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Organs-on-a-Chip: Revolutionizing Drug Development

Drug discovery and development is a demanding, costly and lengthy process that takes an average of 10 to 15 years with an estimated cost of over US$1 to US$2 billion for each new clinically-approved target drug (Hinkson et al., 2020). Despite the implementation of many successful strategies over the past decades, there is still a 90% failure rate during clinical development, with the majority of drug candidates in clinical trials failing to reach the market (Sun et al., 2022). The reasons underlying such an astonishingly high failure rate include lack of clinical efficacy (40% to 50%), unpredicted toxicity (30%), poor drug-like properties (10% to 15%), and lack of commercial need or poor strategic planning (10%) (Dowden & Munro, 2019; Harrison, 2016).

In the absence of robust and reliable human preclinical models, drug development lies on laboratory-based preclinical assessments that combine two- (2D) and three-dimensional (3D) in vitro cell culture and in vivo animal testing. While in vitro settings lack the complexity of living systems, animal models often have difficult readouts. Animal research and in vivo testing have played a critical role in almost every medical breakthrough of the last century. In fact, it is a legal requirement for potential new drug candidates to be tested in animal models before moving on to human testing. Most drug compounds are tested in two distinct animal species before administration to humans (Greek, 2013). While animal testing has fueled the advancement of thousands of therapeutics we use today, it comes with numerous ethical and experimental constraints, as animal-derived data often fails to predict results obtained in human clinical trials (Golding et al., 2018; Junhee Seok et al., 2013). This translates into high failure rates, with most new drugs that have been shown safe and effective during animal studies later failing in human clinical trials due to unforeseen safety and efficacy issues.

Figure 1 – The drug discovery process and the failure rate at each developmental stage (Sun et al., 2022).

As a consequence, healthcare costs have soared unsustainably, with fewer effective medicines reaching the market and patients who need them most. In fact, high failure rates are a bottleneck for pharmaceutical innovation, as they ultimately favor the development of me-too drugs. A me-too drug, or a follow-on drug, is a drug that takes advantage of the basic chemical structure of an existing drug —also referred to as a first-in-class drug— with only minor formulation changes. It thus has the same pharmacological mode of action and therapeutic indications (Hitchings et al., 2012). A first-in-class drug, on the other hand, is the first drug in a class that modulates a previously unidentified pharmacological target. While modifications in me-too drugs can result in a molecule that outperforms its parent drug with regards to tolerance, specificity, and efficacy, they can also lead to unanticipated adverse effects due to variations in the specificity of pharmacological action, side-effect profiles, or drug–drug interactions (Aronson & Green, 2020). By building on existing knowledge and research, me-too drugs have become a mainstay in the pharmaceutical field, significantly reducing the time and cost of developing new forefront compounds. However, as me-too drugs consume resources that could be used to bring new medicines (targeting new diseases) to the industry, they might come at a cost by curtailing research into new treatments for currently incurable diseases (Aronson & Green, 2020).

The reliance on preclinical studies using in vitro or animal models has therefore resulted in unprecedented wastage of time and resources in the pharmaceutical industry. Alternative tissue models that better represent human organs and diseases are of paramount importance for the industry to bridge the gap between in vivo studies and clinical trials along the drug development pipeline. Recent progresses in microfluidics-based Organ-on-a-Chip (OoC) technology, which mimics the physiology and functionality of human tissues and organs, is expected to foster a paradigm shift in drug development. It aims to replace animal testing while offering cutting-edge, multidisciplinary solutions that contribute to new medicines and affordable healthcare (Zhang et al., 2018).

Figure 2 - Graph showing over 100% growth in the price of launching a new drug from 2010 to 2018 (left). Drug development has become more costly and time-consuming, taking an average of 10-15 years as opposed to 9.7 years in the 1990s (right). ("Improving efficiency", 2021).

Bridging the Gap: From 2D to Advanced 3D Models

Cell culture encompasses all laboratory methods that allow cells to develop under physiological conditions, i.e., in a controlled artificial environment isolated from their natural environment. Two-dimensional (2D) cell culture systems were introduced many decades ago and are still the method of choice in numerous fields. This traditional approach consists of growing cells as a monolayer on controlled flat environments, including plastic or glass flasks, with dead cells detaching from the surface (Zhang et al., 2018).

This allows for even distribution and access to the nutrients and growth factors present in the medium, so that cells can proliferate faster compared to an in vivo setting (Zhang et al., 2018). However, these systems have numerous drawbacks, most notably the inability to mimic the natural structures of tissues. In this culture method, neither cell-cell nor cell-extracellular environment interactions are preserved, which are known to be key for cellular differentiation, proliferation, morphology, and gene expression (Kapałczyńska et al., 2016). Transfer to the 2D conditions is thereby associated with alterations in cell morphology which ultimately affect cellular organization and function (Mahmud et al., 2009). Although most cells are still cultured using 2D monolayers due to their lower cost and ease of readability, these systems often lag behind in the modern drug discovery race, as they lack specificity and cell-to-cell/matrix interactions (Breslin & O’Driscoll, 2013; Pampaloni et al., 2007). The importance of overcoming such shortcomings has led to the development of more sophisticated methods, such as three-dimensional models using organoids to better represent the spatial and chemical complexity of living tissues.

Figure 3 – Traditional 2D (left) or 3D (right) cell culture of the same Caco-2 cell line (Wu et al., 2017).

If we think that our body is three-dimensional, we easily understand why the intricate behavior of cells cannot be correctly modeled in just two dimensions. The transition from 2D to 3D cell culture techniques is an important step towards improved biomimetic tissue models that better reproduce in vivo conditions. In contrast to a 2D setting, conventional 3D cell culture provides an environment in which cells can grow and interact with the surrounding extracellular framework in all three dimensions. These cultures can be grown with or without a support scaffold structure, which is typically provided by a hydrogel - an extracellular matrix (ECM) where cells can survive, grow and multiply. Through their tiny pores, these models allow the flow of nutrients and gases required for cells to thrive (Badr-Eldin et al., 2022).

Although traditional 3D technologies are widely used nowadays, they still entail some challenges including maintenance of the cellular microenvironment and lack of reproducibility. Many also fall short in recapitulating human body physiology and pathophysiology. Furthermore, although animal models allow for in vivo analysis, they are far from reproducing the complex mechanisms of human in vivo physiology, subsequently weakening the accuracy and reproducibility of experimental results (Ma et al., 2011). In modern life, most of the aforementioned limitations are overcome by microfluidic organ-on-chip models that better mimic the microstructure, functionalities, and the dynamic or mechanical properties of living organs. They allow for a continuous delivery of nutrients and pharmaceutical compounds (Huh et al., 2011). In addition, the small size of these models makes them suitable for high-throughput screening as the amount of drug consumption is small.

Figure 4 - From 2D to microfluidic organ-on-a-chip platform (Ma et. al., 2021)

The Coming Age of Organs-on-a-Chip: A Paradigm Shift in Drug Development

Organ-on-a-Chip (OoC) technology is breaking new ground for many pharmaceutical and medical applications. It is proving to be a viable alternative to traditional in vitro cell culture and animal models. These OoCs, also referred to as microphysiological systems or ‘tissue chips’, are systems containing engineered or miniature biological tissues that recreate the cellular microenvironment, while recapitulating the microarchitecture and functions of living human organs. These innovative devices exhibit functionality at the tissue and organ level and have attracted great interest as next-generation experimental platforms owing to their applications in the biomedical field (Esch et al., 2015). The relatively reduced cost, small size, shorter experiment times, and ability to perform in vitro experiments under tightly controlled parameters give such devices a great advantage in the medical and biological fields (Bhatia & Ingber, 2014).

From a technical point of view, OoCs are tiny devices, comparable in size to a USB flash drive, made of a flexible polymer containing hollow microfluidic channels encapsulated by living human cells of a specific organ of interest. The ability to mimic the cellular microenvironment and ensure organ-level functions is mediated by media perfusion – a hallmark of OoC devices – which serves as an artificial circulatory system equilibrating and ensuring a concentration gradient for nutrients and cellular waste (Leung et al., 2022). OoCs consist of microfluidic cell culture systems with tightly controlled but dynamic conditions that reproduce the microenvironment of human tissues in the body. In fact, through the combination of cell biology, engineering, and biomaterials, the microenvironment inside the chip is capable of simulating that of the organ in terms of tissue-specific functions, interactions, and mechanical stimulation. The latter enables reproduction of the physical microenvironment of living organs including lung-related respiratory movements and peristalsis-like deformations in the intestine (Wu et al., 2020).

Figure 5 – Gut-on-a-chip mimicking the human gut environment. It constricts, relaxes, and produces finger-like projections known as villi, shown at left (Ingber, 2021).

Engineered to emulate the behavior of different cells, tissues, or even organs, OoCs are able to mimic complex physiological and pathological processes (Danku et al., 2022), providing invaluable insight into normal organ function as well as the pathophysiology of diseases. Additionally, by reflecting the structural and functional properties of human tissue, these microchips can predict the response to a variety of stimuli, including environmental and drug responses (Wu et al., 2020), with the potential to be informative at multiple stages of the drug discovery and development process.

In what sounds like something straight out of science fiction, organs-on-a-chip will pave the way for researchers to test out drugs as if they were testing on humans. Their ability to create complex and dynamic, yet manageable physiological environments has attracted notable attention for drug development and disease modeling. Microfluidic technology is emerging as an innovative and disruptive technology that has enabled the pharmaceutical industry to pre-clinically screen drugs in a much more realistic way compared to traditional 2D or 3D cell cultures and animal models. As a major achievement of the 21st century, microfluidic systems have found their way into various fields, offering the possibility to assess the response of cells, tissues, or organs to a specific drug, thus supporting the development of novel and tailored therapies. Another promising aspect of such systems is the combination of microfluidic devices and sensor platforms for drug delivery. These systems have the potential to revolutionize treatment methods and the entire drug development life cycle.

Bibliographical References

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Badr-Eldin, S. M., Aldawsari, H. M., Kotta, S., Deb, P. K., & Venugopala, K. N. (2022). Three-dimensional in vitro cell culture models for efficient drug discovery: progress so far and future prospects. Pharmaceuticals, 15(8), 1–28. Bhatia, S. N., & Ingber, D. E. (2014). Microfluidic organs-on-chips. Nature Biotechnology, 32(8), 760–772. Breslin, S., & O’Driscoll, L. (2013). Three-dimensional cell culture: the missing link in drug discovery. Drug Discovery Today, 18(5–6), 240–249. Danku, A. E., Dulf, E. H., Braicu, C., Jurj, A., & Berindan-Neagoe, I. (2022). Organ-on-a-chip: a survey of technical results and problems. Frontiers in Bioengineering and Biotechnology, 10(February), 1–11. Dowden, H., & Munro, J. (2019). Trends in clinical success rates and therapeutic focus. Nature Reviews. Drug Discovery, 18(7), 495–496. Esch, E. W., Bahinski, A., & Huh, D. (2015). Organs-on-chips at the frontiers of drug discovery. Nature Reviews Drug Discovery, 14(4), 248–260. Golding, H., Khurana, S., & Zaitseva, M. (2018). What is the predictive value of animal models for vaccine efficacy in humans? The importance of bridging studies and species-independent correlates of protection. Cold Spring Harbor Perspectives in Biology, 10(4), 1–12. Greek, R. (2013). Medical breakthroughs underpinned by animal research. In S. J. T. Gowder (Ed.), New Insights into Toxicity and Drug Testing. IntechOpen. Harrison, R. K. (2016). Phase II and phase III failures: 2013-2015. Nature Reviews Drug Discovery, 15(12), 817–818. Hinkson, I. V., Madej, B., & Stahlberg, E. A. (2020). Accelerating therapeutics for opportunities in medicine: a paradigm shift in drug discovery. Frontiers in Pharmacology, 11(June), 1–7. Hitchings, A. W., Baker, E. H., & Khong, T. K. (2012). Making medicines evergreen. BMJ (Online), 345(7886), 1–6. Huh, D., Hamilton, G. A., & Ingber, D. E. (2011). From three-dimensional cell culture to organs-on-chips. Trends Cell Biol, 21(12), 745–754. Junhee Seok, H. Shaw Warren, Alex, G. C., Michael, N. M., Henry, V. B., Xu, W., Richards, D. R., McDonald-Smith, G. P., Gao, H., Hennessy, L., Finnerty, C. C., López, C. M., Honari, S., Moore, E. E., Minei, J. P., Cuschieri, J., Bankey, P. E., Johnson, J. L., Sperry, J., … Tompkins, R. G. (2013). Genomic responses in mouse models poorly mimic human inflammatory diseases. Proceedings of the National Academy of Sciences of the United States of America, 110(9), 3507–3512. Kapałczyńska, M., Kolenda, T., Przybyła, W., Zajączkowska, M., Teresiak, A., Filas, V., Ibbs, M., Bliźniak, R., Łuczewski, Ł., & Lamperska, K. (2016). 2D and 3D cell cultures – a comparison of different types of cancer cell cultures. Archives of Medical Science, 14(4), 910–919. Leung, C. M., de Haan, P., Ronaldson-Bouchard, K., Kim, G. A., Ko, J., Rho, H. S., Chen, Z., Habibovic, P., Jeon, N. L., Takayama, S., Shuler, M. L., Vunjak-Novakovic, G., Frey, O., Verpoorte, E., & Toh, Y. C. (2022). A guide to the organ-on-a-chip. Nature Reviews Methods Primers, 2(1). Ma, C., Peng, Y., Li, H., & Chen, W. (2011). Organ-on-a-Chip: a new paradigm for drug development chao. Trends Pharmacol Sci., 176(5), 139–148. Mahmud, G., Campbell, C. J., Bishop, K. J. M., Komarova, Y. A., Chaga, O., Soh, S., Huda, S., Kandere-Grzybowska, K., & Grzybowski, B. A. (2009). Directing cell motions on micropatterned ratchets. Nature Physics, 5(8), 606–612. Pampaloni, F., Reynaud, E. G., & Stelzer, E. H. K. (2007). The third dimension bridges the gap between cell culture and live tissue. Nature Reviews Molecular Cell Biology, 8(10), 839–845. Sun, D., Gao, W., Hu, H., & Zhou, S. (2022). Why 90% of clinical drug development fails and how to improve it? Acta Pharmaceutica Sinica B, 12(7), 3049–3062. Wu, Q., Liu, J., Wang, X., Feng, L., Wu, J., Zhu, X., Wen, W., & Gong, X. (2020). Organ-on-a-chip: Recent breakthroughs and future prospects. BioMedical Engineering Online, 19(1), 1–19. Zhang, B., Korolj, A., Lai, B. F. L., & Radisic, M. (2018). Advances in organ-on-a-chip engineering. Nature Reviews Materials, 3(8), 257–278.

Visual Sources

Cover Image: Folch, Albert. (2022). The Organ-on-a-Chip Revolution is Here. [image]. The MIT Press Reader.

Figure 1: Sun, D., Gao, W., Hu, H., & Zhou, S. (2022). Why 90% of clinical drug development fails and how to improve it? Acta Pharmaceutica Sinica B, 12(7), 3049–3062. [image]

Figure 2: Improving efficiency in drug discovery and development. (2021). [image]. Abcam.

Figure 3: Wu, Z., Guan, R., Tao, M., Lyu, F., Cao, G., Liu, M., Gao, J. (2020) Assessment of the toxicity and inflammatory effects of different-sized zinc oxide nanoparticles in 2D and 3D cell cultures. RSC Advances. 10. 44397-44397. [image]

Figure 4: Ma, C., Peng, Y., Li, H., & Chen, W. (2011). Organ-on-a-Chip: a new paradigm for drug development chao. Trends Pharmacol Sci., 176(5), 139–148. [image]

Figure 5: Ingber, Donald E. (2021). Human organ chips for radiation countermeasure development. [image]. U. S. Food & Drug Administration.


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Maria Inês Marreiros

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