There is a need for tissue-based tools to drive drug development both in the pre-clinical and clinical phase to improve the success rate of drug development. Drug development is a long, complex, and expensive process. On average, it takes about 10 years to get from idea to an approved drug. Additionally, it costs billions of dollars to develop a drug, including developing drugs that are not approved.

Consequently, it is important to improve the probability of success, so innovation will not be attenuated. In accordance with this, FDA and EMA have expressed a view that biomarker-based drug development strategies in combination with translational research could potentially provide a biology targeted approach, which will decrease time and cost and give an overall increased probability of success


The need to translate results from basic research to clinical research arises from the nature of the initial in vitro experiments, which are simplified models of the more complex clinical setting. For example, primary chondrocytes cultured in mono-cell layers with serum have different conditions and are less clinically relevant than chondrocytes scattered in a dense ECM in the articular cartilage of a human joint. Ex vivo cultures have slightly more clinical relevance than in vitro experiment due to their more natural ECM environment, but are also more complex and can be more difficult to manipulate experimentally. Our models aim to bring the high throughput of intro studies and the superior translation from in models closer together by characterizing cellular function in a more translatable 3D environment. Naturally, the ex vivo models are still cultured under artificial conditions in the laboratory and should be backed by in vivo and clinical research.

Current models and the translational gap

A broad range of in vitro models is usually employed to verify target engagement, profile stability, and test cellular modulation. Common for many of these models is that they lack the complexity needed and the profiling of downstream effects on the tissue making them less suited for translational use further up the drug development chain 

From arthritic diseases across different forms of fibrosis to cancer, the need for translational models that can accurately profile extra-cellular matrix remodeling and inform decision making in clinical development is becoming increasingly important.

Nordic Bioscience translational models employ ex vivo, fibroblast, or primary cell cultures cultured in or on suitable matrices allowing for active profiling of tissue turnover using the protein fingerprint biomarkers.

-Quantitative and dynamic measure of tissue turnover

-In vivo likeness where cells are maintained in a close to native matrix.

-Translational from in vitro to clinic allowing use of the same biomarker across different stages of development.

The tissue derived Protein Fingerprint biomarkers can be measured in supernatants from cell or ex vivo culture systems to accurately quantify tissue specific changes arising from cellular activity in the individual tissues. An example of the application of biomarkers to describe tissue specific turnover is shown in the figure below.


The cartilage explant model allows us to study cellular function and structural changes in a native-like 3D environment of bovine or human knee cartilage. and evaluate anti-catabolic or anabolic treatment efficacy.

The model can be used to evaluate efficacy of novel treatments on chondrocyte function and cartilage ECM turnover and interrogate compound mode of action by measuring protein fingerprint markers in the culture supernatant.

Cartilagedegradationquantified by aggrecanasedegradedaggrecan (AGNx1) cartilage formation quantified by release of the type II collage pro-peptide PRO-C2 in bovinecartilageexplantstreated with either pro-inflammatorycytokines or growh factors.

Reference: Thudium et. al.,  JoVE (2020)

Mechanical compression is essential for cartilage maintenance and homeostasis. Cartilage can be loaded in a multi-well setup to mimic physiological or pathological loading in vitro or to investigate the efficacy of novel treatments under physiological-like conditions. Protein Fingerprint biomarkers are measured in the culture supernatants to characterize tissue turnover.


Time-dependent levels of the biomarkers C3M and acMMP3 in supernatants of human osteoarthritic synovial explant cultures after treatment with cytokines.

The synovial membrane explant model allows us to study the cellular function and structural changes in a native-like 3D environment of human knee synovium and evaluate the effect of cytokines, growth factors, or novel treatments. Protein Fingerprint biomarkers are measured directly in the supernatant and allow dynamic profiling of tissue turnover.


Time-dependent levels of the biomarkers C3M and acMMP3 in supernatants of human osteoarthritic synovial explant cultures after treatment with cytokines.

Reference: Kjelgaard-Petersen C. et. al.,  Biomarkers (2015)

The Fibroblast like synoviocyte (FLS) model is a well-established model to characterize the function of synovial cells in rheumatology. The cells can be isolated directly from human synovium and by stimulating primary synoviocytes with inflammatory or pro-fibrogenic cytokines and stimuli we can model the inflammatory environment of the synovium in vitro and evaluate direct anti-inflammatory or anti-fibrotic treatment efficacy. Nordic Bioscience biomarkers are measured in the supernatants to determine tissue turnover and efficacy.

Culture of primary human osteoclasts is a well-established method to investigate osteoclastogenesis and bone resorption. This model allows the study of osteoclast function in response to cytokines and evaluate anti-resorptive or osteoclastogenic treatment efficacy. Biomarkers are measured in the supernatants to determine efficacy.


Reference: Sørensen MG et al, Journal of Bone and Mineral Metabolism (2007)

Precision-Cut Lung Slices (PCLS) of human fibrotic tissue is an established ex vivo model of pulmonary fibrosis. This model allows us to study the three-dimensional lung tissue from a patient and evaluate anti-fibrotic treatment efficacy. Nordic Bioscience biomarkers are measured in the supernatants to determine efficacy.


Reference: Leeming DJ and Sand JMB et al, presented at ERS 2018

The prolonged Scar-in-a-Jar is a novel model that employs macro-molecular crowding to promote the formation, maturation and deposition of extracellular matrix in vitro. Stimulating primary fibroblasts with pro-fibrogenic cytokines and stimuli we can model fibrosis in vitro and evaluate direct anti-fibrotic treatment efficacy. Nordic Bioscience biomarkers are measured in the supernatants to determine efficacy.

Types of fibroblasts:
- Pulmonary fibroblasts
- Dermal fibroblasts
- Cardiac fibroblasts
- Hepatic stellate cells
- Cancer associated fibroblasts
- Fibroblast-like synoviocytes (FLS)

The Scar-in-a-Jar model for the above mentioned different celltypes are described respectively in the below.


Stimulating primary pulmonary fibroblasts with pro-fibrogenic cytokines and stimuli we can model lung fibrosis in vitro and evaluate direct anti-fibrotic treatment efficacy. Nordic Bioscience biomarkers are measured in the supernatants to determine efficacy.


Reference: Rønnow SR et al. 2020 Respir Res.

Cancer associated fibroblasts (CAFs) are key players in orchestrating a pro-tumorigenic microenvironment amongst others by altering the ECM deposition and remodeling (desmoplasia) affecting cancer cells and immune cells. Therefore, CAFs are a potential target for optimizing therapeutic strategies against cancer and attempts to modulate CAFs for therapeutic benefit is ongoing. Nonetheless, limitations in our current understanding of CAFs challenge this strategy. The SiaJ model offers a simple in vitro tool to address CAF biology and the direct impact of therapeutic intervention, in particular related to ECM remodeling.


Stimulating primary hepatic stellate cells with pro-fibrogenic cytokines and stimuli we can model liver fibrosis in vitro and evaluate direct anti-fibrotic treatment efficacy. Nordic Bioscience biomarkers are measured in the supernatants to determine efficacy. Unpublished data

Protein Fingerprint biomarkers allow for testing of anti-fibrotic effects of novel treatments by measuring protein formation fragments in the Scar-In-a-Jar model. Dermal fibroblasts are driven into a fibrotic state by growth factors. This fibrotic stimulation may be inhibited by anti-fibrotic drugs, here exemplified by Nintedanib.


Accumulation of extracellular matrix (ECM) proteins is the hallmark of fibrosis, which can lead to altered tissue homeostasis, organ failure and ultimately death. Many different cell types and growth factors are involved in this process, but fibroblasts are the main source of ECM proteins. In the adult heart, net collagen deposition is normally very low. In disease states, such as cardiac hypertrophy, heart failure, and myocardial infarction, collagen production by activated cardiac fibroblasts is dramatically increased. Excessive fibroblast proliferation and increase in ECM protein content (fibrosis) induce myocardial stiffening, an important process in cardiac patho-physiology. Cardiac fibroblasts are not only collagen producing cells, but they also function as local immune modulators and contribute to cardiac electrophysiologyBy modeling fibrogenesis using cardiac fibroblasts in the in vitro Scar-in-a-Jar (SiaJ) system, we can provide insight in potential pro-fibrotic signaling mediated by different molecules, such as TGF-β and endotrophin.


Type I and III collagen formation quantified by PRO-C1 and PRO-C3 is increased in supernatants from cardiacfibroblastscultured in the SiaJ model and treated with either TGF-β or endotrophincompared to controls (unpublished data).

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