--- name: 'myeloma-mrd-agent' description: 'AI-powered minimal residual disease (MRD) analysis for multiple myeloma using next-generation flow cytometry, NGS, and mass spectrometry approaches.' measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- # Myeloma MRD Agent The **Myeloma MRD Agent** provides comprehensive AI-driven minimal residual disease assessment for multiple myeloma. It integrates next-generation flow cytometry (NGF), NGS-based clonotype tracking, and mass spectrometry M-protein detection for ultra-sensitive MRD monitoring. ## When to Use This Skill * When assessing MRD status in multiple myeloma patients post-treatment. * To select optimal MRD testing modality (NGF vs NGS vs MS). * For predicting progression-free survival based on MRD kinetics. * When integrating MRD with other response criteria (IMWG). * To guide treatment intensification or de-escalation decisions. ## Core Capabilities 1. **NGF Analysis**: AI-enhanced next-generation flow cytometry for MRD detection at 10^-5 to 10^-6 sensitivity. 2. **NGS Clonotype Tracking**: Analyze IGH/IGK/IGL rearrangements for molecular MRD. 3. **Mass Spectrometry**: MALDI-TOF or LC-MS/MS for M-protein detection. 4. **Multi-Modal Integration**: Combine modalities for comprehensive MRD assessment. 5. **Kinetic Modeling**: Track MRD dynamics and predict outcomes. 6. **Response Classification**: Apply IMWG MRD criteria. ## MRD Detection Methods | Method | Sensitivity | Sample | Advantages | |--------|-------------|--------|------------| | NGF (EuroFlow) | 10^-5 to 10^-6 | BM | Standardized, fast | | NGS (clonoSEQ) | 10^-6 | BM | Ultra-sensitive | | ASO-qPCR | 10^-5 | BM | Quantitative | | PET-CT | N/A | Whole body | Extramedullary | | MS (MALDI/LC-MS) | 10^-5 | Serum | Non-invasive | ## IMWG MRD Response Criteria | Category | Definition | |----------|------------| | MRD-negative (10^-5) | No clonal plasma cells by NGF or NGS at 10^-5 | | MRD-negative (10^-6) | No clonal plasma cells at 10^-6 sensitivity | | Sustained MRD-neg | MRD-neg confirmed ≥1 year apart | | Flow MRD-neg | NGF negative, sensitivity ≥10^-5 | | Sequencing MRD-neg | NGS negative, sensitivity ≥10^-5 | ## Workflow 1. **Input**: Flow cytometry FCS files, NGS clonotype data, M-protein MS data, clinical parameters. 2. **NGF Analysis**: AI-assisted gating and aberrant plasma cell identification. 3. **NGS Analysis**: Clonotype frequency calculation and threshold application. 4. **MS Analysis**: M-protein peak detection and quantification. 5. **Integration**: Combine multi-modal MRD data. 6. **Kinetics**: Model MRD trajectory and predict outcomes. 7. **Output**: MRD status, response category, prognostic estimate. ## Example Usage **User**: "Analyze MRD status for this myeloma patient using flow and NGS data." **Agent Action**: ```bash python3 Skills/Hematology/Myeloma_MRD_Agent/myeloma_mrd.py \ --flow_fcs bone_marrow_ngf.fcs \ --ngs_clonotype clonoseq_results.json \ --ms_mprotein maldi_spectrum.csv \ --baseline_clone diagnosis_clone.json \ --treatment_phase post_consolidation \ --output mrd_report.json ``` ## NGF Panel (EuroFlow-Based) **Tube 1**: CD138/CD38/CD45/CD19/CD56/CD27/CD81/CD117 **Aberrant Plasma Cell Phenotype**: - CD138+, CD38++ - CD19- or dim (normal PC: CD19+) - CD56+ (normal PC: CD56-) - CD45- or dim (normal PC: CD45+) - CD27- or dim - CD117+ (often aberrant) ## AI-Assisted Flow Cytometry **Automated Gating**: - CNN-based plasma cell identification - Aberrant vs normal PC discrimination - Consistent quantification across samples **Quality Control**: - Sample adequacy assessment - Hemodilution detection - Event count validation ## NGS Clonotype Analysis **Process**: 1. Identify dominant clone at diagnosis (IGH/IGK/IGL) 2. Design clone-specific assay or use multiplex (clonoSEQ) 3. Track clonal frequency in follow-up samples 4. Apply MRD threshold (typically 10^-5 or 10^-6) **Considerations**: - Clonal evolution may affect tracking - Biclonal disease requires tracking both - IGK/IGL backup if IGH fails ## Prognostic Significance | MRD Status | PFS HR | OS HR | |------------|--------|-------| | MRD-neg (10^-5) | 0.35-0.45 | 0.40-0.50 | | MRD-neg (10^-6) | 0.25-0.35 | 0.30-0.40 | | Sustained MRD-neg | 0.20-0.30 | 0.25-0.35 | ## Clinical Decision Support **MRD-Guided Treatment**: - De-escalation in sustained MRD-neg - Intensification if MRD conversion - Maintenance duration decisions **Monitoring Frequency**: - Post-induction - Post-consolidation - Post-transplant (Day +100) - Every 6-12 months on maintenance ## Prerequisites * Python 3.10+ * FlowJo or equivalent for FCS files * NGS analysis pipelines * Mass spectrometry processing tools ## Related Skills * Flow_Cytometry_AI - For general flow analysis * Multiple_Myeloma_AI - For disease-specific analysis * Liquid_Biopsy_Analytics_Agent - For ctDNA approaches ## Emerging Methods 1. **Circulating tumor cells**: Blood-based PC detection 2. **Cell-free DNA**: Myeloma-specific mutations 3. **Imaging**: PET/MRI for extramedullary disease 4. **Serum-based NGS**: M-protein sequencing ## Author AI Group - Biomedical AI Platform --- Source attribution: FreedomIntelligence Original project: https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills License: MIT License information: https://opensource.org/license/mit Original upstream instructions; downloaded from Mega AI Hub. ## Upstream license notice MIT License Copyright (c) 2026 FridrichMethod Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. --- NOTE ON BUNDLED CONTENT This repository aggregates skills from multiple upstream projects (see the README for the source list). Each `skills//` directory may carry its own license inherited from its upstream source. The MIT license above applies to this repository's curation and the scripts/workflows in `/`, `/scripts/`, and `/.github/` — not to the upstream skill content itself. Consult the upstream repository linked in the README and any LICENSE file inside a skill directory before reusing skill content commercially. # Mega AI Hub resource metadata Creator / publisher: FreedomIntelligence Original project: https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills Attribution basis: Exact package in biomedical source index and publisher source table Fields of work: Healthcare & Life Sciences Roles: Clinical Research, Health Informatics, Medical Writer Specialties: API Tools: Python Country applicability: Global Classification basis: Source catalog labels Instruction SHA-256: bc3650a7ba5e7a638438dc8ae743c6359e9ee35b4eec188ce6bf844f15488875 Metadata reviewed: 2026-10-27 This metadata supersedes earlier Mega AI Hub catalog attribution. Original instruction and supporting files are preserved.