Your Body, Your Treatment: The Clinical Potential of Microphysiological Systems in Personalized Medicine

By Loza Taye | March 7th, 2024

Personalized medicine targets a patient's unique characteristics to provide more accurate diagnoses and effective treatment. Prevention, diagnosis, and progression for a single disease vary across individuals making standardized treatment difficult. Many hope that innovative technologies will solve this obstacle by allowing these processes to be tailored to a patient’s individual characteristics.

Microphysiological systems (MPS) are in vitro systems that mimic physiological aspects of tissues and organs. Over the last few decades, researchers have made remarkable strides in developing these miniature models. These miniature platforms can replicate multi-organ systems that allow researchers to observe a "mini body" response to stimuli in a controlled environment. These systems are more sophisticated than traditional in vitro models as they can replicate the complexity of interactions between multiple cell types. MPS also overcome shortcomings of in vivo animal models where species-specific differences limit the translation of findings.

Researchers can incorporate patient-specific genetic information into MPS for several purposes. Genetic variations affect how individuals metabolize drugs, which influences a prescribed treatment's efficacy and side effects. Multiple areas of clinical research can benefit from using systems that consider genetic variations.

1. Disease Modeling

Induced Pluripotent Stem Cells (iPSCs) are cells derived from patients that are reprogrammed back to a stem cell can then be differentiated into almost any cell type. As they are sourced directly from the patient, there is significantly lower risk of an immunogenic response – meaning the body will not treat the iPSCs as foreign pathogens. Incorporating these cells into MPS create personalized disease models containing the patient's genetic makeup. It allows clinicians and researchers to study the mechanism of disease progression more accurately.

A recently published review outlined several ways MPS are applied in disease modeling. These systems help scientists better understand what happens at a cellular level. For example, to study Amyotrophic Lateral Sclerosis (ALS or Lou Gehrig's disease), a group at MIT created a tiny system with muscle and nerve cells. When the system was exposed to too much of a certain chemical, they observed the nerves shrink and the muscles waste away. This highlights the importance of the interaction between nerves and muscles in ALS. Other research groups made a 3D model using cells that showed characteristics similar to Parkinson's disease. These models serve as tiny snapshots of a disease and can be incredibly useful when studying disease progression in individuals.

2. Drug Testing

MPS also allow scientists to assess how patients respond to drugs in a controlled environment. This form of personalized drug testing provides insights into efficacy and minimizes the risk of side effects. An additional benefit is the high-throughput capabilities of these systems. This makes them much more cost-effective compared with their animal model counterpartsHuman iPSC-derived “neurospheres” made of cells found in the nervous system have already been developed. Combined with machine learning, these methods can also predict the toxicity of unknown compounds with over 90% success rate.

3. Regenerative Medicine

The challenge in regenerative medicine is to repair or replace damaged tissue in the body. Researchers can use MPS to develop functional tissue to serve as a replacement or to study and understand the tissue itself.

A group of researchers designed a scaled-up MPS of vascularized engineered tissue to mimic the real thing. When this system was implanted into mice with circulation problems, it prevented cell death and improved overall circulatory function. This engineered system provide a new understanding of tissue functionality during disease progression. With continued research, similar models can be adapted for human patients and further developed to aid in repair or replacement of different tissue types.

The use of MPS can revolutionize healthcare by providing patients with tailored treatments. While the initial costs of developing MPS are high, many believe it is a worthy investment with cost-reduction estimates of 10-26% over 5 years in drug discovery alone. This cost-effectiveness comes from the reduced need for animal facilities, fewer resource requirements, and high-throughput capabilities.

However, while the potential of MPS is vast, many technical challenges remain. As the technology is in its relative infancy, the high complexity of these systems still requires further development. For example, adaptive immune system responses are challenging to replicate in vitro as immunity must be built up over time and these experimental platforms do not yet have long-term functionality. Interdisciplinary collaboration is also needed to improve standardization, validation, and scalability for widespread use across public and private sectors. Finally, there is the need to address ethical considerations regarding privacy and accessibility to ensure successful integration into healthcare systems.

Despite challenges, MPS are a promising platform in personalized medicine. MPS enhance research capabilities within disease modeling, drug testing, and regenerative medicine. As the technology advances, it offers unprecedented insights into disease progression and customized treatment strategies.

References

Ajalik, R.E., Alenchery, R.G., Cognetti, J.S., Zhang, V.Z., McGrath, J.L., Miller, B.L. and Awad, H.A. (2022). Human Organ-on-a-Chip Microphysiological Systems to Model Musculoskeletal Pathologies and Accelerate Therapeutic Discovery. Frontiers in Bioengineering and Biotechnology, 10. https://doi.org/10.3389/fbioe.2022.846230.

Bang, S., Dongha Tahk, Young Hwan Choi, Lee, S., Lim, J., Lee, S.-R., Kim, B.-S., Hong Nam Kim, Hwang, N.S. and Noo Li Jeon (2021). 3D Microphysiological System‐Inspired Scalable Vascularized Tissue Constructs for Regenerative Medicine. Advanced Functional Materials, 32(1). doi:https://doi.org/10.1002/adfm.202105475.

Fosse, V., Emanuela Oldoni, Gerardi, C., Banzi, R., Maddalena Fratelli, Biétrix, F., Ussi, A., Antonio Lorenzo Andreu and McCormack, E. (2022). Evaluating Translational Methods for Personalized Medicine—A Scoping Review. Journal of Personalized Medicine, 12(7), pp.1177–1177. https://doi.org/10.3390/jpm12071177.

Ingber, D.E. (2022). Human organs-on-chips for disease modelling, drug development and personalized medicine. Nature Reviews Genetics, [online] 23, pp.467–491. https://doi.org/10.1038/s41576-022-00466-9.

Irrechukwu, O., Yeager, R., David, R., Ekert, J., Saravanakumar, A. and Choi, C. K. (2023) “Applications of microphysiological systems to disease models in the biopharmaceutical industry: Opportunities and challenges”, ALTEX - Alternatives to animal experimentation, 40(3), pp. 485–518. doi: 10.14573/altex.2204071.

Kostrzewski, T. (2021). Hype or hope - microphysiological systems? [online] Drug Discovery World (DDW). Available at: https://www.ddw-online.com/hype-or-hope-microphysiological-systems-13760-202110/

Low, L. and Tagle, D. (2017). Microphysiological Systems (‘Organs-on-Chips’) for Drug Efficacy and Toxicity Testing. Clinical and Translational Science, 10(4), pp.237–239. doi:https://doi.org/10.1111/cts.12444.

National Centre for the Replacement Refinement & Reduction of Animals in Research (2023). Microphysiological Systems (MPS).

Park, S., Gwon, Y., Ahmed Khan, S., Jang, K.-J. and Kim, J. (2023). Engineering considerations of iPSC-based personalized medicine. Biomaterials Research, 27. doi:https://doi.org/10.1186/s40824-023-00382-x.

Palasantzas, V.E.J.M Tamargo-Rubio, I., Le, K., Slager, J., Cisca Wijmenga, Jonkers, I., Kumar, V., Fu, J. and Withoff, S. (2023). iPSC-derived organ-on-a-chip models for personalized human genetics and pharmacogenomics studies. Trends in Genetics, 39(4), pp.268–284. https://doi.org/10.1016/j.tig.2023.01.002.

The views expressed do not necessarily reflect the official policy or position of Johns Hopkins University or Johns Hopkins Bloomberg School of Public Health.

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