Certara Phoenix Winnonlin Software

Along with the Phoenix 8.1 release, Certara is introducing its Professional Certification Program through Certara University. Earning professional certification through this new online accreditation program will validate scientists’ PK/PD data analysis skills using Certara software such as Phoenix WinNonlin and expand their professional reach. Oct 3, 2017 - Phoenix is the most advanced, intuitive, and widely-used software for. Included in this Phoenix® rollout are Phoenix WinNonlin® 8.0, Phoenix.

Part 2 of the WinNonlin review will cover the non-compartmental and PK modeling functions of. To many people, these two features have defined WinNonlin for many years. And the updated software does not disappoint with significant improvements to the functionality, ease of use, automated graphics, and other features. As I discussed in, the new Phoenix platform allows integration of data and analysis methods. The “WinNonlin” feature includes the non-compartmental analysis and individual PK modeling features. These features were the basis for the previous versions of standalone WinNonlin versions 3, 4, and 5.

6es7 214 1ae30 0xb0 wiring an outlet online. Thus using the term “Phoenix WinNonlin” signifies the use of the new Phoenix platform to execute analyses with WinNonlin. This confusing nomenclature for the products is not helpful to the user, but it can be fixed very easily. Non-compartmental analysis The non-compartmental analysis workflow object is shown here. NCA Workflow Setup Within this workflow object you can select the options for the non-compartmental analysis, including the type of model, if sparse data is included, the AUC calculation method, and the terminal slope method. One change in the non-compartmental analysis engine from previous versions of WinNonlin is that C max is no longer included in the terminal slope calculation.

In addition to the analysis options, the concentration-time data to be used is identified in the “Main” item, dosing information can be imported from a data set or by manual entry, slopes can be selected by the WinNonlin algorithm (maximize adjusted r 2) or manually, partial areas can be defined, units can be specified, and parameter names can be selected or modified. A new feature of the non-compartmental engine is the ability to define a therapeutic response window. Lower and upper bounds can be specified by treatment or by subject. These bounds then appear on plots of concentration-time data. This feature is great for identifying either efficacy levels or toxicity margins. After all of the input options have been selected, the model can be executed to produce the desired output. The results are presented in a set of tables under the results option.

These include parameter estimates, exclusions, dosing information, and various settings. An example of the parameters table, in CDISC-like format is shown below: NCA Parameter Output Each of the output worksheets can be sent to other Phoenix objects such as tables or plots. If standard tables and plots templates have been created prior to analysis, the delivery of report-ready tables and graphics can be instantaneous. Although it appears that little has changed with the NCA engine, there have been a few modifications that simplify data analysis. First, the number of models has been reduced to three basic model types (plasma, urine, drug effect) with separate selections for the dosing input profile, and steady-state settings.

The second improvement is the improved plotting engine which provides report-ready graphics without having to leave the application. And finally, the dosing input is simplified and can be automatically populated using study design features. PK models The pharmacokinetic model workflow object is shown here. Pharmacokinetic Model Workflow Object The model can be selected by double-clicking the “PK Model” workflow object icon shown at the top of the image to the right. This pulls up the different models that can be selected. It also permits selection of weighting options, the ability to select initial estimates, and minimization options.