What are the current misconceptions surrounding organ-on-a-chip technology?

Organ-on-a-chip (OOC) technology provides a transformative approach to improved science. By building a bridge between traditional cell culture, animal models and the clinic, its complementary use provides human-relevant, mechanistic insights that enable better-informed decisions regarding the right therapeutics to move forward into in vivo animal, or first-in-human clinical trials.

Image Credit: CN-Bio

Image Credit: CN-Bio

OOC has the potential to reduce drug attrition rates and bring novel therapeutics to patients more cost-effectively and rapidly. This has intrigued adopters, who are eager to recreate complex human physiology in the laboratory. Others remain unsure. Do transitional challenges carry more weight than the potential benefits of OOC, and is the technology prepared for primetime?

The adoption of any disruptive technology introduces challenges; however, CN Bio believes that OOC will soon become an essential piece of lab equipment. This is simply because OOC does a better job than existing in vitro assays, whilst enabling the interspecies issues of animal models to be circumvented. By getting started now with the transition into OOC, you can leverage the advantages faster. This article addresses some of the common concerns and presents an honest perspective on adoption challenges.

1. OOC systems are too complicated

OOC systems have come far since prototypes with yards of complicatedly configured tubing that necessitated an associated bioengineer to operate.

Commercial solutions are resolutely designed for the cell biologist; however, some systems are more challenging than others. Microscale designs function at very low volumes, which is beneficial when working with valuable samples, but cell seeding requires steady, experienced hands.

There are alternative, less-futuristic designs that provide a simple transition between traditional 2D cell culture via familiar multi-well plate formats. Their higher working volumes provide advantages in terms of data depth.

Vendors are not solely focused on the technology, however. Creative minds have developed methods to simplify adoption via complete solutions that incorporate hardware, software, off-the-shelf reagents, and support packages that lessen the learning curve by guiding users through the procedure of OOC experimental setup.

2. Primary cells are too challenging to work with

Primary cells are an essential component of OOC models. They are necessary to accurately recapitulate human organs, or disease states, in vitro. However, there is no doubt that they are more difficult to handle than immortalized cells.

Although this challenge is not unique to OOC, there are additional considerations for OOC assays. Primary cells that are appropriate in a standard 2D setting do not always work well in 3D culture. Laboratories can lose valuable time, budget, and resources by wading straight into OOC experiments. It is important to pre-validate primary cell lots to ensure that they form adequately functioning 3D microtissues before embarking on drug evaluation studies. There are two options for users: internally validating multiple cell lots to find those that are OOC compatible, or sourcing pre-validated lots directly from vendors.

OOC vendors like CN Bio have years of experience working with primary cells and can share tips, tricks and protocol guidance through their support channels to ensure your assays are successful and reproducible. More info can be found here.

CN Bio also collaborates closely with the primary cell providers to offer validated cells that thrive in 3D and maintain their function and phenotype for up to four weeks when cultured under perfusion. This allows laboratories to simply purchase "off the shelf" and focus on making discoveries, rather than spending time finding needles in haystacks.

3. OOC offers limited endpoint measurements

There is an element of truth here. Approaches designed for higher throughput screening deliver fewer endpoint measurements from basic OOC models. However, these are complemented by more advanced OOC solutions that sit up and downstream. The latter provides data-rich content to unlock mechanisms of drug, or disease action.

Although each OOC system provides a unique mix and breadth of endpoint measurements, there are rough guidelines. The number of possible endpoints roughly relates to the size of the cultured microtissue, as well as the physiological relevance of the culture conditions.

For instance, large-scale, horsepower-loaded microtissues that are perfused by finely tuned fluidics to mimic the bloodstream provide optimal assay sensitivity, data-richness, and culture longevity.

High volumes of media in these systems allow repeat sampling over multiple weeks for longitudinal metabolomic, clinically translatable, and proteomic biomarker studies. In addition, microtissues are recoverable, which allows for the performance of post-assay microscopic analysis or transcriptomic, genomic, and proteomic profiling.

OOC also allows for the measurement of clinically relevant endpoints that have been challenging to detect in vitro, plus cultures can be maintained for up to four weeks to explore chronic drug dosing effects.

Novel interconnected multi-organ (gut and liver) models also recreate human processes, such as first-pass metabolism to more accurately estimate drug bioavailability, an important parameter currently measured via animal models that offer poor predictability.1,2,3

4. Throughput is limited

There is generally an inverse relationship between physiological relevance and throughput capacity. If there is a need to screen hundreds of thousands of compounds, it is not possible to do this utilizing the most “human-like” in vitro models; however, there may be options to incrementally improve the current status.

For example,1,536-well 3D spheroid assays may offer an incremental improvement in assay performance versus traditional 2D assays for yes/no screening. For hit validation, it is possible to incorporate 96/384-well OOC systems that offer a simple (dependent on gravity) method of perfusion to mimic blood flow. Perfusion enhances the human relevance and longevity of 3D cultures over their static counterparts.

More advanced chip- and plate-based OOC solutions feature adjustable “organ-specific” flow rates that recreate in vivo-like biomechanical stimulus, nutrient delivery, and oxygen. They enable a more accurate recapitulation of human organs and microtissues in vitro and offer significantly increased culture longevity. However, these more sophisticated systems are lower in throughput. Depending on the system, one replicate can be run per chip, or 12-48 replicates per plate. They perfectly complement their higher-throughput siblings by delivering more comprehensive mechanistic insights to ensure that only the most promising candidates progress to in vivo animal and human studies. 

5. All OOC solutions use Polydimethylsiloxane (PDMS)

PDMS is frequently utilized in Organ-on-a-chip technologies but by no means all. This gas-permeable polymer is transparent, low cost, simple to manufacture at a small scale and enables easy imaging. The significant disadvantage of PDMS, however, is its lipophilicity. Unfortunately, this property can cause the non-specific binding of hydrophilic compounds, making it difficult to accurately quantify exposure responses and pharmacokinetics.

PDMS is among several materials available to OOC developers. A viable alternative is Cyclic olefin copolymer (COC), an amorphous polymer known to be the most inert material available for medical devices. The use of COC guarantees minimal non-specific binding when working with a cross-section of therapeutic modalities, including small and large molecules. CN Bio recommends using COC over PDMS for compound testing purposes to maintain data integrity.4

6. OOC systems lack flexibility

It is unfair to suggest that all OOC systems lack flexibility, or that less flexibility is always a negative. It is fair to say that the breadth of validated OOC models available from each vendor is (currently) limited as it takes time to develop, characterize and validate OOC models to demonstrate human translatability. However, as technology develops, the breadth of fully validated models available from each supplier will increase. It is important that this factor doesn’t cause you to “sit on the fence” as there is an onboarding journey. By getting started now, you can reap the benefits faster.

It is important to ask whether a chosen system is flexible enough to grow with you. Can you refine, or design your own models as you gain experience, or when experimental requirements evolve? Does a one-size-fits-all approach to consumable design work best for you, or is this a compromise? Would you prefer the consumable design to be bespoke to the organ/tissue? It is also important to consider the consumable architecture/usability. How closed or open is it? Are cultures easily accessible to change experimental conditions, or manipulate models once an experiment is established?

Also, remember that experienced OOC researchers are in short supply. This “experience gap” has resulted in a prescriptive kit-based approach from some vendors. This “off-the-shelf” convenience enables users with little to no experience to embark on a rapid road to adoption. Whilst this approach may perfectly suit those in drug discovery, it may be too inflexible for those in an academic environment.

7. The technology is too costly

There is an assumed upfront investment when adopting any new technology and working with primary cells is expensive. However, the initial CAPEX outlay and OPEX running costs of OOC can be offset against the potential gains of de-risking the costly drug discovery and development process. A research publication has suggested that incorporating OOC into workflows could save companies up to 26 % of research and development costs.5

Human-relevant, mechanistic data from OOC enables stop/go decisions- while there’s an opportunity to modify drug design and the refinement of pre-clinical experimental design. Unnecessary animal use is also minimized by justifying only the progression of promising drugs into in vivo testing to reduce costs.

For many new drug modalities with human-specific targets, it can be challenging to access suitable in vivo models. OOC circumvents this by providing unrestricted access to human translatable data for more confident progression into first-in-human trials.

8. The technology is not ready to deliver regulatory-grade results

In 2021, efficacy data from a microphysiological system (Hesperos) supported the authorization of a clinical study (NCT04658472) through collaboration with Sanofi for rare neurological disorders and in 2023, CN Bio PhysioMimix® Organ-on-a-Chip data supported Inipharm’s INI-822 for metabolic liver disease treatment, now in clinical testing – so times have changed.

OOC has the potential to deliver human-predictive information that improves data translatability between the laboratory and clinic, however, CN Bio understands that making the strategic shift from known gold standard models to a new approach is not necessarily a simple process.

OOC represents a solid approach to refine, reduce, and complement existing tests, instead of a futuristic proposal replacing the status quo. Regulatory authorities have accepted OOC’s potential and have invested in collaborative initiatives that help underpin the use of OOC and accelerate its adoption.

In a recent publication with CN Bio, the FDA sought to address the lack of available quality control and performance criteria for the consistent use of OOC devices and the reproducibility of results.2 This publication demonstrates the reliability, robustness, and superior performance of the PhysioMimix® liver-on-a-chip (LOAC) for drug evaluation purposes compared to standard technology.

CN Bio continues to collaborate closely with the FDA, whilst consortiums such as the IQ-MPS Affiliative, comprised of biotechnology and pharmaceutical companies as well as leading academics, regularly meet to address challenges and support the implementation of OOC in drug development.

9. We cannot match the complexity of a human

“Do not let perfect be the enemy of the good” is saying that is very relevant here. As the name suggests, a test model is just that, a test. However, the advantage of single- and multi-OOC models is their ability to more accurately mimic a well-defined phenotype, process, function, or disease associated with a certain human organ, or organs.

Performance is validated using published in-human data and, once their translatability is established, there is a wider breadth of scientific questions that can be asked over traditional 2D cell culture.

Animal models offer a dynamic, complete system with all essential cues available, but some significant cross-species differences can be misleading. It has been proven that OOC can predict clinical outcomes that animal models cannot.7 It can therefore be beneficial to run OOC alongside for extra assurance.

Similarly, an area of high potential for OOC is found within new modality development, including gene or cell therapies, which are reliant on human-specific modes of action for which animals are not always suited.

While OOC models are not real life, there is a lack of human-relevant biology to compare potential therapeutics against, which is a contributor to high attrition rates. OOC provides an answer and is available right now, helping to close the divide between the preclinical and clinical phases of medicine discovery.

The simple act of complementing the insights found using traditional approaches with those from OOC offers the chance for better-informed decisions about which drugs to move forward into in vivo animal studies, where appropriate, and the clinic.

CN Bio continues to invest in OOC technology, its road to adoption and regulatory acceptance focusing on the advancement of science and creating a brighter future together. So don't get caught up in myths and misconceptions, its time to start your OOC journey!

References and further reading

  1. Tsamandouras, N., et al. (2017). Integrated Gut and Liver Microphysiological Systems for Quantitative In Vitro Pharmacokinetic Studies. AAPS J 19: 1499–1512 https://doi.org/10.1208/s12248-017-0122-4
  2. Rubiano, A., et al. (2021). Characterizing the reproducibility in using a liver microphysiological system for assaying drug toxicity, metabolism, and accumulation. Clin Transl Sci, 14: 1049-1061. https://doi.org/10.1111/cts.12969
  3. Yassen Abbas et al. (2021). Drug metabolism in a gut-liver microphysiological system
  4. Paul M. van Midwoud, et al. (2012). Comparison of Biocompatibility and Adsorption Properties of Different Plastics for Advanced Microfluidic Cell and Tissue Culture Models. Analytical Chemistry, 84 (9): 3938-3944. https://pubs.acs.org/doi/10.1021/ac300771z
  5. Franzen, N et al. (2019). Impact of organ-on-a-chip technology on pharmaceutical R&D costs. Drug Discovery Today, 24, ( 9): 1720-1724. https://doi.org/10.1016/j.drudis.2019.06.003
  6. MEPs demand EU action plan to end the use of animals in research and testing
  7. Rowe, C et al. (2018). Perfused human hepatocyte microtissues identify reactive metabolite-forming and mitochondria-perturbing hepatotoxins. Toxicol In Vitro, 46:29-38. https://doi.org/10.1016/j.tiv.2017.09.012

About CN Bio

CN Bio develops human organ-on-chip technologies: devices that enable the formation of miniature models of human organs in the lab. We provide products and services to the pharmaceutical industry and in the past 3 years have used our proprietary organ-on-chip models in drug discovery and drug safety programs with more than 25 pharmaceutical companies. CN Bio has also pursued research to develop disease organ-on-chip models with successful programmes resulting in novel models of non-alcoholic steatohepatitis and Hepatitis B virus infection.

Working closely with academic pioneers in the bio-engineering field, and pharmaceutical and industrial partners, CN Bio continues to advance next generation human Organs-on-Chips.

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Last updated: Mar 29, 2024 at 7:47 AM


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