Aubin Ramon
speaker
346 appearances
1 recordings
1 series
first heard Jul 2026
last heard 6 Jul
Aubin Ramon’s voice in public audio — every appearance, attributed to the second.
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Hi Tristan.
Thank you so much for having me.
Yeah, sure.
So I'm um postdoctoral research associate in the Petersomani lab.
uh which is now based at Imperio College London.
We just moved there a few months ago, back in September uh 2025, yeah, uh from Cambridge, where um Pietro uh Somani started his lab.
So I I did my PhD with him and it's during my PhD that I focus a lot on antibody and more specifically nanobody um developability.
So prediction, assessment, optimization,
Um all of these things.
Um yeah, now I'm working on uh multi-objective pipeline optimization, merging all my PhD work together during my postloc.
Yeah, so the problem of small data set for training is particularly true for protein engineering, um, because we have this biophysical characterization issue where um we need for most of this biophysical property, we need uh a good amount of purified protein.
And so you have this expression purification bottleneck to get enough data.
Um and we're lucky with the most stability in my case because you don't need that big amount of uh purifying nanobody.
Basically like how it works is that you just put um your nanobody into a buffer and then you load that uh into a capillary, so you just need a few microliters, and you put this into a a spectrophotometer.
Um that is gonna record the fluorescence while heating the laser your capillary.
So you're gonna measure the intrinsic fluorescence of your proteins, that's gonna change upon heating and upon upon unfolding.
Um and so you don't need much of a protein to do so.
So it's relatively like middle throughput to get data.
But then if you want something else like solubility and if you want the real thermodynamic solubility, you will need a lot of proteins uh to measure the crash out and uh and solution.
So yeah, so um this is the issue for protein engineering.
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