In this episode of Speaking from the Heart, Prof. Pim Pijnappel from Erasmus MC discusses how advanced human skeletal muscle models can help researchers understand rare neuromuscular diseases and develop new therapeutic approaches.
The conversation explores how researchers are using induced pluripotent stem cells (iPSCs), gene editing, and 3D engineered muscle tissues to study diseases such as Pompe disease and muscular dystrophies. A central question is how these models can move beyond cellular and molecular measurements to provide reliable functional readouts of muscle contraction and drug response.
Pim also shares how his group helped develop Cuore, enabling more sensitive, real-time measurements of contractile force, and why advanced human models could improve drug testing, treatment delivery, and the translation of research into therapies.
Watch the conversation here:
Prof. Pim Pijnappel
Prof. Pim Pijnappel is Professor of Cell and Gene Therapy at Erasmus MC in Rotterdam, where he heads the Molecular Stem Cell Biology Group. His research focuses on developing new therapies for rare neuromuscular and metabolic diseases, combining stem cell biology, genetic engineering, and advanced human disease models.
After studying Medical Biology at Utrecht University and completing his PhD at the Hubrecht Institute, he held research positions at EMBL Heidelberg, TU Dresden, and Utrecht University. He has led the Molecular Stem Cell Biology Group at Erasmus MC since 2012 and has been Professor of Cell and Gene Therapy since 2023.
His group’s research includes gene and RNA therapies, muscle regeneration, and muscle-on-a-chip technology, with a particular focus on Pompe disease. By developing human 3D skeletal muscle models that can contract and respond to treatment, the group aims to better understand disease mechanisms and improve the testing of potential therapies.
How do you develop new treatments when so few are available?
For many rare muscle diseases, treatment options remain limited. Developing new therapies requires researchers to understand not only the underlying genetic and molecular defects, but also how these changes affect muscle function.
This is one of the main challenges driving Pim’s research.
His group focuses on Pompe disease, a genetic metabolic disorder caused by a deficiency in acid alpha-glucosidase that leads to glycogen accumulation. The team also collaborates on research involving Duchenne muscular dystrophy, limb-girdle muscular dystrophy, and facioscapulohumeral muscular dystrophy (FSHD).
Studying these conditions in the laboratory is not straightforward. Traditional models, including animal models, do not always predict how a disease or treatment will behave in human patients.
The challenge is therefore not simply to create another model, but to develop human systems that can provide more relevant information about muscle disease and treatment response.
What makes a muscle model truly functional?
A muscle model can contain the right cells, express the expected proteins, and reproduce aspects of disease biology. But does that tell researchers how well the muscle actually works?
For skeletal muscle, function ultimately comes down to its ability to generate force.
Pim’s group uses human iPSC-derived myogenic progenitor cells to develop skeletal muscle models. Through gene editing, researchers can introduce or correct disease-associated mutations, creating models that help isolate the effects of specific genetic changes.
Researchers can study these cells in conventional 2D cultures or develop them into 3D engineered muscle tissues.
While 2D cultures are valuable for rapid experiments and studying molecular targets, they become more limiting when the question turns to muscle function. Strong skeletal muscle cells contract, making it difficult to maintain them in conventional 2D cultures over longer periods.
3D engineered tissues provide a different approach. They let researchers grow muscle bundles between flexible supports, measure the forces they generate, and track their responses over time.
The difference is not simply one of dimensionality. It lets researchers investigate what the tissue actually does.
Why does moving from 2D to 3D matter for drug testing?
Not every stage of drug development requires the most complex model.
Early experiments may benefit from simpler 2D systems that let researchers quickly screen large numbers of potential treatments. But as promising candidates move further through development, more detailed questions begin to emerge.
Does the treatment improve muscle contraction? How does the tissue respond over several weeks? Does the drug change the force generated by the muscle, or the dynamics of contraction itself?
These are questions that become particularly relevant in functional 3D systems.
In the interview, Pim explains that engineered muscle tissues can mature over time and support longer experiments. This makes it possible to study treatment effects that shorter 2D assays may not capture.
Rather than replacing every existing method, the opportunity lies in using the right model at the right stage of development.
What can contractility measurements reveal beyond force alone?
Measuring muscle function involves more than determining how strongly a tissue contracts.
Contraction dynamics can also provide valuable information. For example, changes in the shape of a contraction curve may reveal how a treatment affects how muscle tissue generates force.
Pim’s group uses both internally developed 3D muscle systems and Cuore, which emerged from collaborative research involving Erasmus MC, Leiden, and Optics11 Life.
With Cuore, researchers can perform more sensitive, real-time contractile-force measurements using optical fiber sensing. The system also supports higher-throughput analysis and experiments involving electrical stimulation, including studies of muscle responses to exercise-like conditions and drug exposure.
This opens opportunities to study functional changes that are difficult to observe with conventional approaches.
The goal is to build a more complete picture of muscle behavior by linking biological observations to measurable physiological responses.
Could better human models help researchers identify treatment failures earlier?
One of the most interesting points in the conversation is the potential predictive value of advanced muscle models.
Pim describes work involving drugs where results from a 3D muscle system suggested problems that were also relevant to a treatment that later failed in clinical trials.
This raises an important question: could more representative functional models help researchers identify ineffective or unsuitable treatments before they progress too far through development?
No single model can reproduce the full complexity of the human body. However, adding functional human tissue measurements to drug testing could provide valuable evidence alongside molecular assays, animal studies, and other experimental approaches.
For researchers developing treatments for rare muscle diseases, improving early evaluation of drug responses could make a meaningful difference.
Why is drug delivery still such a major challenge?
Even when researchers identify a promising therapeutic approach, getting that treatment to the right tissue remains difficult.
As Pim explains, drug delivery is a major limitation in skeletal muscle therapy development.
A treatment may work under controlled laboratory conditions but fail to reach its intended target effectively in patients. Researchers must consider delivery barriers, long-term efficacy, and potential toxicity.
This is another area where 3D muscle models could contribute.
Unlike cells grown in flat culture, engineered tissues let researchers investigate how treatments interact with more complex tissue structures. They can study delivery barriers, functional responses, and longer-term effects in a human muscle model.
These questions matter across therapeutic approaches, from small molecules to RNA-based treatments, gene editing, and gene therapy.
What is next for human muscle models?
The field of advanced human models continues to develop, but important challenges remain.
Pim sees opportunities to increase the biological complexity of engineered tissues and connect different organ-on-a-chip systems. Such approaches could eventually let researchers study tissue interactions that cannot be studied with isolated models.
At the same time, wider adoption will depend on improving tissue maturation, throughput, automation, reproducibility, and standardization.
Regulatory acceptance will also be important if these models are to contribute more directly to drug development and clinical decision-making.
Pim does not suggest that advanced human models will immediately replace all animal experiments. Instead, he sees opportunities to substantially reduce their use while developing more reliable approaches to studying human disease.
Ultimately, the value of these technologies will be measured by whether they help researchers better understand disease and bring more effective treatments to patients.
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