$ git clone  MMPKSciML
$ cd MMPKSciML

├── LICENSE
├── README.md                  
├── data
│   ├── 5fu.csv                <- 5FU dataset.
│   ├── Sunitinib              <- Sunitinib dataset.
│       └── ... .csv           <- csv files
│
├── models                     <- Trained models. The code generate all the folders as follows:
│   ├── 5FU                    <- Trained models on the 5FU dataset
│       └──Exp name            <- Folder with all the results for a specific experiment
│   └── Sunitinib              <- Trained models on the Sunitinib dataset
│       └──Exp name            <- Folder with all the results for a specific experiment
│
│
├── 5FU                        <- Code for all the models using the 5FU dataset
│   ├── MMPKSCIML              <- Code for the MMPK-SciML model
│   ├── Classic_ML             <- Code for the classic Machine Learning models
│   └── PopPK                  <- Code for the PopPK model
│
├── Sunitinib                  <- Code for all the models using the Sunitinib dataset
│   ├── MMPKSCIML              <- Code for the MMPK-SciML model
│   ├── Classic_ML             <- Code for the classic Machine Learning models
│   └── PopPK                  <- Code for the PopPK model

@article{valderrama2024integrating,
  title={Integrating machine learning with pharmacokinetic models: Benefits of scientific machine learning in adding neural networks components to existing PK models},
  author={Valderrama, Diego and Ponce-Bobadilla, Ana Victoria and Mensing, Sven and Fr{\"o}hlich, Holger and Stodtmann, Sven},
  journal={CPT: Pharmacometrics \& Systems Pharmacology},
  volume={13},
  number={1},
  pages={41--53},
  year={2024},
  publisher={Wiley Online Library}
}

@article{valderrama2024scientific,
  title={Scientific machine learning for predicting plasma concentrations in anti-cancer therapy},
  author={Valderrama, Diego and Teplytska, Olga and Koltermann, Luca Marie and Trunz, Elena and Schmulenson, Eduard and Fritsch, Schim and Jaehde, Ulrich and Froehlich, Holger},
  journal={medRxiv}, 
  pages={2024--05},
  year={2024}, 
  publisher={Cold Spring Harbor Laboratory Press}
}