From 219587271cf4d7028b0ceaa410a349df1db0a3ba Mon Sep 17 00:00:00 2001 From: Lucas Attia <43359170+lucasattia@users.noreply.github.com> Date: Tue, 3 Sep 2024 22:24:29 -0400 Subject: [PATCH] Update 6_project.md --- _projects/6_project.md | 12 ++++++++++-- 1 file changed, 10 insertions(+), 2 deletions(-) diff --git a/_projects/6_project.md b/_projects/6_project.md index 4b319f1..8d84903 100644 --- a/_projects/6_project.md +++ b/_projects/6_project.md @@ -13,6 +13,14 @@ This paper was the second in my PhD, and was a really exciting foray into using {% include figure.html path="assets/img/crystallinity.png" title="Crystallinty" class="img-fluid rounded z-depth-1 mx-auto d-block" %} -Crystallinity is crucial to drug formulation because it impacts how quickly a drug dissolves, which directly affects its bioavailability—the extent and rate at which the active drug is absorbed and becomes available at the site of action. So this lack of control is quite problematic in terms of applying our technology to formulating a variety of drugs into nanoparticles. Since we were looking at molecular-scale interactions, I turned to molecular dynamics simulations to understand what interactions governed this behavior. In this study, I focused on the tug-of-war between surfactants and polymers on the nanocrystal surface. This competition isn’t just a minor detail; it’s a key player in determining whether the drug remains in a crystalline form or transitions to an amorphous state, which dissolves faster and is often more effective. +Crystallinity is crucial to drug formulation because it impacts how quickly a drug dissolves, which directly affects its bioavailability—the extent to which the active drug is absorbed and becomes available in the body. So, the lack of control we observed experimentally posed a challenge that we wanted to understand and ultimately mitigate. Since we were looking at molecular-scale interactions, I turned to molecular dynamics simulations (using GROMACS) to understand what interactions governed this behavior. We modeled our system by building a nanocrystal surface of our drug, then treating that surface with different ratios of excipients. + +{% include figure.html path="assets/img/simulate.png" title="simulation" class="img-fluid rounded z-depth-1 mx-auto d-block" %} + +We looked at how the structure of the nanocrystal responded to these different treatments to understand the molecular-level driver of crystallinity in these nanoparticles. One of my favorite parts of this project is the crystallinity metric we defined to quantify the degree of crystallinity in the simulation. This was a challenging task, and no one has really established a good way to do this. We decided to base the metric off of the [RMSD](https://www.compchems.com/what-is-the-rmsd-and-how-to-compute-it-with-gromacs/)- which basically describes the amount of deviation of the atoms in the nanoparticle from their original lattice positions. We time-average the RMSD (since it can vary quite rapidly during the simulation), and normalize the value for any given simulation against the minimum deviation (RMSD for a simulation with no excipients), and the maximum deviation (the spacing between molecules in the lattice). This is summarized in the equation below. +\[ +\Gamma_{\text{effective}}= \frac{\frac{a}{2} - \langle \text{RMSD} \rangle}{\frac{a}{2} - \langle \text{RMSD}_{0} \rangle} +\] + +We discovered that two phenomena drive the crystallinity result of the surface. First, we find that the surfactant and polymer excipients we use experimentally compete at the interface, since both are surface active. However, since the surfactant is more surface active, it can outcompete the polymer, even at low concentrations, and 'protect' the surface from de-stabilizing polymer interactions. Additionally, the surfactant and polymer can themselves complex (a [well-studied phenomena in soft materials](https://pubs.acs.org/doi/pdf/10.1021/la00022a026?casa_token=kONkmMNElfcAAAAA:Yj3PE_TvPQXbxuhaA8STo8VxnfCAplcXX3S5bkmY6juMhgh7LOix7kS9x4aWR7PNMEDSEpahSETJLg)), which de-localizes the polymer from the drug surface, and prevents it from disrupting the crystal structure and amorphizing the surface. -The takeaway from my research is that by carefully tuning these surfactant-polymer interactions, we can create drug formulations with controlled crystallinity, leading to more precise and potentially more effective treatments. It’s a small but significant step forward in the world of drug delivery, and I’m excited about the potential applications this could have in developing better medications.