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Updated: May 4, 2026
08:38
Quantification of the Immunosuppressant Tacrolimus on Dried Blood Spots Using LC-MS/MS
Published on: November 8, 2015
16.8K
Long short-term memory algorithm for personalized tacrolimus dosing: A simple and effective time series forecasting
Haruki Choshi1, Kentaroh Miyoshi1, Maki Tanioka2
1Department of General Thoracic Surgery and Breast and Endocrinological Surgery, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama, Japan.
Summary
A new tool accurately predicts tacrolimus trough levels (TTLs) using only historical dosing data. This simplifies monitoring and aids clinical decision-making in lung transplant patients.
Area of Science:
- Immunology
- Pharmacology
- Biomedical Engineering
Background:
- Tacrolimus trough levels (TTLs) are critical for lung transplant outcomes.
- Existing monitoring models often require complex variables not routinely available.
- This study explores a simplified approach to TTL prediction.
Purpose of the Study:
- To develop and validate a novel method for predicting tacrolimus trough levels.
- To assess the efficacy of using only time series dosing data for TTL forecasting.
- To create a tool for simulating TTLs and supporting clinical decisions.
Main Methods:
- A multivariate long short-term memory algorithm was employed.
- The model utilized time series data of tacrolimus dosing and prior trough levels.
- Development involved 87,112 data points from 117 patients, validated on 6 cases.
Main Results:
- The model accurately predicted TTLs within 30% of actual values for 88.5% of time points.
- Shapley additive explanations confirmed the strong correlation between trough levels and prior dose-concentration data.
- The developed tool demonstrated potential in rectifying clinical misjudgments in simulations.
Conclusions:
- Precise prediction of tacrolimus trough levels is achievable using only historical dose-concentration trends.
- The time series forecasting tool offers a simplified, effective method for TTL management.
- This approach is independent of complex clinical variables, enhancing accessibility.
Keywords:
artificial Intelligencelong short-term memorylung transplantationpredictiontacrolimus trough levelMore Related Videos
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