Replacing microemulsion formulations experimental solubility studies with in-silico methods comprising molecular dynamics and docking experiments

Implementation of green-assessed nanotechnology and quality by design approach for development of optical sensor for determination of tobramycin in ophthalmic formulations and spiked human plasma

A fast eco-friendly colorimetric method was developed for the determination of Tobramycin in drug substance, ophthalmic formulations, and spiked human plasma using silver nanoparticles optical sensor. Even though tobramycin is non-UV-visible absorbing, the developed method is based on measuring the absorbance quenching of silver nanoparticles resulting from the interaction with tobramycin. Different factors affecting the absorbance intensity were studied as; silver nanoparticle concentration, pH, buffer type, and reaction time using quality by design approach. Validation of the proposed method was performed according to ICH guidelines and was found to be accurate, precise, and sensitive. The linearity range of tobramycin was 0.35-4.0 μg/mL. The optical sensor was successfully applied for the determination of Tobramycin in ophthalmic formulations and spiked human plasma without pre-treatment. Additionally, the binding between Tobramycin and PVP- capped silver nanoparticles was studied using molecular docking software. The method was assessed and compared to colorimetric reported methods for the green character using Green Analytical Procedure Index (GAPI) and Analytical GREEnness calculator (AGREE) tools and found to be greener.

Evolution of the Computational Pharmaceutics Approaches in the Modeling and Prediction of Drug Payload in Lipid and Polymeric Nanocarriers

This review describes different trials to model and predict drug payload in lipid and polymeric nanocarriers. It traces the evolution of the field from the earliest attempts when numerous solubility and Flory-Huggins models were applied, to the emergence of molecular dynamic simulations and docking studies, until the exciting practically successful era of artificial intelligence and machine learning. Going through matching and poorly matching studies with the wet lab-dry lab results, many key aspects were reviewed and addressed in the form of sequential examples that highlighted both cases.

Using Microemulsions: Formulation Based on Knowledge of Their Mesostructure

Microemulsions, as thermodynamically stable mixtures of oil, water, and surfactant, are known and have been studied for more than 70 years. However, even today there are still quite a number of unclear aspects, and more recent research work has modified and extended our picture. This review gives a short overview of how the understanding of microemulsions has developed, the current view on their properties and structural features, and in particular, how they are related to applications. We also discuss more recent developments regarding nonclassical microemulsions such as surfactant-free (ultraflexible) microemulsions or ones containing uncommon solvents or amphiphiles (like antagonistic salts). These new findings challenge to some extent our previous understanding of microemulsions, which therefore has to be extended to look at the different types of microemulsions in a unified way. In particular, the flexibility of the amphiphilic film is the key property to classify different microemulsion types and their properties in this review. Such a classification of microemulsions requires a thorough determination of their structural properties, and therefore, the experimental methods to determine microemulsion structure and dynamics are reviewed briefly, with a particular emphasis on recent developments in the field of direct imaging by means of electron microscopy. Based on this classification of microemulsions, we then discuss their applications, where the application demands have to be met by the properties of the microemulsion, which in turn are controlled by the flexibility of their amphiphilic interface. Another frequently important aspect for applications is the control of the rheological properties. Normally, microemulsions are low viscous and therefore enhancing viscosity has to be achieved by either having high concentrations (often not wished for) or additives, which do not significantly interfere with the microemulsion. Accordingly, this review gives a comprehensive account of the properties of microemulsions, including most recent developments and bringing them together from a united viewpoint, with an emphasis on how this affects the way of formulating microemulsions for a given application with desired properties.

Computational and Experimental Approaches to Investigate Lipid Nanoparticles as Drug and Gene Delivery Systems

Lipid nanoparticles (LNPs) have been widely applied in drug and gene delivery. More than twenty years ago, DoxilTM was the first LNPs-based drug approved by the US Food and Drug Administration (FDA). Since then, with decades of research and development, more and more LNP-based therapeutics have been used to treat diverse diseases, which often offer the benefits of reduced toxicity and/or enhanced efficacy compared to the active ingredients alone. Here, we provide a review of recent advances in the development of efficient and robust LNPs for drug/gene delivery. We emphasize the importance of rationally combining experimental and computational approaches, especially those providing multiscale structural and functional information of LNPs, to the design of novel and powerful LNP-based delivery systems.

Comparing cefotaxime and ceftriaxone in combating meningitis through nose-to-brain delivery using bio/chemoinformatics tools

Bio/chemoinformatics tools can be deployed to compare antimicrobial agents aiming to select an efficient nose-to-brain formulation targeting the meningitis disease by utilizing the differences in the main structural, topological and electronic descriptors of the drugs. Cefotaxime and ceftriaxone were compared at the formulation level (by comparing the loading in gelatin and tripalmitin matrices as bases for the formation of nanoparticulate systems), at the biopharmaceutical level (through the interaction with mucin and the P-gp efflux pumps) and at the therapeutic level (through studying the interaction with S. pneumoniae bacterial receptors). GROMACS v4.6.5 software package was used to carry-out all-atom molecular dynamics simulations. Higher affinity of ceftriaxone was observed compared to cefotaxime on the investigated biopharmaceutical and therapeutic macromolecules. Both drugs showed successful docking on mucin, P-gp efflux pump and S. pneumoniae PBP1a and 2b; but ceftriaxone showed higher affinity to the P-gp efflux pump proteins and higher docking on mucin. Ceftriaxone showed less out-of-matrix diffusion and higher entrapment on the gelatin and the tripalmitin matrices. Accordingly, Ceftriaxone gelatin nanospheres or tripalmitin solid lipid nanoparticles may pose a more feasible and efficient nose-to-brain formulation targeting the meningitis disease compared to the cefotaxime counterparts.

Prediction of Drug Loading in the Gelatin Matrix Using Computational Methods

The delivery of drugs is a topic of intense research activity in both academia and industry with potential for positive economic, health, and societal impacts. The selection of the appropriate formulation (carrier and drug) with optimal delivery is a challenge investigated by researchers in academia and industry, in which millions of dollars are invested annually. Experiments involving different carriers and determination of their capacity for drug loading are very time-consuming and therefore expensive; consequently, approaches that employ computational/theoretical chemistry to speed have the potential to make hugely beneficial economic, environmental, and health impacts through savings in costs associated with chemicals (and their safe disposal) and time. Here, we report the use of computational tools (data mining of the available literature, principal component analysis, hierarchical clustering analysis, partial least squares regression, autocovariance calculations, molecular dynamics simulations, and molecular docking) to successfully predict drug loading into model drug delivery systems (gelatin nanospheres). We believe that this methodology has the potential to lead to significant change in drug formulation studies across the world.

Bio-Inspired Strategies against Diabetes and Associated Complications: A Review

Bio-molecules are the most important target to be considered while designing any drug delivery system. The logic lies in using such bio-sensing or bio-mimicking systems in their formulations that can mimic the active site of those receptors to which the drug is going to bind. Polymers mimicking the active site of target enzymes are regarded as bio-inspired polymers and can be used to ameliorate many diseased conditions. Nowadays, this strategy is also being adopted against diabetes and its complications. Under hyperglycemic conditions, many pathways get activated which are responsible for the progression of diabetes-associated secondary complications viz. retinopathy, neuropathy, and nephropathy. The enzymes involved in the progression of these complications can be mimicked for their effective management. For an instance, Aldose Reductase (ALR2), a rate-limiting enzyme of the polyol pathway (downstream pathway) which gets over-activated under hyperglycemic condition is reported to be mimicked by using polymers which are having same functionalities in their structure. This review aims at critically appraising reports in which target mimicking bio-inspired formulations have been envisaged against diabetes and its complications. The information summarized in this review will provide an idea about the bio-sensing approaches utilized to manage blood glucose level and the utility of bio-inspired polymers for the management of diabetic complications (DC). Such type of information may be beneficial to pharmaceutical companies and academia for better development of targeted drug delivery systems with sustained-release property against these diseased conditions.

Curcumin or bisdemethoxycurcumin for nose-to-brain treatment of Alzheimer disease? A bio/chemo-informatics case study

The current study introduces a new idea of utilising several bio/chemoinformatics tools in comparing two bio-similar natural molecules viz. curcumin and bisdemethoxycurcumin (BDMC) in order to select a potential nose-to-brain remedy for Alzheimer disease. The comparison comprised several bio/chemo informatics tools. It encompassed all levels starting from loading the drug in a certain carrier; PLGA nanoparticles, to the biopharmaceutical level investigating the interaction with mucin and inhibition of P-gp blood-brain barrier efflux pumps. Finally, the therapeutic level was investigated by studying the interaction with pharmacological targets such as amyloid peptide plaques and cyclooxygenase2 enzyme responsible for the inflammatory reactions of the studied disease. The comparison revealed the superiority of curcumin over BDMC. Five new analogues were also hypothesised where diethoxybisdemethoxycurcumin was  recommended as a superior molecule. This work introduced the virtual utilisation of bio/chemo informatics tools as a reliable and economic alternative to the exhausting and resources-consuming wet-lab experimentation.

Statins anticancer targeted delivery systems: re-purposing an old molecule

OBJECTIVES

Exploring the use of statins as anticancer agents and exploiting different drug delivery systems in targeting these molecules to cancerous sites. Literature review was performed to investigate the use of statins in cancer treatment in one hand, and the different pharmaceutical approaches to deliver and target these drugs to their site of action.

KEY FINDINGS

Statins were used for decades as antihypercholestrolemic drugs but recently have been proven potential for broad anticancer activities. The incorporation of statins in nanoparticulate drug delivery systems not only augmented the cytotoxicity of statins but also overcame the resistance of cancerous cells against the traditional chemotherapeutic agents. Statins-loaded nanoparticles could be easily tampered to target the cancerous cells and consequently minimal drug amount could be utilized.

SUMMARY

This review reconnoitered the different endeavors to incorporate statins in various nanoparticles and summarized the successful effects in targeting cancerous cells and reducing their proliferation without the side effects of commonly used chemotherapeutic agents.

Selecting optimum protein nano-carriers for natural polyphenols using chemoinformatics tools

BACKGROUND

The normal fate of any natural product with a therapeutic potential is to be formulated into an effective medicine. However, the conventional methods of selecting the suitable formulations or carriers based on the formulator experiences, trials and errors as well as materials availability do not usually yield the optimal results.

HYPOTHESIS

We hypothesize the possibility of the virtual optimum selection of a protein carrier for two polyphenolic compounds widely investigated for their chemopreventive effects; resveratrol and curcumin using a combination of some chemoinformatics tools.

METHODS

Two protein-based nanoparticles namely; albumin and gelatin nanoparticles were compared as carriers for the two selected phytochemicals; resveratrol and curcumin. Resveratrol-albumin, resveratrol-gelatin and curcumin-albumin results were gathered from the literature. While, a new combination (formulation), comprising curcumin as the cargo and gelatin nanoparticles as the carrier, was prepared and evaluated as a potential medicine for breast cancer. Combined chemoinformatics tools, namely; molecular dynamics and molecular docking were used to determine the optimum carrier for each of the two chemopreventive agents.

RESULTS

A new curcumin-gelatin nanoparticulate formulation was prepared and proven cytotoxic after an application period of 48h on MCF-7 breast cancer cell-lines scoring an IC₅₀ value of 64.8µg/ml. The utilized chemoinformatics tools comprising the molecular dynamics simulations of the protein nano-particulate drug-carriers followed by the molecular docking of phytochemical drugs on these carriers could capture the optimum protein carrier for each of the tested phytochemical and hence propose a successful formulation.

CONCLUSION

This study presents one in a series that proves the novel addressed concept of the utilization of computational tools rather than wet-lab experimentation in providing better selection of drug-carrier pairs aiming for better formulations and the subsequent successful therapeutic effects.

Exploring the use of nanocarrier systems to deliver the magical molecule; Curcumin and its derivatives

Curcumin and its derivatives; curcuminoids have been proven as potential remedies in different diseases. However, their delivery carries several challenges owing to their poor aqueous solubility, photodegradation, chemical instability, poor bioavailability and rapid metabolism. This review explores and criticizes the numerous attempts that were adopted through the years to entrap/encapsulate this valuable drug in nanocarriers aiming to reach its most appropriate and successful delivery system.