This month, we sat down with Dr. Maryna Panamarova, a technical expert in the 3D culture space. Dr. Panamarova is working to develop and upscale novel organoid models at the Wellcome Sanger Institute. She is an advocate for making knowledge open source and believes it’s key to advancing the industry forward.
Provide a little bit of background on your journey so far, your expertise in life science, and also how that relates to the field of 3D cell culture and 3D technologies.
Dr. Panamarova: My name is Maryna Panamarova, and I work as a Cellular Modelling Specialist at the Wellcome Sanger Institute.
My journey into scientific research began during my undergraduate years at the University of Edinburgh when I landed an internship at the Centre for Regenerative Medicine. It was around 2007, a time when induced pluripotent stem cell technology was just starting to emerge, and work with human embryonic stem cells was not easily accessible and viewed as potentially controversial by some. I feel incredibly fortunate to have had the chance to learn and grow in such an innovative research environment with fantastic mentors so early in my career.
My interest in regenerative medicine led me to pursue a Ph.D. at the University of Cambridge and the Gurdon Institute. There, I focused on understanding the basic epigenetic mechanisms that govern cell fate decisions during early embryonic development. Working alongside my Ph.D. mentor, Magdalena Zernicka-Goetz, we illustrated the effectiveness of utilising advanced cellular models to investigate complex biological processes, such as cell fate determination.
During my postdoctoral research at King’s College London, I focused on finding new treatments for incurable muscular dystrophy (FSHD), a condition that only affects humans and primates. Given the challenges of using mouse models to study this disease, I explored genomic methods and advanced 3D models to gain a deeper understanding of its complexities for drug discovery.
Where are you now? What’s your focus at the moment?
Dr. Panamarova: I work within the Scientific Operations team at the Wellcome Sanger Institute. The Sanger Institute, based in the UK, is a world-leader in genomic research that delivers insights into human, evolutionary, and pathogen biology.
The Scientific Operations department helps deliver science at scale by developing and championing an array of cutting-edge technologies in sequencing, cellular and molecular biology, and spatial genomics.
In the Cellular Modelling team within Scientific Operations, we focus on large-scale production, biobanking, and validation of advanced cellular models from patient-derived tissues and reprogrammed stem cells. Over the years, our team has made significant contributions to various global and national initiatives aimed at developing improved models for studying human diseases. Among them are the Human Cancer Model Initiative (HCMI), an international effort to establish patient-derived next-generation cancer models, and IBD Response, a UK-wide study to predict and model patient responses to therapeutics in Inflammatory Bowel Disease.
How have you seen the industry change since you’ve been a part of it?
Dr. Panamarova: I joined Sanger in 2020. Since then, organoid technology has undergone remarkable advancements that broadened our access, understanding, and application of in-vitro models of human biology and disease.
One significant development is the refinement of protocols for organoid generation and culture. There have been advancements in optimising culture conditions, media compositions, and growth factors, leading to more efficient and standardised protocols. At Sanger, our team openly shares the protocols that we use via our protocol.io and YouTube channel. We also collaborate with Wellcome Connecting Science to offer an Advanced Organoid Course designed for experienced researchers seeking to get experimental skills in organoid culture and applications.
There has been a notable increase in the complexity of organoid models. There is currently a big drive to create advanced microphysiological systems (MPS) by incorporating multiple cell types and recapitulating tissue architecture more accurately. This increased complexity enhances the physiological relevance of organoids and allows for more accurate modelling of tissue function and disease pathology.
The surge in interest surrounding organoids has catalysed technological advancements, enabling improvements in throughput and downstream processing. The integration of organoid technology with other state-of-the-art methods, such as single-cell RNA sequencing and CRISPR-Cas9 genome editing, has amplified the potential of organoid models in fundamental research and drug development.
From my discussions with people who are working in industry, specifically in pharma, there’s still a hesitancy to bring 3D models in. There might be some individual groups here and there who are doing some experiments or growing their own organoids, but they haven’t been adopted on a wider scale.
What obstacles are still preventing this from happening?
Dr. Panamarova: From my perspective, I see several challenges that hinder the pharmaceutical industry’s widespread adoption of organoids. Firstly, organoid models originating from different patients and tissues inherently display complexity and variability, complicating efforts to standardise them. The diversity in cell composition, structure, and function presents challenges in achieving reproducibility and consistency, which are critical for drug screening applications requiring dependable results. However, I have seen a recent noticeable shift in perspective, with scientists increasingly embracing heterogeneity as a more representative portrayal of tissues or populations. Nevertheless, this shift necessitates significantly higher experimental throughput to yield meaningful insights compared to traditional 2D models.
The second major challenge revolves around scaling up organoid production to meet the demands of high-throughput screening in pharma settings. While potential solutions remain largely model-specific, there is a pressing need for efficient and cost-effective methods to upscale organoid production while maintaining model fidelity.
You’ve tested systems to automate and standardise 3D work. What have you liked, and what do you feel still needs work?
Dr. Panamarova: The automated platforms that we’ve implemented into our organoid pipelines offer multiple advantages to our team. Among them are the increased consistency and reproducibility of the experimental steps we’ve automated, as well as enhanced efficiency and reduction of ergonomic stress by minimising manual labour. Platforms with integrated analytics also facilitate a quantitative, data-driven approach to decision-making and troubleshooting, rather than relying solely on qualitative assessments. Naturally, automation can also enable higher throughput, allowing us to upscale processes more efficiently.
That said, some cell culture processes may not be easily adaptable to automation, particularly those requiring complex manual manipulations. Different organoid models may also require subtly different approaches in how they are handled, which requires automated platforms to be easily adaptable to those requirements, which is not always the case.
When you look to invest in a new technology, what are the high-level check boxes that you go through?
Dr. Panamarova: Our main goals are to ensure we have the latest and most fit-for-purpose platforms available.
We work closely with our Procurement colleagues and other user groups to ensure we make a technology-led decision, which provides the best overall value for the Institute.
This may be achieved via a tender and business case process, but we are flexible in approach depending on the different markets, our requirements, and the funding available.
Procurement and the user community generally look to build partnerships with our key technology suppliers, to collaborate on getting maximum performance from instruments and to feed into development pipelines; all of this helps us to stay ahead of the curve, scientifically.
If you could wave a magic wand and create the perfect 3D workflow, what would it look like?
Dr. Panamarova: In four words: standardised, automated, modular, and transparent.
Standardisation is paramount, and I would like to also emphasise the need for robust quality control measures in any workflow, not just an ideal one.
Automation is key for streamlining processes and reducing variability. Integrating robotics into the workflow for tasks such as liquid handling and imaging ensures high-throughput capabilities and minimises manual intervention.
A modular approach allows for the integration of the organoid workflow with multi-omics, imaging and computational platforms. This comprehensive assessment provides a holistic analysis of the organoid model and its underlying molecular mechanisms.
Since we are talking about a perfect-world scenario, I would like to also emphasise the importance of transparency. Open-access repositories and platforms for sharing protocols, data, and resources promote transparency and reproducibility across the scientific community.
What would be 1 example of standardisation in a 3D workflow that you would love to see?
Dr. Panamarova: Let’s say a QC check. That may be a different process starting from the derivation going back to your bank that you generate, and then to a downstream application.
QC can be many different things. It could be morphological, genomic, it could be just matching it back to their original cancer tissue and genomic transcriptomic data.
Just to make sure that before you run your massive drug screen with hundreds of thousands of molecules, your initial starting material is actually what you think it is. That it’s the right model.
From an automation standpoint, what would be an example of current manual steps you would love to see automated?
Dr. Panamarova: When it comes to a derivation pipeline, there are various steps that can be automated, but I have not seen a fully automated pipeline in action.
Many steps between tissue dissociation and banking of organoids that you generate must be done manually in our labs.
But some of the downstream processes, for example, whether you’re going to do drug screening, genomics readings, or spatial readings, could all be automated using the appropriate equipment.
There’s a lot of moving parts. Creating automation technologies for handling, sorting and dispensing. Optimising culturing. And there’s data analysis downstream. Everything is advancing simultaneously, but nothing’s established yet.
How do we get industry to align these moving parts and develop a consensus as opposed to working in silos?
Dr. Panamarova: Building on my previous answer, I think a big part of alignment has to be transparency to a degree. This involves a dedication to open dialogue and exchange of information among the members of the scientific community.
That extends far beyond individual pharma companies and individual labs or research institutes. It fosters an environment where researchers can share protocols and methodologies and it really strengthens the field. Within this framework, an institute like Sanger plays an important role. One of our core tenets is that we are championing open access to the data we generate.
We aim to share all the models we produce with the scientific community, disseminate the protocols, and the data associated with 3D workflows. We try to do as much of that as possible. Through the repositories, I think the scientific community can access published models, methods, and expand on existing knowledge.
I just wanted to give you a really good example from our colleagues at EMBL’s European Bioinformatics Institute (EMBL-EBI). They sit on the Wellcome Genome Campus with us, so I know their work really well.
A notable example of an open-source resource is called cancermodels.org. It was developed by EMBL-EBI in collaboration with the Jackson Laboratory. This platform simplifies access to published cancer organoid models from academic and commercial providers. It utilises a standardised approach to all the data that are published and associated with it.
Because if you are a wet lab scientist and you want to select a tumour model that has a particular phenotype, you need to go through the publication, download all of the associated data, and compare it with some other model. Usually, it requires a huge time investment and computational skills which not everyone has.
And if you gatekeep it at that level, the field will move at a slower pace than it otherwise could.
So for people who are working with tumour models, I recommend going to that platform because they do their job really well and it’s a great example of an open-source resource.
What are some of the exciting new technologies in the 3D space that have caught your eye?
Dr. Panamarova: Microfluidic chips really caught my eye recently. I think they have a massive potential to advance complex organic culture techniques.
By leveraging microfluidics, I think organoids can be cultured in an environment that more closely resembles in-vivo conditions than your standard Matrigel dome culture.
That means including something that simulates the blood flow, gradients of nutrients and oxygen, and signaling molecules.
That said, this isn’t something that we’ve been actively looking into. But from the conferences and meetings that I attend, I certainly keep my eye on that territory.
The hope is that these new complex in-vitro models can completely replace animal models. There’s people who think that it’s possible, and there’s people that think we will only be able to reduce animal testing, not replace it. Where do you land?
Dr. Panamarova: I’ve definitely landed in a camp of reducing. I hope reducing significantly.
I don’t believe that 3D models will completely replace 2D or animal models in the future. If we think about the ideal world scenario where 3D models offer the ability to accurately simulate multiple organs and tissues simultaneously, you still can’t do them all.
There is no substitute for studying effects on whole organisms in a preclinical setting which can be impactful and significant from a toxicological standpoint.
However, I do see the FDA Modernisation Act that removed the mandate for animal testing as an important step towards reducing the reliance on animal models in drug development.
Looking 5-10 years ahead, what possibilities excite you about 3D culture? What do you see as the big upcoming opportunities for disruption?
Dr. Panamarova: I think the biggest technological disruption that is really needed in the field is going to come in the space of making organoid culture and running the assays efficient and cost effective.
Organoid culture and production are still very costly. You can see that usually organoid workflows are either in very well-funded research organisations, or in big pharma. Small pharma can’t afford it. They usually outsource to contract research organisations (CROs).
If there was a technology that could scale up organoids to be cost efficient, that would be really disruptive.
How do you foresee the trickledown effect of the increase in access to these models?
Dr. Panamarova: I see more companies being able to perform such experiments, which means potentially more drugs coming to the market.
If these models and new technologies can help pharma companies develop drugs more efficiently, in theory, they save a lot of money. And in theory, that would mean that the drugs themselves should then be made more affordable for everybody. What’s your view on that?
Dr. Panamarova: You very well know the statistic of how 99% of drugs fail.
Where exactly is the costliest mistake being made? Very likely it is preclinical development because a lot of assumptions are based on particular 2D cell lines and extrapolated onto a population that contains a variety of cells and genetic mutations.
I hope that there’ll be a shift in a perspective where, even though you need to invest more into a screen with 3D models, eventually it will pay off because there wouldn’t be so many failures when it gets to clinical stage.
As someone who’s at the forefront of the field, how do you stay up to date on the recent developments in the 3D culture space?
Dr. Panamarova: I’ve tried to use Google Scholar notifications to search for specific keywords like ‘organoids’ and ‘3D culture’, but I had to switch that off because the sheer volume of information was overwhelming.
So instead, I found that signing up for relevant webinars and newsletters and attending conferences is the best.
Are there any specific people or research groups that you look to as fellow pioneers in the space?
Dr. Panamarova: I really like the work that is done at the Swiss Federal Institute of Technology in Lausanne (EPFL). It’s quite new, but still very impressive work coming out of there.
I like it because, like Sanger, they not only publish very interesting work, but also put significant emphasis on developing technology behind organoid culture and screening. I always keep a lookout for new ideas that I can bring back.
Are there any conferences that you would recommend that you’ve particularly enjoyed that have had a central focus on in-vitro 3D biology?
Dr. Panamarova: We had a conference back in February at the Wellcome Genome Campus called World Organoid Day, which was really good. And then there was an organoid modelling conference in London in March that I went to that was more industry-centered.
There is another organoid conference that’s going to be here at the Wellcome Genome Campus in September and it’s run by Wellcome Connecting Science.
Any final thoughts from you before we wrap up that you’d like to share?
Dr. Panamarova: I just wanted to thank you for asking me to contribute my perspective.
It’s been wonderful to be involved in the discussion and I’m looking forward to more chances to collaborate and share ideas.
Want to connect with Dr. Panamarova? You can find her here:
LinkedIn: Maryna Panamarova
mp35@sanger.ac.uk
