multimodal-analysis
Analyzes medical images (X-ray, MRI, CT) using multimodal LLMs to identify anomalies and generate reports.
Drug delivery formulation skill for optimizing drug loading, encapsulation efficiency, and release kinetics
---
name: drug-encapsulation-optimizer
description: Drug delivery formulation skill for optimizing drug loading, encapsulation efficiency, and release kinetics
allowed-tools:
- Read
- Write
- Glob
- Grep
- Bash
metadata:
specialization: nanotechnology
domain: science
category: applications
priority: high
phase: 6
tools-libraries:
- Dissolution modeling software
- Stability testing protocols
graph:
domains: [domain:nanotechnology]
skillAreas: [skill-area:mathematical-reasoning, skill-area:physics-simulation, skill-area:data-analysis]
workflows: [workflow:experiment-design]
roles: [role:research-engineer]
---
# Drug Encapsulation Optimizer
## Purpose
The Drug Encapsulation Optimizer skill provides systematic optimization of nanoparticle drug delivery formulations, enabling maximized drug loading, controlled release kinetics, and formulation stability.
## Capabilities
- Drug loading optimization
- Encapsulation efficiency calculation
- Release kinetics modeling (zero-order, Higuchi, Korsmeyer-Peppas)
- Stability testing protocols
- Size optimization for target application
- Payload-to-carrier ratio optimization
## Usage Guidelines
### Formulation Optimization
1. **Loading Optimization**
- Screen loading methods
- Optimize drug:carrier ratio
- Maximize encapsulation efficiency
2. **Release Kinetics**
- Characterize release profile
- Fit to kinetic models
- Design sustained release
3. **Stability Assessment**
- Monitor size over time
- Track drug leakage
- Accelerated stability testing
## Process Integration
- Nanoparticle Drug Delivery System Development
- Nanomaterial Safety Assessment Pipeline
## Input Schema
```json
{
"drug": "string",
"carrier_type": "liposome|polymer|micelle|lipid_np",
"target_loading": "number (wt%)",
"release_target": "immediate|sustained|triggered",
"route": "iv|oral|topical|inhalation"
}
```
## Output Schema
```json
{
"optimized_formulation": {
"drug_loading": "number (wt%)",
"encapsulation_efficiency": "number (%)",
"particle_size": "number (nm)",
"pdi": "number"
},
"release_kinetics": {
"model": "string",
"parameters": {},
"t50": "number (hours)",
"t90": "number (hours)"
},
"stability": {
"shelf_life": "number (months)",
"storage_conditions": "string"
}
}
```
---
name: drug-encapsulation-optimizer
description: Drug delivery formulation skill for optimizing drug loading, encapsulation efficiency, and release kinetics
allowed-tools:
- Read
- Write
- Glob
- Grep
- Bash
metadata:
specialization: nanotechnology
domain: science
category: applications
priority: high
phase: 6
tools-libraries:
- Dissolution modeling software
- Stability testing protocols
graph:
domains: [domain:nanotechnology]
skillAreas: [skill-area:mathematical-reasoning, skill-area:physics-simulation, skill-area:data-analysis]
workflows: [workflow:experiment-design]
roles: [role:research-engineer]
---
# Drug Encapsulation Optimizer
## Purpose
The Drug Encapsulation Optimizer skill provides systematic optimization of nanoparticle drug delivery formulations, enabling maximized drug loading, controlled release kinetics, and formulation stability.
## Capabilities
- Drug loading optimization
- Encapsulation efficiency calculation
- Release kinetics modeling (zero-order, Higuchi, Korsmeyer-Peppas)
- Stability testing protocols
- Size optimization for target application
- Payload-to-carrier ratio optimization
## Usage Guidelines
### Formulation Optimization
1. **Loading Optimization**
- Screen loading methods
- Optimize drug:carrier ratio
- Maximize encapsulation efficiency
2. **Release Kinetics**
- Characterize release profile
- Fit to kinetic models
- Design sustained release
3. **Stability Assessment**
- Monitor size over time
- Track drug leakage
- Accelerated stability testing
## Process Integration
- Nanoparticle Drug Delivery System Development
- Nanomaterial Safety Assessment Pipeline
## Input Schema
```json
{
"drug": "string",
"carrier_type": "liposome|polymer|micelle|lipid_np",
"target_loading": "number (wt%)",
"release_target": "immediate|sustained|triggered",
"route": "iv|oral|topical|inhalation"
}
```
## Output Schema
```json
{
"optimized_formulation": {
"drug_loading": "number (wt%)",
"encapsulation_efficiency": "number (%)",
"particle_size": "number (nm)",
"pdi": "number"
},
"release_kinetics": {
"model": "string",
"parameters": {},
"t50": "number (hours)",
"t90": "number (hours)"
},
"stability": {
"shelf_life": "number (months)",
"storage_conditions": "string"
}
}
```
Imported from the listed AgentSkill.sh category. Complete supplied package files and notices are retained. Required external tools and credentials are not installed. No bundled code was executed during import. Individual agent task behavior has not been tested.