Journal: Journal of Clinical Pharmacology

Article Title: Physiologically Based Pharmacokinetic Modeling Approaches for Patients With SARS‐CoV‐2 Infection: A Case Study With Imatinib

doi: 10.1002/jcph.2065

Figure Lengend Snippet: Summary of Clinical Studies Used to Verify the PBPK Models of Imatinib and Dexamethasone and Comparison Between Clinically Reported Values and PBPK Model Predictions of Key Pharmacokinetics Parameters of the Drugs

Article Snippet: A previously published PBPK model of remdesivir was employed with additional parameter of CYP3A inhibitory constant (K i ) of 0.8 µmol/L, assuming a competitive inhibition of the isoenzymes.

Techniques: Infection

Journal: Journal of Clinical Pharmacology

Article Title: Physiologically Based Pharmacokinetic Modeling Approaches for Patients With SARS‐CoV‐2 Infection: A Case Study With Imatinib

doi: 10.1002/jcph.2065

Figure Lengend Snippet: Physiologically based pharmacokinetic (PBPK) model predictions of total and unbound plasma concentrations of imatinib in patients with gastrointestinal stromal tumor (a, b) and in a patient cohort with severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) (c, d). Comparison of PBPK simulations and clinically observed concentrations of dexamethasone (6 mg) given as a single oral dose in patients with community‐acquired pneumonia (e) and as multiple oral doses in patients with SARS‐CoV‐2 infection (f). Mean simulated concentrations (blue lines) and the prediction interval (5 th to 95 th percentile as gray area) are depicted in linear scale with the corresponding semilogarithmic plots as insets. Clinically observed individual (a‐d, f) and median plasma concentrations (e) are represented by the black circles.

Article Snippet: A previously published PBPK model of remdesivir was employed with additional parameter of CYP3A inhibitory constant (K i ) of 0.8 µmol/L, assuming a competitive inhibition of the isoenzymes.

Techniques: Infection

Journal: Journal of Clinical Pharmacology

Article Title: Physiologically Based Pharmacokinetic Modeling Approaches for Patients With SARS‐CoV‐2 Infection: A Case Study With Imatinib

doi: 10.1002/jcph.2065

Figure Lengend Snippet: Potential Enablers and Barriers to Implementation of a PBPK Modeling Approach for Prediction of Drug Pharmacokinetics in Patients With SARS‐CoV‐2 Infection

Article Snippet: A previously published PBPK model of remdesivir was employed with additional parameter of CYP3A inhibitory constant (K i ) of 0.8 µmol/L, assuming a competitive inhibition of the isoenzymes.

Techniques: In Vivo, Activity Assay, Infection, Derivative Assay, Sampling, Permeability

Journal: CPT: Pharmacometrics & Systems Pharmacology

Article Title: Evaluation of drug–drug interaction potential for pemigatinib using physiologically based pharmacokinetic modeling

doi: 10.1002/psp4.12805

Figure Lengend Snippet: Summary of key input parameters for the pemigatinib physiologically based pharmacokinetic model

Article Snippet: In addition, the pemigatinib PBPK model was further validated by simulation of pemigatinib PK at 6, 9, 13.5, and 20 mg q.d. doses using the Simcyp virtual cancer population, with the study design matching the corresponding phase I study in adults with advanced malignancies.

Techniques: Molecular Weight, Solubility

Journal: CPT: Pharmacometrics & Systems Pharmacology

Article Title: Evaluation of drug–drug interaction potential for pemigatinib using physiologically based pharmacokinetic modeling

doi: 10.1002/psp4.12805

Figure Lengend Snippet: Simulated and observed mean plasma concentration–time profiles of pemigatinib: (a) single oral dose of 4.5 mg pemigatinib in the absence of itraconazole, (b) single oral dose of 13.5 mg pemigatinib in the absence of rifampin, (c) multiple oral dose (6–20 mg) of pemigatinib in patients with cancer. Simulated mean = red solid line; simulated 5% and 95% = red dashed line; observed = black circle

Article Snippet: In addition, the pemigatinib PBPK model was further validated by simulation of pemigatinib PK at 6, 9, 13.5, and 20 mg q.d. doses using the Simcyp virtual cancer population, with the study design matching the corresponding phase I study in adults with advanced malignancies.

Techniques: Clinical Proteomics, Concentration Assay

Journal: CPT: Pharmacometrics & Systems Pharmacology

Article Title: Evaluation of drug–drug interaction potential for pemigatinib using physiologically based pharmacokinetic modeling

doi: 10.1002/psp4.12805

Figure Lengend Snippet: Predicted and observed pemigatinib exposures (geometric mean) for single oral doses of 4.5 or 13.5 mg pemigatinib in healthy volunteers and multiple oral doses of pemigatinib in patients with cancer

Article Snippet: In addition, the pemigatinib PBPK model was further validated by simulation of pemigatinib PK at 6, 9, 13.5, and 20 mg q.d. doses using the Simcyp virtual cancer population, with the study design matching the corresponding phase I study in adults with advanced malignancies.

Techniques:

Journal: CPT: Pharmacometrics & Systems Pharmacology

Article Title: Evaluation of drug–drug interaction potential for pemigatinib using physiologically based pharmacokinetic modeling

doi: 10.1002/psp4.12805

Figure Lengend Snippet: Predicted and observed pemigatinib C max and AUC ratios following a single oral dose of 9 mg pemigatinib tablets with and without itraconazole or rifampin administration

Article Snippet: In addition, the pemigatinib PBPK model was further validated by simulation of pemigatinib PK at 6, 9, 13.5, and 20 mg q.d. doses using the Simcyp virtual cancer population, with the study design matching the corresponding phase I study in adults with advanced malignancies.

Techniques:

Journal: CPT: Pharmacometrics & Systems Pharmacology

Article Title: Evaluation of drug–drug interaction potential for pemigatinib using physiologically based pharmacokinetic modeling

doi: 10.1002/psp4.12805

Figure Lengend Snippet: Simulated and observed plasma concentration–time profiles of a single oral dose of 9 mg pemigatinib when coadministered with (a) itraconazole (200 mg once daily [q.d.]) and (b) rifampin (600 mg q.d.)

Article Snippet: In addition, the pemigatinib PBPK model was further validated by simulation of pemigatinib PK at 6, 9, 13.5, and 20 mg q.d. doses using the Simcyp virtual cancer population, with the study design matching the corresponding phase I study in adults with advanced malignancies.

Techniques: Clinical Proteomics, Concentration Assay

Journal: CPT: Pharmacometrics & Systems Pharmacology

Article Title: Evaluation of drug–drug interaction potential for pemigatinib using physiologically based pharmacokinetic modeling

doi: 10.1002/psp4.12805

Figure Lengend Snippet: Simulated pemigatinib drug–drug interactions with various CYP3A4 inhibitors or inducers

Article Snippet: In addition, the pemigatinib PBPK model was further validated by simulation of pemigatinib PK at 6, 9, 13.5, and 20 mg q.d. doses using the Simcyp virtual cancer population, with the study design matching the corresponding phase I study in adults with advanced malignancies.

Techniques: Inhibition

Journal: CPT: Pharmacometrics & Systems Pharmacology

Article Title: Evaluation of drug–drug interaction potential for pemigatinib using physiologically based pharmacokinetic modeling

doi: 10.1002/psp4.12805

Figure Lengend Snippet: Observed and simulated AUC and C max ratios of a single dose of 13.5 mg pemigatinib with various cytochrome P450 3A4 inhibitors and inducers. AUC, area under the plasma drug concentration–time curve; C max , maximum plasma drug concentration; CI, confidence interval; DDI, drug–drug interaction

Article Snippet: In addition, the pemigatinib PBPK model was further validated by simulation of pemigatinib PK at 6, 9, 13.5, and 20 mg q.d. doses using the Simcyp virtual cancer population, with the study design matching the corresponding phase I study in adults with advanced malignancies.

Techniques: Clinical Proteomics, Concentration Assay

Journal: The AAPS Journal

Article Title: Physiologically Based Pharmacokinetic Predictions of Tramadol Exposure Throughout Pediatric Life: an Analysis of the Different Clearance Contributors with Emphasis on CYP2D6 Maturation

doi: 10.1208/s12248-015-9803-z

Figure Lengend Snippet: A one-compartment linear disposition model was used to fit the parent drug. An additional compartment for the ODT metabolite was linked to the central compartment by its formation clearance (CLP2M). Urinary excretion of tramadol (CLPR) was estimated based on the total amount of tramadol found in urine (UR). ODT moiety-related clearance (CLM) and volume (VM) were estimated based on the ODT plasma concentrations and total ODT amount found in urine (UR); CLPO other clearance parent

Article Snippet: An intravenous tramadol retrograde PBPK model was set up in Simcyp® using adult clearance values, qualified for CYP2D6, CYP3A4, CYP2B6, and renal contributions.

Techniques: Clinical Proteomics

Journal: The AAPS Journal

Article Title: Physiologically Based Pharmacokinetic Predictions of Tramadol Exposure Throughout Pediatric Life: an Analysis of the Different Clearance Contributors with Emphasis on CYP2D6 Maturation

doi: 10.1208/s12248-015-9803-z

Figure Lengend Snippet: Criteria by which CYP contributions in the retrograde model are assessed. CYP2D6 involvement was estimated by comparing hepatic clearance fold increase from PM to EM between predictions and in vivo. CYP2B6-CYP3A4 involvement was estimated by comparing AUCinduced/AUCcontrol ratios between predictions and observations

Article Snippet: An intravenous tramadol retrograde PBPK model was set up in Simcyp® using adult clearance values, qualified for CYP2D6, CYP3A4, CYP2B6, and renal contributions.

Techniques: In Vivo, Control

Journal: The AAPS Journal

Article Title: Physiologically Based Pharmacokinetic Predictions of Tramadol Exposure Throughout Pediatric Life: an Analysis of the Different Clearance Contributors with Emphasis on CYP2D6 Maturation

doi: 10.1208/s12248-015-9803-z

Figure Lengend Snippet: DDI clinical trial simulation of tramadol and rifampicin to assess the CYP2B6-3A4 contribution. The figure depicts the results of 100 trial simulations mimicking the original trial, when CYP2B6-3A4 contributions are assumed to be 10–42%, respectively. Black horizontal lines represent the in vivo observed ratio of AUC geo means (solid) and 90% confidence limits (dashed). The solid red line represents the average ratio of simulated AUC geo means. Since the solid black line still is in the 90% confidence region (grayed area) of the simulated ratio, we assume that CYP2B6 contribution should be between 0 and 10%

Article Snippet: An intravenous tramadol retrograde PBPK model was set up in Simcyp® using adult clearance values, qualified for CYP2D6, CYP3A4, CYP2B6, and renal contributions.

Techniques: In Vivo

Journal: The AAPS Journal

Article Title: Physiologically Based Pharmacokinetic Predictions of Tramadol Exposure Throughout Pediatric Life: an Analysis of the Different Clearance Contributors with Emphasis on CYP2D6 Maturation

doi: 10.1208/s12248-015-9803-z

Figure Lengend Snippet: Fractional Activities of Pediatric Tramadol Metabolism (Relative to Adult Activity) for the Formation of ODT and NDT Are Provided, Together with Those for the Probe Substrates DEX and MDZ Representative of CYP2D6 and CYP3A4 Activity, Respectively

Article Snippet: An intravenous tramadol retrograde PBPK model was set up in Simcyp® using adult clearance values, qualified for CYP2D6, CYP3A4, CYP2B6, and renal contributions.

Techniques: Activity Assay

Journal: The AAPS Journal

Article Title: Physiologically Based Pharmacokinetic Predictions of Tramadol Exposure Throughout Pediatric Life: an Analysis of the Different Clearance Contributors with Emphasis on CYP2D6 Maturation

doi: 10.1208/s12248-015-9803-z

Figure Lengend Snippet: Maturation of total tramadol clearance as a function of PMA (left) and body weight (right). PBPK predictions, represented as blue dots, are compared to in vivo maturation functions: Hill model (19) (black), exponential model (20) (red), and WinNonlin fits (light brown)

Article Snippet: An intravenous tramadol retrograde PBPK model was set up in Simcyp® using adult clearance values, qualified for CYP2D6, CYP3A4, CYP2B6, and renal contributions.

Techniques: In Vivo

Journal: The AAPS Journal

Article Title: Physiologically Based Pharmacokinetic Predictions of Tramadol Exposure Throughout Pediatric Life: an Analysis of the Different Clearance Contributors with Emphasis on CYP2D6 Maturation

doi: 10.1208/s12248-015-9803-z

Figure Lengend Snippet: Maturation of CYP2D6 tramadol clearance as a function of PMA (left) and body weight (right). PBPK predictions, represented as blue dots, are compared to in vivo maturation functions: Hill model (19) (black), exponential model (20) (red), and WinNonlin fits (light brown)

Article Snippet: An intravenous tramadol retrograde PBPK model was set up in Simcyp® using adult clearance values, qualified for CYP2D6, CYP3A4, CYP2B6, and renal contributions.

Techniques: In Vivo

Journal: The AAPS Journal

Article Title: Physiologically Based Pharmacokinetic Predictions of Tramadol Exposure Throughout Pediatric Life: an Analysis of the Different Clearance Contributors with Emphasis on CYP2D6 Maturation

doi: 10.1208/s12248-015-9803-z

Figure Lengend Snippet: Maturation of renal tramadol clearance as a function of PMA (left) and body weight (right). PBPK predictions, represented as blue dots, are compared to WinNonlin fits (light brown)

Article Snippet: An intravenous tramadol retrograde PBPK model was set up in Simcyp® using adult clearance values, qualified for CYP2D6, CYP3A4, CYP2B6, and renal contributions.

Techniques:

Journal: The AAPS Journal

Article Title: Physiologically Based Pharmacokinetic Predictions of Tramadol Exposure Throughout Pediatric Life: an Analysis of the Different Clearance Contributors with Emphasis on CYP2D6 Maturation

doi: 10.1208/s12248-015-9803-z

Figure Lengend Snippet: Maturation of total tramadol clearance as a function of PMA. Comparing the PBPK predictions (blue dots) to the in vivo Hill maturation function (red dots) reveals that the largest underprediction in total clearance is manifested between 2 and 13 years (100–650 weeks) of age

Article Snippet: An intravenous tramadol retrograde PBPK model was set up in Simcyp® using adult clearance values, qualified for CYP2D6, CYP3A4, CYP2B6, and renal contributions.

Techniques: In Vivo

Journal: The AAPS Journal

Article Title: Physiologically Based Pharmacokinetic Predictions of Tramadol Exposure Throughout Pediatric Life: an Analysis of the Different Clearance Contributors with Emphasis on CYP2D6 Maturation

doi: 10.1208/s12248-015-9803-z

Figure Lengend Snippet: Maturation of CYP2D6 tramadol clearance as a function of PMA. Comparing the PBPK predictions (blue dots) to the in vivo Hill maturation function (red dots) reveals that the largest underprediction in CYP2D6 clearance is manifested between 2 and 13 years (100–650 weeks) of age

Article Snippet: An intravenous tramadol retrograde PBPK model was set up in Simcyp® using adult clearance values, qualified for CYP2D6, CYP3A4, CYP2B6, and renal contributions.

Techniques: In Vivo