Objectives and ambition
NARCOSIS aims at developing a fast, robust and reliable non-targeted multidisciplinary approach to harmonise investigations in DRDs and drug-related operations by means of an up-to-date and updateable diagnostic platform.
NARCOSIS will:
- use an innovative approach, a multisectoral, multiagency, and multidisciplinary approach.
- improve capacity (such as infrastructure, policies and procedures, knowledgeable and trained personnel).
- improve capability (ability to provide the outputs required by the Regulation) to detect, assess, report, and respond to drug-related events at all levels within a MS (local, intermediate, and national) and European level.
- overcome the limitations of information provided by a single laboratory by being part of a network of laboratories and by providing an added value to analytical information from laboratories by means of AI and data fusion from orthogonal sensors for effective responses to emerging drug threats.
NARCOSIS will provide a set of features for:
- Updated instrument databases: establishing a continuously updated, AI-analysable cross-organisation database (“need-to-share” model) possibly hosted by
- This database will contain harmonised and digitised data obtained from spectral analyses of multiple DRDs investigations or other drug-related law enforcement operations.
- Platform for harmonise investigations: an up-to-date and updateable screening, classification, and identification platform for:
- fast, robust, and reliable multidisciplinary approach to harmonise investigations in DRDs and other drug-related law enforcement operations.
Key features of the NARCOSISS project:
- Analysis: To combine a set of selected fast and portable orthogonal sensors/instruments (Raman/SERS, IR, HSI), with conventional laboratory instruments (HRMS, GC-MS, LC-MS/MS) to:
- Deliver a better and more effective analysis capability of NPSs and their metabolites.
- Integrate fast and portable instruments into protocols adopted by laboratories and during on-site/field investigations.
- Increase detection confidence and reduce false alarms, evaluating several orthogonal techniques, in order to select the most effective ones depending on prevailing scenarios.
- Improve the analysis of powders and tablets and their envelopes and marks by means of HSI to correlate seizures from detailed chemical and merceological information with compositions or proportions of active ingredients.
- Feed the NARCOSIS Platform with data obtained by the identification and characterization of NPS metabolites from forensic and clinical toxicology caseworks.
- Processing: An AI-assisted spectra management and integration system for analytical measurements (sensor agnostic and comparable between different instruments) and decision support:
- ML models to compare, classify and associate suspected substances based on their spectra.
- Sharing: A comparable (cross-instrument) and shareable (cross-organisation) reference spectra (meta-spectra) database to:
- Detect and identify confirmed and suspected substances or their metabolites applying instrument agnostic methods.
- Store identified suspected substances (including metadata) to support further investigations.
- Enable information sharing and coordination among police authorities, forensic laboratories, clinical and forensic toxicologists.
- Data assurance: An established digital chain-of-custody, ensuring data integrity, traceability, accessibility, and confidentiality, making only anonymised analytical data shareable at European level, while classified information remains stored at National level.
- Investigations: Novel tools for investigators (g., geo-intelligence, spatial-temporal graphs, logo & packaging similarity search and trend analysis) based on the collected instruments’ and investigations’ data.
This project has received funding from the European Union’s Horizon Europe research and innovation programme (Civil Security for Society) under grant agreement No 101168195.
For administrative and contractual information visit the European Commission's Cordis website.