Translational Model-Informed Dose Selection for Iruplinalkib, a Selective Oral ALK/ROS1 Tyrosine Kinase Inhibitor

Area of Science:

• Pharmacology
• Oncology
• Translational Medicine

Background:

• Iruplinalkib is a selective oral ALK and ROS1 tyrosine kinase inhibitor.
• Determining the optimal dose is crucial for maximizing efficacy and minimizing toxicity in cancer therapy.

Purpose of the Study:

• To predict the recommended phase 2 dose (RP2D) of iruplinalkib using an integrated model-informed dose selection approach.
• To establish a reliable method for predicting RP2D by integrating preclinical and clinical data.

Main Methods:

• Pharmacokinetics/pharmacodynamics (PKPD) modeling using xenograft data to determine human iruplinalkib tumor static concentration (TSC).
• Population pharmacokinetic (PopPK) analysis of pooled clinical data to model iruplinalkib plasma concentration-time profiles.
• Simulation of steady-state plasma concentrations to predict the optimal dose for >90% of patients.

Main Results:

• The human iruplinalkib TSC was estimated at 98 ng/mL for ROS1-positive and 78 ng/mL for ALK-positive tumors.
• A two-compartment PopPK model accurately described iruplinalkib's pharmacokinetic properties (RSE < 30%).
• Iruplinalkib 180 mg QD was predicted to be effective for over 90% of the patient population and was recommended as the RP2D.

Conclusions:

• The integrated model-based approach using preclinical PK/PD and PopPK modeling is a reliable method for predicting RP2D.
• The predicted RP2D of 180 mg QD for iruplinalkib was validated in advanced clinical trials and incorporated into prescribing information.
• This strategy supports efficient dose selection for targeted cancer therapies.