Story | 06/06/2024 10:21:50 | 16 min Read time

A new era in drug discovery and development – From research to treatments

In November 2023, UPM Biomedicals hosted its 9th annual conference. This time around, the conference focused on the future of 3D cell culture: from research to treatments. Featuring a host of informative talks from experts and representatives from industry and academia, the event shone a light on the current and future 3D cell culture landscape, particularly in the arena of drug discovery and development.

In this article series, we will cover some of the highlights and key takeaways from the conference and explore how 3D cell culture is transforming drug discovery and helping to improve the success rate of new drugs entering the clinic. First up, we will be looking at how to get the best from your 3D cell models during different phases of drug discovery.

3D cell models in drug discovery 

3D cell culture has exploded in popularity in recent years, especially in the area of drug discovery. In comparison to traditional 2D cell culture, 3D cell culture provides augmented modelling that more closely replicates the intricate physiological cellular interactions and tissue architecture of the human body. The opportunity to create disease-specific models, miniaturized screening platforms, as well as primary models based on patient-derived cells, bring value right across the drug discovery pipeline.  

The shift away from 2D cell models in place of more physiologically relevant 3D models is not merely a trend, but instead marks a transformative leap in drug discovery. The enhanced biological relevance and data yield provided by 3D cell models is enabling the identification of better lead molecules earlier in the discovery pipeline, and helping to improve the poor success rate of new candidate compounds entering the clinic.  

3D cell culture models vary widely in their composition, morphology and architecture. Ranging from organoids and spheroids to hydrogel-based cultures, 3D cell culture encompasses a wide variety of cell models and technologies.  

Different phases of preclinical drug discovery demand different properties from 3D cell models. Developers must consider automation and high-throughput compatibility, the overall cost of the model and cost per sample, plus the level of complexity required to represent the right biology. Therefore, adopting tailored approaches can cater for the specific requirements of each phase1.  

Let’s take a closer look at how 3D cell models can be leveraged for drug discovery, and the ideal 3D cell models and characteristics required at each phase.

Phase one of the drug development process: 3D models for target identification 

Target identification and validation is the first critical phase in drug discovery and can be a substantially time-consuming endeavor. When approached using traditional 2D monolayer models, data often lacks human relevance, falling short in recapitulating the complex microenvironment of in vivo tissues. As such it can be difficult and longwinded to extract meaningful information about potential targets, their druggability, or mechanisms of action using 2D models. 

3D cell culture unlocks unique possibilities in the identification and characterization of novel drug targets. 3D models can more closely capture the spatial arrangement, stiffness, cell-cell and cell-extracellular matrix interactions and gene expression patterns of human tissues. As a result, 3D models empower developers with enhanced insights into the behavior and characteristics of potential drug targets, their interactions in the cellular microenvironment and which signaling pathways are activated.  

In early phase drug discovery, the use of 3D models presents a strategic balance between complexity, cost and operational efficiency. At this stage, a large volume of compounds may need to be screened, necessitating models that are not only cost-effective but also less biologically complex. Simplified 3D models, such as spheroids, offer a pragmatic solution by providing more relevant biological insights than traditional 2D cultures without the extensive complexity and cost associated with more intricate systems like organoids.  

For 3D models to be effective in high-throughput screening environments, they must be robust and compatible with automation technologies. This means they should be easy to reproduce, maintain consistent behaviors across batches, and be amenable to the automated processes used in large-scale drug screening. 

For some target ID and preliminary applications, developers may need to create models resembling the in vivo setting as closely as possible to interrogate cell interactions and identify potential therapeutic targets. When lower throughput and increased complexity is required, organoid models can be highly effective. 

Organoid applications in target ID 

3D organoid models are adept at capturing the architecture and complexity of in vivo tissues, providing the opportunity to create life-like disease models and the ability to maintain key parameters and microenvironmental properties. In contrast to spheroid models, 3D organoid models are generally less cost-effective and less compatible with high throughput and automation technologies. This is because organoid models instead aim to achieve a greater level of detail and more closely mimic in vivo conditions. Although organoid models are more commonly associated with the later stages of the drug discovery pipeline, they can be valuable for the identification of therapeutic targets. 

A 2022 paper2 highlighted a great example of this: A research team in Quebec developed a self-assembly 3D disease model of bladder cancer with tumor organoids and cancer-associated fibroblasts. The advanced model provided a window into the dynamics governing the critical interactions between cancer cells, cancer-associated fibroblasts, and the extracellular matrix. This revealed signaling pathways that are activated in the presence of cancer-associated fibroblasts, highlighting a novel therapeutic target.  

Organoids are well suited for modelling complex genetic and heterogenous diseases like cancer. Patient-derived organoids retain the genetic and phenotypic heterogeneity of the source tissue, and therefore can be used to determine tumor expression profiles and inform personalized therapies. Looking to the future, patient-derived organoids could be used to capture the heterogeneity of disease profiles and identify more effective drug targets.  

High throughput screening drug discovery 

During the hit identification and hit-to-lead phases of drug discovery, high throughput screening (HTS), is an essential process that evaluates the effects of vast compound libraries against the therapeutic target to identify potential lead candidates. HTS relies heavily on automation and speed to enable the screening of thousands to millions of compounds in a short space of time.  

The integration of 3D cell culture into HTS has been more challenging, primarily because of the high cost and complexity of 3D models versus 2D grown cells. 3D culture is not always necessary for HTS, but can bring significant advantages and versatility, offering enhanced predictive value, multi-parameter analysis and the possibility of creating patient-derived models to query heterogeneity in drug responses. While some applications of 3D models require a high level of complexity to closely replicate the in vivo setting; throughput, automation, and cost become more important considerations in screening applications.   

The vast number of compounds screened in a HTS campaign demands an equally large number of 3D cell models to test upon. As such, 3D models for HTS should be compatible with automation and miniaturized formats such as microwell plates to enable the assessment of numerous compounds and conditions at a satisfactory throughput rate. While 3D models come nowhere close to the cost-effectiveness of 2D screening, miniaturization is helping to make 3D screening models cost-efficient by yielding more datapoints per cell. 

Spheroids and ultra-miniaturization for HTS 

Thomas Lundbäck, Senior Director of Mechanistic and Structural Biology at AstraZeneca gave an informative talk about his work on the ultra-miniaturization of primary hepatocyte spheroids. Working in collaboration with UPM Biomedicals and a number of academic and industry stakeholders, AstraZeneca has been a key partner in the nanoscale drug testing project, a collaboration set up with the aim of developing an ex vivo drug testing platform based upon primary human hepatocytes. 

One of the main contributing factors to the substantial failure rate of candidate drugs entering clinical trials, is the gap between preclinical screening/testing models and patient populations. By incorporating primary tissue into early drug discovery, the nanoscale project hopes that this gap can be bridged, enabling improved translation to patients. Since primary tissue is notoriously hard to source and highly expensive, miniaturization is necessary to yield enough data to make the platform viable. 


Figure 1: Image of a primary human hepatocyte mini-spheroid cultured in GrowDex.

Some cells cannot be cultured in 2D – and primary human hepatocytes are dependent on cell-cell interaction and the 3D setting to preserve their primary phenotype. As such, scaffold-based spheroid culture stood out as an ideal 3D culture approach to maintain cell functionality and to prevent spheroid aggregation, which is a known problem with suspension-based 3D cell culture technologies.  

The project developed a microfluidic device for dispensing primary hepatocytes as mini-spheroids (clusters of ~60-100 cells), and GrowDex hydrogel was selected as the cell culture matrix, facilitating the embedding of minispheroids into a 3D cell culture hydrogel. The main reason for selecting GrowDex was its compatibility with automated liquid handling systems and high lot-to-lot consistency. 

Although work is still ongoing, the mini-spheroid approach demonstrates the ability to integrate primary 3D models into a HTS platform, and the importance of miniaturization to make this possible. The project continues to push the boundaries on miniaturization and seeks to move from 96- and 384-well plates into even smaller formats (1536-well plate) for screening applications

High content screening drug discovery – intestinal organoids 

Not all screening applications demand high throughput, or the evaluation of thousands of compounds. Sometimes, more targeted screening or functional testing is required, and in such cases, researchers may require an increased level of complexity in their 3D culture models. High content screening (HCS) is one such application, in which quantitative image analysis is leveraged to extract detailed information about cellular processes.

Christian Parker, European Ambassador for the Society for Lab Automation and Screening (SLAS) and scientist at Novartis, talked about his group’s endeavors at Novartis to identify compounds with the ability to increase the resistance of intestinal crypts against radiation. The aim was to find a compound that would enable cancer patients to cope with longer-term or higher-dose radiation treatment while limiting tissue damage and gastro-intestinal disturbance.

Figure 2: Time lapse images displaying morphological and organizational development of an intestinal crypt organoid, as seen in Christian Parker's presentation.

Christian’s team at Novartis developed a self-organizing human intestinal crypt organoid platform which captured the complexity of the in vivo setting. The complex model was then used for various morphological, functional and phenotypic HCS helping the team to unpick underlying mechanisms of action and gene regulation in response to radiation, and to identify compounds that could be effective for cancer patients.

The intestinal crypt organoid platform developed by Christian’s team at Novartis was initially developed using Matrigel—an animal-derived hydrogel culture matrix—but the platform soon ran into problems with automated liquid handling and organoid behavior. The varied animal proteins from Matrigel also affected the morphology of the organoids and produced unwanted experimental effects.

Functional testing, lead discovery and optimization  

Following screening, lead optimization aims to refine and enhance the properties of potential drug candidates to optimize their potency at the primary target. 3D cell cultures can be highly valuable during this phase, offering a more physiologically relevant environment for assessing drug efficacy, pharmacokinetics, and safety.  

Lead optimization is a multifaceted process requiring rigorous biological testing – from pharmacokinetics and pharmacodynamics studies, to drug-drug interactions and metabolism and stability testing. During this phase, a range of 3D modelling approaches, including organoids and spheroids, as well as novel technologies like organs-on-chips, may be integrated to address the specific needs of the program.  

Mini-spheroids and SAR studies  

In addition to screening applications, Thomas Lundbäck also spoke about the primary human hepatocyte mini-spheroid platform for chemistry optimization. In the pharmaceutical industry, lead optimization is a cyclical process known as DMTA: design of compounds, making or synthesis of compounds, testing and analysis of the compounds. 

Structure-activity relationship (SAR) studies are a major feature at this stage, seeking to identify key chemical structures and moieties responsible for activity at the target. This involves synthesizing a range of structurally altered lead molecule ligands which undergo extensive biological testing to confirm activity. The large number of compounds that need to be tested and conditions (e.g., concentration) that need to be interrogated make miniaturized platforms a favorable choice in terms of cost-effectiveness. The key problem for wider adaptation of matrix-based 3D cell culture technologies is the cost, limited automation compatibility and reproducibility.  

Once again, patient-derived spheroids can provide enhanced predictability and translation to patient populations. From a practical perspective, mini-spheroids also offer an extraordinary level of reproducibility, which is especially important when testing is performed in a cyclical or sporadic manner.  

A question of balance in new drug development 

The speakers at the 2023 UPM annual conference highlighted the growing role of 3D cell culture across the drug discovery pipeline. From target ID to lead optimization, different phases demand unique characteristics from 3D cultures – and finding the balance between system complexity, cost effectiveness and throughput is critical to successfully implementing 3D models for drug discovery.

3D cell culture may not always be necessary – HTS applications in particular require highly standardized, replicable cultures which can be achieved with the traditional ‘workhorse’ 2D cell lines. However, 3D culture unlocks a host of additional analytical possibilities, and the ability to screen against cell types that cannot be grown in 2D, such as human primary hepatocytes. 

The conference drew our attention to a diverse range of 3D culture systems that can be harnessed for drug discovery. Where scaffold-based 3D culture was implemented, many of our speakers experienced issues with animal-based hydrogels, which are not compatible with automated dispensing systems, and express lot-to-lot variability that produces unwanted experimental effects. Opting for an animal-free and highly defined hydrogel matrix like GrowDex can ensure that you can automate your 3D cell culture assays and get the best possible consistency in your cultures and reproducibility in results.  

All of the presentations from UPM Biomedicals 9th annual conference are available to view online. Stay tuned as we continue to cover the highlights from the conference in our article series!  

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  1. Fang, Y., Eglen, R. M. (2017). Three-Dimensional Cell Cultures in Drug Discovery and Development. SLAS Discovery. 22(5), 456–472.  
  2. Millet, M., Bollmann, E., Ringuette Goulet, C. et al. (2022). Cancer-Associated Fibroblasts in a 3D Engineered Tissue Model Induce Tumor-like Matrix Stiffening and EMT Transition. Cancers. 14(15), 3810. 
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