Drug Encapsulation Optimizer

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Drug delivery formulation skill for optimizing drug loading, encapsulation efficiency, and release kinetics

Instructions available. Your AI can read the instructions. Execution depends on the setup they require.

Account requirements not reviewed. Check the skill instructions before use; ahel provides instructions and does not run this skill.

Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.

Then ask your AI: use the Drug Encapsulation Optimizer skill

What this skill tells your AI

The instructions your AI receives, as published by a5c-ai/babysitter in library/specializations/domains/science/nanotechnology/skills/drug-encapsulation-optimizer/SKILL.md and read by ahel’s review.

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

Loading Optimization
- Screen loading methods
- Optimize drug:carrier ratio
- Maximize encapsulation efficiency
Release Kinetics
- Characterize release profile
- Fit to kinetic models
- Design sustained release
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

{
  "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

{
  "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"
  }
}

Signals

GitHub stars: 2k
Forks: 112
Last commit: Sep 2026

Advanced

Item type: skill
Key: drug-encapsulation-optimizer
Source: github.com/a5c-ai/babysitter

github.com/a5c-ai/babysitter