drug repositioning

Finding new applications for existing pharmaceuticals,known as drug repositioning,is a validated strategy for resolving the problem of high expenditure but low productivity in drug discovery.Currently,the prevalent computational methods for drug repositioning are focused mainly on the similarity or relevance between known drugs based on their "features",including chemical structure,side effects,gene expression profile,and/or chemical-protein interactome.However,such drug-oriented methods may constrain the newly predicted functions to the pharmacological functional space of the existing drugs.Clinically,many drugs have been found to bind "off-target"(i.e.to receptors other than their primary targets),which can lead to undesirable effects.In this study,which integrates known drug target information,we propose a disease-oriented strategy for evaluating the relationship between drugs and disease based on their pathway profile.The basic hypothesis of this method is that drugs exerting a therapeutic effect may not only directly target the disease-related proteins but also modulate the pathways involved in the pathological process.Upon testing eight of the global best-selling drugs in 2010(each with more than three targets),the FDA(Food and Drug Administration,USA)-approved therapeutic function of each was included in the top 10 predicted indications.On average,60% of predicted results made using our method are proved by literature.This approach could be used to complement existing methods and may provide a new perspective in drug repositioning and side effect evaluation.