Build a better database to detect designer drugs

How do you identify something for which no one has a test? Drugs of designers reproduce the effects of known illicit drugs but escape the police. Variations in chemical structure that help these compounds to avoid detection also make them unpredictable in the body – a quality that poses serious health consequences.

Now, a research team has used IT modeling to create a chemical structure database provided for improving the detection of designer medicines.

Jason Liang, a senior upwards of the science, mathematics and computer science magnet program at Montgomery Blair secondary school, presented the results of the team at the autumn meeting of the American Chemical Society (ACS Fall 2025), held from August 17 to 21.

“This library of metabolic signatures generated by calculation and mass spectra, which we call the database of drug metabolites (DAMD), could lead to more in -depth detection of new psychoactive substances and to more precise monitoring of the consumption of drugs of designers,” explains Liang.

An illegal medication that can be used to unhappy is generally identified by its chemical “digital imprint” called mass spectrum. This digital imprint is a reason created by the form, weight and composition of the drug molecule.

When a person’s urine is detected for drugs, a technician uses a technician called mass spectrometry to acquire and compare the spectra of sample molecules to spectra catalogs for known drugs and their metabolites (small molecules created when the body breaks down a drug). However, new psychoactive substances and their metabolites generally do not have correspondence in existing databases.

“It’s a bit of a chicken and egg problem,” said Liang mentor, Tytus Mak, statistician and scientist of data from the Mass Spectrometry Center of the National Institute of Standards and Technology (NIST).

“How do you know what this new drug is if you have never measured it, and how do you measure it if you don’t know what you are looking for? Could a calculation prediction methodology help us find a solution?”

The idea of developing the DAMD began with Mak and Hani Habra, a former post-doctorator in the NIST and a current bioinformatian at Michigan State University. They thought that IT modeling could follow the apparently endless iterations of unknown synthetic compounds in charge of health care systems and difficult medication monitoring initiatives. Then, in the summer of 2024, Mak and Habra approached Liang to work with them.

“The construction of a planned mass spectral library requires solid programming skills and a solid base in chemistry, which align with my history,” explains Liang.

“After learning the devastating number of overdose deaths, including cases within the local community, I was impatient to work on this project which could potentially help people.”

As a starting point, the researchers used the mass spectral database maintained by the scientific working group produced by the US Drug Enfancement Administration for the analysis of the seized drugs (SWGDRUG). This database provides reliable mass spectra for the identification of more than 2,000 drugs confiscated by the police.

Then, using calculation approaches, Habra, Liang and Mak predicted nearly 20,000 chemical structures and corresponding mass spectral fingerprints for possible metabolites of SWGDRUG substances and their metabolites.

The team currently validates its mass spectra provided by matching them with real spectra from data of human urine analysis. These data sets are spectra catalogs of all detectable substances found in samples of human urine.

Finding a correspondence, or something close to correspondence, in these data sets “tells us if the chemical structures and the spectra that our algorithms produce are plausible,” explains Habra. Subsequently, the team will compare the data already collected and real to DAMD, showing proof of concept for forensic toxicology.

DAMD could one day be an additional additional supplement to current drug -mass spectral databases, which facilitates the detection and identification of evidence of drug use in human urine samples. One of its main applications is to develop a system to help people get the medical interventions they need.

“Someone could have ingested a substance which, without their knowledge, was cut with a fentanyl derivative,” explains Mak. “Using the DAMD, a doctor could see metabolites from the toxicological relationship of the person who are solid candidates for a fentanyl type medication and light up their treatment plan.”