Adequate aqueous solubility has been one of the desired properties while selecting drug molecules and other bio-actives for product development. Often solubility of a drug determines its pharmaceutical and therapeutic performance. Majority of newly synthesized drug molecules fail or are rejected during the early phases of drug discovery and development due to their limited solubility. Sufficient permeability, aqueous solubility and physicochemical stability of the drug are important for achieving adequate bioavailability and therapeutic outcome. A number of different approaches including co-solvency, micellar solubilization, micronization, pH adjustment, chemical modification, and solid dispersion have been explored towards improving the solubility of various poorly aqueous-soluble drugs. Dendrimers, a new class of polymers, possess great potential for drug solubility improvement, by virtue of their unique properties. These hyper-branched, mono-dispersed molecules have the distinct ability to bind the drug molecules on periphery as well as to encapsulate these molecules within the dendritic structure. There are numerous reported studies which have successfully used dendrimers to enhance the solubilization of poorly soluble drugs. These promising outcomes have encouraged the researchers to design, synthesize, and evaluate various dendritic polymers for their use in drug delivery and product development. This review will discuss the aspects and role of dendrimers in the solubility enhancement of poorly soluble drugs. The review will also highlight the important and relevant properties of dendrimers which contribute toward drug solubilization.

Nanotechnological advancement has become a key standard for the diagnosis and treatment of several complex disorders such as cancer by utilizing the enhanced permeability and retention effect and tumor-specific targeting. Synthesis and designing the formulation of active agents in terms of their efficient delivery is of prime importance for healthcare. The use of nanocarriers has resolved the undesirable characteristics of anticancer drugs such as low solubility and poor permeability in cells. Several types of nanoparticles (NPs) have been designed with the use of various polymers along or devoid of surface engineering for targeting tumor cells. All NPs include polymers in their framework and, of these, polylactide-co-glycolide (PLGA) is biodegradable and Food and Drug Administration approved for human use. PLGA has been used extensively in the development of NPs for anticancer drug delivery. The extensive use of PLGA NPs is promising for cancer therapy, with higher efficiency and less adverse effects. The present review focused on recent developments regarding PLGA NPs, the methods used for their preparation, their characterization, and their utility in the delivery of chemotherapeutic agents.

This study proposes an innovative framework integrating geographic information systems (GISs), water quality index (WQI) analysis, and advanced machine learning (ML) models to evaluate the prevalence and impact of organic and inorganic pollutants across the urban–industrial confluence zones (UICZ) surrounding the National Capital Territory (NCT) of India. Surface water samples (n = 118) were systematically collected from the Gautam Buddha Nagar, Ghaziabad, Faridabad, Sonipat, Gurugram, Jhajjar, and Baghpat districts to assess physical, chemical, and microbiological parameters. The application of spatial interpolation techniques, such as kriging and inverse distance weighting (IDW), enhances WQI estimation in unmonitored areas, improving regional water quality assessments and remediation planning. GIS mapping highlighted stark spatial disparities, with industrial hubs, like Faridabad and Gurugram, exhibiting WQI values exceeding 600 due to untreated industrial discharges and wastewater, while rural regions, such as Jhajjar and Baghpat, recorded values below 200, reflecting minimal anthropogenic pressures. The study employed four ML models—linear regression (LR), random forest (RF), Gaussian process regression (GPR), and support vector machines (SVM)—to predict WQI with high precision. SVM_Poly emerged as the most effective model, achieving testing CC, RMSE, and MAE values of 0.9997, 11.4158, and 5.6085, respectively, outperforming RF (0.9925, 29.8107, 21.7398) and GPR_PUK (0.9811, 68.4466, 54.0376). By leveraging machine learning models, this study enhances WQI prediction beyond conventional computation, enabling spatial extrapolation and early contamination detection in data-scarce regions. Sensitivity analysis identified total suspended solids as the most critical predictor influencing WQI, underscoring its relevance in monitoring programs. This research uniquely integrates ML algorithms with spatial analytics, providing a novel methodological contribution to water quality assessment. The findings emphasize the urgency of mitigating the fate and transport of organic and inorganic pollutants to protect Delhi’s hydrological ecosystems, presenting a robust decision-support system for policymakers and environmental managers.

Background: Conjugation of several bio-actives to macromolecular nanocarriers is a promising approach to improve the efficiency and reduce side effects. Dendrimer represents a novel class of synthetic nanocarriers, comprised of different branched materials with tailor-made functionalities to conjugate wide varieties of bioactive molecules, therapeutic agents and different pharmacological substances including antibodies, ligands etc. Such opportunistic properties has been equally explored for the purpose of diagnostic applications as well. Methods: We have accomplished thorough bibliographic search and compilation of referred/indexed peer-reviewed literature to concisely review the above mentioned concept. The organized study was carried out concerned for dendrimer-drug conjugates employed in drug delivery and targeting to specific sites for their biological and clinical evaluation. Results: One hundred forty one papers were referred in this review after throughout literature survey. The conjugation is favorable and is easy to perform with the carriers like dendrimers due to its unique properties and multiple functional groups at the surface. The present review highlights the general properties class and applications of dendrimers in drug delivery. The focus is particularly on the dendrimer drug conjugates which are comparatively less explored area than the non-covalent dendrimer drug interactions. Conclusion: Conjugation of drugs to the dendrimers has particularly resulted into the increased drug payload and improved drug activity as evidenced by the reports discussed here in this article. Therefore in future it would be more advantageous to explore the dendrimer drug conjugation approaches for delivering drugs through dendrimers.