BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Metrum Research Group - ECPv4.6.1//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-WR-CALNAME:Metrum Research Group
X-ORIGINAL-URL:http://metrumrg.com
X-WR-CALDESC:Events for Metrum Research Group
BEGIN:VEVENT
DTSTART;TZID=UTC+2:20180529T083000
DTEND;TZID=UTC+2:20180529T163000
DTSTAMP:20180423T211222
CREATED:20180110T235041Z
LAST-MODIFIED:20180225T010734Z
UID:1613-1527582600-1527611400@metrumrg.com
SUMMARY:Advanced Use of Stan\, rstan\, and Torsten for Pharmacometric Applications
DESCRIPTION:Montreux\, Switzerland (PAGE satellite meeting\, exact location TBD) \nInstructor: Bill Gillespie\, Ph.D. \nMetrum Research Group will present a one-day workshop entitled “Advanced Use of Stan\, rstan and Torsten for Pharmacometric Applications” on Tuesday 29 May 2018. We will provide a guided hands-on experience in the advanced use of Stan\, rstan\, and Torsten\, for Bayesian PKPD modeling. Stan is a flexible open-source software tool for Bayesian data analysis using Hamiltonian Monte Carlo (HMC) simulation—a type of MCMC simulation. Torsten is a Stan extension containing a library of functions to simplify implementation of PKPD models. This workshop builds on the foundations presented in our previous introductory Stan workshops. Topics include model evaluation and comparison\, models with systems of ODEs\, optimizing Stan code\, using MCMC results for population and trial simulations\, and more. You will execute Bayesian data analysis examples using Stan. Via the examples you will learn to implement population PKPD models including those involving censoring\, numerical solution of ODEs\, and user-defined probability distributions and likelihoods. \nFull Price: $600\nAcademia/government attendees: $300\nStudents: $150 \nMaterials Provided by Metrum: Metworx user login (with 1-week access post-workshop)\, course slides\, data and code for all examples. \nRequirements for Attendees: Knowledge and experience in PKPD modeling and simulation\, nonlinear mixed effects modeling and the use of R (or S-PLUS). \nParticipants should bring a laptop that meets the following requirements:\n– Browser: Chrome\, Firefox\, or Safari\n– Internet access via Wi-Fi \nCourse Outline:\nBrief review of the use of Stan and rstan\n– User-defined functions\n– Implementing popPKPD models\n– Modeling workflow using rstan\nModels with systems of ODEs\n– Linear case\n– General case\nTorsten: Prototype library of PKPD functions for Stan\n– Built-in models: 1 and 2 compartment models with 1st order absorption\n– Numerical solution of user-specified ODEs\nHands-on example 1: popPK using a 2 compartment model with 1st order absorption\nReview of HMC/NUTS\nDiagnosing and remedying sampling problems encountered w/Stan\nOptimizing Stan code\n– Parameterization\, e.g.\, centered vs non-centered parameterizations for hierarchical models\n– Constructing/choosing prior distributions\nHands-on example 2: popPKPD using a model based on a linear system of ODEs\nModel evaluation and comparison\nUse of informative prior distributions in pharmacometrics applications\nUsing MCMC results for statistical inference\n– Population and trial simulations based on MCMC results\nHands-on example 3: physiologically-based popPKPD model\nCensoring\nUser-defined probability distributions and likelihoods\nMixture models\nHands-on example 4: parametric time-to-event model\nWhat didn’t we cover? \n \n
URL:http://metrumrg.com/event/advanced-use-stan-rstan-torsten-pharmacometric-applications-2/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC+2:20180602T083000
DTEND;TZID=UTC+2:20180602T163000
DTSTAMP:20180423T211222
CREATED:20180110T223612Z
LAST-MODIFIED:20180225T011150Z
UID:1603-1527928200-1527957000@metrumrg.com
SUMMARY:Simulation from ODE-based population PK/PD and systems pharmacology models in R using mrgsolve
DESCRIPTION:Montreux\, Switzerland (PAGE satellite meeting\, exact location TBD) \nInstructors: Matthew Riggs\, Ph.D. and Kyle Baron\, Pharm.D.\, Ph.D. \nWorkshop summary: We will provide a guided hands-on experience in the use of the R package mrgsolve. mrgsolve is a free\, open source\, validated R package to facilitate simulation from hierarchical\, ODE-based PK/PD and systems pharmacology models frequently employed in pharmaceutical research and development programs. You will code\, execute\, and summarize PK\, PK/PD and systems pharmacology model simulations using mrgsolve and R. Through many examples\, you will learn to implement model-based simulations to help address questions at a variety of stages of a development program. \nFull Price: $600\nAcademia/government attendees: $300\nStudents: $150 \nMaterials Provided by Metrum: Metworx user login (with 1-week access post-workshop)\, course slides\, data and code for all examples. \nRequirements for Attendees: Knowledge and experience in PKPD modeling and simulation\, nonlinear mixed effects modeling and the use of R (or S-PLUS). \nParticipants should bring a laptop that meets the following requirements:\n– Browser: Chrome\, Firefox\, or Safari\n– Internet access via Wi-Fi\n \nUpon completion of this workshop\, participants should be able to: \n\nCode ODE-based models in mrgsolve format
\nWork with mrgsolve model objects and simulation output
\nCreate simulations of varying complexity\, including sensitivity analyses\, using event objects and simulation data sets
\nCreate population simulations that incorporate uncertainty in the parameters to address questions in drug development
\n\nCourse Outline: \n\nAssign login credentials and check out course materials
\nHands-on Introduction to mrgsolve (morning coffee break included)
\n\nInstallation overview\n\nWhere to get mrgsolve\n\n\nBasic introduction to mrgsolve\n\nCode a very basic model\nLoad and work with model object\nSimulation with event objects and data sets\nHandling simulated output\n\n\nModels with covariates and population elements\nUpdating the model object and sensitivity analyses\n\n\nLunch\nApplied simulation with PK/PD\, PBPK\, and QSP models (afternoon coffee break included)
\n\nSimulation from a population model with and without uncertainty in the parameters using a PK/PD model for Fc-OPG in postmenopausal women\nProbability of technical success assessment using EPO PK/PD model\nEvaluate combination chemotherapy regimens with a QSP model characterizing MAP kinase signalling in colorectal cancer\nSensitivity analysis and parameter optimization in a PBPK model characterizing drug-drug interaction between HMG-CoA reductase inhibitors and cyclosporine\n\n\n\n\nDiscussion and summary \n\n
URL:http://metrumrg.com/event/simulation-ode-based-population-pk-pd-systems-pharmacology-models-r-using-mrgsolve/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC+0:20180606T130000
DTEND;TZID=UTC+0:20180607T170000
DTSTAMP:20180423T211222
CREATED:20180412T172524Z
LAST-MODIFIED:20180413T174641Z
UID:1699-1528290000-1528390800@metrumrg.com
SUMMARY:Introduction to PBPK modeling in R with mrgsolve
DESCRIPTION:This 1.5 day workshop will be held at Cambridge Innovation Center (101 Main St Cambridge\, MA)\nJune 6\, 2018 1:00 pm – 5:30 pm\nJune 7\, 2018 9:00 am – 5:00 pm \nCourse Instructors: Ahmed Elmokadem\, Ph.D.\, Kyle Baron\, Pharm.D.\, Ph.D.\, Matthew Riggs\, Ph.D.\, Marc R Gastonguay\, Ph.D. \nSummary \nThis hands-on workshop will provide participants with a technical foundation for physiologically-based pharmacokinetic (PBPK) model development in R using mrgsolve\, a free\, open-source modeling and simulation platform for ODE-based model development in R (https://mrgsolve.github.io). The workshop gets started with an introduction to simulation with mrgsolve. We’ll cover the essentials of a tidy simulation workflow in R. Then we’ll jump into PBPK modeling with mrgsolve. After a brief introduction to principles of PBPK\, we’ll work through case studies using PBPK modeling. The case studies use published models focused on problems like drug-drug interactions and exploring pharmacokinetics in special populations. Finally\, we will introduce tools and workflows in R to help you accomplish modeling tasks such as sensitivity analysis and parameter estimation. \n \nTopic outline of Workshop: \nDay1 (1:00 PM – 5:30 PM) \n\nIntroduction\nPBPK concepts\nA tidy PBPK model-based simulation workflow in R \n\nDay 2 (9:00 AM – 5:00 PM) \n\nCase studies in PBPK modeling\n\nHands-on builds \n\nA simple PBPK model \nScaling voriconazole PK: adults to pediatrics\n\n\nModel-based mechanistic exploration\n\nSite-specific considerations (e.g.\, gut vs. liver clearance)\nDrug-drug interactions\n\n\n\n\nApplied modeling and simulation\n\nSensitivity analyses\nParameter estimation\nPopulation simulation\nShiny app demonstration\n\n\n\n \nRequirements for Attendees: Knowledge and experience in PK modeling and the use of R (or S-PLUS). Previous exposure to the mrgsolve simulation package (https://mrgsolve.github.io/) is helpful\, but not required. Participants should bring a laptop that meets the following requirements:\n – Browser: Chrome\, Firefox\, or Safari\n– Internet access via Wi-Fi \nMaterials Provided: Course slides\, data and code for all examples\, online access for one week to a cloud-based compute server on which the software used in the course is installed. \nCost:\n$1500 Industry\n$750 Academia/Gov/NonProfit\n$150 Student \n
URL:http://metrumrg.com/event/introduction-pbpk-modeling-r-mrgsolve-2/
LOCATION:101 Main Street\, Cambridge\, MA\, 02142\, United States
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC+0:20181007T080000
DTEND;TZID=UTC+0:20181007T170000
DTSTAMP:20180423T211222
CREATED:20180405T175103Z
LAST-MODIFIED:20180405T193621Z
UID:1688-1538899200-1538931600@metrumrg.com
SUMMARY:Bayesian analysis of categorical\, count and time-to-event data with Stan\, rstanarm and Torsten
DESCRIPTION:We will provide a guided hands-on experience in the use of Stan (http://mc-stan.org/)\, rstan (http://mc-stan.org/interfaces/rstan.html)\, rstanarm (http://mc-stan.org/users/interfaces/rstanarm.html) and Torsten (https://github.com/metrumresearchgroup/example-models) for Bayesian analysis of categorical\, count and time-to-event data. Stan is a flexible open-source software tool for Bayesian data analysis using Hamiltonian Monte Carlo (HMC) simulation—a type of MCMC simulation. Torsten is a Stan extension containing a library of functions to simplify implementation of PKPD models. This workshop builds on the foundations presented in our previous introductory Stan workshops (http://metrumrg.com/events/2016/10/23/bayesianpkpd.html). The hands-on examples will focus on implementation of Stan models for each of the basic data types covered in the workshop\, i.e.\, binary\, ordinal\, count and time-to-event data. We will also present examples that illustrate how those component models may be extended and combined for joint analysis of multiple data types. Those examples include latent variable models such as IRT models as well as joint modeling of continuous and time-to-event data. \nOctober 7\, 2017 8:00am-5:00pm (1.5 day ACoP9 satellite workshop) \nCourse Instructor: Bill Gillespie \nTopic Outline of Workshop: \nStart: 8:00am \n\nSome general theory/background:\n\nModeling from a probabilistic point of view: the likelihood function\nMaximum likelihood for continuous data\nExtending ML to odd-type data\nBayesian modeling of odd-type data\n\n\nBrief review of the use of Stan and rstan\n\nUser-defined functions\nModeling workflow using rstan\n\n\nModeling binary data\n\nLogistic regression models\nBernoulli model for individual binary data\nBinomial model for summary data\nMixed effects modeling of longitudinal binary data\n\n\n\nBreak: 10:15-10:30am \n\nModeling ordered categorical (ordinal) data\n\nCumulative logit models\n\n\nModeling count data\n\nThe Poisson model\nVariations on the Poisson model to deal with over-dispersion or zero inflation\n\n\n\nLunch: 12:00-1:00pm \n\nModeling time-to-event data for a single event per individual\n\nPrinciples and methods of survival analysis for modeling censored data\n\n\nTorsten: Library of PKPD functions for Stan\n\nBuilt-in models: 1 and 2 compartment models with 1st order absorption\nNumerical solution of user-specified ODEs\n\n\nModels with time-varying hazard\n\nBreak: 3:00-3:15pm \n\nModeling repeated time-to-event data\nMarkov models for joint modeling of event times and their magnitudes\nItem response theory (IRT) and related models for joint modeling of multiple outcomes\nJoint modeling of continuous and time-to-event data\n\nAdjourn: 5:00pm \nMaterials Provided by Sponsor: Course slides\, data and code for all examples\, online access for one week to a cloud-based compute server on which the software used in the course is installed \nRequirements for Attendees: Knowledge and experience in population PKPD modeling and the use of R and Stan. The workshop assumes a knowledge of Stan comparable to the content of our previous introductory workshops (http://metrumrg.com/events/2016/10/23/bayesianpkpd.html). For those who do not yet have the required knowledge of Stan we offer a recorded online version of an introductory workshop (http://metrumrg.com/course/brief-introduction-bayesian-modeling-using-stan/). \nParticipants should bring a laptop on which the Google Chrome browser has been installed and that may access the internet via Wi-Fi. \nPricing:\n\nIndustry $700\nAcademia/Gov/NonProfit $400\nStudent $250\n\n
URL:http://metrumrg.com/event/bayesian-analysis-categorical-count-time-event-data-stan-rstanarm-torsten/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC+0:20181011T130000
DTEND;TZID=UTC+0:20181012T170000
DTSTAMP:20180423T211222
CREATED:20180405T175031Z
LAST-MODIFIED:20180405T193444Z
UID:1683-1539262800-1539363600@metrumrg.com
SUMMARY:Introduction to PBPK modeling in R with mrgsolve
DESCRIPTION:This hands-on workshop will provide participants with a technical foundation for physiologically-based pharmacokinetic (PBPK) model development in R using mrgsolve\, a free\, open-source modeling and simulation platform for ODE-based model development in R (https://mrgsolve.github.io). The workshop gets started with an introduction to simulation with mrgsolve. We’ll cover the essentials of a tidy simulation workflow in R. Then we’ll jump into PBPK modeling with mrgsolve. After a brief introduction to principles of PBPK\, we’ll work through case studies using PBPK modeling. The case studies use published models focused on problems like drug-drug interactions and exploring pharmacokinetics in special populations. Finally\, we will introduce tools and workflows in R to help you accomplish modeling tasks such as sensitivity analysis and parameter estimation. \n \nOctober 11-12\, 2017 (1.5 day ACoP9 satellite workshop)\n \nCourse Instructors: Ahmed Elmokadem\, Ph.D. and Kyle Baron\, Pharm.D.\, Ph.D. \nTopic outline of Workshop:\n \n\nPBPK concepts\n\nWhy PBPK?\nTypes of PBPK models (flow-limited and permeability-limited)\nDevelopment of model equations\nDatabases for PBPK model parameters\n\n\nIntroduction to mrgsolve for PBPK modeling\n\nA tidy PBPK model-based simulation workflow in R\nImplement dosing events\nCustomize simulation output\nApproaches to sensitivity analysis with mrgsolve\nModel specification basics\n\n\nCase studies in PBPK modeling\n\nStatin/cyclosporine DDI model (Yoshikado et al. 2016\, PMID 27170342)\nPediatric voriconazole PBPK model (Zane and Thakker 2014\, PMID 25245942)\n\n\nPBPK modeling workflow in R\n\nSensitivity analyses\n\nExploratory simulation\nLocal sensitivity analysis\nGlobal sensitivity analysis via sobol method\n\n\nParameter estimation \n\nGeneral optimization in R\nGlobal search tools\n\n\n\n\nDiscussion and wrap-up\n\nRequirements for Attendees: Knowledge and experience in PK modeling and the use of R (or S-PLUS). Previous exposure to the mrgsolve simulation package (https://mrgsolve.github.io/) is helpful\, but not required. \nMaterials Provided by Sponsor: Course slides\, data and code for all examples\, online access for one week to a cloud-based compute server on which the software used in the course is installed. \nPricing:\nIndustry $1\,050\nAcademia/Gov/NonProfit $600\nStudent $375\n
URL:http://metrumrg.com/event/introduction-pbpk-modeling-r-mrgsolve/
END:VEVENT
END:VCALENDAR