Haefliger David, Mina Lynn, Guidi Monia, Marzolini Catia, Thoueille Paul, Rothuizen Laura E, Thoma Yann, Decosterd Laurent A, Guery Benoit, Girardin François R, Buclin Thierry
Service of Clinical Pharmacology, Lausanne University Hospital and University of Lausanne, Rue du Bugnon 17, 1011, Lausanne, Switzerland.
Centre for Research and Innovation in Clinical Pharmaceutical Sciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.
J Antimicrob Chemother. 2025 Mar 3;80(3):840-847. doi: 10.1093/jac/dkaf007.
Model-informed precision dosing (MIPD) combines population pharmacokinetic knowledge with therapeutic drug monitoring (TDM) to optimize dosage adjustment. It could improve target concentration attainment over empirical TDM, still widely practised for broad-spectrum antibiotics.
To evaluate the respective performance of TDM and MIPD in achieving target piperacillin exposure.
Measurements from 80 courses of intermittent piperacillin infusions, each with two TDM samples, were retrospectively submitted to our MIPD software TUCUXI. We considered six dosage adjustment strategies: identical dosage for all (4000 mg q8h), actual initial dosage (chart-based), actual empirical adjustment following first TDM, a priori MIPD-based dosage, a posteriori MIPD-based adjustment after first TDM and MIPD including both TDM measurements. Dosing strategies were compared regarding daily dosage, trough levels distribution and PTA (with target trough 8-32 mg/L).
Median trough concentration fell within 8-32 mg/L for all strategies except a priori MIPD-based dosage (42 mg/L). Distributions of trough concentrations predicted with the six dosage adjustment strategies showed significant differences, with both a posteriori MIPD-based strategies best reducing their standard deviation (P < 0.001). PTA of 32%, 32%, 55%, 29%, 83% and 94% were estimated, respectively for the six strategies (P < 0.001). Poor performance of a priori MIPD-based dosage did not hinder a posteriori MIPD-based strategies from significantly improving target attainment.
Whilst empirical TDM improves exposure standardization and target attainment compared with no TDM, MIPD can still bring further improvement. Prospective trials remain warranted to confirm MIPD benefits not only on target attainment but also on clinical endpoints.
模型指导的精准给药（MIPD）将群体药代动力学知识与治疗药物监测（TDM）相结合，以优化剂量调整。与经验性TDM相比，它可以提高目标浓度的达成率，经验性TDM目前仍广泛应用于广谱抗生素。
评估TDM和MIPD在实现哌拉西林目标暴露方面的各自性能。
回顾性地将80个间歇输注哌拉西林疗程的测量数据（每个疗程有两个TDM样本）输入我们的MIPD软件TUCUXI。我们考虑了六种剂量调整策略：所有人相同剂量（4000mg，每8小时一次）、实际初始剂量（基于图表）、首次TDM后实际经验性调整、基于先验MIPD的剂量、首次TDM后基于后验MIPD的调整以及包括两次TDM测量的MIPD。比较了各给药策略在每日剂量、谷浓度分布和PTA（目标谷浓度为8 - 32mg/L）方面的情况。
除基于先验MIPD的剂量（42mg/L）外，所有策略的中位谷浓度均落在8 - 32mg/L范围内。六种剂量调整策略预测的谷浓度分布显示出显著差异，基于后验MIPD的两种策略在降低标准差方面效果最佳（P < 0.001）。六种策略的PTA分别估计为32%、32%、55%、29%、83%和94%（P < 0.001）。基于先验MIPD的剂量表现不佳并不妨碍基于后验MIPD的策略显著提高目标达成率。
虽然与不进行TDM相比，经验性TDM改善了暴露标准化和目标达成率，但MIPD仍可带来进一步改善。仍有必要进行前瞻性试验，以确认MIPD不仅在目标达成方面，而且在临床终点方面的益处。
