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Genotype Informed Bayesian Dosing of Tacrolimus in Paediatric Solid Organ Transplant Individuals
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  • Dhrita Khatri,
  • Ben Felmingham,
  • Claire Moore,
  • Smaro Lazarakis,
  • Tayla Stenta,
  • Lane Collier,
  • David Elliott,
  • David Metz,
  • Rachel Conyers
Dhrita Khatri
Murdoch Children's Research Institute
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Ben Felmingham
Murdoch Children's Research Institute
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Claire Moore
Murdoch Children's Research Institute
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Smaro Lazarakis
The Royal Melbourne Hospital City Campus
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Tayla Stenta
Murdoch Children's Research Institute
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Lane Collier
Murdoch Children's Research Institute
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David Elliott
Murdoch Childrens Research Institute
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David Metz
Royal Children's Hospital Research Institute
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Rachel Conyers
Murdoch Childrens Research Institute

Corresponding Author:[email protected]

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Abstract

Tacrolimus, a calcineurin inhibitor, is an effective immunosuppressant for solid organ transplants (SOT). However, its narrow therapeutic index and high variability in pharmacokinetics can lead to inefficacy, toxicities, and suboptimal outcomes. Genotyping for CYP3A5 gene prior to SOT can identify individuals at risk of high or low tacrolimus levels and guide first-dose dosing. Genotype-guided Bayesian dosing uses population pharmacokinetic data and individual patient characteristics to accurately predict the tacrolimus dose required to achieve a target concentration. This can help achieve target tacrolimus concentrations sooner and maintain them within range, reducing risk of organ rejection or tacrolimus toxicity. This review aims to assess the benefits of genotype-guided Bayesian dosing for tacrolimus and its ability to accurately predict tacrolimus dosing, leading to increased maintenance of therapeutic drug exposure in these individuals. This systematic review identified three studies that incorporated genotyping and Bayesian informed methods to predict tacrolimus dosing in the paediatric population post SOT. The studies included 369 kidney, 231 heart, 246 liver and 16 lung transplant individuals. The review found that combination of clinical, demographic, and genetic data has a significant influence on tacrolimus clearance. Combining these parameters allowed the prediction of first dose tacrolimus post SOT and ongoing therapeutic tacrolimus dosing to optimally maintain target tacrolimus levels. In conclusion, personalised tacrolimus dosing models in paediatric SOT can be developed using clinical, demographic, and genetic data to predict first dose and ongoing adjustments to meet therapeutic tacrolimus targets and reduce the risk of under- and over- exposure.