ArticleClinical pharmacology and therapeutics2023
Prediction of Busulfan Clearance by Predose Plasma Metabolomic Profiling.
Article in Clinical pharmacology and therapeutics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
12 citing papers in PubMed, 1 synthesis or guideline pooled it, 15 citations in OpenAlex.
- Population Pharmacokinetic Model of Intravenous Busulfan in Hematopoietic Cell Transplantation: Systematic Review and Comparative Simulations.Clinical pharmacokinetics · 2023Pooled it
- Comparing the Predictive Performance of Machine Learning Models with a Newly Developed Population Pharmacokinetic Model for Busulfan in Paediatric Patients.Clinical pharmacokinetics · 2026Article
- Machine Learning-Integrated Metabolomics for Precision Pharmacotherapy: Advances, Challenges, and Clinical Translation.Metabolites · 2026Review
- Model-Informed Precision Dosing of Busulfan for Children and Adults Undergoing Allogeneic Hematopoietic Stem Cell Transplantation: A Critical Evaluation of Current PK Models and Dose Recommendations.Clinical pharmacology and therapeutics · 2025Article
- Predicting Vancomycin Clearance in Neonates and Infants by Integrating Machine Learning and Metabolomics With Population Pharmacokinetics.Clinical and translational science · 2025Article
- Advancements in Mass Spectrometry-Based Targeted Metabolomics and Lipidomics: Implications for Clinical Research.Molecules (Basel, Switzerland) · 2024Review
- Maximum a posteriori Bayesian methods out-perform non-compartmental analysis for busulfan precision dosing.Journal of pharmacokinetics and pharmacodynamics · 2024Article
- Push forward LC-MS-based therapeutic drug monitoring and pharmacometabolomics for anti-tuberculosis precision dosing and comprehensive clinical management.Journal of pharmaceutical analysis · 2024Review
- The presence of busulfan metabolites and pharmacometabolomics in plasma drawn immediately before allograft infusion in hematopoietic cell transplant recipients.Clinical and translational science · 2023Article
- Pharmacokinetics in Pharmacometabolomics: Towards Personalized Medication.Pharmaceuticals (Basel, Switzerland) · 2023Review
- Pharmacometabolomics of trabectedin in metastatic soft tissue sarcoma patients.Frontiers in pharmacology · 2023Article
- Precision sirolimus dosing in children: The potential for model-informed dosing and novel drug monitoring.Frontiers in pharmacology · 2023Review
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Authors and funding
13 authors at 4 institutions in 2 countries.
Funding
Abstract
Intravenous busulfan doses are often personalized to a target plasma exposure (targeted busulfan) using an individual's busulfan clearance (BuCL). We evaluated whether BuCL could be predicted by a predose plasma panel of 841 endogenous metabolomic compounds (EMCs). In this prospective cohort of 132 hematopoietic cell transplantation (HCT) patients, all had samples collected immediately before busulfan administration (preBU) and 96 had samples collected 2 weeks before busulfan (2-week-preBU). BuCL was significantly associated with 37 EMCs after univariate linear regression analysis and controlling for false discovery (< 0.05) in the 132 preBU samples. In parallel, with preBU samples, we included all 841 EMCs in a least absolute shrinkage and selection operator-penalized regression which selected 13 EMCs as predominantly associated with BuCL. Then, we constructed a prediction model by estimating coefficients for these 13 EMCs, along with sex, using ordinary least-squares. When the resulting linear prediction model was applied to the 2-week-preBU samples, it explained 40% of the variation in BuCL (adjusted R
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.