Background/Objectives:
Etoposide, busulfan, and melphalan are commonly used cytotoxic agents in high-dose chemotherapy and haematopoietic stem cell transplantation. Their effectiveness varies between malignant and normal cells due to overlapping yet distinct molecular mechanisms. This in vitro and in silico study aimed to mechanistically interpret IC₅₀ values and dose–response curves in two leukaemia cell lines (HL-60, K-562) and normal fibroblasts (MRC-5), integrating drug–protein interactions, gene expression, and functional profiling.

Methods:
IC₅₀ values were measured in vitro using MTT assays and four-parameter logistic regression. Hill coefficients and IC₈₀/IC₂₀ ratios were calculated to characterise the steepness and dynamic range of cytotoxic responses. In silico analyses incorporated data from UniProt, DrugBank, and the Human Protein Atlas to identify pharmacologically relevant proteins and quantify their transcriptomic expression (nTPM).

Results:
Etoposide demonstrated the highest efficacy in HL-60 cells, where elevated TOP 2 A expression and apoptotic priming outweighed efflux and repair pathways. Busulfan produced broad, flat dose–response curves across all cell lines, with limited selectivity mainly driven by glutathione-based detoxification and transporter activity. Melphalan induced steep, threshold-like responses in K-562 cells, attributable to LAT 1-mediated uptake and decreased detoxification. High Hill slopes and narrow IC₈₀/IC₂₀ ratios reflected cooperative apoptosis with an abrupt transition to cell death, while shallow slopes with wide ranges suggested heterogeneous or buffered responses.

Conclusions:
Parameters of dose–response curves capture biologically meaningful dynamics of cytotoxicity beyond IC₅₀ values alone. Integration of IC₅₀, Hill slopes, and IC₈₀/IC₂₀ ratios with proteomic and transcriptomic profiling identified key molecular determinants—including drug targets, transporters, detoxification enzymes, and apoptosis regulators—that shape cell-specific responses. This mechanistically informed framework enhances the predictive value of cytotoxicity assays and may support biomarker-guided drug selection and safer, personalised chemotherapy strategies.