Triple negative breast cancer (TNBC) is the most fatal subtype of breast cancer. Cytotoxic chemotherapy and immune therapy remain the only available therapeutic strategies for treatment, but unfortunately, patients frequently develop drug-resistance. Drug resistance towards chemotherapeutic agents is a major obstacle for effective cancer treatment. Genetic mutations that result in the increased expression of drug efflux transporter proteins may contribute to the development of multi-drug resistance (MDR). Two-dimensional (2D) cell culture models are conventionally used for in vitro screening of anticancer compound efficacy; however, these models do not accurately represent the complexities associated with the tumor microenvironment, thus limiting the reliability of research. In contrast, three-dimensional (3D) models are designed to enhance the fidelity of in vitro studies by more accurately mimicking in vivo tumor characteristics. This study introduces a TNBC (MDA-MB-231) chemotherapeutic responsive spheroid model developed using a rotating clinostat-based bioreactor system (ClinoStar®; CelVivo ApS, Odense, Denmark) . The 3D MDA-MB 231 TNBC spheroid model was functionally characterized over a period of 27 days based on growth and viability, using the following parameters: planimetric analysis, soluble protein content, intracellular adenosine triphosphate content (ATP), extracellular adenylate kinase (AK) and glucose consumption assays. Data obtained from the characterization was used to determine the metabolically stable period (days 15–23), identified as the experimental window of the spheroids. The spheroid model was characterized using a clinical dosage of cisplatin (4.435 ×10 ⁻⁶ µg/µg protein) and doxorubicin (1.064 ×10 ⁻⁵ µg/µg protein) over a 96-h treatment period . A chemotherapeutic responsive MDA-MB 231 TNBC spheroid model was successfully developed and characterized. The spheroid model demonstrated sensitivity towards a clinical dose of cisplatin, whilst displaying resistance to a clinical dose of doxorubicin, based on the viability parameters.