modelR03BA04
Extends from Pharmacokinetic.Models.PK_1C_enteral.
Information
| name: | Betamethasone | |
| ATC code: | R03BA04 | route: | oral |
| compartments: | 1 | |
| dosage: | 4.0 | mg |
| volume of distribution: | 1.5 | L |
| clearance: | 0.19 | L/h/kg |
| other parameters in model implementation | ||
Betamethasone is a potent synthetic glucocorticoid corticosteroid with anti-inflammatory and immunosuppressive properties. It is used for treating various allergic, inflammatory, and autoimmune disorders, and is also used for fetal lung maturation in preterm labor. This drug is approved and used in clinical practice, although specific administrations and indications may vary by region.
Pharmacokinetics
Estimated pharmacokinetic parameters for oral administration in healthy adult population, as no direct publications for R03BA04 exist. Parameters are derived from general knowledge of betamethasone and clinical pharmacology references.
References
Krzyzanski, W, et al., & Jusko, WJ (2021). Population pharmacokinetic modeling of intramuscular and oral dexamethasone and betamethasone in Indian women. Journal of pharmacokinetics and pharmacodynamics 48(2) 261–272. DOI:10.1007/s10928-020-09730-z PUBMED:https://pubmed.ncbi.nlm.nih.gov/33389521
Krzyzanski, W, et al., & Jusko, WJ (2021). Population pharmacodynamic modeling of intramuscular and oral dexamethasone and betamethasone effects on six biomarkers with circadian complexities in Indian women. Journal of pharmacokinetics and pharmacodynamics 48(3) 411–438. DOI:10.1007/s10928-021-09755-y PUBMED:https://pubmed.ncbi.nlm.nih.gov/33954911
Lim, SY, et al., & Heard, CM (2020). Mucoadhesive thin films for the simultaneous delivery of microbicide and anti-inflammatory drugs in the treatment of periodontal diseases. International journal of pharmaceutics 573 118860–None. DOI:10.1016/j.ijpharm.2019.118860 PUBMED:https://pubmed.ncbi.nlm.nih.gov/31759104
Parameters
| Type | Name | Default | Description |
|---|---|---|---|
| Modelica.Units.SI.Mass | weight (from PK_1C) | 75 | patient weight (kg) |
| Modelica.Units.SI.SpecificVolume | VdPerKg (from PK_1C) | 0.9 | Volume of distribution (L/kg) |
| Modelica.Units.SI.MassFraction | F (from PK_1C) | 0.8 | bioavailiability (0-1) |
| Pharmacolibrary.Types.Clearance | Cl (from PK_1C) | 20 | clearance |
| Modelica.Units.SI.Time | adminTime (from PK_1C) | 60 | first administration time (s) |
| Modelica.Units.SI.Time | adminDuration (from PK_1C) | 600 | administration duration (s) |
| Modelica.Units.SI.Time | adminPeriod (from PK_1C) | 8*60*60 | period of administration (default 8 hours)(s) |
| Pharmacolibrary.Types.Mass | adminMass (from PK_1C) | 1000 | administration mass (mg) |
| Integer | adminCount (from PK_1C) | 8 | number of dose administered (1) |
| Pharmacolibrary.Types.Volume | Vd (from PK_1C) | VdPerKg*weight | Volume of distribution (m3) |
| Pharmacolibrary.Types.MassConcentration | Cmin (from PK_1C) | 0.004 | minimal therapeutic range |
| Pharmacolibrary.Types.MassConcentration | Cmax (from PK_1C) | 0.008 | minimal therapeutic range |
| Pharmacolibrary.Types.MassConcentration | Ctox_peak (from PK_1C) | 0.012 | toxicity peak level |
| Pharmacolibrary.Types.MassConcentration | Ctox_trough (from PK_1C) | 0.006 | toxicity trough level |
| Pharmacolibrary.Types.TransferRate | ka (from PK_1C_enteral) | 0.016666666666666666 | first order absorption rate |
| Modelica.Units.SI.Time | Tlag (from PK_1C_enteral) | 600 | delay between oral administration and absorption (default 10min) |
Connectors
| Type | Name | Default | Description |
|---|---|---|---|
| Types.ConcentrationOutput | C_central (from PK_1C) | ||
| Interfaces.ConcentrationPort_b | centralCPort (from PK_1C) |
Components
| Type | Name | Default | Description |
|---|---|---|---|
| Pharmacokinetic.NoPerfusedTissueCompartment | central (from PK_1C) | ||
| Pharmacokinetic.ClearanceDrivenElimination | elim (from PK_1C) | ||
| Sources.PeriodicDose | periodicDose (from PK_1C) | ||
| Modelica.Units.SI.Time | t1_2 (from PK_1C) | elimination half-life |
Revisions
- 06/2025 Tomas Kulhanek, generated model from data extracted from PUBMED, DrugBank and LLM(GPT4.1)