Organ-on-a-chip (OOC) technology offers you a transformative approach to better science. By bridging the gaps between traditional cell culture, animal models and the clinic, its complementary use delivers deeper, human-relevant insights that enable better-informed decisions about the right therapeutics to take into trials.

The potential of OOC to reduce drug attrition rates and bring novel therapeutics to patients more rapidly and cost-effectively has piqued the interest of early adopters, eager to recreate intricate human physiology in the laboratory to gain a competitive advantage. For others, the jury remains out and questions remain. Do transitional challenges outweigh the potential benefits, is the technology ready for primetime?

While there are hurdles associated with adopting any technology, by considering these upfront you can make the complex simple and ease your transition into OOC so that you can reap the benefits faster. In this article, we address some common concerns and present a realistic perspective on the adoption challenges that surround OOC.

1. OOC systems are too complicated to set up

Every myth has a kernel of insight, but OOC systems have come a long way since prototypes with yards of intricately set-up tubing that required an associated bioengineer to make them run.

Whilst commercial solutions are firmly designed for the cell biologist’s hands, some systems will “feel” more familiar than others. Microscale designs operate at extremely low volumes, which is advantageous when working with precious samples, but cell seeding requires steady, experienced hands. Alternative, less-futuristic designs provide a straightforward transition from traditional 2D cell culture via familiar multi-well plate formats. Their higher working volumes offer benefits that will be explored further below.

Rest assured that vendors are not just focused on technology development. Our creative minds have identified additional ways to ease adoption through complete solutions that include off-the-shelf reagents, protocols, software, and support packages to shorten the learning curve.

2. Primary cells are too challenging to work with

Naturally, primary cells are an important component of OOC models. They are required to accurately recapitulate human organs, or disease states, in vitro and are certainly more challenging to work with than immortalized cells. Whilst this challenge isn’t unique to OOC, there is an extra dimension to consider versus 2D primary cell assays! In our experience, primary cells that work well in a standard 2D assay, do not always translate well into 3D culture. Your laboratory could lose valuable time, resources, and budget validating cell lot, after cell lot, to find OOC-compatible donors. To address this issue, we collaborate closely with primary cell providers to supply cells that thrive in 3D, maintaining their function and phenotype for up to 4 weeks when cultured under perfusion. So, rather than wasting time finding needles in haystacks, you can focus on making new discoveries!

Also, don’t forget that OOC vendors like us have had years of experience working with primary cells and will willingly share tips and tricks through protocols, or via our support channels to ensure your assays are successful and reproducible.

3. OOC offers limited endpoint measurements

As you may expect, approaches designed for high throughput screening deliver fewer endpoint measurements from simpler OOC models. However, this statement couldn’t be further from the truth for complementary OOC solutions that sit up and downstream to unlock disease mechanisms,  investigate new targets, evaluate drug safety or efficacy and derive ADME profiles.

Whilst every OOC system offers a different mix and breadth of endpoint measurements, there is a rough rule of thumb. The number of possible endpoints roughly correlates to the size of the microtissue generated and the physiological relevance of the culture conditions. For example, large-scale, horsepower-loaded microtissues perfused by finely tuned fluidics to mimic the bloodstream offer ultimate assay sensitivity, culture longevity, and data-richness. High media volumes in these systems enable repeat sampling over multiple weeks for longitudinal metabolomic, proteomic, and clinically translatable biomarker studies, plus, their ample microtissues are recoverable allowing you to perform post-assay microscopic analysis or genomic, transcriptomic, and proteomic profiling.

OOC also enables you to perform studies that weren’t previously possible in vitro. Liver cultures, for example, can be maintained for up to 4 weeks to study the effects of chronic drug dosing so that you can identify drug-induced-liver injury liabilities ahead of the clinic. New, interconnected multi-organ (gut and liver) models recreate human processes such as first-pass metabolism to estimate drug bioavailability, an important parameter currently determined using animal models that deliver poor predictability 1, 2, 3. OOC also offers a viable path forward for testing newer human-specific drug modalities where animal use is less suited due to interspecies differences.

4. Throughput is limited

There is no avoiding the fact that there is an inverse relationship between physiological relevance and throughput capacity. If you need to screen hundreds of thousands of compounds, it won’t be possible to do this using the most “human-like” in vitro models, but there may well be a way to incrementally improve from where you are currently.

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

From here, chip- and plate-based OOC solutions featuring adjustable “organ-specific” flow rates that recreate in vivo-like biomechanical stimulus, oxygen, and nutrient delivery, enable the most accurate recapitulation of human organs and microtissues in vitro. These more sophisticated systems are indeed relatively low in throughput. Only one replicate can be run per chip, or 6-48 replicates per Multi-chip plate. Generally, most vendors offer the capability to run several chips, or plates, simultaneously to improve capacity. However, due to their data richness, enhanced sensitivity and data translatability, they perfectly complement their higher-throughput siblings by helping to ensure the right lead candidates enter in vivo animal studies or the clinic.

5. All OOC solutions use Polydimethylsiloxane (PDMS)

PDMS is often used in organ-on-a-chip technologies but by no means all.  This gas-permeable polymer is straightforward to manufacture at a small scale, low cost, and transparent, enabling easy imaging. The crucial disadvantage of PDMS is its lipophilicity. Unfortunately, this property causes the non-specific binding of hydrophilic compounds, making it difficult to accurately quantify drug exposure-responses, or pharmacokinetics.

PDMS is not the only material currently available to OOC developers. A viable alternative is Cyclic olefin copolymer (COC), an amorphous polymer known to be the most inert material available. COC use minimizes non-specific binding when working with a cross-section of therapeutic modalities, including small and large molecules. We recommend using COC over PDMS for compound testing to maintain data integrity4.

6. OOC systems lack flexibility

It’s unfair to imply that all OOC systems lack flexibility, or that a lack of flexibility is necessarily a negative. But, it is fair to say that one solution may not cover all of your application needs. To fully characterize and subsequently validate a model/assay using a range of drug standards takes time, however, as the field develops, the breadth available from each vendor will increase. It is important not to delay adoption for this reason. A range of options is available from each vendor to serve your immediate contexts of use so that you can reap the benefits of OOC faster.

As experienced OOC researchers are in short supply, the “experience gap” has led to a prescriptive approach by some vendors who provide “off-the-shelf” convenience and a fast-track route to adoption. If flexibility is important, look to the future, can you make tweaks as you gain experience? Does a one-size-fits-all approach to consumable design work for you, is it a compromise, or would you prefer the design to be bespoke for the organ/tissue model?

Additionally, if you have invested time and energy developing an in-house model using standard inserts, such as Transwell®, ensure that the commercially available system you choose is flexible enough to accommodate before investing.

One final point to consider relates to the architecture of the system. How open or closed is it? This is particularly pertinent to consider when inducing/studying disease onset. Can you easily access the cultures to change experimental conditions, or manipulate the models once the experiment is set up? Can you easily remove samples for longitudinal bioanalysis studies?

7. The technology is too costly

There is naturally an upfront investment associated with adopting any new technology, however, the initial CAPEX outlay and running costs are probably much smaller than you think when offset against the potential gains. OOC systems fulfil critical unmet needs within R&D and can enable your organization to realize significant savings. A research publication suggests that incorporating OOC into drug discovery workflows to generate human-relevant data that better predict clinical outcomes, could save companies up to 26% of their R&D costs5.

The human-relevant, mechanistic data that OOC delivers enables stop/go decisions- while there’s an opportunity to modify drug design. Insights facilitate the refinement of pre-clinical experimental design and reductions in animal use by justifying only the progression of promising drugs to reduce costs.

Furthermore, finding a suitable in vivo model for testing new drug modalities that require human-specific target expression can be challenging. 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

OOC offers the potential to deliver human-predictive information that improves data translatability between the lab and clinic. However, we understand that embarking on a strategic shift from entrenched gold standard models to a novel approach is not always straightforward, especially at the later stages of drug development. So, let’s not jump the gun. Currently, OOC is being used to drive major improvements in the accuracy and efficiency of drug discovery. It represents a concrete approach to reduce, refine, and complement existing tests, right now – rather than a futuristic proposal to sweep away the status quo.

However, in December 2023, we were delighted to announce that our PhysioMimix® NASH assay was used to provide human-relevant data on compound efficacy to support the initiation of Inipharm’s Phase 1 clinical trial for INI-822. The submission represents the first example of an OOC provider’s data supporting the clinical progression of a drug for a complex metabolic liver disease, demonstrating the transformative potential of these models to provide human-relevant insights within preclinical programmes.

Regulatory authorities have recognized OOC’s potential and are investing in collaborative initiatives to help underpin the use of OOC and fast-track 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 results2. This publication demonstrates the robustness, reliability, and superior performance of our PhysioMimix® Liver-on-a-chip (LOAC) for drug evaluation purposes versus standard technology.

Alongside researchers from the FDA, we are now working with broader industry stakeholders as part of the Predictive Safety Testing Consortium (coordinated by the Critical Path Institute) to develop a framework for qualifying complex in vitro models for regulatory assessment. This consortium has the overall goal of formally obtaining regulatory acceptance of novel drug safety tests including the use of organ-on-a-chip technologies. For more information, click here.

Additionally, consortiums such as the IQ-MPS Affiliative, made up of pharmaceutical and biotechnology companies plus leading academics, meet regularly to address challenges and support the implementation of OOC in drug development.

There is a strong foundation in place that, we foresee, will lead to more widespread regulatory acceptance of OOC data within regulatory submissions in the not-too-distant future. For now, this should not be a reason to hold back from adopting a technique that enables better science.

9. We cannot match the complexity of a human

The saying ‘Don’t let perfect be the enemy of the good’ is highly relevant here. A test model is, as its name suggests, a model and not real! However, the unique advantage of single-and multi-OOC models is that they mimic a well-defined phenotype, function, or process associated with a specific human organ or organs. Their performance is validated against published in-human data and once translatability has been established, you can explore a much wider range of scientific questions than via traditional 2D cell culture.

While animal models provide a dynamic, whole system with all essential cues present, some significant cross-species differences can mislead. OOC has been proven to predict clinical outcomes that animal models cannot7 so, why not run OOC alongside for a sanity check? And, whilst on the topic, an area of high potential for OOC lies within new modality development, such as cell or gene therapies, which rely on human-specific modes of action for which animals are unsuited.

So, although OOC models are not “real”, the lack of human-relevant pre-clinical models for testing potential therapeutics is causing undeniably high attrition rates. OOC offers a solution to bridge gaps between the preclinical and clinical phases of medicine discovery. By complementing the insights derived using traditional approaches with those from OOC, you can make more informed decisions about which drugs to take into humans.

Going forward, we will continue to invest in OOC technology, the path to adoption, and regulatory acceptance. We hope that by ironing out the misunderstandings, misconceptions, and myths surrounding OOC you may join us so that we can focus on advancing science and creating a brighter future together.

For more information on the PhysioMimix OOC range, including the PhysioMimix Single-organ and PhysioMimix Multi-organ Systems, click here.

Updated in 2024

AUTHOR

Atefeh Mobasseri, MSc, PhD

Field Application Scientist, CN Bio
  1. Tsamandouras, N., et al. (2017). Integrated Gut and Liver Microphysiological Systems for Quantitative In Vitro Pharmacokinetic Studies. AAPS J 19: 1499–1512 [Access Full Article]
  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. [Access Full Article]
  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. [Access Full Article]
  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. [Access Full Article]
  6. MEPs demand EU action plan to end the use of animals in research and testing [Read Press Release]
  7. Rowe, C et al. (2018). Perfused human hepatocyte microtissues identify reactive metabolite-forming and mitochondria-perturbing hepatotoxins. Toxicol In Vitro, 46:29-38. [Access Full Article]