Improving Results in Forensic Testing
Others | 2019 | BiotageInstrumentation
Modern forensic toxicology faces an ever-growing array of novel psychoactive substances and opioid derivatives, requiring analytical methods with high sensitivity, broad compound coverage, and efficient workflows. Reliable sample preparation and detection protocols are critical for accurate identification and quantitation of drugs in biological matrices, directly impacting criminal investigations, public health responses, and legal outcomes.
The Boston University School of Medicine team, led by Professor Sabra Botch-Jones and in collaboration with Research Triangle Institute under NIJ funding, aims to:
Sample preparation methods were systematically validated for recovery, matrix cleanliness, and limits of detection across major drug classes: synthetic cannabinoids, benzodiazepines, barbiturates, opioids, stimulants, cannabinoids and others. Key steps included optimization of extraction parameters and evaluation at various time points and temperatures. Instrumental analysis employed high-performance liquid chromatography coupled to tandem mass spectrometry (HPLC-MS/MS) with triple quadrupole systems, enabling targeted quantitation of dozens of analytes.
Preliminary results indicate that supported liquid extraction and phospholipid depletion methods significantly reduce matrix interferences while achieving comparable or improved recoveries relative to traditional LLE and SPE. Stability studies showed that certain synthetic cannabinoids degrade rapidly at room temperature, underscoring the benefit of controlled storage and preservatives. Head-to-head comparisons with the RTI dataset remain ongoing, given the volume of validation data.
Automation of multi-well plate sample preparation is poised to further increase throughput and consistency. Expanding targeted panels to include emerging designer drugs and metabolites will address evolving forensic needs. Integration of ultra-high-resolution MS techniques may complement current workflows for non-targeted screening.
The collaborative NIJ-funded projects at Boston University demonstrate that modern sample preparation techniques, when paired with sensitive LC-MS/MS detection, can effectively meet the demands of contemporary forensic toxicology. Continued method validation, automation adoption, and student training will drive improvements in casework efficiency and reliability.
“Improving Results in Forensic Testing,” Biotage white paper, 2019.
Sample Preparation, Consumables
IndustriesForensics
ManufacturerBiotage
Summary
Significance of the Topic
Modern forensic toxicology faces an ever-growing array of novel psychoactive substances and opioid derivatives, requiring analytical methods with high sensitivity, broad compound coverage, and efficient workflows. Reliable sample preparation and detection protocols are critical for accurate identification and quantitation of drugs in biological matrices, directly impacting criminal investigations, public health responses, and legal outcomes.
Objectives and Study Overview
The Boston University School of Medicine team, led by Professor Sabra Botch-Jones and in collaboration with Research Triangle Institute under NIJ funding, aims to:
- Assess the stability of synthetic cannabinoids in human blood and urine under different storage conditions and with preservatives.
- Compare multiple sample preparation techniques—liquid–liquid extraction (LLE), solid-phase extraction (SPE), supported liquid extraction (SLE) and phospholipid depletion—for a wide panel of common forensic drugs.
Methodology and Instrumentation
Sample preparation methods were systematically validated for recovery, matrix cleanliness, and limits of detection across major drug classes: synthetic cannabinoids, benzodiazepines, barbiturates, opioids, stimulants, cannabinoids and others. Key steps included optimization of extraction parameters and evaluation at various time points and temperatures. Instrumental analysis employed high-performance liquid chromatography coupled to tandem mass spectrometry (HPLC-MS/MS) with triple quadrupole systems, enabling targeted quantitation of dozens of analytes.
Used Instrumentation
- Biotage ISOLUTE SLE+ supported liquid extraction columns (1 mL)
- LC-MS/MS with triple quadrupole detectors
- Automated evaporation and sample handling platforms (under evaluation)
Key Findings and Discussion
Preliminary results indicate that supported liquid extraction and phospholipid depletion methods significantly reduce matrix interferences while achieving comparable or improved recoveries relative to traditional LLE and SPE. Stability studies showed that certain synthetic cannabinoids degrade rapidly at room temperature, underscoring the benefit of controlled storage and preservatives. Head-to-head comparisons with the RTI dataset remain ongoing, given the volume of validation data.
Benefits and Practical Applications
- Broader compound coverage with a single preparation workflow streamlines toxicology labs’ throughput.
- Enhanced sensitivity and cleaner extracts reduce instrument downtime and reanalysis rates.
- Validated stability data inform sample storage policies in forensic laboratories.
- Training and involvement of graduate students ensure future workforce readiness.
Future Trends and Potential Applications
Automation of multi-well plate sample preparation is poised to further increase throughput and consistency. Expanding targeted panels to include emerging designer drugs and metabolites will address evolving forensic needs. Integration of ultra-high-resolution MS techniques may complement current workflows for non-targeted screening.
Conclusion
The collaborative NIJ-funded projects at Boston University demonstrate that modern sample preparation techniques, when paired with sensitive LC-MS/MS detection, can effectively meet the demands of contemporary forensic toxicology. Continued method validation, automation adoption, and student training will drive improvements in casework efficiency and reliability.
Reference
“Improving Results in Forensic Testing,” Biotage white paper, 2019.
Content was automatically generated from an orignal PDF document using AI and may contain inaccuracies.
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