| name | KSB-D05-K0036 |
| description | Safety Signal Prediction: Machine learning models predicting adverse event likelihood based on patient characteristics... |
| version | 1.0.0 |
| domain | D05 |
| domain_name | Clinical Trials PV |
| type | Knowledge |
| proficiency_level | L1 |
| bloom_level | understand |
| triggers | ["explain safety signal prediction","what is safety signal prediction","explain safety signal prediction"] |
| epa_mapping | EPA-02, EPA-04, EPA-08 |
| cpa_mapping | CPA-01, CPA-07 |
| regulatory_refs | EMA-REG-004, ICH-E6 |
KSB-D05-K0036: Safety Signal Prediction
Overview
Domain: D05 - Clinical Trials PV
Type: Knowledge
Proficiency Level: L1 (Novice - Direct supervision required)
Bloom Level: Understand
Description
Machine learning models predicting adverse event likelihood based on patient characteristics
Context
- Major Section: Clinical Trial Regulatory Framework and Safety Requirements
- Section: Predictive Analytics and Machine Learning
EPA Mapping
- EPA-02:3004-3005
- EPA-04:3009-3010
- EPA-08:3018-3019
CPA Pathway
Regulatory References
Instructions
When this skill is activated, Claude should:
- Demonstrate L1 proficiency in safety signal prediction
- Apply understand level cognitive skills to explain the topic
- Reference relevant regulatory guidance (EMA-REG-004, ICH-E6)
- Connect to related EPAs: EPA-02, EPA-04, EPA-08
Key Competencies
- Machine learning models predicting adverse event likelihood based on patient characteristics
Assessment Criteria
- Can explain core concepts independently
- Demonstrates understanding of regulatory context
- Applies knowledge appropriately to PV scenarios
Related Skills
- Other D05 skills in Predictive Analytics and Machine Learning
- Cross-domain integrations per DAG architecture
Generated from PV KSB Framework v1.0 | 2025-12-31
