I can't help but reflect on some words from a session chair the other day at this year's Biophysical Society Meeting. I certainly don't remember it word-for-word, but the flavor was something akin to, "In this era of machine learning and artificial intelligence, some people might say we have no need for theory anymore. But the truth is, right now we need it more than ever."

This immediately strikes me as true, but of course I would say that since my main focuses are theoretical and computational at the moment. Of course, I would never come close to claiming that the recent advances in AI are trivial or unnecessary in the field of biophysics, but current versions of AI do not come close to replacing what we get from good theoretical biophysics.

Unraveling that thought fully would take a separate long and nuanced blog post... rather, I'll focus on some of the success I've observed from integrative experimental-computational work at this year's meeting, to help explain why I still see so much value in theoretical work. In the session I spoke in (Cell Mechanics, Mechanosensing, and Motility), you might expect the vast majority of work to solely focus on experiments, but I was encouraged to see that wasn't the case. In fact, from my work modeling the mechanosensitivity of cell circadian clocks to simulations of bleb-aided motility by T-cells to a model of actin filaments driving the formation of helical-shaped membrane protrusions, the session was full of theoretical work. Importantly, these models were all leveraged directly against experimental data, demonstrating the constructive feedback between experimental and theoretical work we hope to achieve in physics.

And this feedback doesn't go one way. A good biophysical model makes testable predictions, ideally ones with some implications for human health and disease. For instance, the model presented in the final talk of our session by Dr. Roberto Alonso-Matilla predicts the conditions for optimal bleb-mediated T cell motility, such as that pictured in the figure above from Tabdanov et al 2021.. In particular, he showed that an intermediate amount of contractility acting in the cell cortex should enhance migration speeds. This can be tested in future experiments and may help bioengineers better understand how T cells can move so quickly through tissues in the human body.

This dynamic interface between biophysical experiments and models certainly excites me each year at the BPS meeting. Furthermore, just attending meetings like this offers unique opportunities for those of us working on theory to connect with experimentalists and foster mutual progress.

I'll close with some further inspiration I heard from a speaker earlier in the conference. "Biophysics has done an excellent job making advances in experimental techniques over the past couple decades," she stated. "But we've often failed to apply these new tools to contribute to actual medical innovation." I believe that between these new experimental tools and novel theoretical work, we can improve on this in future decades as biophysicists. It's certainly something I'll keep in mind moving forward.