'mdr' 검색 결과

Supports preparation for EU medical device regulation reviews by organizing device classification, technical documentation, clinical evidence, and post-market monitoring. Includes a tool to identify documentation and compliance gaps and prioritize the next steps.

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• Documenting a device classification rationale under MDR
• Checking technical documentation before a review
• Planning clinical evaluation and identifying evidence gaps

Prepare medical device regulatory strategies and submission documents for FDA, EU, and other markets. Compare application routes, organize technical and clinical evidence, draft responses to regulator questions, and track submission schedules.

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• Comparing FDA application routes for a new medical device
• Organizing technical documentation for EU MDR
• Drafting responses to FDA or Notified Body questions

Prepares medical device quality systems for ISO 13485 audits using six focused questions. Reviews design records, corrective actions, process validation, risk files, post-market monitoring, and management reviews, then summarizes readiness gaps and three priority actions.

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• Check readiness before an ISO 13485 internal audit
• Review design history files before a product launch
• Check evidence that corrective actions were effective

EU MDR 2017/745 compliance specialist for medical device classification, technical documentation, clinical evidence, and post-market surveillance. Use for Annex VIII classification, GSPR, clinical evaluation, EUDAMED, and UDI.

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Read, write, and edit ChemDraw CDX/CDXML files with RDKit's rdkit.Chem.rdChemDraw plus direct XML editing, always paired with a rendered PNG. Parse molecules and reactions from .cdxml/.cdx, write structures with good 2D depiction, and hand-build or modify the parts RDKit cannot write: reaction arrows, plus signs, schemes/steps, and text/labels. Use for reaction schemes, synthesis routes, mechanisms, retrosynthesis, or SI figures. Critical: RDKit writes structures only — round-tripping a reaction through a Mol silently drops arrows and text; this skill shows the XML layer that preserves them. For pure molecular analysis (descriptors, fingerprints, SMARTS) use rdkit-cheminformatics; for multi-format 3D conversion use openbabel.

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Routes regulatory and quality management requests to one of 15 specialist skills. Helps HealthTech and MedTech teams select the right workflow for audits, medical device regulations, information security, privacy, or AI compliance.

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• Choosing a skill for ISO 13485 audit preparation
• Routing questions about EU AI Act risk classification
• Finding the right workflow for GDPR requests

Audit medical device technical files against EU MDR 2017/745 regulations.

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Senior Regulatory Affairs Manager for HealthTech and MedTech. Use for regulatory strategy, FDA 510(k)/PMA/De Novo submissions, EU MDR CE marking, global market access, and regulatory intelligence.

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Reconstructed reference notes on EU and UK medical-device software, built from six sources captured 2026-10-13: MDCG 2019-11 rev.1 (June 2025), MDCG 2020-6 (April 2020), MDCG 2020-13 (July 2020), MDCG 2020-7 (April 2020), MDCG 2020-8 (April 2020), and the MHRA software-applications guidance (2023-07-01) with its stand-alone software PDF. Use for SaMD qualification and classification, legacy-device clinical evidence, the clinical evaluation assessment report, the PMCF plan, and the PMCF evaluation report, under EU MDCG guidance or UK MHRA guidance. SCOPE LIMITS: EU MDR and UK MHRA device software only; no IEC 62304, ISO 13485, or ISO 14971 text; no MDR or IVDR regulation body text; MDCG guidance is not legally binding; MHRA guidance is UK-specific; synthesized notes, not legal advice. LICENCE: Per-document: European Commission reuse policy (Decision 2011/833/EU, CC BY 4.0, attribution and indication of changes) for the MDCG documents; Open Government Licence v3.0 for the MHRA guidance; reconstructed notes with attribution; official PDFs not redistributed.

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12 regulatory & QM agent skills and plugins for Claude Code, Codex, Gemini CLI, Cursor, OpenClaw. ISO 13485 QMS, MDR 2017/745, FDA 510(k)/PMA, ISO 27001 ISMS, GDPR/DSGVO, risk management (ISO 14971), CAPA, document control, auditing. Python tools (stdlib-only).

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Organize ISO evidence for medical devices and laboratories, including controlled documents, risk records, corrective actions, and supplier controls. Produce structured gap reports for authorized human review while keeping certification, accreditation, and regulatory processes distinct.

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• Organize controlled documents and implementation records
• Check links in medical-device risk and design records
• Review corrective-action and supplier-control evidence

Supports medical device risk management from planning through post-market review using ISO 14971:2019. Helps identify hazards, evaluate risks, select and verify controls, assess remaining risks, and maintain records as new information arrives.

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• Create a medical device risk management plan
• Identify hazards and choose risk analysis methods
• Compare risk controls and assess remaining risks

Plan a prospective clinical study by ranking endpoints, estimating participant numbers and statistical power, and assessing feasibility. Outputs include assumptions and named reviewers, providing material for expert review before a protocol is finalized.

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• Choosing primary and secondary study endpoints
• Estimating sample size with dropout allowance
• Assessing feasibility before a study review

Coordinate compliance work across multiple standards and regulations. Use a company profile to identify relevant frameworks, map shared controls, prepare mock audits, and build a unified evidence checklist showing where documents can be reused.

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• Starting a compliance program across multiple frameworks
• Planning an annual audit calendar
• Preparing for a certification audit

Prepare for FDA medical device quality audits through six evidence-focused questions. Review complaints, adverse event reports, process validation, manufacturing records, corrective actions, labeling, and inspection history, then organize readiness gaps and three next actions with owners.

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• Preparing for an annual internal quality audit
• Reviewing readiness before an FDA inspection
• Organizing evidence for a Form 483 response

Comprehensive toolkit for preparing ISO 13485 certification documentation for medical device Quality Management Systems. Use when users need help with ISO 13485 QMS documentation, including (1) conducting gap analysis of existing documentation, (2) creating Quality Manuals, (3) developing required procedures and work instructions, (4) preparing Medical Device Files, (5) understanding ISO 13485 requirements, or (6) identifying missing documentation for medical device certification. Also use when users mention medical device regulations, QMS certification, FDA QMSR, EU MDR, or need help with quality system documentation.

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Assess, report, and manage serious incidents involving high-risk AI systems under Article 73 EU AI Act. Covers incident qualification, deadline buckets (2/10/15 days), authority notification, deployer duties (Art. 26(5)), cross-regulation mapping (GDPR/NIS2/MDR), corrective measures, and DACH-specific routing. Use when asked to evaluate whether an AI incident is reportable, draft an Article 73 notification, identify the right authority, or build an AI incident response process.

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AiZynthFinder retrosynthetic route planning (CASP) from AstraZeneca Molecular AI. Monte Carlo tree search guided by a template-based neural expansion policy recursively disconnects a target SMILES until precursors are found in a purchasable stock. Covers config.yml (v4 format), aizynthcli batch screening, the AiZynthFinder/AiZynthExpander Python API, one-step disconnections, custom stocks via smiles2stock, scorers, Retro*/breadth-first/DFPN search alternatives, and reading output.json.gz / trees.json. Use for synthesis route planning, synthesizability screening, and building-block/precursor search. For reaction barriers use neb-irc-activation-energy; for 2D reaction scheme drawing use rdkit-chemdraw-cdxml.

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NEB-IRC activation energy pipeline for reaction barriers using GFN2-xTB and pysisyphus. Optimize reactant and product geometries, run CI-NEB path search, optimize the transition state with a Hessian, verify with IRC (one imaginary mode, endpoints matching reactant/product, single NEB maximum), and report the electronic and Gibbs barriers. Use when you need a transition state, reaction barrier, activation energy, minimum energy path, or intrinsic reaction coordinate. Covers reactant/product atom-ordering pitfalls, feasibility sizing for single-core runs, and thermochemistry corrections. Renders an IRC energy-profile plot and an animated TS imaginary-mode HTML viewer. For 2D reaction scheme drawing use rdkit-chemdraw-cdxml.

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3Dmol.js WebGL molecular visualization emitted as self-contained HTML. Render structures (PDB/SDF/XYZ/MOL2/cube) with stick, sphere, cartoon, line, and surface styles; animate trajectories with a frame-delay (interval, ms) control; and animate vibrational normal modes via vibrate() from per-atom dx/dy/dz displacements or from precomputed frames. Output standalone HTML that loads 3Dmol from a CDN, with optional play/pause and speed controls. Use for transition-state imaginary-mode animations, MD or reaction-path playback, docking poses, and orbital/density isosurfaces. For static 2D chemical structure drawings use rdkit-chemdraw-cdxml; for 2D statistical plots use matplotlib or plotly.

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Think and work like an expert Clinical Microbiologist. Use when a task calls for Clinical Microbiologist judgment. Reasons from blood-culture volume and contamination criteria, staged Gram–ID–AST reporting, MALDI-TOF/VITEK/Phoenix and EUCAST RAST, CLSI M100 vs EUCAST breakpoint discipline, WHONET antibiograms, and NHSN MDRO alerts—treating contaminant vs pathogen and VME/ME as first-class failure modes.

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Grill the user relentlessly about a plan, decision, or idea. Use when the user wants to stress-test their thinking, or uses any 'grill' trigger phrases.

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Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.

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Use for any question about a codebase, its architecture, file relationships, or project content — especially when graphify-out/ exists, where the question should be treated as a graphify query first. Turns any input (code, docs, papers, images, videos) into a persistent knowledge graph with god nodes, community detection, and query/path/explain tools.

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