SimpLi: Simulation-Based Standardization of Serum Lithium Concentrations to 12 Hours

Overview This repository provides the full simulation dataset and R code accompanying the study on standardization of serum lithium concentrations measured at non-12-hour time points to a 12-hour reference level. The project introduces SimpLi, a simulation-based and model-driven framework that allows recalculation of serum lithium concentrations measured at arbitrary times after the last dose to a standardized 12-hour level, which is the conventional reference in clinical practice. All data provided here are fully simulated and do not contain any real patient information. Contents Files SimpLi.RMain R script containing: generation of simulation datasets primary (sqrt-normal) and sensitivity (lognormal) scenarios dose generation with predefined correlation structure model training and validation multiplicative standardization formula final web-ready SimpLi() function dat_sqrt_with_discrete_dose_300.csvPrimary simulated dataset (n = 1000) with: discrete lithium doses (300 mg step) serum lithium concentrations time since last dose (hours) time bins matching published summary statistics Simulation Design Sample size: 1000 simulated observations Time since last dose: 0–24 hours Deterministic design ensuring interquartile range 11–14 hours Pronounced peak at 12 hours Serum lithium concentration (seLi, mEq/L): Primary scenario: sqrt-normal distribution Sensitivity scenario: lognormal distribution Dose (dose_mg, mg/day): Generated to match published mean and SD within time bins Target correlation with serum lithium: r ≈ 0.40 Discretized to 300 mg steps with within-bin recalibration Target summary statistics were derived from published aggregate data (Table 1 in the associated article). Statistical Modeling Outcome: serum lithium concentration (mEq/L) Predictors: time since last dose (hours) daily lithium dose (mg/day) Model: seLi=β0+βt⋅t+βd⋅dose\sqrt{\text{seLi}} = \beta_0 + \beta_t \cdot t + \beta_d \cdot \text{dose}seLi=β0+βt⋅t+βd⋅dose Validation strategy: 70/30 train–test split stratified by time bins 5-fold cross-validation on the training set Performance metrics: RMSE, MAE, R² Evaluation both overall and by time bin Multiplicative Standardization to 12 Hours Standardization from an observed concentration CmeasC_{\text{meas}}Cmeas at time tmeast_{\text{meas}}tmeas to a 12-hour level is performed as: C12=C^12×CmeasC^measC_{12} = \hat{C}_{12} \times \frac{C_{\text{meas}}}{\hat{C}_{\text{meas}}}C12=C^12×C^measCmeas where: C^meas\hat{C}_{\text{meas}}C^meas is the model-predicted concentration at the observed time C^12\hat{C}_{12}C^12 is the model-predicted concentration at 12 hours for the same dose This approach preserves individual deviations while adjusting for time-dependent pharmacokinetics. Example Usage (R) source("SimpLi.R") SimpLi( C_meas = 0.90, t_meas = 14.9, dose_mg = 450 ) Intended Use Methodological research on lithium pharmacokinetics Simulation studies and sensitivity analyses Reproducibility of results reported in the accompanying article Educational and methodological demonstration of standardization approaches This code and dataset are not intended for direct clinical decision-making without external validation. Data Availability All data in this repository are synthetic (simulated) and were generated exclusively for methodological and reproducibility purposes.No real patient data were used. Author Evgeny KasyanovEmail: [e-mail]