Scipion PKPD

Scipion PKPD performs comprehensive analysis of biopharmaceutics, pharmacokinetics (PK), and pharmacodynamics (PD) data to evaluate absorption, distribution, metabolism, excretion (ADME) and to predict drug concentrations and effects.

Key Features:

• Integration with Scipion workflow engine: Integrates with the Scipion workflow engine via a Python module that provides numerical analysis and metadata handling.
• Biopharmaceutics/PK/PD support: Supports analysis across biopharmaceutics, pharmacokinetics (PK), and pharmacodynamics (PD) domains.
• PK time-series handling: Handles time-series samples of drug concentration in plasma or specific tissues.
• PD time-series handling: Handles time-series measurements of biophysical quantities such as temperature and blood pressure.
• Non-parametric analyses: Provides descriptive statistics including Area Under the Curve (AUC).
• Parametric analyses: Performs parametric model fitting, often using differential equations, to enable prediction of future events.
• Model library and extensibility: Implements a wide array of pharmacometric models and supports incorporation of new models.
• Protocols: Provides nearly 100 high-level operations ("protocols") to address diverse analytical tasks.
• ADME modeling: Evaluates absorption, distribution, metabolism, and excretion processes using mathematical models.

Scientific Applications:

• ADME evaluation: Evaluate drug movement through the body via absorption, distribution, metabolism, and excretion.
• Pharmacokinetic analysis: Analyze plasma or tissue concentration time-series to derive PK parameters and exposure metrics.
• Pharmacodynamic analysis: Analyze time-series of biophysical measures (e.g., temperature, blood pressure) to assess drug effects.
• Integrated biopharmaceutics–PK–PD studies: Integrate formulation, dose, and administration route effects with PK and PD modeling to interpret complex datasets.

Methodology:

Performs non-parametric analyses (descriptive statistics including Area Under the Curve), parametric model fitting often based on differential equations for prediction, and numerical analysis and metadata handling via a Python module within Scipion protocols.