Precision Dosing – Clinical Decision Support Tools

The Clinical Pharmacy group at Saarland University develops open-access, web-based clinical decision support tools that translate pharmacometric research into practical applications for individualized drug therapy. Our tools integrate population pharmacokinetic (popPK) and physiologically-based pharmacokinetic (PBPK) models with patient-specific data — including genetics, co-medications, and clinical parameters — to support evidence-based dosing decisions.

All tools are freely available for research and educational purposes. They are intended to support — not replace — clinical judgment.

DDGI Decision Support System

Link:dss.precisiondosing.de

The Drug-Drug-Gene Interaction (DDGI) Decision Support System is a key deliverable of the SafePolyMed project — an EU Horizon-funded consortium (Grant No. 101057639) coordinated by Prof. Dr. Thorsten Lehr. SafePolyMed brings together twelve European partner institutions with the goal of improving medication safety in patients taking multiple drugs (polypharmacy). The project combines machine learning on real-world data, pharmacogenomic profiling, and mechanistic PBPK modeling to identify patients at risk of adverse drug reactions and to provide individualized dose recommendations.

The DSS translates this research into a practical clinical tool. It currently integrates PBPK models for imatinib, paroxetine, tacrolimus, and voriconazole, accounting for key CYP450 polymorphisms (CYP2C19, CYP2D6, CYP3A5) and clinically relevant drug-drug interactions. Clinicians can enter patient demographics, genetic phenotypes, measured drug concentrations, and dosing histories to obtain model-informed dose adaptation recommendations with downloadable reports.

Underlying PBPK model publications:

  • Ruedesheim S, Loer HLH, Feick D, et al. A Comprehensive CYP2D6 Drug-Drug-Gene Interaction Network for Application in Precision Dosing and Drug Development. Clin Pharmacol Ther. 2025;117(6):1718–1731. doi:10.1002/cpt.3604
  • Loer HLH, Feick D, Ruedesheim S, et al. Physiologically based pharmacokinetic modeling of tacrolimus for food-drug and CYP3A drug-drug-gene interaction predictions. CPT Pharmacometrics Syst Pharmacol. 2023;12(5):724–738. doi:10.1002/psp4.12946
  • Loer HLH, Feick D, Ruedesheim S, et al. Physiologically based pharmacokinetic modeling of imatinib and N-desmethyl imatinib for drug-drug interaction predictions. CPT Pharmacometrics Syst Pharmacol. 2024;13(6):926–940. doi:10.1002/psp4.13127
  • Li X, Frechen S, Moj D, Lehr T, et al. A Physiologically Based Pharmacokinetic Model of Voriconazole Integrating Time-Dependent Inhibition of CYP3A4, Genetic Polymorphisms of CYP2C19 and Predictions of Drug-Drug Interactions. Clin Pharmacokinet. 2020;59(6):781–808. doi:10.1007/s40262-019-00856-z

Precise Platelets – Platelet Engraftment Predictor

Link:hsct.precisiondosing.de

Precise Platelets is a prediction tool for platelet engraftment following hematopoietic stem cell transplantation (HSCT). Based on patient-specific clinical data — including conditioning regimen, donor type, anti-thymocyte globulin (ATG) dosing, serial platelet counts, and transfusion history — the tool forecasts individual platelet recovery trajectories.

This supports transplant clinicians in anticipating engraftment timing, identifying patients at risk of delayed recovery, and optimizing post-transplant management.

Publication: Goetz KM, Turki AT, Och K, Selzer D, et al. Model-Based Prediction of Clinically Relevant Thrombocytopenia after Allogeneic Hematopoietic Stem Cell Transplantation. Clin Pharmacol Ther. 2025;117(5):1413–1426. doi:10.1002/cpt.3580

Infliximab Dosing Simulator

Link:ifx.precisiondosing.de

This pharmacokinetic simulator predicts serum infliximab concentrations in patients with Crohn’s disease and ulcerative colitis. Built on the validated population PK model by Fasanmade et al. (2011), it allows clinicians to simulate different dose and interval combinations, model stepwise dose escalation strategies, and evaluate whether target trough concentrations are achieved.

The tool accepts patient dosing data and generates concentration-time profiles with downloadable reports to support therapeutic drug monitoring (TDM) workflows.

Publication: Schraepel C, Kovar L, Selzer D, Hofmann U, Tran F, Reinisch W, Schwab M, Lehr T. External Model Performance Evaluation of Twelve Infliximab Population Pharmacokinetic Models in Patients with Inflammatory Bowel Disease. Pharmaceutics. 2021;13(9):1368. doi:10.3390/pharmaceutics13091368

Simvastatin PBPK Simulator

Link:simvastatin.precisiondosing.de

The Simvastatin Therapy Assistant uses a physiologically-based pharmacokinetic (PBPK) model network to simulate drug exposure across the 5–80 mg dose range. It accounts for clinically important drug-drug interactions (clarithromycin, itraconazole, gemfibrozil, rifampicin) and genetic polymorphisms in SLCO1B1, ABCG2, and CYP3A5.

Based on the simulated exposure, the tool calculates dose adjustments required to maintain equivalent systemic exposure when perpetrator drugs or genetic risk factors are present — supporting safe and effective statin therapy.

Publication: Wojtyniak JG, Selzer D, Schwab M, Lehr T. Physiologically Based Precision Dosing Approach for Drug-Drug-Gene Interactions: A Simvastatin Network Analysis. Clin Pharmacol Ther. 2021;109(1):201–211. doi:10.1002/cpt.2111

Mefloquine Exposure Simulator

Link:mefloquine.precisiondosing.de

This simulator models mefloquine pharmacokinetics in pregnant women receiving intermittent preventive treatment for malaria (IPTp). Based on clinical trial data from 264 pregnant women, it predicts concentration-time profiles for both mefloquine enantiomers and the carboxy-metabolite in maternal blood and umbilical cord blood.

Users can define up to 20 dosing events, incorporate interindividual variability with 95% confidence intervals, and export results as PDF, Word, or HTML reports.

Publication: Ramharter M, Schwab M, Mombo-Ngoma G, et al. Population Pharmacokinetics of Mefloquine Intermittent Preventive Treatment for Malaria in Pregnancy in Gabon. Antimicrob Agents Chemother. 2019;63(2):e01113-18. doi:10.1128/AAC.01113-18

Dabigatran Dosing Simulator

Link:dabigatran.precisiondosing.de

This tool supports individualized dosing of dabigatran etexilate, an oral direct thrombin inhibitor widely used for stroke prevention in non-valvular atrial fibrillation and for treatment and prevention of venous thromboembolism. The simulator is based on a population pharmacokinetic model developed from over 9,000 patients in the landmark RE-LY trial and allows clinicians to predict dabigatran plasma concentrations based on patient-specific characteristics such as renal function, age, weight, and concomitant medications.

By relating predicted concentrations to clinical outcomes (ischemic stroke and major bleeding), the tool helps clinicians identify patients who may benefit from dose adjustments — particularly in the context of renal impairment or co-administration of P-glycoprotein inhibitors.

Publications:

  • Liesenfeld KH, Lehr T, Dansirikul C, Reilly PA, Connolly SJ, Ezekowitz MD, Yusuf S, Wallentin L, Haertter S, Staab A. Population pharmacokinetic analysis of the oral thrombin inhibitor dabigatran etexilate in patients with non-valvular atrial fibrillation from the RE-LY trial. J Thromb Haemost. 2011;9(11):2168–2175. doi:10.1111/j.1538-7836.2011.04498.x
  • Reilly PA, Lehr T, Haertter S, Connolly SJ, Yusuf S, Eikelboom JW, Ezekowitz MD, Nehmiz G, Wang S, Wallentin L; RE-LY Investigators. The Effect of Dabigatran Plasma Concentrations and Patient Characteristics on the Frequency of Ischemic Stroke and Major Bleeding in Atrial Fibrillation Patients: The RE-LY Trial. J Am Coll Cardiol. 2014;63(4):321–328. doi:10.1016/j.jacc.2013.07.104

Contact

For questions, collaboration inquiries, or access issues, please contact:
Prof. Dr. Thorsten Lehr
Chair of Clinical Pharmacy, Saarland University
www.uni-saarland.de/lehrstuhl/lehr