Kalman filtering for tacrolimus dose titration in the early hospital course after kidney transplant
Creators: name: Norris, David C.
name: Gohh, Reginald Y.
name: Akhlaghi, Fatemeh
name: Morrissey, Paul E.
Publisher: name: F1000Research
Year: 2017

description: PROBLEM<br><br>The calcineurin inhibitors are the most widely used class of immunosuppressant after solid organ transplant, yet they are pharmacologically troublesome agents. Their narrow therapeutic windows necessitate therapeutic drug monitoring (TDM), which is markedly complicated by the pharmacokinetic variability of these agents across populations and even within individuals over time.<br><br>HYPOTHESES	A rigorous, model-based dose titration algorithm will outperform standard informal dose titration done without support from a formal decision aid.	The intra-individual pharmacokinetic variability of the calcineurin inhibitors strongly indicates application of adaptive algorithms such as the Kalman Filter (KF).	A Kalman Filter-based dose titration algorithm will prove robust to model misspecification.	The technique is conceptually intuitive enough to be readily accepted by practitioners.<br><br>METHODS	IRB approval was obtained for retrospective review of inpatient medical records for kidney transplants at Rhode Island Hospital in the years 2005-2010.	We retrospectively studied tacrolimus dose titration courses of 32 kidney transplant recipients, selected for uniformity in the protocols applied to immunosuppression and dose titration. Each subject had received basiliximab induction, tacrolimus, mycophenylate mofetil and prednisone; each subject's tacrolimus dose had been titrated by a clinical protocol targeting trough blood levels of 8-12 ng/mL by post-operative day 4.	For each subject separately, an extended Kalman filter was applied to estimate a one-compartment pharmacokinetic model against the time series of that subject’s recorded doses and measured drug levels. This yielded for each subject a running estimate of the twice-daily dose needed to achieve a target trough concentration C<sub>12</sub> of 10 ng/mL.	A counterfactual exercise was undertaken, in which these running estimates – regarded as KF-suggested dosing – were contrasted graphically with the actual dosing, in light of actual drug concentrations achieved.<br><br>RESULTS<br><br>In half (16/32) of our cohort, actual and KF-suggested dosing largely coincided. In the remainder, KF dosing appeared superior for 10 subjects, and inferior for 6.<br><br>DISCUSSION<br><br>TDM in our cohort was done every 24 hours, on roughly a C<sub>9</sub> basis; 70% of draws were done 9±1.5 hours after the previous dose. This regular TDM timing offered us insufficient degrees of freedom to simultaneously estimate both compartmental volume V<sub>1</sub>/F and elimination half-life τ<sub>1/2</sub> in our pharmacokinetic model. We therefore fixed V<sub>1</sub>/F at 3L per kg body mass, leaving τ<sub>1/2</sub> as the sole free parameter of the model. As hypothesized, the Kalman filter performed well, despite what was surely a grossly misspecified model. We credit this to the adaptive nature of the filter.<br><br>A key insight from this effort is that scheduling TDM at whole-number multiples of the dosing cycle poorly supports model-based dosing. Prospective studies of adaptive filters may benefit from TDM scheduled every 18 hours, to sample (alternately) two points on the elimination curve – say C<sub>6</sub> and C<sub>12</sub>. Of course, in a sufficiently sophisticated approach to this problem, TDM scheduling will itself be adaptive and model-driven. <br><br>CONCLUSION<br><br>The Kalman filter appears capable of performing at least on par with experienced clinicians in tacrolimus titration. Good reason exists to evaluate our approach prospectively, under a TDM regime favorable to simultaneous estimation of both free parameters of our pharmacokinetic model.<br><br>REFERENCES	Botsman K, Tickle K, Smith JD. A Bayesian formulation of the Kalman filter applied to the estimation of individual pharmacokinetic parameters. <i>Comput. Biomed. Res.</i> 1997;30(2):83-9.	<br>	Asberg A, Falck P, Undset LH, et al. Computer-assisted cyclosporine dosing performs better than traditional dosing in renal transplant recipients: results of a pilot study. <i>Ther Drug Monit.</i> 2010;32(2):152-158.<br>ACKNOWLEDGEMENTS<br><br>Steven Reinert, of Lifespan IS, offered essential assistance with access to electronic medical record data.