Three-dimensional (3D) cell culture is increasingly recognized as a more accurate model for drug discovery compared to traditional two-dimensional (2D) cell cultures. While 2D cultures are commonly used for initial screening of drug candidates, they fail to replicate the complex microenvironment of tissues in vivo, leading to potential inaccuracies in predicting drug efficacy and toxicity. 3D cultures, which mimic the in vivo environment more closely, offer a more realistic representation of tissue architecture, cell-cell interactions, and extracellular matrix (ECM) signaling, which are essential for proper cell function and response to drugs. The development of anticancer drugs is a costly and time-consuming process, with only about 10% of candidates progressing through clinical trials. Early identification of ineffective or toxic compounds is crucial to reduce costs and improve efficiency. 3D cell cultures can provide more accurate predictions of drug behavior by simulating the complex interactions within tissues, thus enabling better screening of drug candidates before clinical trials. Various methods for generating 3D cell cultures include forced-floating techniques, hanging drop methods, agitation-based approaches, matrices, scaffolds, and microfluidic systems. Each method has its advantages and limitations, with some offering better control over cell growth and environment than others. For example, forced-floating methods use surfaces that prevent cell adhesion, allowing cells to form spheroids. Hanging drop methods rely on surface tension to create spheroids, while microfluidic platforms enable precise control over cell environment and drug exposure. 3D cultures have been shown to better predict drug responses compared to 2D cultures, as demonstrated by studies showing differences in drug sensitivity and cellular behavior. For instance, 3D spheroids of breast cancer cells exhibited different responses to drugs like trastuzumab compared to 2D cultures, highlighting the importance of 3D models in drug development. Additionally, 3D cultures can replicate hypoxic conditions found in solid tumors, which is critical for understanding drug resistance and efficacy. Despite their advantages, 3D cultures are more labor-intensive and costly than 2D cultures. However, their ability to provide more accurate predictions of drug behavior makes them essential for improving the efficiency and success rate of drug development. The integration of 3D cell cultures into drug screening processes is therefore recommended to enhance the accuracy of preclinical testing and reduce the risk of drug failures in clinical trials.Three-dimensional (3D) cell culture is increasingly recognized as a more accurate model for drug discovery compared to traditional two-dimensional (2D) cell cultures. While 2D cultures are commonly used for initial screening of drug candidates, they fail to replicate the complex microenvironment of tissues in vivo, leading to potential inaccuracies in predicting drug efficacy and toxicity. 3D cultures, which mimic the in vivo environment more closely, offer a more realistic representation of tissue architecture, cell-cell interactions, and extracellular matrix (ECM) signaling, which are essential for proper cell function and response to drugs. The development of anticancer drugs is a costly and time-consuming process, with only about 10% of candidates progressing through clinical trials. Early identification of ineffective or toxic compounds is crucial to reduce costs and improve efficiency. 3D cell cultures can provide more accurate predictions of drug behavior by simulating the complex interactions within tissues, thus enabling better screening of drug candidates before clinical trials. Various methods for generating 3D cell cultures include forced-floating techniques, hanging drop methods, agitation-based approaches, matrices, scaffolds, and microfluidic systems. Each method has its advantages and limitations, with some offering better control over cell growth and environment than others. For example, forced-floating methods use surfaces that prevent cell adhesion, allowing cells to form spheroids. Hanging drop methods rely on surface tension to create spheroids, while microfluidic platforms enable precise control over cell environment and drug exposure. 3D cultures have been shown to better predict drug responses compared to 2D cultures, as demonstrated by studies showing differences in drug sensitivity and cellular behavior. For instance, 3D spheroids of breast cancer cells exhibited different responses to drugs like trastuzumab compared to 2D cultures, highlighting the importance of 3D models in drug development. Additionally, 3D cultures can replicate hypoxic conditions found in solid tumors, which is critical for understanding drug resistance and efficacy. Despite their advantages, 3D cultures are more labor-intensive and costly than 2D cultures. However, their ability to provide more accurate predictions of drug behavior makes them essential for improving the efficiency and success rate of drug development. The integration of 3D cell cultures into drug screening processes is therefore recommended to enhance the accuracy of preclinical testing and reduce the risk of drug failures in clinical trials.