Isolation of bluish anthocyanin-derived pigments obtained from blueberry surplus using centrifugal partition chromatography.

Replacement of synthetic colorants with natural ones is a current marketing trend. Nevertheless, the naturally occurring blue color is rare compared to other colours. In this work, centrifugal partition chromatography (CPC) process was developed as a more efficient and sustainable alternative to reversed phase column chromatography (RP-CC) for the preparative-scale purification of portisins. The strategy began with the extraction of anthocyanins from blueberry surplus and hemi-synthesis of respective portisins. Then, the CPC method development started with the biphasic solvent system selection followed by the optimization of the operating parameters and ended up with a comparison with RP-CC. Aiming at maximizing the portisin content, process throughput, efficiency, and minimizing the environmental risk factor, the effect of sample load (100-500 mg/100 mL of column volume), mobile phase flow rate (10-20 mL/min), and rotation speed (1000-1600 rpm) was evaluated. The two-phase solvent system consisted of tert­butyl­methyl ether, n-butanol, acetonitrile, and water (volume ratio 2:2:1:5) acidified with 0.1 vol.% of HCl was selected. The best conditions were 464 mg of sample/100 mL of column volume, 20 mL/min of mobile phase flow rate, and 1600 rpm of rotation speed at reversed phase mode, allowing the purification of portisins by 5-fold. Compared to the RP-CC, the CPC process efficiency was 2.4 times higher, while the CPC process environmental risk factor was 5.5 times lower. Overall, this study suggests that CPC can be considered an effective, and sustainable alternative process for the preparative isolation of portisins. With this purification approach, the blueberry surplus has been valorized and a naturally derived product has been prepared, allowing its subsequent use as a natural blue colorant.

Anacardium occidentale Bark as an Antidiabetic Agent.

Anacardium occidentale L. is used throughout the world to treat type 2 diabetes. In Portugal, a traditional herbal preparation made with stem bark of this species (AoBTHP) has been used for more than 30 years to treat this pathology. The AoBTHP was standardized on total phenolic content, and its hypoglycemic activity was assessed using db/db mice (n = 26) for 92 days. Three doses (40.2, 71.5, and 127.0 mg/kg/day, per os) were tested, and glibenclamide (5 mg/kg/day) was used as positive control. During the study, glycemia was measured under non-fasting or fasting states. In sequence, thin-layer chromatography bioautographic assays were used for the detection of possible alpha- and beta-glucosidase inhibitors. A significant hypoglycemic effect in fasting glycemia in days 31 and 57 was observed with the three tested doses. The 71.5 mg/kg and 127.0 mg/kg AoBTHPs significantly reduced non-fasting glycemia on day 24. The highest dose showed the most significant hypoglycemic effect. Gallic acid was identified as the major alpha- and beta-glucosidase inhibitor. The 127 mg/kg/day AoBTHP dose showed a greater glucose-lowering effect than glibenclamide. For the first time, a standardized AoBTHP was tested using an in vivo diabetes model, and its usage was preclinically validated for type 2 diabetes treatment. The hypoglycemic activity of an AoBTHP can be related to the presence of alpha- and beta-glucosidase inhibitors, such as gallic acid, but other mechanisms can also be involved.

Polymeric Micellar Formulation Enhances Antimicrobial and Anticancer Properties of Salinomycin.

PURPOSE: Salinomycin (SAL) is a polyether compound that exhibits strong antimicrobial as well as anticancer activity. Nanomedicine has been at the forefront of drug delivery research with the aim of increasing the efficacy, specificity and reduce toxicity of drugs. There is an intersection between infection and cancer, and cancer patients are prone to bacterial infections. In this study, polymeric micelles were prepared using Pluronic® F127 (PM) to encapsulate SAL (PM_SAL) with the view of enhancing antimicrobial and anticancer activity. METHODS: A Quality by Design (QbD) approach was utilized to synthesize PM_SAL, and nanoformulation activity was determined against bacterial (S. aureus, MRSA and E. coli). Effects on cancer cell line A549, i.e. cell viability, prevention of P-gp efflux, vimentin expression, effects on migratory ability of A549 cells. Anticancer activity was determined by ability to eradicate cancer stem-like cells. RESULTS: PM_SAL demonstrated only efficacy against MRSA, being even higher than that obtained with SAL. In A549 cells, a 15-fold increase in P-gp's expression as well as a significant decrease of the cell's migration, was observed. CONCLUSIONS: PM_SAL can interfere with the oncogenic protein VIM, involved in the crucial mechanisms EMT, downregulating its expression. Altogether data obtained indicates that this antibiotic and the developed polymeric micelle system is a very promising inhibitor of tumor cell growth.

Evaluation of dissolution profile similarity - Comparison between the f2, the multivariate statistical distance and the f2 bootstrapping methods.

A simulation study is presented, evaluating the performance of the f2, the model-independent multivariate statistical distance and the f2 bootstrap methods in the ability to conclude similarity between two dissolution profiles. Different dissolution profiles, based on the Noyes-Whitney equation and ranging from theoretical f2 values between 100 and 40, were simulated. Variability was introduced in the dissolution model parameters in an increasing order, ranging from a situation complying with the European guidelines requirements for the use of the f2 metric to several situations where the f2 metric could not be used anymore. Results have shown that the f2 is an acceptable metric when used according to the regulatory requirements, but loses its applicability when variability increases. The multivariate statistical distance presented contradictory results in several of the simulation scenarios, which makes it an unreliable metric for dissolution profile comparisons. The bootstrap f2, although conservative in its conclusions is an alternative suitable method. Overall, as variability increases, all of the discussed methods reveal problems that can only be solved by increasing the number of dosage form units used in the comparison, which is usually not practical or feasible. Additionally, experimental corrective measures may be undertaken in order to reduce the overall variability, particularly when it is shown that it is mainly due to the dissolution assessment instead of being intrinsic to the dosage form.

Evading P-glycoprotein mediated-efflux chemoresistance using Solid Lipid Nanoparticles.

Multidrug resistance (MDR), whereby cancer cells become resistant to the cytotoxic effects of various structurally and mechanistically unrelated chemotherapeutic agents, is a major problem in the clinical treatment of cancer. P-glycoprotein (P-gp) is a transmembrane protein responsible for drug efflux, which decreases drug intracellular bioavailability, consequently decreasing their efficacy against cancer. Solid Lipid Nanoparticles (SLNs) have not only the ability to protect the entrapped drug against proteolytic degradation, but also allow a selective intracellular targeting. Hypothetically, the entrapped drug enter the target cells by different uptake mechanisms, "nanocitose", as compared to the free drug and may evade efflux-transporters, like P-gp. The functional role of P-gp in limiting the permeability of the anticancer drug paclitaxel (Ptx) was assessed in MDA-MB-436 cells. The observed increase in the pharmacologic efficacy of drug entrapped in SLN relatively to the free drug indicates that this system is shielding the drug. Therefore, "blinding" the nanoparticle from the efflux transporters. The effect was confirmed by the decrease expression of P-gp with loaded-SLNs and through the impact on cellular MDR1 expression. Besides the ability to prevent MDR events, functionalization of SLN with a specific antibody against membrane receptors (anti-CD44v6) improves the nanoparticle capability to target selectively malignant cells. This results allow to anticipate that poor clinical outcomes related to tumour P-gp overexpression might be overcome in a near future.

Self-assembly PEGylation assists SLN-paclitaxel delivery inducing cancer cell apoptosis upon internalization.

In past years, a considerable progress has been made in the conversion of conventional chemotherapy into potent and safe nanomedicines. The ultimate goal is to improve the therapeutic window of current chemotherapeutics by reducing systemic toxicities and to deliver higher concentrations of the chemotherapeutic agents to malignant cells. In this work, we report that PEGylation of the nanocarriers increases drug intracellular bioavailability leading therefore to higher therapeutic efficacy. The surface of the already patented solid lipid nanoparticles (SLN) loaded with paclitaxel (SLN-PTX) was coated with a PEG layer (SLN-PTX_PEG) through an innovative process to provide stable and highly effective nanoparticles complying with the predefined pharmaceutical quality target product profile. We observed that PEGylation not only stabilizes the SLN, but also modulates their cellular uptake kinetics. As a consequence, the intracellular concentration of chemotherapeutics delivered by SLN-PTX_PEG increases. This leads to the increase of efficacy and thus it is expected to significantly circumvent cancer cell resistance and increase patient survival and cure.

Melatonin-based pickering emulsion for skin's photoprotection.

CONTEXT: Based on its antioxidant activity, melatonin was recently found to have a protection effect against photocarcinogenesis. OBJECTIVE: This work aimed to develop an innovative sunscreen formulation based on the Pickering emulsions concept, stabilized by physical UV filters, modified starch and natural oils associated to melatonin as a key strategy for prevention against UV-induced skin damage. MATERIALS AND METHODS: For this purpose, melatonin was incorporated in Pickering emulsions that were characterized using physicochemical, in vitro and in vivo testing. Physicochemical studies included physical and chemical stability by a thorough pharmaceutical control. The possible protective effects of melatonin against UV-induced cell damage in HaCaT cell lines were investigated in vitro. The safety assessment and the in vivo biological properties of the final formulations, including Human Repeat Insult Patch Test and sunscreen water resistance tests were also evaluated. RESULTS AND DISCUSSION: These studies demonstrated that melatonin sunscreen Pickering emulsion was beneficial and presented a powerful protection against UVB-induced damage in HaCat cells, including inhibition of apoptosis. The inclusion of zinc oxide, titanium dioxide, green coffee oil and starch ensured a high SPF (50+) against UVA and UVB. CONCLUSION: The combination of melatonin, multifunctional solid particles and green coffee oil, contributed to achieve a stable, effective and innovative sunscreen with a meaningful synergistic protection against oxidative stress.

Prediction of drug distribution in rat and humans using an artificial neural networks ensemble and a PBPK model.

PURPOSE: To develop a QSAR model, based on calculated molecular descriptors and an Artificial Neural Networks Ensemble (ANNE), for the estimation of rat tissue-to-blood partition coefficients (Kt:b), as well as the assessment of the applicability domain of the model and its utility in predicting the drug distribution in humans. METHODS: A total of 1460 individual Kt:b values (75% train and 25% validation), obtained in 13 different rat tissues were collected in the literature. A correlation between simple molecular descriptors for lipophilicity, ionization, size and hydrogen bonding capacity and Kt:b data was attempted by using an ANNE. RESULTS: Similar statistics were observed between the train and validation group of data with correlations, between the observed values and the predicted average ANNE values, of 0.909 and 0.896, respectively. A degradation of the correlations was observed for predicted values with high uncertainty, as judged by the standard deviations of the ANNE outputs. This was further observed when using the ANNE Kt:b values in a Physiologically based pharmacokinetic (PBPK) model for predicting the Human Volume of distribution of another 532 drugs. CONCLUSIONS: This model (available as a MS Excel® workbook in the Supporting material of this article) may be a valuable tool for prediction and simulation in early drug development, allowing the in silico estimation of rat Kt:b values for PBPK purposes and also indicating its applicability domain.

Tissue-to-blood distribution coefficients in the rat: utility for estimation of the volume of distribution in man.

A compilation of rat tissue-to-blood partition coefficient data obtained both in vitro and in vivo in thirteen different tissues for a total of 309 different drugs is presented. An evaluation of the relationship between several fundamental physicochemical molecular descriptors and these distribution parameters was made. In addition, the ability to predict the Human Volume of distribution by regression analysis and by a Physiologically-based approach was also tested. Results have shown different trends between the drug classes and tissues, consistent with earlier described relationships between physicochemical properties and pharmacokinetic behavior. It was also possible to conclude for the acceptable ability to predict the volume of distribution in Humans by both regression and mechanistic approaches, which suggests that this type of data represents a convenient tool to describe the drug distribution on a new drug development context. These observations and analyses, along with the large database of rat tissue distribution data, should enable future efforts aimed toward developing a full in silico quantitative structure-pharmacokinetic relationships and improving our understanding of the correlations between fundamental chemical characteristics and drug distribution.

Experimental design towards an optimal lipid nanosystem: a new opportunity for paclitaxel-based therapeutics.

Lipid based nanoparticles represent a class of nanocarriers that have caused great expectation, particularly due to their suitability to incorporate BCS class II and IV drugs. The use of solid lipid nanoparticles (SLNs) as a nanocarrier for antineoplastic agents has been underexplored when compared to the encapsulation of the same agents in polymeric particles. The preparation and efficacy assessment of a SLN platform as drug delivery carrier for anticancer agents, herein proposed as a strategy to find innovative formulations, could dramatically improve the outcome of cancer therapy. Considering these lipid nanoparticles, despite the great amount of insights described in the literature, it seems that improving their manufacturability could be the missing step to convert this system into a drug product. A way to circumvent that problem would be to select a preparation method that could take advantage of the pharmaceutical industry installed capabilities, thus speeding-up the scale-up translational steps while maintaining both regulatory compliance and flexibility. The High Pressure Homogenization (HPH) has proved to be a reliable process for SLN preparation. However, the use of the high-shear mixer, a well established process to manufacture coarse dispersions at industrial scale, has still not been fully explored to prepare SLN. In this study, we explore the possibility of using the hot emulsification/solidification method to prepare SLN's that complies with the current pharmaceutical quality requirements. Thus, a high-shear based process that consistently accomplishes performance requirements was optimized in order to standardize the nanocarrier production following the identification of some process and formulation critical parameters. A hydrophobic drug, Paclitaxel (Ptx) was successfully incorporated using the proposed developed method. The particles physicochemical characteristics changes caused by the drug entrapment as well as the particles stability were also evaluated. In addition the ability of SLN to travel across biological barriers due to its matrix lipid nature was explored upon comparing the efficacy of the drug loaded SLN with the conventional marketed drug product (Taxol®). The cellular uptake studies showed that the developed Ptx loaded SLN were in fact internalized and demonstrated higher efficacy in the cancer cells death process than Taxol. The experimental data demonstrated that the hot homogenization technique using a high-shear mechanical homogenizer allows the preparation of suitable size (around 150 nm) SLN. Overall, the results obtained can be particularly impactful in the forthcoming SLN research.

Prediction of the human oral bioavailability by using in vitro and in silico drug related parameters in a physiologically based absorption model.

Estimates of the human oral absolute bioavailability were made by using a physiological-based pharmacokinetic model of absorption and the drug solubility at the gastrointestinal pH range 1.5-7.5, the apparent permeability (P(app)) in Caco-2 cells and the intrinsic clearance (Cl(int)) in human hepatocytes suspensions as major drug related parameters. The predictive ability of this approach was tested in 164 drugs divided in four levels of input data: (i) in vitro data for both P(app) and Cl(int); (ii) in vitro data for Cl(int) only; (iii) in vitro data for P(app) only and (iv) in silico data for both P(app) and Cl(int). In all scenarios, solubility was estimated in silico. Excellent predictive abilities were observed when in vitro data for both P(app) and Cl(int) were used, with 84% of drugs with oral bioavailability predictions within a±20% interval of the correct value. This predictive ability is reduced with the introduction of the in silico estimated parameters, particularly when Cl(int) is used. Performance of the model using only in silico data provided 53% of drugs with bioavailability predictions within a±20% acceptance interval. However, 74% of drugs in the same scenario resulted in bioavailability predictions within a±35% interval, which indicates that a qualitative prediction of the absolute bioavailability is still possible. This approach is a valuable way to estimate a fundamental pharmacokinetic parameter, using data typically collected in the drug discovery and early development phases, providing also mechanistic information of the limiting bioavailability steps of the drug.

An alternative single dose parameter to avoid the need for steady-state studies on oral extended-release drug products.

Use of single and multiple-dose studies is required to establish the bioequivalence between two extended-release oral dosage forms under the current European Guidelines. However, FDA is less strict in this regard and only requires a single-dose study. The objective of this work is to use a computer simulation in order to test the two approaches. Three pharmacokinetic models, representing different release mechanisms, were considered, and Monte Carlo simulations with intra- and inter-individual variabilities were performed. Five different bioequivalence protocols were used and a new pharmacokinetic metric -C(τ), the concentration at the end of the intended dosing interval obtained in the single-dose study - is proposed in order to avoid the need for steady-state studies while keeping the ability to detect differences between formulations. Results have shown that the European requirements are more capable to discriminate between two potentially different formulations but at the cost of the multiple-dose study and with an increased number of subjects when compared to the FDA requirements. However, the use of C(max) and AUC(0-)(t) obtained on a single-dose study with the added C(τ) metric equals the discriminatory ability of the current EMA requirements, without the need of a multiple-dose study. This proposed approach results in the reduction in the number of studies and volunteers enrolled in clinical bioequivalence trials, without compromising the quality assurance of a new extended-release oral formulation.

Prediction of the in vitro permeability determined in Caco-2 cells by using artificial neural networks.

Caco-2 cells are currently the most used in vitro tool for prediction of the potential oral absorption of new drugs. The existence of computational models based on this data may potentiate the early selection process of new drugs, but the current models are based on a limited number of cases or on a reduced molecular space. We present an artificial neural network based only on calculated molecular descriptors for modelling 296 in vitro Caco-2 apparent permeability (P(app)) drug values collected in the literature using also a pruning procedure for reducing the descriptors space. LogP(app) values were divided into a training group of 192 drugs for network optimization and a testing group of another 59 drugs for early stop and internal validation resulting in correlations of 0.843 and 0.702 and RMSE of 0.546 and 0.791 for the training and testing group, respectively. External validation was made with an additional group of 45 drugs with a correlation of 0.774 and RMSE of 0.601. The selected molecular descriptors encode information related to the lipophilicity, electronegativity, size, shape and flexibility characteristics of the molecules, which are related to drug absorption. This model may be a valuable tool for prediction and simulation in the drug development process, as it allows the in silico estimation of the in vitro Caco-2 apparent permeability.

Prediction of the in vitro intrinsic clearance determined in suspensions of human hepatocytes by using artificial neural networks.

Use of in vitro suspensions of human hepatocytes is currently accepted as one of the most promising tools for prediction of metabolic clearance in new drugs. The possibility of creating computational models based on this data may potentiate the early selection process of new drugs. We present an artificial neural network for modelling human hepatocyte intrinsic clearances (CL(int)) based only on calculated molecular descriptors. In vitro CL(int) data obtained in human hepatocytes suspensions was divided into a train group of 71 drugs for network optimization and a test group of another 18 drugs for early-stop and internal validation resulting in correlations of 0.953 and 0.804 for the train and test group respectively. The model applicability was tested with 112 drugs by comparing the in silico predicted CL(int) with the in vivo CL(int) estimated by the "well-stirred" model based on the in vivo hepatic clearance (CL(H)). Acceptable correlations were observed with r values of 0.508 and 63% of drugs within a 10-fold difference when considering blood binding in acidic drugs only. This model may be a valuable tool for prediction and simulation in the drug development process, allowing the in silico estimation of the human in vivo hepatic clearance.

Prediction of drug distribution within blood.

Drug distribution in blood, defined as drug blood-to-plasma concentration ratio (R(b)), is a fundamental pharmacokinetic parameter. It relates the plasma clearance to the blood clearance, enabling the physiological interpretation of this parameter. Although easily experimentally determined, R(b) values are lacking for the vast majority of drugs. We present a systematic approach using mechanistic, partial least squares (PLS) regression and artificial neural network (ANN) models to relate various in vitro and in silico molecular descriptors to a dataset of 93 drug R(b) values collected in the literature. The ANN model resulted in the best overall approach, with r(2)=0.927 and r(2)=0.871 for the train and the test sets, respectively. PLS regression presented r(2)=0.557 for the train and r(2)=0.656 for the test set. The mechanistic model provided the worst results, with r(2)=0.342 and, additionally, is limited to drugs with a basic ionised group with pKa<7. The ANN model for drug distribution in blood can be a valuable tool in clinical pharmacokinetics as well as in new drug design, providing predictions of R(b) with a percentage of correct values within a 1.25-fold error of 86%, 84% and 87% in the train, test and validation set of data.

Lymphatic uptake of pulmonary delivered radiolabelled solid lipid nanoparticles.

UNLABELLED: Lymphatic drainage plays an important role in the uptake of particulates in the respiratory system, being also associated to the spreading of lung cancer through metastasis development. In recent years solid lipid nanoparticles (SLN) have been proposed as carriers of anti-tumoural drugs, for their low toxicity and surface characteristics make them suitable for either imaging (gamma-scintigraphy) or therapy upon encapsulation of cytotoxic drugs. Assessment of inhaled radiolabelled SLN biodistribution is described in the present work. METHODS: Nanoparticles (200 nm) were radiolabelled with 99mTc using the lipophilic chelator D,L-hexamehylpropyleneamine oxime (HMPAO). Biodistribution studies were carried out following aerosolisation and administration of a 99mTc-HMPAO-SLN suspension to a group of adult male Wistar rats. A 60 min dynamic image acquisition was performed in a gamma-camera, followed by static image collection at 30 min intervals up to 4 h postinhalation. Radiation counting was performed in organ samples, collected after the animals were sacrificed. RESULTS: The data show an important and significant uptake of the radiolabelled SLN into the lymphatics after inhalation, and a high rate of distribution in periaortic, axillar and inguinal lymph nodes. CONCLUSION: Results indicate that SLN could be effective colloidal carriers for lymphoscintigraphy or therapy upon pulmonary delivery.