Despite recent advances in bioinformatics, systems biology, and machine learning, the accurate prediction of drug properties remains an open problem. Indeed, because the biological environment is a complex system, the traditional approach—based on knowledge about the chemical structures—can not fully explain the nature of interactions between drugs and biological targets. Consequently, in this paper, we propose an unsupervised machine learning approach that uses the information we know about drug–target interactions to infer drug properties. To this end, we define drug similarity based on drug–target interactions and build a weighted Drug–Drug Similarity Network according to the drug–drug similarity relationships. Using an energy-model network layout, we generate drug communities associated with specific, dominant drug properties. DrugBank confirms the properties of 59.52% of the drugs in these communities, and 26.98% are existing drug repositioning hints we reconstruct with our DDSN approach. The remaining 13.49% of the drugs seem not to match the dominant pharmacologic property; thus, we consider them potential drug repurposing hints. The resources required to test all these repurposing hints are considerable. Therefore we introduce a mechanism of prioritization based on the betweenness/degree node centrality. Using betweenness/degree as an indicator of drug repurposing potential, we select Azelaic acid and Meprobamate as a possible antineoplastic and antifungal, respectively. Finally, we use a test procedure based on molecular docking to analyze Azelaic acid and Meprobamate’s repurposing.

Asthma represents a heterogeneous disorder characterized by a dynamic balance between pro-inflammatory and anti-inflammatory forces, with allergic sensitization contributing substantially to airway hyperresponsiveness and remodeling. Central to its pathogenesis are cytokines such as IL-4, IL-5, IL-13, IL-17, and IL-33, which drive recruitment of eosinophils, neutrophils, and other effector cells, thereby precipitating episodic exacerbations in response to viral and environmental triggers. Conventional biomarkers, including blood and sputum eosinophil counts, IgE levels, and fractional exhaled nitric oxide, facilitate phenotypic classification and guide the emerging biologic era. Monoclonal antibodies targeting IgE (omalizumab) and IL-5 (mepolizumab, benralizumab, reslizumab, depemokimab) have demonstrated the ability to reduce exacerbation frequency and improve lung function, with newer agents such as depemokimab offering extended dosing intervals. Itepekimab, an anti-IL-33 antibody, effectively engages its target and mitigates tissue eosinophilia, while CM310-stapokibart, tralokinumab, and lebrikizumab inhibit IL-4/IL-13 signaling with variable efficacy depending on patient biomarkers. Comparative analyses of these biologics, encompassing affinity, dosing regimens, and trial outcomes, underscore the imperative of personalized therapy to optimize disease control in severe asthma.

Cyclodextrins (CDs) have traditionally been recognized as excipients that enhance solubility and stability of drugs. However, growing evidence shows that CDs themselves can act as active therapeutic agents. Their unique supramolecular properties enable them to interact with biological membranes, mobilize cholesterol, and modulate immune responses. This review highlights four therapeutic areas where CDs demonstrate particular promise. First, in gene and mRNA therapy, cationic CD derivatives form nanoparticles that protect nucleic acids, promote endosomal escape, and achieve targeted delivery. Second, in neurodegenerative disorders such as Niemann–Pick type C and Alzheimer’s disease, hydroxypropyl-β-CD facilitates cholesterol clearance and reduces pathological lipid accumulation. Third, in detoxification, the γ-CD derivative sugammadex exemplifies a clinically approved agent that encapsulates neuromuscular blockers to reverse anesthesia. Finally, CDs have emerged as safe vaccine adjuvants, inducing robust systemic and mucosal immunity with reduced IgE responses compared to alum. Together, these examples illustrate a paradigm shift: CDs are not only versatile excipients but also active molecules with direct therapeutic effects. Future translation will require careful optimization of safety, scalability, and regulatory compliance, but CDs are poised to contribute meaningfully to next-generation medicines.

Risperidone (RSP) is an atypical antipsychotic drug used in treating schizophrenia, behavioral, and psychological symptoms of dementia and irritability associated with autism. The drug substance is practically insoluble in water and exhibits high lipophilicity. It also presents incompatibilities with pharmaceutical excipients such as magnesium stearate, lactose, and cellulose microcrystalline. RSP encapsulation by randomly methylated β-cyclodextrin (RM-β-CD) was performed in order to enhance drug solubility and stability and improve its biopharmaceutical profile. The inclusion complex formation was evaluated using thermal methods, powder X-ray diffractometry (PXRD), universal-attenuated total reflectance Fourier transform infrared (UATR-FTIR), UV spectroscopy, and saturation solubility studies. The 1:1 stoichiometry ratio and the apparent stability constant of the inclusion complex were determined by means of the phase solubility method. The compatibility between the supramolecular adduct and pharmaceutical excipients starch, anhydrous lactose, magnesium stearate, and cellulose microcrystalline was studied employing thermoanalytical tools (TG-thermogravimetry/DTG-derivative thermogravimetry/HF-heat flow) and spectroscopic techniques (UATR-FTIR, PXRD). The compatibility study reveals that there are no interactions between the supramolecular adduct with starch, magnesium stearate, and cellulose microcrystalline, while incompatibility with anhydrous lactose is observed even under ambient conditions. The supramolecular adduct of RSP with RM-β-CD represents a valuable candidate for further research in developing new formulations with enhanced bioavailability and stability, and the results of this study allow a pertinent selection of three excipients that can be incorporated in solid dosage forms.

Risperidone (RSP) is an atypical antipsychotic drug which acts as a potent antagonist of serotonin-2 (5TH2) and dopamine-2 (D2) receptors in the brain; it is used to treat schizophrenia, behavioral and psychological symptoms of dementia and irritability associated with autism. It is a poorly water soluble benzoxazole derivative with high lipophilicity. Supramolecular adducts between drug substance and two methylated β-cyclodextrins, namely heptakis(2,6-di-O-methyl)-β-cyclodextrin (DM-β-CD) and heptakis(2,3,6-tri-O-methyl)-β-cyclodextrin (TM-β-CD) were obtained in order to enhance RSP solubility and improve its biopharmaceutical profile. The inclusion complexes were evaluated by means of thermoanalytical methods (TG—thermogravimetry/DTG—derivative thermogravimetry/HF—heat flow), powder X-ray diffractometry (PXRD), universal-attenuated total reflectance Fourier transform infrared (UATR-FTIR), UV spectroscopy and saturation solubility studies. Job’s method was employed for the determination of the stoichiometry of the inclusion complexes, which was found to be 2:1 for both guest–host systems. Molecular modeling studies were carried out for an in-depth characterization of the interaction between drug substance and cyclodextrins (CDs). The physicochemical properties of the supramolecular systems differ from those of RSP, demonstrating the inclusion complex formation between drug and CDs. The RSP solubility was enhanced as a result of drug encapsulation in the CDs cavity, the higher increase being obtained with DM-β-CD as host; the guest–host system RSP/DM-β-CD can thus be a starting point for further research in developing new formulations containing RSP, with enhanced bioavailability.

Obesity is a major, modifiable driver of endometrial carcinogenesis. This review distills how excess adiposity promotes malignant change and synthesizes prevention strategies across the hyperplasia–cancer continuum. Three converging axes underpin risk: aromatase-mediated estrogen excess; insulin resistance with hyperinsulinemia activating PI3K–AKT–mTOR signaling; and adipokine-driven low-grade inflammation with downstream NF-κB/STAT3 activity. Within this framework, EIN is the key precursor in which these pathways coalesce. Risk can be attenuated through progestin-based therapy (levonorgestrel-releasing intrauterine system or continuous oral regimens), structured weight management, and metabolic adjuncts in selected phenotypes (e.g., metformin for insulin resistance; incretin-based anti-obesity agents as emerging options). Bariatric surgery produces substantial weight loss and favorable metabolic shifts, though evidence for cancer risk reduction is largely observational. Overall, a practical precision-prevention approach—combining progestins with durable weight control and metabolic optimization under guideline-concordant surveillance—appears feasible in routine gynecologic care. Future research should establish causal effects, durability, and optimal sequencing/combination of interventions in trials with endometrial endpoints.