Journal: Clinical and Translational Science

Article Title: Physiologically‐Based Pharmacokinetic Modeling to Investigate Piperaquine Exposure in Pregnant Women Using an Individualized Profile Approach

doi: 10.1111/cts.70589

Figure Lengend Snippet: Overview of the workflow for physiologically‐based pharmacokinetic modeling of piperaquine for a pregnant population using an individualized profile (‘virtual twin’) approach.

Article Snippet: The piperaquine PBPK model was previously developed and validated within Simcyp for a healthy non‐pregnant population.

Techniques:

Journal: Clinical and Translational Science

Article Title: Physiologically‐Based Pharmacokinetic Modeling to Investigate Piperaquine Exposure in Pregnant Women Using an Individualized Profile Approach

doi: 10.1111/cts.70589

Figure Lengend Snippet: Individual piperaquine normalized AUC ratios ( R AUC / Dose ) for the first dose (blue solid line) and last dose (blue dotted line) in (a) Sudanese pregnant women, second trimester; (b) Sudanese pregnant women, third trimester; (c) Thai pregnant women, second trimester; (d) Thai pregnant women, third trimester. Internal gray line: R AUC = 0 , middle gray line: R AUC = 1 , and external gray line: R AUC = 2 . ID, identification number for the women included in the clinical trials. ID = patient identification number.

Article Snippet: The piperaquine PBPK model was previously developed and validated within Simcyp for a healthy non‐pregnant population.

Techniques: Clinical Proteomics

Journal: Clinical and Translational Science

Article Title: Physiologically‐Based Pharmacokinetic Modeling to Investigate Piperaquine Exposure in Pregnant Women Using an Individualized Profile Approach

doi: 10.1111/cts.70589

Figure Lengend Snippet: Mean plasma concentration–time plots for piperaquine in plasma in representative individualized profiles compared to observed data for (a) a Sudanese pregnant woman (second trimester, patient ID7), and (b) a Thai pregnant woman (second trimester, patient ID6). The shaded area is 95% prediction interval.

Article Snippet: The piperaquine PBPK model was previously developed and validated within Simcyp for a healthy non‐pregnant population.

Techniques: Clinical Proteomics, Concentration Assay

Journal: Clinical and Translational Science

Article Title: Physiologically‐Based Pharmacokinetic Modeling to Investigate Piperaquine Exposure in Pregnant Women Using an Individualized Profile Approach

doi: 10.1111/cts.70589

Figure Lengend Snippet: Predicted vs. observed piperaquine clearance up to Day 7 in (a) Sudanese pregnant women, and (b) Thai pregnant women. The central line is the median, the box represents the interquartile range, the cross is the mean, and the whiskers are the lowest and highest values.

Article Snippet: The piperaquine PBPK model was previously developed and validated within Simcyp for a healthy non‐pregnant population.

Techniques:

Journal: Clinical and Translational Science

Article Title: Physiologically‐Based Pharmacokinetic Modeling to Investigate Piperaquine Exposure in Pregnant Women Using an Individualized Profile Approach

doi: 10.1111/cts.70589

Figure Lengend Snippet: Piperaquine concentrations on Day 7 for (a) individual predicted vs. observed plasma concentrations and predictive performance assessed by (b) prediction error (PE), and (c) relative difference (RD). The central line is the median, the box represents the interquartile range, the cross is the mean, and the whiskers are the lowest and highest values. All the predicted concentrations were normalized by the actual mg/kg dose administered to the patient. T2 = second trimester; T3 = third trimester.

Article Snippet: The piperaquine PBPK model was previously developed and validated within Simcyp for a healthy non‐pregnant population.

Techniques: Clinical Proteomics

Journal: CPT: Pharmacometrics & Systems Pharmacology

Article Title: Open Systems Pharmacology Community Conference ( OSP ‐ CC ) Proceedings 2025

doi: 10.1002/psp4.70217

Figure Lengend Snippet: OSP Extension Module concept. PK‐Sim models are composed of individual Building Blocks ( https://docs.open‐systems‐pharmacology.org/v12/open‐systems‐pharmacology‐suite/modules‐philsophy‐building‐blocks ) separating information used for model building into dedicated groups. Building Blocks are combined to generate a model, they can be reused and combined to create different models. When transferring a PK‐SIM simulation to MoBi, model Building Blocks are further organized into a module. Modules represent either a full‐scale PBPK model imported from PK‐Sim (blue rectangle), or extension modules (orange rectangles) that represent model modifications or adaptations such as disease populations, custom administration routes, altered or new special structures that represent tissues or any other modification of the underlaying Building Blocks. Extension Modules provide a standardized, systematic, and reproducible way to efficiently develop and share complex models or model modifications across different projects and modeling scientists.

Article Snippet: Systematic development of PBPK models to support candidate selection and accelerate drug discovery , Grégori Gerebtzoff (Novartis).

Techniques: Transferring, Modification