Modern pediatric formulations of the soft candies in the form of a jelly: determination of metoclopramide content and dissolution.

In pediatrics, it is crucial to ameliorate the unpleasant taste of oral pharmaceutical formulations in order to facilitate patient compliance. Scientists' attempt to develop modern products for children is included among the new trends in pharmaceutical technology. Designing the preparation procedures and selecting the age-appropriate dosage form should be based on a benefit-risk approach, taking into account safety, efficacy, ease of use and accessibility to the patient. Part of this process should examine the necessity for taste masking, considering organoleptic and physicochemical properties of the active pharmaceutical ingredient. This research describes the incorporation of metoclopramide hydrochloride in the form of a soft candy (jelly) containing pomegranate juice. The low cost excipients and the ease of preparation are such characteristics that qualify the proposed technique as one of the alternative methods for modern drug formulations. At the same time, metoclopramide is quantitatively determined by developing a reverse phase HPLC method. The method is accurate (%RSD = 2.63, %mean recovery = 100.75) and can be used for routine analysis. The stability of metoclopramide was satisfactory after 6 months of storage (recovery 103.43%). Dissolution of the drug exceeded 92%. The proposed formulation enclosing metoclopramide in a jelly is modern, palatable and can be administered to children.

Examining barbiturate scaffold for the synthesis of new agents with biological interest.

Aim: Barbiturates have a long history of being used as drugs presenting wide varieties of biological activities (antimicrobial, anti-urease and antioxidant). Reactive oxygen species are associated with inflammation implicated in cancer, atherosclerosis and autoimmune diseases. Multitarget agents represent a powerful approach to the therapy of complicated inflammatory diseases. Results: A novel series of barbiturates has been synthesized and evaluated in several in vitro assays. Compound 16b (lipoxygenases inhibitor, 55.0 µM) was found to be a cyclooxygenase-2 inhibitor (27.5 µM). Compound 8b was profiled as a drug-like candidate. Conclusion: The barbiturate core represents a new scaffold for lipoxygenases inhibition, and the undertaken derivatives show promise as multiple-target agents to combat inflammatory diseases.

Free Cortisol Is a More Accurate Marker for Adrenal Function and Does Not Correlate with Renal Function in Cirrhosis.

BACKGROUND: The accuracy of diagnosis and clinical implications of the hepatoadrenal syndrome, as currently diagnosed using total cortisol, remain to be validated. AIM: The aim of this study was to assess adrenal function using free cortisol in stable cirrhosis and study the potential implications of any abnormalities for renal and/or cardiac function. METHODS: Sixty-one stable consecutively enrolled patients with cirrhosis underwent assessment of adrenal function using the low-dose short Synacthen test, renal function by 51Cr-EDTA glomerular filtration rate (GFR), and cardiac function by two-dimensional echocardiography. RESULTS: Eleven patients (18%) had total peak cortisol (PC) < 500 nmol/L, but no patient had free PC < 33 nmol/L indicating that diagnosis of AI using total cortisol is not confirmed using free cortisol. Free cortisol did not correlate with GFR or parameters of cardiac function. Patients with higher Child-Pugh class had progressively lower free cortisol. Patients with low GFR < 60 mL/min (N = 22) had more frequently grade II-III diastolic dysfunction (66.7% vs. 17.6%; p = 0.005) and had higher Child-Pugh and MELD score compared to those with normal GFR. CONCLUSIONS: Diagnosis of AI using total cortisol is not confirmed using free cortisol and is thus considered unreliable in cirrhosis. Free cortisol is not associated with renal or cardiac dysfunction. Lower free cortisol in more advanced stages of liver disease might be secondary to decreased synthesis due to lower cholesterol levels. Irrespective of free cortisol, parameters of cardiac dysfunction are associated with renal impairment supporting the cardio-renal hypothesis.

A new descriptor via bio-mimetic chromatography and modeling for the blood brain barrier (Part II).

Within the context of drug design methodology for the central nervous system (CNS), a predictive model which can shorten the process of finding new candidate drugs was developed. Therefore, the retention time of 51 molecules which are clinically established to enter the blood brain barrier (BBB), were recorded on two HPLC columns. For this purpose, a lipophilic butyl (C4) stationary phase was used to simulate the behavior of a drug regarding BBB permeability and a zwitterionic-HILIC to simulate blood. The results were plotted as Y variables on two Partial Least Squares (PLS) models, while 25 specific physicochemical properties (significant for lipid bilayers BBB permeation or blood) were used as X descriptors. Both models can be utilized to predict the drugability of a new molecule avoiding needless animal experiments, as well as time and material consuming syntheses. The developed models were validated (R2 ≥ 0.90, Q2 ≥ 0.83), and based on the results specific variables were proved to be significant for the studied phenomenon. Additionally, a new factor symbolized as MT was introduced. MT incorporated the experimental results and it was calculated by the fraction of the sum of the retention time of the drug on the two columns (tr(butyl) + tr(HILIC)) divided by the molecular volume (Vm) of each analyte. This new descriptor was used as an equivalent to the logarithm of BBB permeability (logBB) and may indicate the ability of a new molecule to act as a candidate drug able to enter the BBB. Comprehending the extend of contribution of several molecular attributes to the in vivo distribution of a drug may enlighten the knowledge on pharmacokinetics and clinical variation, and enable scientists to design more efficient drug molecules.

A Complementary Study of Mechanisms and Behaviors in Chromatography via Modeling.

Evolution in preparation of chromatographic columns has created the need for studying and evaluating them with the use of smart software. This research is an attempt to compare the retention mechanism between two stationary phases (butyl and phenyl) with the use of multivariate analysis for a large number of probes. Partial least squares has the ability to spot either major or minor differences in the chromatographic behavior of probes, with regard to changes in the stationary or mobile phases. The models developed refer to a total of 108 miscellaneous chemical compounds, described by 63 X variables (physicochemical properties and structural features) and one Y variable (retention time). The results showed that in both columns and mobile phases (40% methanol or 40% acetonitrile) the retention of an analyte is mainly affected by its lipophilicity, molar volume, and refractivity, which tend to cause delayed elution. On the contrary, solubility in water, polar surface area, and hydrogen bond donor or acceptor properties promote faster elution. The most important difference proved to be the effect of the presence of the carboxylic group and the solubility that affected the retention in a similar way in both columns but not with both mobile phases.

Using the partial least squares method to model the electrospray ionization response produced by small pharmaceutical molecules in positive mode.

RATIONALE: The signal intensity in electrospray ionization mass spectrometry (ESI-MS) positive mode is affected by parameters that are related to the physicochemical properties and structural features of a molecule. Accordingly, the combined interactions of an analyte and the mobile phase used is still an area that demands further clarifications since there is no general pattern regarding the nature of a molecule and the mechanism by which vapor-phase ions are produced. METHODS: A multivariate analysis method, such as Partial Least Squares (PLS), provides the opportunity to correlate the effect of a large number of parameters interpreting this complex procedure with the use of appropriate mathematical algorithms. This work involves the development of models containing up to 84 X variables which characterize the analytes studied (99) focusing on their positive or negative effect on the vapor-phase ion formation process. These descriptors are correlated with the signal response of the positively charged analyte ions which corresponds to the Y variable. RESULTS: The results showed that parameters referring or directly related to the ionization percentage of basic or acidic groups of an analyte can be used to determine the signal response on positive ESI-MS mode. Structural characteristics, polar surface area, lipophilicity, the ability of analytes to acts as hydrogen bond donors or acceptors, water solubility, density of a solid, surface tension of the substance and the number of free rotatable bonds are descriptors which are of secondary importance, still they cannot be considered negligible. CONCLUSIONS: The models derived are proved to be reliable for the investigation of such mechanisms, with a small number of components and good linearity (R(2) >83%, Q(2) >70%).

Negative electrospray ionization mode in mass spectrometry: A new perspective via modeling.

Electrospray ionization technique is used for production of gas phase ions without fragmentation and is considered as one of the most sensitive analytical methods for structural characterization of molecules. Nonetheless, the determination of some parameters (physicochemical properties or structural features) that may enhance the signal response especially in the negative ion mode has not yet been clarified. The present work is an attempt to correlate the signal response behavior of 110 compounds used as probes, with their characteristics (molecular descriptors, X variables). In order to quantify this phenomenon, Partial Least Squares which is a software capable of performing linear multivariate analysis was applied. The models derived explore the positive or negative effect of 49 X variables on the signal response of each analyte, expressed as Y variable. The process of gas phase ions formation was verified by both flow injection and column analysis. The models derived are proven reliable for the study of such mechanisms, with small number of components and good linearity (R(2)>83%, Q(2)>70%). The present study showed that parameters as pKa, ionization percentage of the analyte, PSA, HBA, COOH, water solubility and surface tension of a solid are affecting ion formation. At the same time, slight differentiations of the influence of certain parameters were observed on column injection analysis due to the chromatographic delay of some analytes.

Chemometric of the retention mechanism on butyl column: effect and relation of pH and pKa.

Reversed phase chromatographic separations are optimized for analytes containing ionizable groups by adjustment of pH of mobile phases. As it seems the pK(a). values of compounds affect their retention because of the variety in their solvation. However, it is of stressful need to predict their behavior taking into account also a series of other parameters. This work focuses on the development of ten different models, using partial least squares regression, which will identify and quantify the impact of several factors in the chromatographic behavior of 104 analytes. The combined effect of their numerous characteristics is obvious since along with pH (at 2.3 and 6.2), factors such as lipophilicity, molecular volume, polar surface area and the presence of specific moieties in their structures are not diminished. On the contrary, they work increasing or counterbalancing several effects on the retention time. The models compiled can be applied to predict with reliability (R2 > 0.865 and Q2 > 0.777) the behavior of unknown drugs.

Modeling the drugs' passive transfer in the body based on their chromatographic behavior.

One of the most challenging aims in modern analytical chemistry and pharmaceutical analysis is to create models for drugs' behavior based on simulation experiments. Since drugs' effects are closely related to their molecular properties, numerous characteristics of drugs are used in order to acquire a model of passive absorption and transfer in the human body. Importantly, such direction in innovative bioanalytical methodologies is also of stressful need in the area of personalized medicine to implement nanotechnological and genomics advancements. Simulation experiments were carried out by examining and interpreting the chromatographic behavior of 113 analytes/drugs (400 observations) in RP-HPLC. The dataset employed for this purpose included 73 descriptors which are referring to the physicochemical properties of the mobile phase mixture in different proportions, the physicochemical properties of the analytes and the structural characteristics of their molecules. A series of different software packages was used to calculate all the descriptors apart from those referring to the structure of analytes. The correlation of the descriptors with the retention time of the analytes eluted from a C4 column with an aqueous mobile phase was employed as dataset to introduce the behavior models in the human body. Their evaluation with a Partial Least Squares (PLS) software proved that the chromatographic behavior of a drug on a lipophilic stationary and a polar mobile phase is directly related to its drug-ability. At the same time, the behavior of an unknown drug in the human body can be predicted with reliability via the Artificial Neural Networks (ANNs) software.

Elucidation of the retention mechanism on a reverse-phase cyano column by modeling.

Partial least squares and quantitative structure-retention relationship models have been used mainly to explain and then to predict the retention mechanism on a cyanopropyl high-performance liquid chromatography column. Developing and applying the models involves studying the chromatographic behavior of 100 probes. Characterization of the probes took place under optimized isocratic conditions at variable proportions of two mobile phase mixtures. Retention time was correlated with numerous physicochemical properties and structural features of the probes. The goodness-of-fit for both models was estimated by the coefficient of multiple determinations, while the prediction of a test set was achieved by the root mean square error of prediction. The contribution of the descriptors in partial least squares is confirmed by the information derived from the variable importance in the projection and loadings plots, while a quantitative structure-retention relationship reflects the behavior model. In both cases, the descriptors determining the retention mechanism are lipophilicity, solubility in water, molecular volume and the presence of -COOH and/or condensed rings. Such techniques are proven useful tools for visualizing, exploring, and modeling the complex interactions between solutes and the mobile and stationary phase while at the same time this information can be quantified.

Study and development of reversed-phase HPLC systems for the determination of 2-imidazolines in the presence of preservatives in pharmaceutical preparations.

Different HPLC chromatographic systems were investigated on a C18 ACE 5 pm, 150 x 4.6 mm id column for the determination of tymazoline, tramazoline, and antazoline, with either naphazoline or xylometazoline, in commercial preparations. For the development and optimization of the systems, a Response Surface Method (r=0.925-0.980) was used to illustrate the changes in k as a function of pH values and different salt concentrations. The simultaneous separation of 2-imidazolines was accomplished at 40 degrees C with 0.01 M ammonium acetate-methanol (50+50, v/v, pH 6.0) mobile phase at a flow rate of 1.2 mL/min. In order to deal with the usual coexistence of 2-imidazolines with benzethonium and benzalkonium chloride preservatives, it was necessary to use another chromatographic system, 0.01 M ammonium acetate-methanol (50+50, v/v) mobile phase on a cyano ACE 5 pm, 150 x 4.6 mm id column. As part of a more thorough theoretical investigation, a partial least-squares (PLS) technique was used for modeling the RP-HPLC retention data. The model was based on molecular structure descriptors of the analytes' X variables and on their retention time (Log K) Y. The goodness of fit was estimated by the PLS correlation coefficient (r2) and root mean square error of estimation values, which were 0.994 and 0.0479, respectively.

Modelling by partial least squares the relationship between the HPLC mobile phases and analytes on phenyl column.

Twenty-five descriptors and 61 structurally different analytes have been used on a partial least squares (PLS) to latent structure technique in order to study chromatographically their interaction mechanism on a phenyl column. According to the model, 240 different retention times of the analytes, expressed as Y variable (log k), at different % MeOH mobile-phase concentrations have been correlated with their theoretical most important structural or molecular descriptors. The goodness-of-fit was estimated by the coefficient of multiple determinations r(2) (0.919), and the root mean square error of estimation (RMSEE=0.1283) values with a predictive ability (Q(2)) of 0.901. The model was further validated using cross-validation (CV), validated by 20 response permutations r(2) (0.0, 0.0146), Q(2) (0.0, -0.136) and validated by external prediction. The contribution of certain mechanism interactions between the analytes, the mobile phase and the column, proportional or counterbalancing is also studied. Trying to evaluate the influence on Y of every variable in a PLS model, VIP (variables importance in the projection) plot provides evidence that lipophilicity (expressed as Log D, Log P), polarizability, refractivity and the eluting power of the mobile phase are dominant in the retention mechanism on a phenyl column.