According to the American Cancer Society, an estimated 618,120 people in the U.S. were projected to have died from cancer in 2025, making it the second-leading cause of death in the country after heart disease and the leading cause for people younger than 85.
While some types of cancer are curable, particularly when detected early, there is still no universal cure for the disease. Not just because cancer is biologically complex, but because many promising drugs cannot be delivered to tumors in high enough concentrations to work.
“We’ve passed over a lot of really excellent drugs,” says Richard D’Arcy, an assistant professor of chemical engineering in the School for Engineering of Matter, Transport and Energy, part of the Ira A. Fulton Schools of Engineering at Arizona State University.
D’Arcy is developing an innovation that could one day significantly increase survival rates for diseases like cancer. He recently received the National Science Foundation Faculty Early Career Development Program (CAREER) Award, one of the most prestigious honors for early-career faculty. The five-year award supports his project, “Decoding Polymer-Drug Interactions with AI for Rational Carrier Design,” which aims to unlock a new way for scientists to design new drugs and increase the efficacy of existing ones.
The drug dilemma
For a cancer drug to work effectively, two things must be true: it must reach the tumor in high enough concentrations and limit exposure to healthy organs.
Many conventional cancer drugs are systemic, meaning they circulate widely through the bloodstream.
Like common over-the-counter pain relievers such as Tylenol, these drugs distribute throughout the body. However, that widespread circulation can reduce their effectiveness against tumors because fewer molecules get absorbed by the cancerous cells. At the same time, the drugs’ molecules that accumulate in healthy tissue can cause serious side effects, including damage to the heart.
This challenge is compounded by the fact that around 90% of new drug discoveries in development pipelines are poorly water-soluble, making it difficult to administer effectively without specialized interventions.
Enter nanomedicine.
Using nanotechnology, scientists package drugs into polymer-based nanoparticles that help deliver them to tumors while reducing exposure to healthy organs. By encapsulating these otherwise overlooked hydrophobic compounds, nanomedicine can improve solubility, enable targeted delivery and increase bioavailability, rescuing promising candidates that might otherwise be discarded.
D’Arcy says that despite major advances in nanomedicine, many promising drugs either still cannot be loaded into existing nanoparticles or achieve low loading levels.
“Unfortunately, if a drug doesn’t load, then scientists just move on,” says d’Arcy.
In other words, drugs that show promise in the lab may never reach clinical trials because scientists lack reliable ways to package and deliver them inside the body. That limitation slows the development of new cancer therapies and narrows the treatment options available to patients.
Funded by a CAREER Award, d’Arcy is embarking on a five-year effort to tackle this research bottleneck.
Solving nanomedicine with AI
“My goal with this project is to make sure that we can load all drugs in the future,” says d’Arcy. “It’s quite a grand idea, and there’s always some risk involved, but I think it’s an area where I can have the biggest impact.”
Working with Christopher Muhich, d’Arcy plans to develop a predictive model that identifies which polymer nanoparticles are best suited to load specific drugs. Muhich, an associate professor of chemical engineering in the Fulton Schools, specializes in machine learning and density functional theory, or DFT, a quantum-level computational method used to analyze molecular interactions.
The two researchers have been collaborating for the past few years and recently submitted work for publication on using machine learning to identify the key polymer features that influence drug loading.
With CAREER Award funding, d’Arcy plans to build on his understanding of nanoparticles to develop a predictive machine learning model that can predict optimal nanoparticle carriers for thousands of drug compounds.
These carriers are formed from polymers, long spaghetti-like chains, that self-assemble into nanoparticle structures. The outer layer is hydrophilic, meaning it interacts well with water, while the inner core is hydrophobic and holds the drugs. The hydrophilic exterior protects the particles from the body’s immune system as they circulate through the bloodstream, giving them time to preferentially accumulate in tumors.
D’Arcy says that a limited understanding of the molecular forces governing drug-polymer interactions remains a major barrier to efficiently loading many compounds.
To address that challenge, he and Muhich will train machine learning models using data on how existing nanoparticles interact with drugs that load successfully, allowing the system to predict effective carriers for many more compounds.
He won’t pursue that goal alone.
Opening research doors to students
Beyond collaborating with Muhich, d’Arcy has also enlisted the help of Fatemeh Kashani Asadi Jafari, a biological design graduate student who is supporting the project.
“She’s a superstar, for sure,” says d’Arcy. “She came in with a background in machine learning and drug formulation, and she’s been learning a lot of polymer synthesis these last few months and is picking it up really well.”
D’Arcy says receiving the CAREER Award came as a surprise given the number of amazing researchers competing for the same funding.
“I’ve put a lot of time and effort into the proposal, and getting the award is a great sign for the potential impact of this research,” he says. “In five years, technology from this project could help usher many promising new drug candidates into the clinical development pipeline that might otherwise have been passed over.”
Anthony Waas, a professor and director of the School for Engineering of Matter, Transport and Energy, commends d’Arcy for his unwavering efforts to advance nanomedicine.
“This is very satisfying to see,” says Waas. “Through this project, Richard could break new ground in fundamentally altering the nature of nanoparticles’ use in drug development.”
