CLN3 disease, also known as juvenile neuronal ceroid lipofuscinosis, is a severe autosomal recessive neurodegenerative lysosomal storage disorder. Pathogenesis arises from mutations in the CLN3 gene, causing lysosomal dysfunction and accumulation of lipofuscin in neurons. This triggers long-term neuroinflammation that is mediated by microglia, leading to cerebral impairment over time.[1] Symptoms include vision loss, cognitive decline, and motor impairments. The global prevalence is approximately 1 to 3 cases per 100,000 live births. Treatment provides symptomatic relief, with no cure currently available. Mortality is common before the third decade of life. Genetic testing and detection of inflammatory biomarkers are the main diagnostic approaches.[2]

Recently, three-dimensional (3D) bioprinting technology has been explored for creating neural tissue models, including those incorporating microglia, to study neuroinflammatory environments relevant to neurodegenerative diseases such as CLN3. It uses hydrogel-based bioinks to deposit microglia, generating brain tissue-like structures. The approach retains cell viability, facilitating reliable therapeutic evaluation. This platform is potent for drug discovery and analysis, essential for the evaluation of CLN3 pathology. By examining cytokine production and microglial response, these models enable the screening of anti-inflammatory medications. Success rates in recreating disease features and predicting treatment effectiveness have been encouraging, with improved reproducibility reported in recent studies. Apart from CLN3, these bioprinted models have proven effective for other neuronal ceroid lipofuscinosis and some neurodegenerative conditions like Alzheimer's and Parkinson's research, indicating potential for neurological applications.[3] Additionally, emerging applications of 3D bioprinting extend to neurotrauma, where it has shown promise in fabricating scaffolds and neural constructs to support regeneration after traumatic brain or spinal cord injuries.[4]

Preclinical studies using 3D-bioprinted neural constructs have advanced the understanding of neuroinflammation in CLN3 disease. Studies have identified inflammatory pathways and lipid metabolism defects using these constructs and related models, expanding knowledge of microglial involvement.[5] The safety profile of hydrogel scaffold materials remains excellent, with high cell viability and minimal cytotoxicity reported.[6]

The clinical application of these 3D-bioprinted microglia models encounters some notable challenges. In vivo complexity remains exceedingly difficult to replicate. Critical factors like the blood–brain barrier (BBB) are often missing or inadequately represented in current models. This limitation reduces the accuracy of predicting drug penetration across the BBB, diffusion into brain tissue, and overall therapeutic efficacy in physiological conditions, potentially leading to translational failures from in vitro to in vivo settings. In addition, advanced bioprinters and hydrogel bioinks present a high initial economic barrier. This significantly limits its deployment and accessibility across less-funded research laboratories. Limited awareness among health care professionals and researchers about this cutting-edge technology restricts its widespread implementation. More extensive clinical research is required to address these gaps and ensure reliable application from experiment to patient care.[7]

Despite the fact that the use of 3D-bioprinted neural constructs to mimic the neuroinflammatory cascades of CLN3 disease has been documented with significant progress and reproducible profiling in preclinical models,[3] [7] insights into impaired lipid metabolism and myelin turnover associated with CLN3 loss in microglia,[6] and challenges in translational prediction, the field is still restricted to some extent by the incomplete emulation of in vivo barriers like BBB as well as economic inaccessibility, which shuts the resource-limited labs out from the pool of the iterative model refinement.[7]

In conclusion, 3D-bioprinted microglia models demonstrated encouraging advances for CLN3 disease investigation. Future efforts need to emphasize increasing clinical trials to validate therapeutic efficacy and safety. Subsidies to reduce expenditures could improve accessibility for research institutions. Promoting awareness through targeted education programs will assist its adoption across the scientific community. Advancing the technology's potential to simulate physiological states more precisely will further enhance its role in pharmaceutical development. These measures will help reduce current constraints and promote more effective clinical interventions for CLN3 and associated progressive neurological diseases.

Article published online:
26 March 2026

© 2026. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution License, permitting unrestricted use, distribution, and reproduction so long as the original work is properly cited. (https://creativecommons.org/licenses/by/4.0/)

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