NTVIC Overview�
Matthew Gamette, M.Sc. C.P.M.
Idaho State Police Forensic Services
Laboratory System Director
Chairman,
National Technology Validation and Implementation Collaborative
WHAT IS THE NTVIC
TOTALLY INDEPENDENT BUT STRATEGICALLY CONNECTED
MISSION
The mission of the National Technology Validation and Implementation Collaborative (NTVIC) is to share resources and strategies to rapidly and robustly implement technology and new methods into publicly funded forensic science service provider (FSSP) and forensic science medical provider (FSMP) facilities in a scientifically sound and defensible manner.
FOCUS
Forensic Science Service Providers
Forensic Science Medical Providers
Law Enforcement Forensic Technology Users
PUBLIC ENTITIES
NTVIC GOALS
Researcher/Industry/Practitioner/Educator/Trainer Collaboration
Best and Brightest Personnel Talent
Transparency
Scientific Scrutiny Through Robust Discussion and Publication
Technology and Method Implementation
PURPOSE
To increase the speed of technology and method validation and implementation
To share available validation resources and avoid duplication
To plan, accomplish, and peer review (open access) publish scientifically sound and defensible validation studies
To contribute to standardization of technology implementation, utilizing the latest standards
To facilitate the establishment of technology specific working groups to support continuous improvement of validated and implemented technology
To publish, after validation, a performance verification implementation plan for other laboratories, complete with purchasing information, appropriate methods, and performance verification plan
To provide a venue for early adopter forensic science providers to interact and collaborate
To ensure each technology, instrument, or method is implemented with appropriate policy, procedure, and quality management
Website
https://sites.google.com/view/ntvic/home
NTVIC PARTICIPATING STATES
NTVIC STRUCTURE
Steering Committee
FIGG
Rapid DNA
Single Cell DNA
3D Firearms
Activity Level DNA
Public Policy Evaluations
(Cost/Benefit)
FIGG Technology Validation Working Groups (TVWG)
Experts are invited to participate based on:
FIGG TVWG
Steering Group
FIGG TVWG
FIGG Policy/Procedure
FIGG Policy/Procedure
1(a) Canada
IGG Public Genealogists
FGG Laboratory Technical Validation
FGG/IGG Training/Education
FGG/IGG Public Contracts
Other TVWGs
TERMINOLOGY IS IMPORTANT
PUBLIC ENTITY FIGG POLICY/PROCEDURES�WORK PRODUCTS
PUBLIC ENTITY IGG PUBLIC GENEALOGISTS
FGG LAB TECHNICAL VALIDATION�WORK PRODUCTS
PUBLIC ENTITY FGG and IGG TRAINING�WORK PRODUCTS
FIGG & IGG PUBLIC CONTRACTS�WORK PRODUCTS
Rapid DNA TVWG
Public Policy Evaluation Task Group
3D Firearms Analysis
Implementation of Virtual Comparison Microscope (VCM) technology into workflows in public law enforcement and forensic science laboratories.
DNA Single Cell Analysis
Activity Level DNA Evaluation
Seeks to provide guidance on a structured method to address questions on Activity Level Evaluation (ALE) that arise in court where a model-based analysis has not been undertaken prior to testimony. This commonly occurs at trial in the United States and other countries which use an adversarial justice system.
The goal of the ALE WG is to apply the scientific principles of the model-based approach to add structure to the judgement-based approach required when witnesses are asked to evaluate activity level questions in real time.
This working group seeks to address training recommendations, implementation, and how and when to address activity level questions using a logical, robust, balanced and transparent framework.
Future Work
Single Cell DNA �Technical Validation �Working Group
Stephanie Stoiloff, Director, Forensic & Technology Division, Miami-Dade Sheriff’s Office
American Society of Crime Laboratory Directors 53rd Annual Symposium
May 19, 2026
Mission
https://www.ojp.gov/pdffiles1/nij/grants/309564.pdf
First Deliverable: �Single Cell DNA (scDNA) Lexicon
Second Deliverable: �scDNA Research Needs
Category | Research topic | Priority | Research / knowledge gap | Level of research being conducted | Description |
Sequencing of single cells | Multi-omics proteome/RNA - phenotyping - source level | Low/Moderate | Minor to moderate | Limited | Determining the cellular or tissue phenotype from which a DNA profile originates (the 'source') is essential for activity-level reporting. For single cell forensics this requires advancing sensitive, robust single-cell transcriptomic and proteomic methods optimized for the damaged and dehydrated cells typically encountered in forensic samples. This extends to epigenomic applications. |
Sequencing of single cells | Determining methods for analytical thresholding in sequence data | Low/Moderate | Minor | Existing | Evaluate analytical thresholding methods for use with single cell sequence data. This will be impacted by the noise present in each sequencing run and the low level/stochasticity of single cell data. |
Non-pristine samples/cells | Degradation vs success / variation in DNA present | High | Major | No or limited | With single-cell research findings demonstrating that most single-cell data carry signal in only a fraction of their allelic locations and that allelic detection rates are cell dependent, there is a need to understand the mechanisms underlying cell dependent drop-out such that we improve data generation, e.g.: (A) Determine what, if any, isolation procedures impart DNA damage, (B) What stage of cell life or environmental factors impact DNA integrity?, (C) Interrogate what DNA extraction, amplification or library procedures improve detection, (D) Identify critical cell (e.g., sperm) and evidence types (e.g., cold case, trace deposits), assess (environmental) quality-impacting factors (e.g., degradation). |
Non-pristine samples/cells | Collection/storage | High | Major | No or limited | Identify the optimal methods to collect and store samples for single cell analyses and how or what methods impact the resulting profiles/success rate and develop measures that prevent cell degradation. |
Category | Research topic | Priority | Research / knowledge gap | Level of research being conducted | Description |
Non-pristine samples/cells | Optimal/minimum number of cells | High | Minor to moderate | Limited | Establish sensitivity thresholds as a critical prerequisite for successful single-cell analysis, including: (A) minimum number of target cells required in the initial sample for successful detection and selection. Including the number of potential contributors (based on case information) and number of potential re-runs. (B) minimum number of selected cells (single or pooled) necessary for reliable genotyping. (C) key factors affecting cell quantity and quality, and their impact on detection, selection, and genotyping outcomes. |
Non-pristine samples/cells | Influence of cell free DNA | High | Major | No or limited | How does cell-free DNA influence the effectiveness of single cell analysis? What, if any, extracellular DNA travels with/adheres to cells and is unintentionally co-sorted? |
Non-pristine samples/cells | Nuclei | High | Major | No or limited | Identify the optimal methods to separate, recover/sort and type intact nuclei from low-quality samples. |
Cost / efficiency of isolation | Optimal/minimum number of cells | High | Minor to moderate | Limited | Evaluate cost and efficiency of methods and instrumentation (single cell recovery and liquid handling) related to hands-on labor, recovery, identification of cell type, minimum number of cells, pooling of cells, extraction, amplification, and detection. As the number of cells isolated increases, so does the time and cost associated with the analysis. By determining the minimum number of cells in isolation or pooled needed to yield an interpretable DNA profile, both the cost and time spent can be reduced. |
Instrumentation/ automation | Evaluate - what is available | High | Minor | Existing | Identify candidate recovery instruments/methods and what additional pre- and post- PCR equipment (e.g., liquid handlers, microarrays, thermal cyclers, sequencers, electrophoresis platforms) are amenable to high-throughput, small-volume procedures. |
Category | Research topic | Priority | Research / knowledge gap | Level of research being conducted | Description |
Instrumentation/ automation | Development | High | Moderate to major | Limited | Develop new single cell isolation/recovery methods that focus on increasing throughput, the cost of the method (instrumentation) and per sample, processing speed, increasing sensitivity and specificity. |
Instrumentation/ automation | Determining DNA/cell quality | High | Major | No or limited | Can sample quality and quantity be more accurately assessed prior to or during cell sorting, e.g., through improved cell counting methods, optimized cell release and staining protocols, and refined analysis parameters such as staining intensity, optical settings, and morphological evaluation? Can pre-analytical considerations be optimized to enhance the reliability of single-cell analysis? |
Instrumentation/ automation | Cell type identification | High | Minor to moderate | Limited | Define metric-based, cell-specific patterns (e.g., staining, morphology) to enable accurate detection, identification, and discrimination of cell types. Which characteristics of cells can be used for single cell sorting? Can characteristics/metrics be compared between different sorting methods? Are certain sorting methods better for specific types of cells? How does the environment influence the cellular characteristics? |
Interpretation | Evaluate/develop methods | Low/Moderate | Minor to moderate | Limited | Continue to develop and evaluate methods and guidelines for interpretation of single cell data – including fragment and multi-omic data. It is expected that single cell data will result in low allelic signal due to low quantities of DNA/cells and thus analytical/stochastic thresholds should be reevaluated. Such methods may include the identification of artifacts (e.g. stutter, drop-in, dropout), genotyping methods and statistical assessment. |
Category | Research topic | Priority | Research / knowledge gap | Level of research being conducted | Description |
Enrichment and cell selection | Sampling and cell characterization | Low/Moderate | Major | No or limited | Enriching samples based on case types (e.g. mixtures) and cell types of interest can have a dramatic impact on the success of single cell analyses. Enrichment methods and strategies should be evaluated and optimized to enable efficient, sensitive and cost-effective means of recovering specific cell types and comparing results obtained from a targeted selection vs. random sampling approach. This should include the evaluation of methods to identify specific cell types in heterogenous mixtures and in mixtures of like-cells. For example, using labeling to identify sperm cells in a mixture of sperm and epithelial cells or identify male epithelial cells in a mixture of male and female epithelial cells. |
Enrichment and cell selection | Nuclei | Low/Moderate | Major | No or limited | Identify the optimal methods to separate intact nuclei from low-quality samples and thereby reduce noise produced by debris. |
Amplification of single cells | Amplification volumes | Low/Moderate | Minor to moderate | Limited | Evaluate the impact of amplification reagent volumes have on the single cell analysis results. The performance of scaled reactions may be impacted by the recovery, extraction and detection methods being used. Low amplification volumes would result in a lower expense for the overall analysis pipeline and therefore could impact adoption. |
Amplification of single cells | Direct amp | Low/Moderate | Minor | Existing | Evaluate optimal direct lysis solutions in combination with amplification kits for isolating DNA from single cells. |
Category | Research topic | Priority | Research / knowledge gap | Level of research being conducted | Description |
Amplification of single cells | Whole Genome Amplification | Low/Moderate | Major | No or limited | Methods in whole genome amplification have been widely used for over decades in non-forensic single cell analysis pipelines. The ability to generate more DNA from a single cell may remove the low template limitations that single cell analyses present. Although work on this in the forensic DNA field has been done many questions remain such as : Can WGA be used to amplify DNA from single cells for forensic use? Which WGA method or kit is optimal? What are the limitations of WGA used in concert with forensic human identity kits to improve single cells analysis and how does this impact interpretation (i.e., stutter allele dropout, allelic imbalance)? |
Extraction optimization | Extraction methods | Low/Moderate | Minor | Existing | Evaluate and identify the optimal methods including solid versus liquid phase, specific reagents and volumes, etc. for extracting and isolating DNA from single cells of all relevant cell types and conditions (non-pristine). |
scDNA
Survey
Members
Mike Marciano, PhD, Chair, Forensic and National Security Sciences Institute/Professor of Practice—Syracuse University
Stephanie Stoiloff, MS, Co-Chair, Director, Forensic & Technology Division, Miami-Dade Sheriff’s Office
Katja Anslinger, PhD, Dept. of Forensic Genetics, Institute of Legal Medicine, University Hospital LMU, Munich, Germany
Iain Macaulay, Earlham Institute, Norwich, UK
Jack Ballantyne, PhD, University of Central Florida
Bram Bekaert, PhD, Laboratory for Forensic Genetics & Molecular Archaeology—University Hospitals, Leuven, Belgium
Garry Bombard, PhD, Loyola University, Chicago -retired
Kristina Fokias, MS, KU Leuven, Belgium
Catherine Grgicak, PhD, Rutgers University, Camden, New Jersey
Janine Schulte, PhD, Institute for Forensic Medicine, University of Basel, Switzerland
Iris Schulz, PhD, Institute for Forensic Medicine, University of Basel, Switzerland
Amber Vandepoele, MS, Oregon State Police – Forensic Services Division
Thank you.