đź’» Pharmacometrics Modeling Language (PML)
35 articles
PML School (Part 1)
Series of Free Webinars for how to create PK/PD models using Pharmacometric Modeling Language
- PML School IntroductionThis is a series of webinars that were hosted by Certara to teach people to become more familiar with PML coding of PK and PK/PD models. It is a series…
- Lesson 1: Nonlinear ClearanceA 3-compartment model with nonlinear clearance.
- Lesson 2: Metabolite KineticsSimultaneous fitting of parent and metabolite where the metabolite clearance follows Michaelis-Menten kinetics.
- Lesson 3: Two-Compartment Repeated DosingA two compartment model fitted to pharmacokinetic and pharmacodynamic data in a sequential manner using concentration- and response-time data after multiple oral doses.
- Lesson 4: Multiple Absorption RoutesA model with multiple absorption routes was constructed using the Graphical Model Editor.
- Lesson 5: Simultaneous Fitting of Plasma and Urine DataA one-compartment model with IV and PO dosing, and collection of both plasma and urine data.
- Lesson 6: Target-Mediated Drug DispositionA textual model with target-mediated drug disposition
- Lesson 7: Enterohepatic RecirculationA 2-compartment model with recirculation via bile and gut.
- Lesson 8: One-Compartment 1st and 0-Order InputTwo models built, one with 1st-order input, and a second with zero-order input. The model that fit the data better was identified
- Lesson 9: Allometric ScalingA 2-compartment model fitted to data from mouse, rat, dog and human, Creating Dedrick plots in Phoenix.
- Lesson 10: Turnover III - Nonlinear DispositionA turnover model of an endogenous compound with saturating elimination, and a highly variable multiple dosing scheme. Results compared with a simple linear elimination model.
- Lesson 11: Analysis and Comparison of Link, Turnover and Receptor Binding ModelLink (Effect Compartment) model, Turnover (Indirect) model and receptor binding model are created and compared.
- Lesson 12: Sigmoidal Concentration-Response ModelsGompertz, Hill, Logistic, Morgan-Mercer-Flodin, Richards, and Weibull models were created and compared
- Lesson 13: Modeling Tumor Growth/KillGompertz, Jumbe, and Simeoni models are constructed and compared.
- Lesson 14: Modeling Enzyme Inhibition by Means of TurnoverOne-compartment PK model (frozen parameters) with turnover model that fits the PD data
- Lesson 15: Effect Compartment III - IV InfusionTwo PK/PD models are compared: an effect compartment model, and a model that uses the PML delay command. The process of going from a PK model to a PK/PD model is also…
- Lesson 16: Warfarin IV Bolus Turnover ModelA turnover (Indirect) model, a turnover model with a delay, and two different precursor-pool models.
- Lesson 17: Turnover Model 4 - IV InfusionTurnover model 4 (stimulation of loss) with frozen PK. PK data are simulated using previously-determined parameters, so we can see the hysteresis loop.
- Lesson 18: Turnover Models with Repeated DosingOne-compartment PK model with turnover PD model (inhibition of the build-up of response). PK is frozen.Â
- Lesson 19: Dose-Response-Time AnalysisA model that has only Effect and Time data (no PK data).  First-order PK is assumed. The PD model is a turnover model, with linear stimulation of loss.
- Lesson 20: Transduction ModelingA PK/PD model. The PK is described by a 1-compartment IV bolus model with nonlinear elimination. The PD is delayed by three transit compartments and a feedback loop.
PML School (Part 2) Translate NONMEM to PML
Series of Webinars showing how to translate NONMEM to PML.
- Introduction to the Webinar SeriesThis is an archive of the NONMEM to NLME webinars that were presented during 2018. The goal is to demonstrate how to convert NONMEM models into Phoenix.
- Webinar 1: PK 1-Compartment IV Bolus Model FOCEOne compartment model, single IV Bolus of 100 units, first order kinetics. Parametrization: Cl and V. Multiplicative residual error, and 30% between-subject variability in parameters. Optimized using FOCE ELS.
- Webinar 2: PK 2 compartment multiple dose- IV bolus Plasma and Urine QRPEMIMP2-comparment plasma and urine PK model with IV-bolus dosing, clearance parameterization, multiplicative residual error, using the QRPEM engine.
- Webinar 3: PK 2 compartment oral with Disease State covariate on V and CLcompartment model with Oral Single Dose, Covariate relationship between both V and Cl and categorical covariate disease state
- Webinar 4: PK Nonlinear Elimination and Model Validation I BootstrapOne compartment model, IV Bolus, 3 Dose cohorts (1,10 and 100 ), non linear kinetics, FOCE-ELS engine.
- Webinar 5: Mixed Absorption and Model Validation II VPCTwo compartment model, first-order and zero order saturable absorption, Doses ranging from 1-800
- Webinar 6: Running NONMEM and Phoenix NLME in the CloudCertara Burstable Grid
- Webinar 7: PD Emax inhibitory with baseline and shape factorEmax model with baseline and shape factor, multiplicative residual error, random effects, using the FOCE-ELS engine
- Webinar 8: PD Indirect Response with IV Bolus DosingPD Indirect response model using frozen PK parameters.
- Webinar 9: PK/PD 1 Compartment-IV Infusion - Emax with Baseline, Shape and EffectOne compartment model, single IV infusion of 100 units. Emax model with baseline and shape factor. Effect compartment. Run with FOCE-ELS
- Webinar 10: Comparisons PD Categorical Response AnalysisProbabilistic Model: A binary response versus measured concentrations, e.g. dose.
- Webinar 11: Comparisons PD Time-to-Event AnalysisSurvival model (probablilistic) using the Laplacian engine
- Webinar 12: Comparisons PD Count AnalysisCount model, Poisson distribution. Structural parameters of Loglambda and Coeff. Random effect of 30% BSV on Loglambda
- Webinar 13: TMDD Model translated from NONMEM (NM-TRAN) to Phoenix NLME (PML)Targe mediated drug disposition model with a single IV bolus dose and plasma concentrations of free drug only.