{
  "abstract": "Voriconazole (VRCZ) exhibits highly variable pharmacokinetics. Although CYP2C19 poor metabolizers are common in Japan, routine genetic testing is rarely performed in daily clinical practice. Consequently, existing population pharmacokinetic (Pop-PK) models that lack genetic data require external validation in Japanese clinical settings. This study aimed to identify the most accurate nongenetic Pop-PK model for this population and elucidate the factors influencing prediction errors. We retrospectively analyzed 174 adult inpatients who received VRCZ within the first 14 d of therapy. Eight Pop-PK models were evaluated using prediction error metrics and specific clinical criteria. For the best-performing model, normalized prediction distribution error (NPDE) analysis was conducted. Subsequently, a classification and regression tree (CART) analysis with leave-one-out cross-validation (LOOCV) was performed to identify factors associated with prediction accuracy. Model H, incorporating the albumin-bilirubin (ALBI) score, performed best (relative root mean square error 2.97, criteria 33.91%, median prediction error (MDPE) -29.06%). However, NPDE analysis (mean 0.774, variance 2.394) revealed residual systematic underprediction and substantial unmodeled variability. CART analysis identified C-reactive protein (CRP) as the primary determinant of accuracy. While the best model (age, platelet count, serum creatinine, and CRP) achieved a training accuracy of 69.5%, internal validation via LOOCV yielded an accuracy of 56.9% and a multi-class area under the receiver operating characteristic curve of 0.568. While the ALBI-score-based Model H is the most accurate, predictions remain limited in high-inflammation states due to inherent stochastic variability. Stratifying patients by baseline CRP level is crucial for optimizing the initial VRCZ dosing.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": null,
  "author_total": 5,
  "authors": [
    {
      "name": "Yumi Uemura"
    },
    {
      "name": "Toshiaki Komatsu"
    },
    {
      "name": "Airi Suzuki"
    },
    {
      "name": "Yuto Akamada"
    },
    {
      "name": "Katsuya Otori"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/5xqxq875f48rq.bib",
  "cited_by": 0,
  "doi": "10.1248/bpb.b26-00183",
  "fulltext_url": "https://www.jstage.jst.go.jp/article/bpb/49/7/49_b26-00183/_article",
  "id": "5xqxq875f48rq",
  "issns": [
    "1347-5215",
    "0918-6158"
  ],
  "landing_url": "https://www.jstage.jst.go.jp/article/bpb/49/7/49_b26-00183/_article",
  "language": null,
  "licence": "CC-BY-NC",
  "licence_label": "CC BY-NC",
  "licence_source": "journal",
  "licence_url": "https://creativecommons.org/licenses/by-nc/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "jstage-journal",
      "medicine/pharmacology-toxicology"
    ],
    [
      "openalex",
      "3004|Pharmacogenetics and Drug Metabolism"
    ]
  ],
  "openalex": "W7167665575",
  "pdf_url": "https://www.jstage.jst.go.jp/article/bpb/49/7/49_b26-00183/_pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-07-09",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/5xqxq875f48rq.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:32Z",
      "native_id": "10.1248/bpb.b26-00183",
      "source": "jstage",
      "url": "https://www.jstage.jst.go.jp/article/bpb/49/7/49_b26-00183/_article"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "openalex:3004|Pharmacogenetics and Drug Metabolism",
      "subfield": "pharmacology-toxicology"
    }
  ],
  "title": "Evaluation of Voriconazole Population Pharmacokinetics in Japanese Patients and Factors Influencing Prediction Accuracy: A Machine Learning Approach",
  "title_text": "Evaluation of Voriconazole Population Pharmacokinetics in Japanese Patients and Factors Influencing Prediction Accuracy: A Machine Learning Approach",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:17:32Z",
  "url": "https://research.draconitic.com/paper/5xqxq875f48rq",
  "venue": "Biological and Pharmaceutical Bulletin",
  "versions": []
}