I have spent much of my life translating. Growing up between Mandarin and English taught me that the same idea can take different forms depending on who is listening. Later, as I moved through different scientific environments, from undergraduate research in Vancouver, to graduate training in Boston, to my Ph.D. at Johns Hopkins, I realized that every research community has its own language, assumptions and ways of asking questions.
I assumed that instinct for translation would stay outside the laboratory. I was wrong.
During a meeting with one of our pharmaceutical collaborators, I was presenting a nanoparticle formulation my lab had spent months optimizing. We had generated exciting biological data, and I was prepared to discuss the next experiments. Instead, someone asked a question I had not considered deeply enough: If this works, can it be manufactured the same way every time, by someone who has never stepped into our laboratory?
I did not have a good answer.
It was humbling to realize that the formulation I was most proud of might never become a therapy, not because the biology was wrong, but because reproducibility, scalability and manufacturing were scientific challenges I had not yet learned to fully appreciate.
That conversation changed how I approach research. My work focuses on engineering polymer nanoparticles to deliver messenger RNA (mRNA) to specific immune cells, with the goal of reprogramming immune responses: restoring immune tolerance in autoimmune diseases such as type 1 diabetes or enhancing immunity against infections and cancer. Every formulation is still an opportunity to improve biological performance, but I now ask a second set of questions alongside the traditional scientific ones. Can this approach be scaled? Will it perform consistently from batch to batch? Does it address a problem that matters beyond my own field?
These questions rarely appear in a figure panel. Yet they often determine whether that figure will ever matter outside the laboratory.
Working with industry collaborators and becoming involved in biotechnology entrepreneurship has shown me that transforming a discovery into a medicine requires many communities working together. Researchers, engineers, clinicians, manufacturers, regulators and investors each view innovation through a different lens. Moving science forward requires more than generating data. It requires translating that data so that each group can understand its significance and contribute to the next step.
That realization changed how I think about communication. Writing and presenting are not tasks that happen after the “real” science is complete; they are part of the scientific process itself. Every conversation, manuscript and presentation carries an idea one step further from the bench and closer to the people who can test it, develop it and ultimately deliver it to patients.
Biomedical research is often celebrated for its breakthroughs. But behind every breakthrough are countless acts of translation, between languages, disciplines, institutions and people. These connections are what transform discoveries into medicines, and they are what make the future of biomedical science so promising.
Related Content
- More Than Glue: How Non-Neuronal Cells Contribute to Thinking
- Playing with Fire: Artificial Intelligence at the Bedside
Want to read more from the Johns Hopkins School of Medicine? Subscribe to the Biomedical Odyssey blog and receive new posts directly in your inbox.