Liposomal Co-Delivery of Omacetaxine Mepesuccinate and Doxorubicin for Synergistic Potentiation of Antitumor Activity

Purpose

Anticancer chemotherapy usually involves the administration of several anticancer drugs that differ in their action mechanisms. Here, we aimed to test whether the combination of omacetaxine mepesuccinate (OMT) and doxorubicin (DOX) could show synergism, and whether the liposomal co-delivery of these two drugs could enhance their antitumor effects in cervical carcinoma model.

Method

OMT-loaded liposomes (OL) were prepared by loading the drug in the lipid bilayers. OL were then electrostatically complexed with DOX, yielding double-loaded liposomes (DOL). DOX-loaded liposomes (DL) were formulated by electrostatic interaction with negatively charged empty liposomes (EL). The combination index (CI) values were calculated to evaluate the synergism of two drugs. In vitro antitumor effects against HeLa cells were measured using CCK-8, calcein staining, and crystal violet staining. In vivo antitumor effects of various liposomes were tested using HeLa cell-bearing mice.

Results

Combination of DOX and OMT had ratio-dependent synergistic activities, with very strong synergism observed at a molar ratio of 4:1 (DOX:OMT). The sizes of EL, DL, OL, and DOL did not significantly differ, but the zeta potentials of DL and DOL were slightly higher than those of OL and EL. In vitro, DOL showed higher antitumor activity than OL, DL or EL in cervical carcinoma HeLa cells. In vivo, unlike other liposomes, DOL reduced the tumor growths by 98.6% and 97.3% relative to the untreated control on day 15 and 25 after the cessation of treatment, respectively.

Conclusions

These results suggest that liposomal co-delivery of DOX and OMT could synergistically potentiate antitumor effects.     

Investigations on the Viscoelastic Performance of Pressure Sensitive Adhesives in Drug-in-Adhesive Type Transdermal Films

Purpose

We aimed to investigate the effect of solubility parameter and drug concentration on the rheological behaviour of drug-in-adhesive films intended for transdermal application.

Methods

Films were prepared over a range of drug concentrations (5%, 10% and 20% w/w) using ibuprofen, benzoic acid, nicotinic acid and lidocaine as model drugs in acrylic (Duro-Tak 87-4287 and Duro-Tak 87900A) or silicone (Bio-PSA 7-4301 and Bio-PSA 7-4302) pressure sensitive adhesives (PSAs). Saturation status of films was determined using light microscopy. Viscoelastic parameters were measured in rheology tests at 32°C.

Results

Subsaturated films had lower viscoelastic moduli whereas saturated films had higher moduli than the placebo films and/or a concentration-dependent increase in their modulus. Saturation concentration of each drug in the films was reflected by decreasing/increasing viscoelastic patterns. The viscoelastic windows (VWs) of the adhesive and drug-in-adhesive films clearly depicted the effect of solubility parameter differences, molar concentration of drug in the adhesive film and differences in PSA chemistry.

Conclusions

Drug solubility parameters and molar drug concentrations have an impact on rheological patterns and thus on the adhesive performance of tested pressure sensitive adhesives intended for use in transdermal drug delivery systems. Use of the Flory equation in its limiting form was appropriate to predict drug solubility in the tested formulations.     

Depression-like behavior and mechanical allodynia are reduced by bis selenide treatment in mice with chronic constriction injury: a comparison with fluoxetine, amitriptyline, and bupropion

Rationale

Neuropathic pain is associated with significant co-morbidities, including depression, which impact considerably on the overall patient experience. Pain co-morbidity symptoms are rarely assessed in animal models of neuropathic pain. Neuropathic pain is characterized by hyperexcitability within nociceptive pathways and remains difficult to treat with standard analgesics.

Objectives

The present study determined the effect of bis selenide and conventional antidepressants (fluoxetine, amitriptyline, and bupropion) on neuropathic pain using mechanical allodynic and on depressive-like behavior.

Methods

Male mice were subjected to chronic constriction injury (CCI) or sham surgery and were assessed on day 14 after operation. Mice received oral treatment with bis selenide (1–5 mg/kg), fluoxetine, amitriptyline, or bupropion (10–30 mg/kg). The response frequency to mechanical allodynia in mice was measured with von Frey hairs. Mice were evaluated in the forced swimming test (FST) test for depression-like behavior.

Results

The CCI procedure produced mechanical allodynia and increased depressive-like behavior in the FST. All of the drugs produced antiallodynic effects in CCI mice and produced antidepressant effects in control mice without altering locomotor activity. In CCI animals, however, only the amitriptyline and bis selenide treatments significantly reduced immobility in the FST.

Conclusion

These data demonstrate an important dissociation between the antiallodynic and antidepressant effects in mice when tested in a model of neuropathic pain. Depressive behavior in CCI mice was reversed by bis selenide and amitriptyline but not by the conventional antidepressants fluoxetine and buproprion. Bis selenide was more potent than the other drugs tested for antidepressant-like and antiallodynic effects in mice.     

Synthesis, characterization, biological evaluation and in silico screening of oxadiazinanones

A series of novel oxadiazinan-5-one namely 2-methyl-2-phenyl-1,3,4-oxadiazinan-5-one (6), 2-(3-hydroxyphenyl)-2-methyl-1,3,4-oxadiazinan-5-one (7), 2-(4-hydroxyphenyl)-2-methyl-1,3,4-oxadiazinan-5-one (8), 2-(2,4-dihydroxyphenyl)-2-methyl-1,3,4-oxadiazinan-5-one (9) and 2-(2,5-dihydroxyphenyl)-2-methyl-1,3,4-oxadiazinan-5-one (10) have been synthesized by the reaction of acetophenone and its derivatives with cyanoacetic acid hydrazide. The structural assignments of the products were done on the basis of IR, ¹H NMR, ¹³C NMR, MS, and analytical data. The in vitro antioxidant and antimicrobial activity of all the synthesized compounds (6–10) was tested by the DPPH and disk diffusion method, respectively. The synthesized compounds were screened against Gram-positive and Gram-negative bacterial and fungal strains. Compound (7) showed the highest inhibition comparable with the standard antibiotic drugs Ciprofloxacin and Amphotericin B. The antibacterial activity of the synthesized compounds was further investigated with the help of in silico docking study using Discovery studio 3.1, Molego Virtual Docker and LigandScout to predict the active sites.     

Simulating Intravitreal Injections in Anatomically Accurate Models for Rabbit, Monkey, and Human Eyes

Purpose

To develop models for rabbit, monkey, and human that enable prediction of the clearance after intravitreal (IVT) injections in one species from experimental results obtained in another species.

Methods

Anatomically accurate geometric models were constructed for rabbit, monkey, and human that enabled computational fluid dynamic simulation of clearance of an IVT injected bolus. Models were constructed with and without the retrozonular space of Petit. Literature data on clearance after IVT injection of substances spanning a range of molecular weight up to 157?kDa were used to validate the rabbit model.

Results

The space of Petit had a significant increase on the clearance of slowly diffusing substances cleared by the anterior pathway by reducing the bottleneck for drug efflux. Models that did not include this zone could not accurately predict the clearance of slowly diffusing substances whose clearance was accelerated by intraocular pressure-driven convection.

Conclusions

The ocular anatomy must be carefully reconstructed in the model to enable accurate predictions of clearance. This method offers an alternative means for scaling experimental data from one species to another that may be more appropriate than other simple approaches based entirely upon scaling of compartment volumes and flow rates.     

Drug–Drug Interaction Potential of Marketed Oncology Drugs: In Vitro Assessment of Time-Dependent Cytochrome P450 Inhibition, Reactive Metabolite Formation and Drug–Drug Interaction Prediction

Purpose

To evaluate 26 marketed oncology drugs for time-dependent inhibition (TDI) of cytochrome P450 (CYP) enzymes. Evaluate TDI-positive drugs for potential to generate reactive intermediates. Assess clinical drug–drug interaction (DDI) risk using static mechanistic models.

Methods

Human liver microsomes and CYP-specific probes were used to assess TDI in a dilution shift assay followed by generation of K_I and k_inact. Reactive metabolite trapping studies were performed with stable label probes. Static mechanistic model was used to predict DDI risk using a 1.25-fold AUC increase as a cut-off for positive DDI.

Results

Negative TDI across CYPs was observed for 13/26 drugs; the rest were time-dependent inhibitors of, predominantly, CYP3A. The k_inact/K_I ratios for 11 kinase inhibitors ranged from 0.7 to 42.2 ml/min/μmol. Stable label trapping agent–drug conjugates were observed for ten kinase inhibitors. DDI predictions gave no false negatives, one true negative, four false positives and three true positives. The magnitude of DDI was overestimated irrespective of the inhibitor concentration selected.

Conclusions

13/26 oncology drugs investigated showed TDI potential towards CYP3A, formation of reactive metabolites was also observed. An industry standard static mechanistic model gave no false negative predictions but did not capture the modest clinical DDI potential of kinase inhibitors.     

AVE1625, a cannabinoid CB1 receptor antagonist, as a co-treatment with antipsychotics for schizophrenia: improvement in cognitive function and reduction of antipsychotic-side effects in rodents

Rationale

The psychotomimetic effects of cannabis are believed to be mediated via cannabinoid CB1 receptors. Furthermore, studies have implicated CB1 receptors in the pathophysiology of schizophrenia.

Objective

These studies investigated the effects of the CB1 receptor antagonist, AVE1625, in acute pharmacological and neurodevelopmental models of schizophrenia. AVE1625 was administered to rodents alone or as a co-treatment with clinically used antipsychotic drugs (APDs).

Methods

The antipsychotic potential of AVE1625 was tested using psychotomimetic-induced hyperactivity and latent inhibition (LI) deficit models. The procognitive profile was assessed using hole board, novel object recognition, auditory evoked potential, and LI techniques. In addition, the side-effect profile was established by measuring catalepsy, antipsychotic-induced weight gain, plasma levels of prolactin, and anxiogenic potential.

Results

AVE1625 (1, 3, and 10?mg/kg ip), reversed abnormally persistent LI induced by MK-801 or neonatal nitric oxide synthase inhibition in rodents, and improved both working and episodic memory. AVE1625 was not active in positive symptom models but importantly, it did not diminish the efficacy of APDs. It also decreased catalepsy and weight gain induced by APDs, suggesting that it may decrease APD-induced extrapyramidal side effects (EPS) and compliance. Unlike other CB1 antagonists, AVE1625 did not produce anxiogenic-like effects.

Conclusions

These preclinical data suggest that AVE1625 may be useful to treat the cognitive deficits in schizophrenia and as a co-treatment with currently available antipsychotics. In addition, an improved side-effect profile was seen, with potential to ameliorate the EPS and weight gain issues with currently available treatments.     

Retina-Choroid-Sclera Permeability for Ophthalmic Drugs in the Vitreous to Blood Direction: Quantitative Assessment

Purpose

To determine the outward permeability of retina-choroid-sclera (RCS) layer for different ophthalmic drugs and to develop correlations between drug physicochemical properties and RCS permeability.

Methods

A finite volume model was developed to simulate pharmacokinetics in the eye following drug administration by intravitreal injection. The RCS permeability was determined for 32 compounds by best fitting the drug concentration-time profile obtained by simulation with previously reported experimental data. Multiple linear regression was then used to develop correlations between best fit RCS permeability and drugs physicochemical properties.

Results

The RCS drug permeabilities had values that ranged over 3?×?10^?6?m/s. Regression analysis for hydrophilic compounds showed that more than 92% of the variation in permeability values can be explained by correlative models of drug properties that include logarithm of the octanol-water partition coefficient (LogP), protein binding (PB), number of hydrogen bond acceptors (HBA), hydrogen bond donors (HBD), polar surface area (PSA) and dissociation constant (pKa) as independent variables. Regression analysis for lipophilic compounds showed that no significant correlation can be found between just physicochemical properties and RCS permeability.

Conclusion

Using the RCS permeability obtained from this study for different drugs, one can predict pharmacokinetics of intravitreal drug delivery systems such as solid implants or colloidal systems. Furthermore, the developed correlations between RCS permeability and physicochemical properties of drugs are useful in early drug development by predicting RCS permeability and drug concentration in the vitreous without experimental data.     

Pharmacological prioritisation of signals of disproportionate reporting: proposal of an algorithm and pilot evaluation

Purpose

Data mining in spontaneous reporting databases generates large numbers of signals of disproportionate reporting (SDRs) that need to be prioritised for assessment. The pharmacological relevance of drug–event associations is not considered in SDR prioritisation algorithms. This aimed to propose and test a pharmacological score for SDR prioritisation.

Methods

The Pharmacological Score for SDRs Prioritisation (PS-SP) was developed using a Delphi approach. An expert group agreed that PS-SP should include general criteria concerning SDRs and criteria concerning pharmacological relevance, and that criteria should be weighted for their risk representation. Once defined, the PS-SP was tested for prioritisation of SDRs for extrapyramidal syndrome in the French Pharmacovigilance database; the SDR classification was compared to that obtained using a traditional disproportionality approach.

Results

For a given drug, the general criteria retained were the reporting rate of the adverse drug reaction (ADR) and value of the 95% confidence interval (CI) lower boundary of the Reporting Odds Ratio (ROR). Pharmacological criteria consisted of the ADR reporting rate without concomitant at-risk drugs or those indicated for ADR treatment, and the value of the ROR 95% CI lower boundary as estimated in the subset of reports concerning drugs from the same therapeutic and then pharmacological class. Compared with traditional disproportionality, PS-SP prioritised specific drugs within congeners: metoclopramide, indoramin, and trimetazidine appeared as outliers within their classes; conventional antipsychotics had higher prioritisation than atypical antipsychotics.

Conclusion

The pilot evaluation of PS-SP performed in extrapyramidal syndrome advocates for the use of pharmacological criteria in SDR prioritisation algorithms.     

Combining Computational Methods for Hit to Lead Optimization in Mycobacterium Tuberculosis Drug Discovery

Purpose

Tuberculosis treatments need to be shorter and overcome drug resistance. Our previous large scale phenotypic high-throughput screening against Mycobacterium tuberculosis (Mtb) has identified 737 active compounds and thousands that are inactive. We have used this data for building computational models as an approach to minimize the number of compounds tested.

Methods

A cheminformatics clustering approach followed by Bayesian machine learning models (based on publicly available Mtb screening data) was used to illustrate that application of these models for screening set selections can enrich the hit rate.

Results

In order to explore chemical diversity around active cluster scaffolds of the dose–response hits obtained from our previous Mtb screens a set of 1924 commercially available molecules have been selected and evaluated for antitubercular activity and cytotoxicity using Vero, THP-1 and HepG2 cell lines with 4.3%, 4.2% and 2.7% hit rates, respectively. We demonstrate that models incorporating antitubercular and cytotoxicity data in Vero cells can significantly enrich the selection of non-toxic actives compared to random selection. Across all cell lines, the Molecular Libraries Small Molecule Repository (MLSMR) and cytotoxicity model identified ~10% of the hits in the top 1% screened (>10 fold enrichment). We also showed that seven out of nine Mtb active compounds from different academic published studies and eight out of eleven Mtb active compounds from a pharmaceutical screen (GSK) would have been identified by these Bayesian models.

Conclusion

Combining clustering and Bayesian models represents a useful strategy for compound prioritization and hit-to lead optimization of antitubercular agents.     

Engineering of an Inhalable DDA/TDB Liposomal Adjuvant: A Quality-by-Design Approach Towards Optimization of the Spray Drying Process

Purpose

The purpose of this study was to identify and optimize spray drying parameters of importance for the design of an inhalable powder formulation of a cationic liposomal adjuvant composed of dimethyldioctadecylammonium (DDA) bromide and trehalose-6,6′-dibehenate (TDB).

Methods

A quality by design (QbD) approach was applied to identify and link critical process parameters (CPPs) of the spray drying process to critical quality attributes (CQAs) using risk assessment and design of experiments (DoE), followed by identification of an optimal operating space (OOS). A central composite face-centered design was carried out followed by multiple linear regression analysis.

Results

Four CQAs were identified; the mass median aerodynamic diameter (MMAD), the liposome stability (size) during processing, the moisture content and the yield. Five CPPs (drying airflow, feed flow rate, feedstock concentration, atomizing airflow and outlet temperature) were identified and tested in a systematic way. The MMAD and the yield were successfully modeled. For the liposome size stability, the ratio between the size after and before spray drying was modeled successfully. The model for the residual moisture content was poor, although, the moisture content was below 3% in the entire design space. Finally, the OOS was drafted from the constructed models for the spray drying of trehalose stabilized DDA/TDB liposomes.

Conclusions

The QbD approach for the spray drying process should include a careful consideration of the quality target product profile. This approach implementing risk assessment and DoE was successfully applied to optimize the spray drying of an inhalable DDA/TDB liposomal adjuvant designed for pulmonary vaccination.

Strategies for Selecting the Calibration Set in Pharmaceutical Near Infrared Spectroscopy Analysis. A Comparative Study

Introduction

In recent years, the simplicity and expeditiousness of near infrared spectroscopy (NIRS) have substantially fostered its use for the pharmaceutical analysis. Developing appropriate NIRS calibration models requires careful selection of calibration sets containing all potential sources of variability in the production samples to be analysed. Once the whole variability is included, the predictive capacity of the calculated models is enhanced and those can be considered useful in the quality control. In this work, we assessed three different calibration strategies for the quantification of the active pharmaceutical ingredient (API) in a pharmaceutical granulate in low concentration (10 mg g^?1). Such strategies were used to construct calibration models, allowing all potential variability in new, unknown samples to be considered.

Method

The models were constructed by PLS using samples of variable origin including laboratory-made powder mixtures and industrial samples, and variability in production samples was incorporated via a mathematical algorithm.

Results

All three strategies provide effective multivariate models that were validated according to the normative on various production batches of industrial granulates manufactured at different times.

Conclusions

The quantification of an API in such a low concentration represented a new challenge in the field and the development of the proposed methodologies contributed for further studies in this regard. Although all three are suitable for the strategy involving calculation and addition of the process spectrum has some advantages over the other two including robustness, a good predictive ability (RMSEP?=?0.225 mg g^?1) and the need for no reference method, so it is the preferred choice.     

Pavlovian conditioned approach, extinction, and spontaneous recovery to an audiovisual cue paired with an intravenous heroin infusion

Rationale

Novel stimuli paired with exposure to addictive drugs can elicit approach through Pavlovian learning. While such approach behavior, or sign tracking, has been documented for cocaine and alcohol, it has not been shown to occur with opiate drugs like heroin. Most Pavlovian conditioned approach paradigms use an operandum as the sign, so that sign tracking can be easily automated.

Objectives

We were interested in assessing whether approach behavior occurs to an audiovisual cue paired with an intravenous heroin infusion. If so, would this behavior exhibit characteristics of other Pavlovian conditioned behaviors, such as extinction and spontaneous recovery?

Methods

Rats were repeatedly exposed to an audiovisual cue, similar to that used in standard self-administration models, along with an intravenous heroin infusion. Sign tracking was measured in an automated fashion by analyzing motion pixels within the cue zone during each cue presentation.

Results

We were able to observe significant sign tracking after only five pairings of the conditioned stimulus (CS) with the unconditioned stimulus (US). This behavior rapidly extinguished over 2 days, but exhibited pronounced spontaneous recovery 3 weeks later.

Conclusions

We conclude that sign tracking measured by these methods exhibits all the characteristics of a classically conditioned behavior. This model can be used to examine the Pavlovian component of drug memories, alone, or in combination with self-administration methods.     

Validation of Anatomical Models to Study Aerosol Deposition in Human Nasal Cavities

Purpose

Intranasal deposition of aerosols is often studied using in vitro nasal cavity models. However, the relevance of these models to predict in vivo human deposition has not been validated. This study compared in vivo nasal aerosol deposition and in vitro deposition in a human plastinated head model (NC1) and its replica constructed from CT-scan (NC2).

Methods

Two nebulizers (Atomisor Sonique® and Easynose®) were used to administer a 5.6 μm aerosol of ^99mTc-DTPA to seven healthy volunteers and to the nasal models. Aerosol deposition was quantified by γ-scintigraphy in the nasal, upper nasal cavity and maxillary sinus (MS) regions. The distribution of aerosol deposition was determined along three nasal cavity axes (x, y and z).

Results

There was no significant difference regarding aerosol deposition between the volunteers and NC1. Aerosol deposition was significantly lower in NC2 than in volunteers regarding nasal region (p?<?0.05) but was similar for the upper nasal cavity and MS regions. Mean aerosol distribution for NC1 came within the standard deviation (SD) of in vivo distribution, whereas that of NC2 was outside the in vivo SD for x and y axes.

Conclusions

In conclusion, nasal models can be used to predict aerosol deposition produced by nebulizers, but their performance depends on their design.     

Encapsulation of Poorly Soluble Drugs in Polymer-Drug Conjugates: Effect of Dual-Drug Nanoformulations on Cancer Therapy

Purpose

Current cancer chemotherapy is gradually shifting to the application of drug combinations that prevent development of drug resistance. Many anticancer drugs have poor solubility and limited oral bioavailability. Using an innovative approach, we developed dual-drug nanoformulations of a polymeric nanogel conjugate with anticancer 5-FU nucleoside analog, floxuridine (FLOX), and the second anticancer drugs, paclitaxel (PCL), or a geldanamycin analog, 17-AAG, for combination therapy.

Methods

PCL or 17-AAG had been encapsulated in the cholesteryl-polyvinyl alcohol-floxuridine nanogel (CPVA-FLOX) by simple solution mixing and sonication. Dual nanodrugs formed particles with diameter 180 nm and either drug content (5–20%) that were stable and could be administered orally. Their cytotoxicity in human and mouse cancer cells was determined by MTT assay, and cellular target inhibition – by Western blot analysis. Tumor growth inhibition was evaluated using an orthotopic mouse mammary 4T1 cancer model.

Results

CPVA-FLOX was more potent than free drug in cancer models including drug-resistant ones; while dual nanodrugs demonstrated a significant synergy (CPVA-FLOX/PCL), or showed no significant synergy (CPVA-FLOX/17-AAG) compared to free drugs (PCL or 17-AAG). Dual nanodrug CPVA-FLOX/17-AAG effect on its cellular target (HSP70) was similar to 17-AAG alone. In animal model, however, both dual nanodrugs effectively inhibited tumor growth compared to CPVA-FLOX after oral administration.

Conclusion

Oral dual-drug nanoformulations of poorly-soluble drugs proved to be a highly efficient combination anticancer therapy in preclinical studies.