Jason Liang, a rising senior in the Science, Mathematics and Computer Science Magnet Program at Montgomery Blair High School, has been in the news lately. He brought the amazing research, which he shared at this year’s American Chemical Society fall meeting. Liang presented the outcomes of his crowd-sourced effort, the Drugs of Abuse Metabolite Database (DAMD), at the event. It was held in Pittsburgh, PA from August 17-21, 2025.
DAMD aims to create a reliable repository of mass spectra for more than 2,000 drugs that have been confiscated by law enforcement agencies. This new, innovative database makes it easier for medical professionals to quickly identify those harmful substances. It allows them to act quickly for people who might have inadvertently swallowed lethal drugs.
The Importance of DAMD
DAMD is singularly focused on building an equitable system that brings game-changing medical interventions to all those who need them. This approach focuses on those most affected by substance use. Liang highlighted the eye-opening impact he hopes this project will have. He mentioned that it might someday serve as a freely accessible resource to supplement existing illicit drug mass-spectral databases.
“After learning about the devastating number of overdose deaths, including cases within the local community, I was eager to work on this project that could potentially help people,” – Jason Liang.
Liang collaborated closely with his mentor, Tytus Mak, a statistician and data scientist at the National Institute of Standards and Technology (NIST). Mak served an important role in shepherding Liang through the day-to-day intricacies of such a large, ambitious project. He illustrated some of the pitfalls they experienced with DAMD.
“It’s a bit of a chicken and egg problem,” – Tytus Mak.
Mak elaborated on this issue, stating that understanding new drugs requires prior measurements, which are often impossible without knowing what substances to look for.
“How do you know what this new drug is if you’ve never measured it, and how do you measure it if you don’t know what you’re looking for? Could using a computational prediction methodology help us find a solution?” – Tytus Mak.
Collaborative Efforts
Joining Liang and Mak on this visioning project was Hani Habra. This past summer, 2024 – FUSE cohort and artist faculty member – Mak and Habra joined forces. Asking Liang to join them, they paired Liang’s expertise with their passions to launch this crucial effort. Collectively, they worked to apply some of the most cutting edge, advanced computational methods. Alongside this, they modeled almost 20,000 chemical structures and corresponding mass-spectral fingerprints for possible metabolites identified within the SWGDRUG database.
Hani Habra shared the importance of their algorithms in confirming their predictions.
“It tells us if the chemical structures and spectra our algorithms are producing are plausible,” – Hani Habra.
The DAMD project has become an invaluable tool for drug identification. Additionally, it seeks to develop a better understanding of the latest substances with psychoactive effects that are emerging on the market. It serves as a rich resource of computationally derived metabolic fingerprints and mass spectra. The ultimate goal is to improve detection and monitoring of designer drugs use to prevent abuse and save lives.
A Focus on Safety
The real-world implications of DAMD extend far past just recognition. They affect public safety and health. We know new designer drugs are already flooding into communities every day. Given their potential uses in law enforcement and healthcare, it is imperative that all actors involved understand their metabolic signatures.
In her comments, Mak pointed to a troubling recent example that illustrates the critical need for this research.
“Someone could have ingested a substance that, unbeknownst to them, was cut with a fentanyl derivative,” – Tytus Mak.
DAMD is well-positioned to offer indispensable assistance in our ongoing battle against the opioid crisis. Beyond its scope on fentanyl, it will address many other pressing drug issues. Liang knew he could make a big impact on this project and even said so with swagger. He emphasized his exceptional R programming abilities and firm footing in chemistry as notable strengths.
“Building a predicted mass-spectral library requires strong programming skills and a solid foundation in chemistry—both of which align well with my background,” – Jason Liang.
Jason Liang as he prepares for his senior year of high school. His far-reaching work on DAMD illustrates both his academic prowess and his commitment to affecting real change in the field of public health. Liang, Mak, and Habra have broader ambitions to push scientific knowledge. Their joint initiatives confront urgent social issues with creativity and determination.