Today, most preclinical cancer studies rely on either 2D cell cultures or animal models to simulate how tumours behave and respond to treatments. However, these models have distinct shortcomings. 2D cultures often lack the complexity found in real human tissues, while animal models can respond differently to drugs compared to humans. As a result, many drugs that appear effective in the lab do not work as expected in human clinical trials.
This gap between laboratory success and clinical effectiveness plays a major role in the high failure rate of oncology drugs.
As many as 92 percent of cancer treatments that move into human testing never make it to market, due to a lack of effectiveness or unforeseen side effects. Bioprinted models offer one opportunity to close this gap by providing more accurate, patient-relevant platforms for testing therapies before expensive clinical trials begin.
Read the full article in DPA's November 2025 issue