A limited sampling model to estimate exposure to lenalidomide in multiple myeloma patients
Seiji Shida1, Naoto Takahashi, Masatomo Miura
1*Department of Hematology, Nephrology, and Rheumatology, Akita University Graduate School of Medicine; †Department of Pharmacy, Akita University Hospital, Akita, Japan; ‡Department of Hematology, Nishi-Gunma Hospital, Shibukawa, Japan; §Department of Hematology, Eiju General Hospital, Tokyo, Japan; ¶Division of Blood Transfusion and ‖Clinical Oncology Center, Akita University Hospital, Akita, Japan.
Background:
The aim of this study was to develop a model able to predict the area under the lenalidomide plasma concentration-time curve (AUC) in multiple myeloma (MM) patients using a limited sampling strategy.
Methods:
Forty-six hospitalized Japanese MM patients (25 men and 21 women) participated in this study. On days 3-10 of lenalidomide therapy, whole-blood samples were collected just before oral lenalidomide administration, and 1, 2, 4, 8, 12, and 24 hours thereafter. Plasma concentrations of lenalidomide were analyzed using liquid chromatography-tandem mass spectrometry.
Results:
The AUC0-24 predicted from a single lenalidomide plasma concentration measured 8 hours after the administration (C8h) showed the highest correlation with the measured AUC0-24 of lenalidomide (AUC0-24 = 13.0 × C8h + 1305.0; r = 0.832). To enhance the correlation between the predicted and the actual AUC0-24 of lenalidomide, we included information regarding lenalidomide elimination by entering creatinine clearance (CCr) data in the predictive formula of lenalidomide AUC0-24. Predicting the AUC0-24 of lenalidomide using data from 2 time points, C0h and C4h, along with CCr data further strengthened the correlation with the measured AUC0-24 of lenalidomide [AUC0-24 = 37.1 × C0h + 6.4 × C4h - 32.1 × CCr + 3265.6; r = 0.842].
Conclusions:
The AUC0-24 of lenalidomide can be predicted using plasma concentrations measured at only 2 time points, C0h and C4h, in combination with CCr. Our study also suggests that the limited sampling strategy approach might help to identify patients with renal function impairment and who, despite dose adjustments, accumulate the drug, leading to a high AUC.
Insights
Predicting lenalidomide
Area of Science:
- Pharmacokinetics
- Clinical Pharmacology
- Drug Monitoring
Background:
- Lenalidomide is a key treatment for multiple myeloma (MM).
- Accurate monitoring of lenalidomide exposure (AUC) is crucial for effective treatment.
- Limited sampling strategies (LSS) offer a practical approach to drug monitoring.
Purpose of the Study:
- To develop a predictive model for lenalidomide's area under the concentration-time curve (AUC).
- To utilize a limited sampling strategy for predicting lenalidomide AUC in MM patients.
- To assess the impact of renal function on lenalidomide pharmacokinetics.
Main Methods:
- Collected whole-blood samples from 46 hospitalized Japanese MM patients.
- Measured lenalidomide plasma concentrations at multiple time points (0-24 hours) post-administration.
- Utilized liquid chromatography-tandem mass spectrometry for precise drug quantification.
Main Results:
- A single plasma concentration at 8 hours (C8h) showed good correlation with measured AUC0-24 (r=0.832).
- Incorporating creatinine clearance (CCr) improved prediction accuracy.
- A two-point sampling model (C0h and C4h) combined with CCr yielded the highest correlation (r=0.842).
Conclusions:
- Lenalidomide AUC can be reliably predicted using plasma concentrations at C0h and C4h, plus CCr.
- This LSS approach aids in identifying patients with renal impairment and potential drug accumulation.
- The model supports personalized lenalidomide dosing and monitoring in MM patients.
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