In the world of medicine, the journey from ancient practices to modern pharmaceuticals is both fascinating and complex. The latest episode of the Big Ideas Lab podcast delves into the evolution of drug discovery, and how cutting-edge computing technologies and industry partnerships are transforming the way we develop life-saving medications.
Historically, the quest for effective treatments took centuries-the roots of modern drug discovery can be traced back to natural remedies, and later, the creation of over-the-counter "wonder" drugs like Aspirin. Today, developing new medications is significantly faster due to advancements in technology, yet it can still take up to 15 years to bring a drug to market. In this episode, we hear from experts at Lawrence Livermore National Laboratory (LLNL), who are on a mission to streamline this arduous process. Listen on Apple and Spotify.
"What we want to do is to find a molecule that could actually go into a person and restore their system to its normal operation," says Jim Brase, LLNL's deputy associate director for Computing. "The central theme of what we're doing is the integration of computing and biology to enable better predictive models."
Through the combination of high-performance computing and tools like machine learning and AI, LLNL researchers are using these computer models to help accelerate the time-consuming stages of drug development: discovery and development, preclinical research, clinical trials, FDA review and approval, and post-market safety monitoring.
"We're exploring different kinds of algorithms for machine learning," says Felice Lightstone, who leads the Lab's Biochemical and Biophysical Systems group. "We're using high-performance computing to try to solve biology problems. We start from the basic science where we're looking at new capabilities and actually trying to use the computers to make these methods go faster."
A key bottleneck in the traditional drug discovery process is the discovery and development stage, which can take years. However, with the aid of HPC and advanced computational techniques, Lab researchers are optimistic about making strides in this area. In the realm of cancer, researchers are designing small molecules to target specific protein mutations, an approach that not only speeds up identification of viable drug candidates but also enhances their effectiveness.
Critical to this advancement are partnerships with companies like BridgeBio Oncology Therapeutics and institutions like the Frederick National Laboratory for Cancer Research, which are successfully leveraging their combined expertise in drug design, oncology and computing resources to address significant medical challenges.
The collaboration allows for rapid running of thousands of simulations, narrowing down options to select promising molecules for synthesis and allowing "the computational prowess of the [Department of Energy] labs to show that we can develop new methods and new technologies that will impact the industry," Lightstone explains.
This approach is already achieving promising results, from creating new cancer drugs for previously "undruggable" targets that are making their way to human trials to opening up new molecular designs never before considered. Researchers hope these advancements will soon lead to swifter access to effective treatments for various diseases.
"It's something like 750 FDA-approved drugs right now that are available on the market," explains LLNL informatics scientist Jonathan Allen. "I would love to be able to see our ability expand that pipeline of molecules and therapeutics that can get towards FDA approval much more efficiently and quickly and cheaply… I'm optimistic that we'll have a lot more therapeutic tools in the toolbox, so to speak, to treat various diseases in the next five to 10 years."
On this episode, join LLNL scientists as they highlight the extraordinary teamwork between chemists and computational scientists, discuss how this collaboration is revolutionizing the pharmaceutical landscape, and describe how the combination of traditional science, modern technology and strategic partnerships is not only addressing current health challenges but also paving the way for the future of medicine.
To listen, visit Apple or Spotify.
