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Hydrogel-grown tumors could speed cancer drug testing, reduce animal use

A review by University of Manchester scientists says sophisticated lab-grown tumors could help fast-track the search for new cancer treatments while reducing reliance on animal testing.

Hydrogel-grown tumors could speed cancer drug testing, reduce animal use

Scientists at the University of Manchester have developed sophisticated lab-grown tumors using advanced materials called hydrogels. These hydrogel-based 3D tumor models recreate key features of real tumors, offering a potentially quicker way to study how cancers grow and spread. The technology could help scientists identify promising cancer drugs more rapidly by providing a realistic testing environment before treatments reach clinical trials.

However, the researchers emphasize that animal studies will continue to play a crucial role in cancer research, as they provide valuable insights into disease progression and drug safety. While hydrogel-based 3D tumor models can recreate the tumor microenvironment, cell interactions, and drug resistance more realistically than traditional 2D cultures, they cannot yet replicate the complexity of a whole body.

This means that animal studies remain essential for assessing the full efficacy and safety of drugs. The development of these biomaterial-based cancer models could reduce the reliance on animal testing, save millions of pounds, and expedite the search for life-saving treatments. Nevertheless, it is important to note that cancer remains one of the world's leading killers, and most new drugs fail to reach patients.

Current 2D cell cultures on flat plastic surfaces fail to capture the complexity of real tumors, which include intricate networks of cells, tissues, and chemical signals. Hydrogel-based 3D tumor models bridge this gap, providing a powerful platform for studying cancer biology, improving drug testing, and ultimately bringing effective treatments closer to patients.

Written by urgent.news from Medical Xpress's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.

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