Cheminformatics-driven discovery of polymeric micelle formulations for poorly soluble drugs

GWAS meta-analysis reveals key risk loci in essential tremor pathogenesis

Essential tremor (ET) is a prevalent neurological disorder with a largely unknown underlying biology. In this genome-wide association study meta-analysis, comprising 16,480 ET cases and 1,936,173 controls from seven datasets, we identify 12 sequence variants at 11 loci. Evaluating mRNA expression, splicing, plasma protein levels, and coding effects, we highlight seven putative causal genes at these loci, including CA3 and CPLX1. CA3 encodes Carbonic Anhydrase III and carbonic anhydrase inhibitors have been shown to decrease tremors. CPLX1, encoding Complexin-1, regulates neurotransmitter release. Through gene-set enrichment analysis, we identify a significant association with specific cell types, including dopaminergic and GABAergic neurons, as well as biological processes like Rho GTPase signaling. Genetic correlation analyses reveals a positive association between ET and Parkinson's disease, depression, and anxiety-related phenotypes. This research uncovers risk loci, enhancing our knowledge of the complex genetics of this common but poorly understood disorder, and highlights CA3 and CPLX1 as potential therapeutic targets.

Unravel the Tangle: Atomistic Insight into Ultrahigh Curcumin-Loaded Polymer Micelles

Amphiphilic ABA-triblock copolymers, comprised of poly(2-oxazoline) and poly(2-oxazine), can solubilize poorly water-soluble molecules in a structure-dependent manner forming micelles with exceptionally high drug loading. All-atom molecular dynamics simulations are conducted on previously experimentally characterized, curcumin-loaded micelles to dissect the structure-property relationships. Polymer-drug interactions for different levels of drug loading and variation in polymer structures of both the inner hydrophobic core and outer hydrophilic shell are investigated. In silico, the system with the highest experimental loading capacity shows the highest number of drug molecules encapsulated by the core. Furthermore, in systems with lower loading capacity outer A blocks show a greater extent of entanglement with the inner B blocks. Hydrogen bond analyses corroborate previous hypotheses: poly(2-butyl-2-oxazoline) B blocks, found experimentally to have reduced loading capacity for curcumin compared to poly(2-propyl-2-oxazine), establish fewer but longer-lasting hydrogen bonds. This possibly results from different sidechain conformations around the hydrophobic cargo, which is investigated by unsupervised machine learning to cluster monomers in smaller model systems mimicking different micelle compartments. Exchanging poly(2-methyl-2-oxazoline) with poly(2-ethyl-2-oxazoline) leads to increased drug interactions and reduced corona hydration; this suggests an impairment of micelle solubility or colloidal stability. These observations can help driving forward a more rational a priori nanoformulation design.

Molecular Docking-Guided Design on Glucose-Responsive Nanoparticles for Microneedle Fabrication and "Three-Meal-per-Day" Blood-Glucose Regulation

It was greatly significant, but difficult, to develop stimulus-responsive polymeric nanoparticles with efficient protein-loading and protein-delivering properties. Crucial obstacles were the ambiguous protein/nanoparticle-interacting mechanisms and the corresponding inefficient trial-and-error strategies, which brought large quantities of experiments in design and optimization. In this work, a molecular docking-guided universal "segment-functional group-polymer" process was proposed to simplify the previous laborious experimental step. The insulin-delivering glucose-responsive polymeric nanoparticles for diabetic treatments were taken as the examples. The molecular docking study obtained insights from the insulin/segment interactions. It was then experimentally confirmed in six functional groups for insulin-loading performances of their corresponding polymers. The optimization formulation was further proved effective in blood-glucose stabilization on the diabetic rats under the "three-meal-per-day" mode. It was believed that the molecular docking-guided designing process was promising in the protein-delivering field.

Converting Nanotoxicity Data to Information Using Artificial Intelligence and Simulation

Decades of nanotoxicology research have generated extensive and diverse data sets. However, data is not equal to information. The question is how to extract critical information buried in vast data streams. Here we show that artificial intelligence (AI) and molecular simulation play key roles in transforming nanotoxicity data into critical information, i.e., constructing the quantitative nanostructure (physicochemical properties)-toxicity relationships, and elucidating the toxicity-related molecular mechanisms. For AI and molecular simulation to realize their full impacts in this mission, several obstacles must be overcome. These include the paucity of high-quality nanomaterials (NMs) and standardized nanotoxicity data, the lack of model-friendly databases, the scarcity of specific and universal nanodescriptors, and the inability to simulate NMs at realistic spatial and temporal scales. This review provides a comprehensive and representative, but not exhaustive, summary of the current capability gaps and tools required to fill these formidable gaps. Specifically, we discuss the applications of AI and molecular simulation, which can address the large-scale data challenge for nanotoxicology research. The need for model-friendly nanotoxicity databases, powerful nanodescriptors, new modeling approaches, molecular mechanism analysis, and design of the next-generation NMs are also critically discussed. Finally, we provide a perspective on future trends and challenges.

Influence of Molecular Structure and Physicochemical Properties of Immunosuppressive Drugs on Micelle Formulation Characteristics and Cutaneous Delivery

The aim of this study was to investigate whether subtle differences in molecular properties affected polymeric micelle characteristics and their ability to deliver poorly water-soluble drugs into the skin. D-α-tocopherol-polyethylene glycol 1000 was used to prepare micelles containing ascomycin-derived immunosuppressants-sirolimus (SIR), pimecrolimus (PIM) and tacrolimus (TAC)-which have similar structures and physicochemical properties and have dermatological applications. Micelle formulations were prepared by thin-film hydration and extensively characterized. Cutaneous delivery and biodistribution were determined and compared. Sub-10 nm micelles were obtained for the three immunosuppressants with incorporation efficiencies >85%. However, differences were observed for drug loading, stability (at the highest concentration), and their in vitro release kinetics. These were attributed to differences in drug aqueous solubility and lipophilicity. Differences between the cutaneous biodistribution profiles and drug deposition in the different skin compartments pointed to the impact of differences in thermodynamic activity. Therefore, despite their structural similarities, SIR, TAC and PIM did not demonstrate the same behaviour either in the micelles or when applied to the skin. These outcomes indicate that polymeric micelles should be optimized even for closely related drug molecules and support the hypothesis that drugs are released from micelles prior to skin penetration.

New Advances in Biomedical Application of Polymeric Micelles

In the last decade, nanomedicine has arisen as an emergent area of medicine, which studies nanometric systems, namely polymeric micelles (PMs), that increase the solubility and the stability of the encapsulated drugs. Furthermore, their application in dermal drug delivery is also relevant. PMs present unique characteristics because of their unique core-shell architecture. They are colloidal dispersions of amphiphilic compounds, which self-assemble in an aqueous medium, giving a structure-type core-shell, with a hydrophobic core (that can encapsulate hydrophobic drugs), and a hydrophilic shell, which works as a stabilizing agent. These features offer PMs adequate steric protection and determine their hydrophilicity, charge, length, and surface density properties. Furthermore, due to their small size, PMs can be absorbed by the intestinal mucosa with the drug, and they transport the drug in the bloodstream until the therapeutic target. Moreover, PMs improve the pharmacokinetic profile of the encapsulated drug, present high load capacity, and are synthesized by a reproducible, easy, and low-cost method. In silico approaches have been explored to improve the physicochemical properties of PMs. Based on this, a computer-aided strategy was developed and validated to enable the delivery of poorly soluble drugs and established critical physicochemical parameters to maximize drug loading, formulation stability, and tumor exposure. Poly(2-oxazoline) (POx)-based PMs display unprecedented high loading concerning water-insoluble drugs and over 60 drugs have been incorporated in POx PMs. Among various stimuli, pH and temperature are the most widely studied for enhanced drug release at the site of action. Researchers are focusing on dual (pH and temperature) responsive PMs for controlled and improved drug release at the site of action. These dual responsive systems are mainly evaluated for cancer therapy as certain malignancies can cause a slight increase in temperature and a decrease in the extracellular pH around the tumor site. This review is a compilation of updated therapeutic applications of PMs, such as PMs that are based on Pluronics^®, micelleplexes and Pox-based PMs in several biomedical applications.

Accelerating Discovery of High Fractional Free Volume Polymers from a Data-Driven Approach

As a fundamental structure characteristic in polymers, fractional free volume (FFV) plays an indispensable role in governing polymer properties and performance. However, the design of new high-FFV polymers is challenging. In this study, we report a data-driven approach and aim to accelerate the discovery of high-FFV polymers. First, a computational method is proposed to calculate FFV, and a two-step fragmentation method is developed to construct a fragment library for digital representation of polymer structures. Data mining is employed to identify promising fragments for high FFV. Subsequently, machine learning (ML) models are trained using a data set with 1683 polymers and their excellent transferability is demonstrated by out-of-sample predictions in another data set with 11,479 polymers. Finally, the ML models are used to screen ∼1 million hypothetical polymers, and 29,482 polymers with FFV > 0.2 are shortlisted; representative high-FFV polymers are validated by molecular simulations, and design strategies are highlighted. To further facilitate the discovery of new high-FFV polymers, we develop an online interactive platform https://ffv-prediction.herokuapp.com, which allows for rapid FFV predictions, given polymer structures. The data-driven approach in this study might advance the development of new high-FFV polymers and further explore quantitative structure-property relationships for polymers.

Materiomically Designed Polymeric Vehicles for Nucleic Acids: Quo Vadis?

Despite rapid advances in molecular biology, particularly in site-specific genome editing technologies, such as CRISPR/Cas9 and base editing, financial and logistical challenges hinder a broad population from accessing and benefiting from gene therapy. To improve the affordability and scalability of gene therapy, we need to deploy chemically defined, economical, and scalable materials, such as synthetic polymers. For polymers to deliver nucleic acids efficaciously to targeted cells, they must optimally combine design attributes, such as architecture, length, composition, spatial distribution of monomers, basicity, hydrophilic-hydrophobic phase balance, or protonation degree. Designing polymeric vectors for specific nucleic acid payloads is a multivariate optimization problem wherein even minuscule deviations from the optimum are poorly tolerated. To explore the multivariate polymer design space rapidly, efficiently, and fruitfully, we must integrate parallelized polymer synthesis, high-throughput biological screening, and statistical modeling. Although materiomics approaches promise to streamline polymeric vector development, several methodological ambiguities must be resolved. For instance, establishing a flexible polymer ontology that accommodates recent synthetic advances, enforcing uniform polymer characterization and data reporting standards, and implementing multiplexed in vitro and in vivo screening studies require considerable planning, coordination, and effort. This contribution will acquaint readers with the challenges associated with materiomics approaches to polymeric gene delivery and offers guidelines for overcoming these challenges. Here, we summarize recent developments in combinatorial polymer synthesis, high-throughput screening of polymeric vectors, omics-based approaches to polymer design, barcoding schemes for pooled in vitro and in vivo screening, and identify materiomics-inspired research directions that will realize the long-unfulfilled clinical potential of polymeric carriers in gene therapy.

Soluplus® polymeric nanomicelles improve solubility of BCS-class II drugs

The issue of poor aqueous solubility is often a great hitch in the development of liquid dosage forms for those drugs that the Biopharmaceutics Classification System (BCS) includes in classes II and IV. Among the possible technological solutions, inclusion of the drug molecule within polymeric micelles, and particularly nanomicelles, has been proposed in the last years as a valid strategy. Our attention has been recently attracted by Soluplus^®, an amphiphilic polyvinyl caprolactam-polyvinyl acetate-polyethylene glycol graft copolymer able to form small and stable nanomicelles. The aim of this study was to characterize Soluplus^® nanomicelles to enhance the apparent solubility of three model APIs, categorized in BCS class II: ibuprofen (IBU), idebenone (IDE), and miconazole (MIC). Drug-loaded Soluplus^® micelles with a mean size around 60–70 nm were prepared by two methods (direct dissolution or film hydration method). The prepared nanosystems were characterized in terms of mean particle size and Zeta potential, physical stability, drug solubility, and in vitro drug release. The solubility of the tested APIs was shown to increase linearly with the concentration of graft copolymer. Soluplus^® can be easily submitted to membrane filtration (0.2 µm PES or PTFE membranes), showing the potential to be sterilized by this method. Freeze-drying enabled to obtain powder materials that, upon reconstitution with water, maintained the initial micelle size. Finally, viscosity studies indicated that these nanomicelles have potential applications where a bioadhesive material is advantageous, such as in topical ocular administration.

Nanoformulated Remdesivir with Extremely Low Content of Poly(2-oxazoline) - Based Stabilizer for Aerosol Treatment of COVID-19

The rise of the novel virus SARS-CoV2 which causes the disease known as COVID-19 has led to a global pandemic claiming millions of lives. With no clinically approved treatment for COVID-19, physicians initially struggled to treat the disease, and a need remains for improved anti-viral therapies in this area. We conceived early in the pandemic that an inhalable formulation of the drug remdesivir which directly targets the virus at the site of infection could improve therapeutic outcomes in COVID-19. We developed a set of requirements that would be conducive to rapid drug approval: 1) try to use GRAS reagents 2) minimize excipient concentration and 3) achieve a working concentration of 5 mg/mL remdesivir to obtain a deliverable dose which is 5-10% of the IV dose. In this work, we discovered that Poly(2-oxazoline) block copolymers can stabilize drug nanocrystal suspensions and provide suitable formulation characteristics for aerosol delivery while maintaining anti-viral efficacy. We believe POx block copolymers can be used as a semi-ubiquitous stabilizer for the rapid development of nanocrystal formulations for new and existing diseases. This article is protected by copyright. All rights reserved.

Multipotent Poly(Tertiary Amine-Oxide) Micelles for Efficient Cancer Drug Delivery

The cancer drug delivery process involves a series of biological barriers, which require the nanomedicine to exhibit different, even opposite properties for high therapeutic efficacy. The prevailing design philosophy, i.e., integrating these properties within one nanomedicine via on-demand property transitions such as PEGylation/dePEGylation, complicates nanomedicines' composition and thus impedes clinical translation. Here, polyzwitterionic micelles of poly(tertiary amine-oxide)-block-poly(ε-caprolactone) (PTAO-PCL) amphiphiles that enable all the required functions are presented. The zwitterionic nature and unique cell membrane affinity confer the PTAO micelles long blood circulation, efficient tumor accumulation and penetration, and fast cellular internalization. The mitochondrial targeting capability allows drug delivery into the mitochondria to induce mitochondrial dysfunction and overcome tumor multidrug resistance. As a result, the PTAO/drug micelles exhibit potent anticancer efficacy. This simple yet multipotent carrier system holds great promise as a generic platform for potential clinical translation.

Merging data curation and machine learning to improve nanomedicines

Nanomedicine design is often a trial-and-error process, and the optimization of formulations and in vivo properties requires tremendous benchwork. To expedite the nanomedicine research progress, data science is steadily gaining importance in the field of nanomedicine. Recently, efforts have explored the potential to predict nanomaterials synthesis and biological behaviors via advanced data analytics. Machine learning algorithms process large datasets to understand and predict various material properties in nanomedicine synthesis, pharmacologic parameters, and efficacy. "Big data" approaches may enable even larger advances, especially if researchers capitalize on data curation methods. However, the concomitant use of data curation processes needed to facilitate the acquisition and standardization of large, heterogeneous data sets, to support advanced data analytics methods such as machine learning has yet to be leveraged. Currently, data curation and data analytics areas of nanotechnology-focused data science, or 'nanoinformatics', have been proceeding largely independently. This review highlights the current efforts in both areas and the potential opportunities for coordination to advance the capabilities of data analytics in nanomedicine.

Emerging Landscape of Computational Modeling in Pharmaceutical Development

Computational chemistry applications have become an integral part of the drug discovery workflow over the past 35 years. However, computational modeling in support of drug development has remained a relatively uncharted territory for a significant part of both academic and industrial communities. This review considers the computational modeling workflows for three key components of drug preclinical and clinical development, namely, process chemistry, analytical research and development, as well as drug product and formulation development. An overview of the computational support for each step of the respective workflows is presented. Additionally, in context of solid form design, special consideration is given to modern physics-based virtual screening methods. This covers rational approaches to polymorph, coformer, counterion, and solvent virtual screening in support of solid form selection and design.

Drug-Dependent Morphological Transitions in Spherical and Worm-Like Polymeric Micelles Define Stability and Pharmacological Performance of Micellar Drugs

Significant advances in physicochemical properties of polymeric micelles enable optimization of therapeutic drug efficacy, supporting nanomedicine manufacturing and clinical translation. Yet, the effect of micelle morphology on pharmacological efficacy is not adequately addressed. This work addresses this gap by assessing pharmacological efficacy of polymeric micelles with spherical and worm-like morphologies. It is observed that poly(2-oxazoline)-based polymeric micelles can be elongated over time from a spherical structure to worm-like structure, with elongation influenced by several conditions, including the amount and type of drug loaded into the micelles. The role of different morphologies on pharmacological performance of drug loaded micelles against triple-negative breast cancer and pancreatic cancer tumor models is further evaluated. Spherical micelles accumulate rapidly in the tumor tissue while retaining large amounts of drug; worm-like micelles accumulate more slowly and only upon releasing significant amounts of drug. These findings suggest that the dynamic character of the drug-micelle structure and the micelle morphology play a critical role in pharmacological performance, and that spherical micelles are better suited for systemic delivery of anticancer drugs to tumors when drugs are loosely associated with the polymeric micelles.

Drug-Dependent Morphological Transitions in Spherical and Worm-Like Polymeric Micelles Define Stability and Pharmacological Performance of Micellar Drugs

Significant advances in physicochemical properties of polymeric micelles enable optimization of therapeutic drug efficacy, supporting nanomedicine manufacturing and clinical translation. Yet, the effect of micelle morphology on pharmacological efficacy is not adequately addressed. This work addresses this gap by assessing pharmacological efficacy of polymeric micelles with spherical and worm-like morphologies. It is observed that poly(2-oxazoline)-based polymeric micelles can be elongated over time from a spherical structure to worm-like structure, with elongation influenced by several conditions, including the amount and type of drug loaded into the micelles. The role of different morphologies on pharmacological performance of drug loaded micelles against triple-negative breast cancer and pancreatic cancer tumor models is further evaluated. Spherical micelles accumulate rapidly in the tumor tissue while retaining large amounts of drug; worm-like micelles accumulate more slowly and only upon releasing significant amounts of drug. These findings suggest that the dynamic character of the drug-micelle structure and the micelle morphology play a critical role in pharmacological performance, and that spherical micelles are better suited for systemic delivery of anticancer drugs to tumors when drugs are loosely associated with the polymeric micelles.

Alkyl Chain Length in Poly(2-oxazoline)-Based Amphiphilic Gradient Copolymers Regulates the Delivery of Hydrophobic Molecules: A Case of the Biodistribution and the Photodynamic Activity of the Photosensitizer Hypericin

Self-assembled nanostructures of amphiphilic gradient copoly(2-oxazoline)s have recently attracted attention as promising delivery systems for the effective delivery of hydrophobic anticancer drugs. In this study, we have investigated the effects of increasing hydrophobic side chain length on the self-assembly of gradient copolymers composed of 2-ethyl-2-oxazoline as the hydrophilic comonomer and various 2-(4-alkyloxyphenyl)-2-oxazolines as hydrophobic comonomers. We show that the size of the formed polymeric nanoparticles depends on the structure of the copolymers. Moreover, the stability and properties of the polymeric assembly can be affected by the loading of hypericin, a promising compound for photodiagnostics and photodynamic therapy (PDT). We have found the limitation that allows rapid or late release of hypericin from polymeric nanoparticles. The nanoparticles entering the cells by endocytosis decreased the hypericin-induced PDT, and the contribution of the passive process (diffusion) increased the probability of a stronger photoeffect. A study of fluorescence pharmacokinetics and biodistribution revealed differences in the release of hypericin from nanoparticles toward the quail chorioallantoic membrane, a preclinical model for in vivo studies, depending on the composition of polymeric nanoparticles. Photodamage induced by PDT in vivo well correlated with the in vitro results. All formulations studied succeeded in targeting hypericin at cancer cells. In conclusion, we demonstrated the promising potential of poly(2-oxazoline)-based gradient copolymers for effective drug delivery and sequential drug release needed for successful photodiagnostics and PDT in cancer therapy.

Simplex representation of molecular structure as universal QSAR/QSPR tool

We review the development and application of the Simplex approach for the solution of various QSAR/QSPR problems. The general concept of the simplex method and its varieties are described. The advantages of utilizing this methodology, especially for the interpretation of QSAR/QSPR models, are presented in comparison to other fragmentary methods of molecular structure representation. The utility of SiRMS is demonstrated not only in the standard QSAR/QSPR applications, but also for mixtures, polymers, materials, and other complex systems. In addition to many different types of biological activity (antiviral, antimicrobial, antitumor, psychotropic, analgesic, etc.), toxicity and bioavailability, the review examines the simulation of important properties, such as water solubility, lipophilicity, as well as luminescence, and thermodynamic properties (melting and boiling temperatures, critical parameters, etc.). This review focuses on the stereochemical description of molecules within the simplex approach and details the possibilities of universal molecular stereo-analysis and stereochemical configuration description, along with stereo-isomerization mechanism and molecular fragment "topography" identification.

Preparation and Characterization of Poly(2-oxazoline) Micelles for the Solubilization and Delivery of Water Insoluble Drugs

Many new drug development candidates are highly lipophilic compounds with low water solubility. This constitutes a formidable challenge for the use of such compounds for cancer therapy, where high doses and intravenous injections are needed ( Di et al., 2012 ). Here, we present a poly(2-oxazoline) polymer (POx)-based nanoformulation strategy to solubilize and deliver hydrophobic drugs. POx micelles are prepared by a simple thin-film hydration method. In this method, the drug and polymer are dissolved in a common solvent and allowed to mix, following which the solvent is evaporated using mild heating conditions to form a thin film. The micelles form spontaneously upon hydration with saline. POx nanoformulation of hydrophobic drugs is unique in that it has a high drug loading capacity, which is superior to micelles of conventional surfactants. Moreover, multiple active pharmaceutical ingredients (APIs) can be included within the same POx micelle, thereby enabling the codelivery of binary as well as ternary drug combinations ( Han et al., 2012 ; He et al., 2016 ).

Poly(2-oxazoline)- and Poly(2-oxazine)-Based Self-Assemblies, Polyplexes, and Drug Nanoformulations-An Update

For many decades, poly(2-oxazoline)s and poly(2-oxazine)s, two closely related families of polymers, have led the life of a rather obscure research topic with only a few research groups world-wide working with them. This has changed in the last five to ten years, presumably triggered significantly by very promising clinical trials of the first poly(2-oxazoline)-based drug conjugate. The huge chemical and structural toolbox poly(2-oxazoline)s and poly(2-oxazine)s has been extended very significantly in the last few years, but their potential still remains largely untapped. Here, specifically, the developments in macromolecular self-assemblies and non-covalent drug delivery systems such as polyplexes and drug nanoformulations based on poly(2-oxazoline)s and poly(2-oxazine)s are reviewed. This highly dynamic field benefits particularly from the extensive synthetic toolbox poly(2-oxazoline)s and poly(2-oxazine)s offer and also may have the largest potential for a further development. It is expected that the research dynamics will remain high in the next few years, particularly as more about the safety and therapeutic potential of poly(2-oxazoline)s and poly(2-oxazine)s is learned.

Do genetic risk scores for childhood adiposity operate independent of BMI of their mothers?

OBJECTIVES

Genetic predisposition and maternal body mass index (BMI) are risk factors for childhood adiposity, defined by either BMI or overweight. We aimed to investigate whether childhood-specific genetic risk scores (GRSs) for adiposity-related traits are associated with childhood adiposity independent of maternal BMI, or whether the associations are modified by maternal BMI.

METHODS

We constructed a weighted 26-SNP child BMI-GRS and a weighted 17-SNP child obesity-GRS in overall 1674 genotyped children within the Danish National Birth Cohort. We applied a case-cohort (N = 1261) and exposure-based cohort (N = 912) sampling design. Using logistic regression models we estimated associations of the GRSs and child overweight at age 7 years and examined if the GRSs influence child adiposity independent of maternal BMI (per standard deviation units).

RESULTS

In the case-cohort design analysis, maternal BMI and the child GRSs were associated with increased odds for childhood overweight [OR for maternal BMI: 2.01 (95% CI: 1.86; 2.17), OR for child BMI-GRS: 1.56 (95% CI: 1.47; 1.66), and OR for child obesity-GRS 1.46 (95% CI: 1.37; 1.54)]. Adjustment for maternal BMI did not change the results, and there were no significant interactions between the GRSs and maternal BMI. However, in the exposure-based cohort design analysis, significant interactions between the child GRSs and maternal BMI on child overweight were observed, suggesting 0.85-0.87-fold attenuation on ORs of child overweight at higher values of maternal BMI and child GRS.

CONCLUSION

GRSs for childhood adiposity are strongly associated with childhood adiposity even when adjusted for maternal BMI, suggesting that the child-specific GRSs and maternal BMI contribute to childhood overweight independent of each other. However, high maternal BMI may attenuate the effects of child GRSs in children.

Mechanistic Understanding From Molecular Dynamics Simulation in Pharmaceutical Research 1: Drug Delivery

In this review, we outline the growing role that molecular dynamics simulation is able to play as a design tool in drug delivery. We cover both the pharmaceutical and computational backgrounds, in a pedagogical fashion, as this review is designed to be equally accessible to pharmaceutical researchers interested in what this new computational tool is capable of and experts in molecular modeling who wish to pursue pharmaceutical applications as a context for their research. The field has become too broad for us to concisely describe all work that has been carried out; many comprehensive reviews on subtopics of this area are cited. We discuss the insight molecular dynamics modeling has provided in dissolution and solubility, however, the majority of the discussion is focused on nanomedicine: the development of nanoscale drug delivery vehicles. Here we focus on three areas where molecular dynamics modeling has had a particularly strong impact: (1) behavior in the bloodstream and protective polymer corona, (2) Drug loading and controlled release, and (3) Nanoparticle interaction with both model and biological membranes. We conclude with some thoughts on the role that molecular dynamics simulation can grow to play in the development of new drug delivery systems.

Polymeric micelles for the delivery of poorly soluble drugs: From nanoformulation to clinical approval

Over the last three decades, polymeric micelles have emerged as a highly promising drug delivery platform for therapeutic compounds. Particularly, poorly soluble small molecules with high potency and significant toxicity were encapsulated in polymeric micelles. Polymeric micelles have shown improved pharmacokinetic profiles in preclinical animal models and enhanced efficacy with a superior safety profile for therapeutic drugs. Several polymeric micelle formulations have reached the clinical stage and are either in clinical trials or are approved for human use. This furthers interest in this field and underscores the need for additional learning of how to best design and apply these micellar carriers to improve the clinical outcomes of many drugs. In this review, we provide detailed information on polymeric micelles for the solubilization of poorly soluble small molecules in topics such as the design of block copolymers, experimental and theoretical analysis of drug encapsulation in polymeric micelles, pharmacokinetics of drugs in polymeric micelles, regulatory approval pathways of nanomedicines, and current outcomes from micelle formulations in clinical trials. We aim to describe the latest information on advanced analytical approaches for elucidating molecular interactions within the core of polymeric micelles for effective solubilization as well as for analyzing nanomedicine's pharmacokinetic profiles. Taking into account the considerations described within, academic and industrial researchers can continue to elucidate novel interactions in polymeric micelles and capitalize on their potential as drug delivery vehicles to help improve therapeutic outcomes in systemic delivery.

Computer-Aided Discovery of New Solubility-Enhancing Drug Delivery System

The poor aqueous solubility of active pharmaceutical ingredients (APIs) places a limit on their therapeutic potential. Cyclodextrins (CDs) have been shown to improve the solubility of APIs, but the magnitude of the improvement depends on the structure of both the CDs and APIs. We have developed quantitative structure-property relationship (QSPR) models that predict the stability of the complexes formed by a popular poorly soluble antibiotic, cefuroxime axetil (CA) and different CDs. We applied this model to five CA-CD systems not included in the modeling set. Two out of three systems predicted to have poor stability and poor CA solubility, and both CA-CD systems predicted to have high stability and high CA solubility were confirmed experimentally. One of the CDs that significantly improved CA solubility, methyl-βCD, is described here for the first time, and we propose this CD as a novel promising excipient. Computational approaches and models developed and validated in this study could help accelerate the development of multifunctional CDs-based formulations.

QSAR without borders

Prediction of chemical bioactivity and physical properties has been one of the most important applications of statistical and more recently, machine learning and artificial intelligence methods in chemical sciences. This field of research, broadly known as quantitative structure-activity relationships (QSAR) modeling, has developed many important algorithms and has found a broad range of applications in physical organic and medicinal chemistry in the past 55+ years. This Perspective summarizes recent technological advances in QSAR modeling but it also highlights the applicability of algorithms, modeling methods, and validation practices developed in QSAR to a wide range of research areas outside of traditional QSAR boundaries including synthesis planning, nanotechnology, materials science, biomaterials, and clinical informatics. As modern research methods generate rapidly increasing amounts of data, the knowledge of robust data-driven modelling methods professed within the QSAR field can become essential for scientists working both within and outside of chemical research. We hope that this contribution highlighting the generalizable components of QSAR modeling will serve to address this challenge.

Think Beyond the Core: Impact of the Hydrophilic Corona on Drug Solubilization Using Polymer Micelles

Polymeric micelles are typically characterized as core-shell structures. The hydrophobic core is considered as a depot for hydrophobic molecules, and the corona-forming block acts as a stabilizing and solubilizing interface between the core and aqueous milieu. Tremendous efforts have been made to tune the hydrophobic block to increase the drug loading and stability of micelles, whereas the role of hydrophilic blocks is rarely investigated in this context, with poly(ethylene glycol) (PEG) being the gold standard of hydrophilic polymers. To better understand the role of the hydrophilic corona, a small library of structurally similar A-B-A-type amphiphiles based on poly(2-oxazoline)s and poly(2-oxazine)s is investigated by varying the hydrophilic block A utilizing poly(2-methyl-2-oxazoline) (pMeOx; A) or poly(2-ethyl-2-oxazoline) (pEtOx; A*). In terms of hydrophilicity, both polymers closely resemble PEG. The more hydrophobic block B bears either a poly(2-oxazoline) and poly(2-oxazine) backbone with C3 (propyl) and C4 (butyl) side chains. Surprisingly, major differences in loading capacities from A-B-A > A*-B-A > A*-B-A* is observed for the formulation with two poorly water-soluble compounds, curcumin and paclitaxel, highlighting the importance of the hydrophilic corona of polymer micelles used for drug formulation. The formulations are also characterized by various nuclear magnetic resonance spectroscopy methods, dynamic light scattering, cryogenic transmission electron microscopy, and (micro) differential scanning calorimetry. Our findings suggest that the interaction between the hydrophilic block and the guest molecule should be considered an important, but previously largely ignored, factor for the rational design of polymeric micelles.