Cancer continues to be a leading cause of death globally, with almost 10 million people dying from the disease annually, presenting a significant global health challenge. While traditional therapies - surgery, radiotherapy, chemotherapy, targeted therapy and immunotherapy - have extended survival rates, they are often compromised due to systemic toxicity, inadequate pharmacokinetics, lack of selectivity, and drug resistance. Innovative drug delivery systems (DDS), especially nanotechnology-based DDS, have recently gained attention as potential methods to improve therapeutic outcomes and outcomes. This review critically examines the advances in drug delivery for cancer treatment, with particular emphasis on nanotechnology-based systems such as liposomes, polymeric nanoparticles, dendrimers, inorganic nanoparticles, exosomes, and antibody–drug conjugates. Various features such as passive and active targeting strategies, drug release in response to stimuli, internalization and intracellular trafficking, administration routes, and in vivo considerations are thoroughly reviewed. Further, the review outlines the current clinical translation, regulatory advances, and key challenges, such as biological barriers, protein corona, scalability and tumor heterogeneity. The review also outlines future perspectives - such as artificial intelligence-driven formulation development, multi-omics integration, organoid-based systems for drug validation and precision nanomedicine - are also discussed as key factors for next-generation cancer treatment. In general, advanced DDS are helping to transform non-specific, conventional chemotherapy into targeted, efficient and individualized cancer therapies.

This study was conducted in the Yangambi Biosphere Reserve, located in the Isangi district, 100 km west of the city of Yangambi, at 0°49′12″ N; 24°27′22″ E. To conduct this study, six one-hectare plots were established in Yangambi, within which seedlings of different height classes were measured and their x and y coordinates recorded. Each of the six plots contained a seed plant, except for plots 1 and 5. A total of 769 seedlings were recorded, averaging 128.1 stems/ha. Height class S1 had the highest number of individuals (358 stems across all six hectares, or 59.6 stems/ha) compared to the other classes, and their numbers decreased as the size of the individuals increased. The variability in the number of seedlings observed between plots confirms that there is a strong correlation (r ≈ 0.79), it is observed that plots with more seed trees generally have more seedlings; however, for dendrometric characteristics such as the diameter at breast height (DBH) of seed trees, which directly influences the abundance of seedlings under their canopy, the correlation is weak (r ≈ 0.27).