GEN-MKT-18-7897-A
Sep 11, 2018 | Blogs, Forensic | 0 comments
Imagine being blindfolded, sent into a large (dark) room filled with obstacles and challenged to find an item, but you don’t know what that item is, and you have never seen it before. Then you must do the same again the next day, but you are looking for a different item, and it will be in a different place. The phrase fumbling around in the dark comes to mind!
Well, this is what it often feels like for forensic toxicologists trying to keep up with the unpredictable minefield of designer drugs — novel psychoactive substances (NPS).
NPS are synthetic chemicals, whether legal or illegal, closely related to known psychoactive compounds but with slightly altered composition. Not only does this make them difficult to recognize in routine screening, the fact that they are continually evolving – to evade regulation and defy law enforcement efforts — leaves drug screening labs in the dark on what compounds to target.
As if things aren’t tough enough, labs often receive wide varieties of sample types, ranging from blood and urine to hair and oral fluids, with complex biological components and challenging matrices. But it doesn’t stop there, some of these drugs are so potent that users only take a tiny amount, so the drug concentration is very low.
Fumbling around in the dark? Definitely! So, let’s remove the blindfold and shed some light on the matter.
Traditionally drug tests employ a range of targeted methods, and LC-MS/MS is recognized as one of the most efficient and reliable techniques available. The challenge is that these methods can only analyze known substances, limiting drug detection to compounds found on lists of pre-characterized analytes. In other words, if it’s not on the list, it won’t be seen.
How can toxicologists tackle the challenge of never-before-seen drugs? They need a screening tool that can detect trace amounts of unusual components in complex biological samples, even without any prior knowledge of their structural identities. This is the equivalent to removing the blindfold, turning the lights on, putting the obstacles aside and placing the item on a pedestal.
When our researchers here at SCIEX set out to do something, they don’t stop until they get there. As the opioid epidemic becomes the center of the drug overdose crisis, our team sought to develop a non-targeted screening workflow to screen novel fentanyl and its analogs in forensic biological samples.
Fill out the form on the right to download the technical note and learn more.
Regulated laboratories are evolving faster than ever. New analytical modalities, higher sample throughput, increasing regulatory scrutiny, and leaner teams are reshaping how work gets done. At the same time, expectations for data integrity, standardization, and operational efficiency continue to increase complexity and/or scope. In this environment, LC-MS software is no longer simply an instrument control platform—it has become a critical part of a laboratory’s quality management system. The question is no longer whether your lab has changed, but whether your software has evolved to support the way regulated labs operate today, and if they are ready and able to meet the demands, they will face tomorrow.
Analyst software has long been a trusted foundation in regulated LC-MS laboratories—and for many, it still performs reliably today. But regulated environments are evolving faster than ever. As labs transition to Windows 11, strengthen cybersecurity policies, modernize IT infrastructure, and prepare for future compliance expectations, software decisions are no longer just about what works today—they’re about managing tomorrow’s risk. Analyst will not be supported on Windows 11. While some labs may continue operating in unsupported environments temporarily, the bigger question is: when that risk becomes reality, will your lab be reacting under pressure—or executing a planned mitigation strategy with confidence?
As regulatory scrutiny increases and detection requirements tighten, laboratories are facing a new question: How can TFA be measured reliably, sensitively, and at scale?
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