# Bone-on-a-Chip Systems for Hematological Cancers

## TL;DR

This paper reviews bone-on-a-chip systems for modeling hematological cancers and improving drug response prediction.

## Contribution

The paper provides a comprehensive review of bone-on-a-chip systems for hematological cancer modeling and drug research.

## Key findings

- Bone-on-a-chip systems can better represent the bone microenvironment than traditional models.
- These systems can predict drug responses and help mitigate drug resistance in hematological cancers.
- BoC systems offer potential for personalized therapeutic interventions and clinical translation.

## Abstract

Hematological malignancies originating from blood, bone marrow, and lymph nodes include leukemia, lymphoma, and myeloma, which necessitate the use of a distinct chemotherapeutic approach. Drug resistance frequently complicates their treatment, highlighting the need for predictive tools to guide therapeutic decisions. Conventional 2D/3D cell cultures do not fully encompass in vivo criteria, and translating disease models from mice to humans proves challenging. Organ-on-a-chip technology presents an avenue to surmount genetic disparities between species, offering precise design, concurrent manipulation of various cell types, and extrapolation of data to human physiology. The development of bone-on-a-chip (BoC) systems is crucial for accurately representing the in vivo bone microenvironment, predicting drug responses for hematological cancers, mitigating drug resistance, and facilitating personalized therapeutic interventions. BoC systems for modeling hematological cancers and drug research can encompass intricate designs and integrated platforms for analyzing drug response data to simulate disease scenarios. This review provides a comprehensive examination of BoC systems applicable to modeling hematological cancers and visualizing drug responses within the intricate context of bone. It thoroughly discusses the materials pertinent to BoC systems, suitable in vitro techniques, the predictive capabilities of BoC systems in clinical settings, and their potential for commercialization.