Insider Insights with Aaron Risinger

Aaron’s surname is of German origin, derived from the Middle High German word "rïz," meaning to rise or ascend.

Fitting, as in this post from our Insider Insights series—where experts share both quick reactions and deep reflections on what it’ll take to prepare life scientists for what’s next—Aaron talks through today’s automated technologies that are helping customers rise above challenges when working with complex biology.

Then, he takes us ever higher to imagine a personalized-medicine future made possible by the innovations we’re advancing now.

Inquiring minds want to know:

How have you seen the development of automating the growth of human-relevant models impact or improve the everyday lives of our customers?

Quick reaction: Automating some of these workflows frees scientific minds out from under the hood, allowing them to really think deeply about the design of their next experiments. This is hugely impactful for our general scientific community, enhancing their own productivity and innovation.

Deep reflection: We’re witnessing a paradigm shift in the use of disease models. Historically, reliance on traditional immortalized cell lines has not yielded the desired results, prompting a transition toward more human-relevant models. Groundbreaking discoveries, such as Dr. Shinya Yamanaka's Nobel Prize-winning work on iPSC adult stem cells and Dr. Hans Clevers' discovery of self-replicating human patient-derived organoids, have opened new avenues. However, producing this complex biology at scale has been challenging. The industrialization of complex biology— building on our expertise with traditional cell lines—is exciting. Automated tools now translate everyday lab cell culture techniques into an industrialized approach, providing complex biology with higher reproducibility while at the necessary scale for early drug screening. This allows for hit selection and lead candidate identification based on human-relevant models, increasing chances of success in clinical trials.

Additionally, automation has significantly impacted our scientists' lives. The demanding nature of cell culture techniques for complex human-relevant models often dictated scientists' schedules, putting a strain on them. By automating these workflows, we have given our cell culture scientists their weekends back, freeing them from the hood and allowing them to focus on designing their next experiments. This shift not only improves their work-life balance but also enhances the overall scientific community's productivity and innovation.

Why do you find this exciting?

Quick reaction: I personally find this exciting because we know that there is a need for change. The idea that these automated tools can now translate some of the cell culture techniques being done in everyday labs into an industrialized approach has the potential to provide complex biology with much higher reproducibility and at scale, making these human-relevant models accessible earlier in the drug discovery process.

Deep reflection: This need for change is staring us right in the face. We believe in the data and have seen the unacceptable rate of new drugs failing to make it through clinical trials alongside associated costs. The fact that there are still rare diseases that cannot be accessed due to a lack of appropriate model systems is a significant issue. The excitement is building with the potential that exists in these new human-relevant models, both in the iPSC world and the patient-derived organoid world, complemented by automating and industrializing the cell culture process through tools like the CellXpress.ai™ Automated Cell Culture System. I'm excited about the science and can't wait to see the discoveries that will come from this.

I'm also excited about the process of doing comparative studies based on the models we've relied on for years; studying them deeply, and finding out what's the same and—more importantly—what's different. Do those differences matter? Do they make an impact? I'm enamored with scientists like Dr. Lee Rubin at Harvard and others who are leading the charge in this field. They have had the foresight to identify the importance of this shift toward human-relevant models and have fought hard alongside Dr. Hans Clevers and Dr. Yamanaka to make these advancements a reality.

What trends or customer feedback have driven innovation in this area?

Quick reaction: We’ve adopted a tenant from our parent company, Danaher, that states, “Customers talk, we listen.” This principle has driven our innovation and helped us shift from focusing solely on endpoint analysis to addressing the comprehensive workflows required by our customers for drug discovery.

Deep reflection: At Molecular Devices, we've made a significant shift over the past 7-8 years, driven by feedback from key opinion leaders and super users of our instrumentation. These experts have asked for assistance in generating more complex 2D and 3D biology that enable their downstream discovery. This has taken us from being an excellent endpoint analysis company to focusing on enabling comprehensive workflows required to create biological materials, disease models, and various molecules for drug discovery. Our customers have played a part in our innovation efforts. These relationships enhance our ability to design tools that industrialize complex biological processes, making them reproducible and scalable.

For example, our customers need large volumes of biological material. This is especially important with the introduction of multi-omics—particularly spatial multi-omics—which requires significantly more biology. The challenge is to create models that are scalable and reproducible. In this paradigm, customers send portions of the material to various analysis centers—such as functional genomic centers and proteomic mass spectrometry centers—while still having enough material for phenotypic high-content screening. If the biological material is reproducible at scale, the data can be corroborated and analyzed for comprehensive insights.

To address challenges of producing complex human-relevant models at scale, we've developed tools like the CellXpress.ai™ Automated Cell Culture System—and its predecessor, the Organoid Innovation Center—which have opened new avenues by industrializing the process.

What common research challenges do customers face now, and how can automating the growth of human-relevant models open new opportunities?

Quick reaction: By providing platform technologies that help overcome key obstacles and industrialize processes, we can convert manual approaches into more routine ones through automation, democratizing access to highly reproducible human-relevant models.

Deep reflection: We’re embarking on an emerging scientific area of discovery, implementing human-relevant models at scale, reproducibly. Due to the fragmented nature of this new field and the rapid prototyping necessary for novel discovery, standardized approaches for the generation of complex disease models have yet to be established. We are attempting to complement classical immortalized cell lines with new biology and personalized medicine approaches, where specific demographic and disease-related tissues are sourced directly from patients. This approach holds great promise but creates new problems that need to be solved. Scientists may need to come together in consortia and form multidisciplinary committees to consolidate findings and approaches from multiple labs, creating consensus.

One way to achieve this is by providing platform technologies that help industrialize these processes, converting manual approaches into more routine ones through automation. As industry catches up with this emerging field, there will be opportunities to consolidate fragmented methods into a more unified approach, leading to higher reproducibility, greater access, and democratization of human-relevant models. This will form consensus throughout the scientific community on the best way to produce these models, creating a significant impact on drug discovery, drug screening, and understanding mechanisms of action.

In a world where automating the growth of human-relevant models reaches its full potential, what do you envision happens next?

Quick reaction: Imagine a world where your specific epigenetics, current disease state, and evolving disease state—as you undergo treatment—become accessible for real-time discovery and testing. This has immense potential to solve important human health crises that affect each and every one of us.

Deep reflection: I love these big-picture, magic wand-type questions because what I see, just out of reach, is the concept of personalized medicine truly becoming a reality. Imagine a world where your specific epigenetics, current disease state, and evolving disease state—as you undergo treatment—become accessible for real-time discovery and testing. Utilizing patient-derived organoids or adult stem cell iPSC models of your own tissue, as the disease changes in response to therapy—or in some cases does not respond—allows us to ask the critical question: What do we do next? The groundwork we are laying now by studying these human-relevant models will lead to advances that speed up the process, enabling us to tackle personalized medicine in a meaningful way.

Through the studies our customers are conducting on human-relevant models, both in patient-derived organoids and iPSC work, we are paving the way for significant advancements. These efforts will eventually allow us to produce and scale personalized tissue models quickly enough to provide timely answers. This has immense potential to solve some of the human health crises that affect each and every one of us. By accelerating the development and application of these models, we can truly revolutionize personalized medicine and improve outcomes for patients worldwide.

Inspired by what you've read? Learn more about automating cell culture here.

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