Dosage Prediction of Chloroquine and Lopinavir/Ritonavir for COVID-19 via PBPK Modelling

A study by Teerachat Saeheng of Nagasaki University uses physiologically-based pharmacokinetic (PBPK) modelling to predict optimal drug regimens for COVID-19. The models were validated against published clinical data, with predicted values showing average errors within 30% of observed data. The research proposes a specific combination dosage of lopinavir/ritonavir and chloroquine.

Use Cases

• Validate PBPK model predictions based on published clinical pharmacokinetic data.
• Simulate optimal drug dosing regimens for combination antiviral therapy.
• Inform clinical trial design for COVID-19 treatments using model-derived dosage schedules.
• Compare predicted plasma drug concentration profiles with efficacy and toxicity thresholds.

Strengths

• Models were validated with average prediction errors reported to be within 30% of observed clinical data.
• The description provides a specific, proposed dosage regimen for the drug combination.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Last update date is unknown; freshness unverified.

Provenance

Source

paperswithcode

Collection Method

Physiologically-based pharmacokinetic (PBPK) modelling constructed and validated against published clinical data.