| S01 |
A.-E. Hein, B. Vrijens, and M. Hiligsmann, “A digital innovation for the personalized management of adherence: analysis of strengths, weaknesses, opportunities, and threats,” Frontiers in medical technology, vol. 2, p. 604183, 2020. |
Process / how to improve its applicability |
Opinion Papers |
| S02 |
T. Oommen, A. Thommandram, A. Palanica, and Y. Fossat, “A free open-source bayesian vancomycin dosing app for adults: design and evaluation study,” JMIR Formative Research, vol. 6, no. 3, p. e30577, 2022. |
Implementation or evaluation of software tool |
Evaluation Research |
| S03 |
X. Zhu, J. Hu, T. Xiao, S. Huang, Y. Wen, and D. Shang, “An interpretable stacking ensemble learning framework based on multi-dimensional data for real-time prediction of drug concentration: the example of olanzapine,” Frontiers in Pharmacology, vol. 13, p. 975855, 2022. |
Proposal of method or technique |
Solution Proposal |
| S04 |
J. S. Barrett, “Asking more of our EHR systems to improve outcomes for pediatric patients,” Frontiers in Pharmacology, vol. 11, p. 253, 2020. |
Process / how to improve its applicability |
Opinion Papers |
| S05 |
J. H. Hughes, D. M. Tong, V. Burns, B. Daly, P. Razavi, J. J. Boelens, S. Goswami, and R. J. Keizer, “Clinical decision support for chemotherapy-induced neutropenia using a hybrid pharmacodynamic/machine learning model,” CPT: Pharmacometrics & Systems Pharmacology, vol. 12, no. 11, pp. 1764–1776, 2023. |
Proposal of method or technique |
Validation Research |
| S06 |
J. H. Hughes, K. H. Woo, R. J. Keizer, and S. Goswami, “Clinical decision support for precision dosing: opportunities for enhanced equity and inclusion in health care,” Clinical Pharmacology & Therapeutics, vol. 113, no. 3, pp. 565–574, 2023. |
Process / how to improve its applicability |
Opinion Papers |
| S07 |
T. Mizuno, M. Dong, Z. L. Taylor, L. B. Ramsey, and A. A. Vinks, “Clinical implementation of pharmacogenetics and model-informed precision dosing to improve patient care,” British Journal of Clinical Pharmacology, vol. 88, no. 4, pp. 1418–1426, 2022. |
Concrete experience |
Experience Papers |
| S08 |
M. B. Oliver, K. D. Boeser, M. K. Carlson, and L. A. Hansen, “Considerations for implementation of vancomycin bayesian software monitoring in a level iv nicu population within a multisite health system,” American Journal of Health-System Pharmacy, vol. 80, no. 11, pp. 670–677, 2023. |
Concrete experience |
Experience Papers |
| S09 |
A. A. Vinks, R. W. Peck, M. Neely, and D. R. Mould, “Development and implementation of electronic health record–integrated model-informed clinical decision support tools for the precision dosing of drugs,” Clinical Pharmacology & Therapeutics, vol. 107, no. 1, pp. 129–135, 2020. |
Process / how to improve its applicability |
Opinion Papers |
| S10 |
V. Reinisch, A. Paudel, and J. T. Pinto, “Development of a digital interface for personalized dosing in renal impaired patients: a case-study using the ace-inhibitor benazepril,” in dHealth 2023. IOS Press, 2023, pp. 133–139. |
Implementation or evaluation of software tool |
Solution Proposal |
| S11 |
A. A. Vinks, N. C. Punt, F. Menke, E. Kirkendall, D. Butler, T. J. Duggan, D. E. Cortezzo, S. Kiger, T. Dietrich, P. Spencer et al., “Electronic health record–embedded decision support platform for morphine precision dosing in neonates,” Clinical Pharmacology & Therapeutics, vol. 107, no. 1, pp. 186–194, 2020. |
Implementation or evaluation of software tool |
Solution Proposal |
| S12 |
R. Lawson, L. Paterson, C. J. Fraser, and S. Hennig, “Evaluation of two software using bayesian methods for monitoring exposure and dosing once-daily intravenous busulfan in paediatric patients receiving haematopoietic stem cell transplantation,” Cancer chemotherapy and pharmacology, vol. 88, no. 3, pp. 379–391, 2021. |
Validation or evaluation of models |
Evaluation Research |
| S13 |
C. Leven, A. Coste, and C. Mané, “Free and open-source posologyr software for bayesian dose individualization: an extensive validation on simulated data,” Pharmaceutics, vol. 14, no. 2, p. 442, 2022. |
Implementation or evaluation of software |
Validation Research |
| S14 |
S. G. Wicha, A.-G. Märtson, E. I. Nielsen, B. C. Koch, L. E. Friberg, J.-W. Alffenaar, I. K. Minichmayr, and I. D. E. International Society of Anti-Infective Pharmacology (ISAP), the PK/PD study group of the European Society of Clinical Microbiology, “From therapeutic drug monitoring to model-informed precision dosing for antibiotics,” Clinical Pharmacology & Therapeutics, vol. 109, no. 4, pp. 928–941, 2021. |
Process / how to improve its applicability |
Evaluation Research |
| S15 |
A. Frymoyer, H. T. Schwenk, J. M. Brockmeyer, and L. Bio, “Impact of model-informed precision dosing on achievement of vancomycin exposure targets in pediatric patients with cystic fibrosis,” Pharmacotherapy: The Journal of Human Pharmacology and Drug Therapy, vol. 43, no. 10, pp. 1007–1014, 2023. |
Concrete experience |
Evaluation Research |
| S16 |
J. Heitzmann, Y. Thoma, R. Bricca, M.-C. Gagnieu, V. Leclerc, S. Roux, A. Conrad, T. Ferry, and S. Goutelle, “Implementation and comparison of two pharmacometric tools for model-based therapeutic drug monitoring and precision dosing of daptomycin,” Pharmaceutics, vol. 14, no. 1, p. 114, 2022. |
Validation or evaluation of models |
Evaluation Research |
| S17 |
S. Goutelle, Y. Thoma, R. Buffet, M. Philippe, T. Buclin, M. Guidi, and C. Csajka, “Implementation and cross-validation of a pharmacokinetic model for precision dosing of busulfan in hematopoietic stem cell transplanted children,” Pharmaceutics, vol. 14, no. 10, p. 2107, 2022. |
Validation or evaluation of models |
Validation Research |
| S18 |
A. Oni-Orisan, N. Srinivas, K. Mehta, J. L. Das, T. T. Nguyen, G. H. Tison, S. R. Bauer, M. Burian, R. S. Funk, R. A. Graham et al., “Leveraging innovative technology to generate drug response phenotypes for the advancement of biomarker-driven precision dosing,” Clinical and translational science, vol. 14, no. 3, pp. 784–790, 2021. |
Process / how to improve its applicability |
Opinion Papers |
| S19 |
A. S. Darwich, T. M. Polasek, J. K. Aronson, K. Ogungbenro, D. F. Wright, B. Achour, J.-L. Reny, Y. Daali, B. Eiermann, J. Cook et al., “Model-informed precision dosing: background, requirements, validation, implementation, and forward trajectory of individualizing drug therapy,” Annual review of pharmacology and toxicology, vol. 61, no. 1, pp. 225–245, 2021. |
Process / how to improve its applicability |
Solution Proposal |
| S20 |
A. Frymoyer, H. T. Schwenk, Y. Zorn, L. Bio, J. D. Moss, B. Chasmawala, J. Faulkenberry, S. Goswami, R. J. Keizer, and S. Ghaskari, “Model-informed precision dosing of vancomycin in hospitalized children: implementation and adoption at an academic children’s hospital,” Frontiers in pharmacology, vol. 11, p. 551, 2020. |
Concrete experience |
Experience Papers |
| S21 |
P. Del Valle-Moreno, P. Suarez-Casillas, M. Mejías-Trueba, P. Ciudad-Gutiérrez, A. B. Guisado-Gil, M. V. Gil-Navarro, and L. Herrera-Hidalgo, “Model-informed precision dosing software tools for dosage regimen individualization: a scoping review,” Pharmaceutics, vol. 15, no. 7, p. 1859, 2023. |
Implementation or evaluation of software |
Evaluation Research |
| S22 |
C. Langebrake, K. Gottfried, A. Dadkhah, J. Eggert, T. Gutowski, M. Rosch, N. Schönbeck, C. Gundler, S. Nürnberg, F. Ückert et al., “Patient-individual 3d-printing of drugs within a machine-learning-assisted closed-loop medication management–design and first results of a feasibility study,” Clinical eHealth, vol. 6, pp. 3–9, 2023. |
Proposal of method or technique |
Evaluation Research |
| S23 |
F. Kluwe, R. Michelet, A. Mueller-Schoell, C. Maier, L. Klopp-Schulze, M. van Dyk, G. Mikus, W. Huisinga, and C. Kloft, “Perspectives on model-informed precision dosing in the digital health era: challenges, opportunities, and recommendations,” Clinical Pharmacology & Therapeutics, vol. 109, no. 1, pp. 29–36, 2021. |
Process / how to improve its applicability |
Opinion Papers |
| S24 |
K. B. Hassine, C. Seydoux, S. Khier, Y. Daali, M. Medinger, J. Halter, D. Heim, Y. Chalandon, U. Schanz, G. Nair et al., “Pharmacokinetic modeling and simulation with pharmacogenetic insights support the relevance of therapeutic drug monitoring for myeloablative busulfan dosing in adult hsct,” Transplantation and Cellular Therapy, vol. 30, no. 3, pp. 332–e1, 2024. |
Validation or evaluation of models |
Evaluation Research |
| S25 |
D. Gonzalez, G. G. Rao, S. C. Bailey, K. L. Brouwer, Y. Cao, D. J. Crona, A. D. Kashuba, C. R. Lee, K. Morbitzer, J. H. Patterson et al., “Precision dosing: public health need, proposed framework, and anticipated impact,” Clinical and translational science, vol. 10, no. 6, p. 443, 2017. |
Process / how to improve its applicability |
Solution Proposal |
| S26 |
N. G. Jager, M. G. Chai, R. M. van Hest, J. Lipman, J. A. Roberts, and M. O. Cotta, “Precision dosing software to optimize antimicrobial dosing: a systematic search and follow-up survey of available programs,” Clinical Microbiology and Infection, vol. 28, no. 9, pp. 1211–1224, 2022. |
Implementation or evaluation of software |
Evaluation Research |
| S27 |
M. Briki, P. André, Y. Thoma, N. Widmer, A. D. Wagner, L. A. Decosterd, T. Buclin, M. Guidi, and S. Carrara, “Precision oncology by point-of-care therapeutic drug monitoring and dosage adjustment of conventional cytotoxic chemotherapies: A perspective,” Pharmaceutics, vol. 15, no. 4, p. 1283, 2023. |
Process / how to improve its applicability |
Opinion Papers |
| S28 |
R. Kalamees, H. Soeorg, M.-L. Ilmoja, K. Margus, I. Lutsar, and T. Metsvaht, “Prospective validation of a model-informed precision dosing tool for vancomycin treatment in neonates,” Antimicrobial Agents and Chemotherapy, vol. 68, no. 5, pp. e01 591–23, 2024. |
Implementation or evaluation of software |
Validation Research |
| S29 |
A. Power-Hays, M. Dong, N. Punt, T. Mizuno, L. R. Smart, A. A. Vinks, and R. E. Ware, “Rationale, development, and validation of hdxsim, a clinical decision support tool for model-informed precision dosing of hydroxyurea for children with sickle cell anemia,” Clinical Pharmacology & Therapeutics, vol. 116, no. 3, pp. 670–677, 2024. |
Implementation or evaluation of software |
Evaluation Research |
| S30 |
Y. Xiong, T. Mizuno, R. Colman, J. Hyams, J. D. Noe, B. Boyle, Y.- T. Tsai, M. Dong, K. Jackson, N. Punt et al., “Real-world infliximab pharmacokinetic study informs an electronic health record-embedded dashboard to guide precision dosing in children with crohn’s disease,” Clinical Pharmacology & Therapeutics, vol. 109, no. 6, pp. 1639–1647, 2021. |
Concrete experience |
Evaluation Research |
| S31 |
B. Ribba, “Reinforcement learning as an innovative model-based approach: Examples from precision dosing, digital health and computational psychiatry,” Frontiers in Pharmacology, vol. 13, p. 1094281, 2023. |
Proposal of method or technique |
Solution Proposal |
| S32 |
W. Kantasiripitak, R. Van Daele, M. Gijsen, M. Ferrante, I. Spriet, and E. Dreesen, “Software tools for model-informed precision dosing: how well do they satisfy the needs?” Frontiers in Pharmacology, vol. 11, p. 620, 2020. |
Implementation or evaluation of software |
Evaluation Research |
| S33 |
J. C. Euteneuer, S. Kamatkar, T. Fukuda, A. A. Vinks, and H. T. Akinbi, “Suggestions for model-informed precision dosing to optimize neonatal drug therapy,” The Journal of Clinical Pharmacology, vol. 59, no. 2, pp. 168–176, 2019. |
Process / how to improve its applicability |
Solution Proposal |
| S34 |
P. Jarugula, S. Scott, V. Ivaturi, A. Noack, B. S. Moffett, A. Bhutta, and J. V. Gobburu, “Understanding the role of pharmacometrics-based clinical decision support systems in pediatric patient management: A case study using lyv software,” The Journal of Clinical Pharmacology, vol. 61, pp. S125–S132, 2021. |
Process / how to improve its applicability |
Validation Research |
| S35 |
T. M. Polasek, “Virtual twin for healthcare management,” Frontiers in Digital Health, vol. 5, p. 1246659, 2023. |
Proposal of method or technique |
Solution Proposal |
