A Compendium of Insightful Information for Our Phoenix Community
Welcome to The Phoenix® Reporter. In this e-newsletter, we will share informative educational content along with practical, implementable resources with our Phoenix user community.
This issue provides an overview of the new features and enhancements in Phoenix 8.1, the newest version of our PK/PD software:
- What’s New in Phoenix 8.1
- Certara Professional Certification
- Reference-scaled Average Bioequivalence (RSABE) for Drugs with Narrow Therapeutic Index (NTID) Using Phoenix WinNonlin®
- Making Sense of 6MWT Variability: Developing a Disease Progression Model for DMD Using Phoenix NLME™
What’s New in Phoenix 8.1—Accomplish More with Phoenix
The newest version of Phoenix features new capabilities and automated tools, which reduce errors, save you time, and support compliance and efficiency.
New NCA Ratios and Differences Tool in Phoenix WinNonlin
Calculating ratios of PK parameters is a common post-processing step required for pre-clinical toxicokinetic studies, clinical Phase 2–3 multiple dose studies, and dose finding studies. Typically, 10–15 steps are required to calculate PK ratios for determining average renal clearance, accumulation ratios, gender differences, parent to metabolite exposure ratios, dose proportionality, exposure ratios for food effects, drug-drug interactions, and relative bioavailability. The new NCA Ratios and Differences tool in Phoenix WinNonlin simplifies the ratios calculations from one to two input worksheets. The function is automated by adding the x/y Ratios and Differences Object to the workflow. Tables are directly created from the Ratios and Differences Object output.
Table of Gender Differences in Exposure Parameters
New Descriptive Statistics Enhanced Charting Capabilities
New Descriptive Statistics have been added to Phoenix WinNonlin and NLME including range, min and max when weighting is used, 2.5% and 97.5% percentiles, user-specified percentiles, and sample and population statistics for skewness and kurtosis.
Enhanced Charting Capabilities
Charting enhancements provide greater flexibility and customization of charts and plots. These include the ability to order the presentation of categorical axes and profiles in XY plots, utilize the offset function left or right on X-axis, add line to XY (X-categorical), and more.
Change Order of Categorical Data
Group by Color and Order of Profiles
Validation Made Fast and Easy
Validation Suite for Phoenix WinNonlin is now integrated into Phoenix and can be accessed without having to install a separate application. Full software validation can be completed in under 30 minutes while working on other applications. Validation Suite for WinNonlin provides locked PDF reports with links to saved reference files, user output files, and difference files. Updated ready-to-use validation template documents are aligned with the latest regulatory guidance computer system validation such as ICH E6 Good Clinical Practice (GCP) R2.
Example of a WinNonlin Validation Report
Visual Predictive Check
Visual Predictive Check (VPC) is a graphical comparison and analysis of observations and simulated predictions. VPC in Phoenix NLME now provides broader applicability and flexibility for users. These enhanced functionalities include the ability to perform separate analyses for different data types such as continuous data, including Below Quantification Limit (BQL), and discrete observations such as categorical, single time-to-event, and count data. Other improvements include separate Visual Predictive Check and Simulation modes and VPC Stratification for categorical covariates.
Time-to-Event with Stratification
Certara Professional Certification—Phoenix WinNonlin Analyst
Certara Professional Certification is a new online accreditation program from Certara University. A recent poll of scientists indicated strong interest in participating in this type of certification program since it would not only validate their knowledge and skills, but also identify gaps in their knowledge and help them learn. The first certification offered in the program is Certara Certified NCA Analyst, which validates proficiency and competence with non-compartmental (NCA) pharmacokinetic (PK) analysis using Phoenix WinNonlin version 8.0 or 8.1. A certified NCA analyst has the ability to process data, perform exploratory data analysis, calculate NCA parameters, and report results for typical PK study designs in pre-clinical and clinical trials.
To successfully earn the NCA Analyst certification, a minimum passing score of 75% must be achieved upon completion of a rigorous online accreditation exam using Phoenix 8.0 or 8.1. The exam is made up of 80–90 questions that cover theoretical knowledge of NCA analysis on different types of study designs, and a practical section that evaluates software proficiency by performing tests related to NCA analysis, data processing, and reporting. There is a time limit to answer each question with a maximum allocated time of 3 hours to complete the exam.
Upon successful completion of the Certara professional certification exam, recipients will be issued a digital badge by Acclaim. This is a secure, verifiable and standardized delivery method of achievement, and includes all the information about the certification that has been earned, including a detailed description of the exam. Recipients can opt to make the badge private or public, and the earned certification can be listed in a publicly searchable directory. The eBadges, valid for three years, can be easily embedded on résumés, emails, web sites, and social and professional networking web sites, including LinkedIn and Facebook. In addition, a printed certificate of your achievement that includes a verification link can be requested.
Although there are no pre-requisites required to take the Certara Certified NCA Analyst certification accreditation, several Certara University courses, or equivalent experience, can help to prepare for the certification: Fundamentals of Pharmacokinetics (103-OD), Noncompartmental Data Analysis (105-OD), and either the On-Demand (100-OD) or Classroom (100-CL) Introduction to Phoenix WinNonlin.
Reference-scaled Average Bioequivalence (RSABE) for Drugs with Narrow Therapeutic Index (NTID) Using Phoenix WinNonlin
Drugs with a narrow therapeutic index (NTIDs) have a narrow range between therapeutic and toxic dose levels. Traditional average bioequivalence (ABE) methodology may be unacceptable for NTIDs, because small differences (eg, 20%) in drug exposure may lead to serious therapeutic failures and/or adverse drug reactions. The usual ABE limits of 80.00–125.00% are not considered sufficient for NTIDs, and several regulatory agencies have narrowed the limits for bioequivalence, typically to 90.00–111.11%.
The US FDA guidance for warfarin sodium proposed a new bioequivalence methodology for NTIDs as an extension of RSABE to scale bioequivalence limits to the within-subject variability of the reference product, and to compare within-subject variabilities of test (σWT) and reference (σWR) products. For NTIDs, a fully replicated design must be used, and the test formulation must pass the following three criteria:
- RSABE, scaled to the reference variability, eg, 90% CI within limits of 90.00–111.11% for reference formulations with CVWR = 10%
- Unscaled ABE, within 90% CI limits of 80.00–125.00%
- The upper bound of the 90% CI of the ratio σWT/σWR must be ≤ 2.5
For EMA, Health Canada, and Japan PMDA guidelines, only the Average BE analysis in Phoenix WinNonlin is required, but with tightened 90% confidence interval limits. On a case-by-case basis for the EMA, but generally to 90.00–111.11%; 90.0–112.0% for Health Canada for AUC but not tightened for Cmax; and 90.00–111.11% for PMDA for AUC and Cmax.
To demonstrate that RSABE and other tests for NTIDs can be performed using reusable workflows (templates) in Phoenix WinNonlin, template workflows were created to test the three criteria for RSABE analysis of NTI drugs as per the FDA Warfarin Guidance. The results were presented in a poster given at the 2017 American Association of Pharmaceutical Scientists conference. Phoenix WinNonlin has a ready-to-use tool to test Average BE, so workflows were developed for the first and third criteria, ie, for RSABE using NTID-specific constraints, and for a test on the ratio of the test-to-reference variability.
The Phoenix template project for NTID analysis included the following workflows:
- Data entry and workflow to prepare dataset for further analysis
After data import and mapping, a data processing workflow automatically prepares the dataset for further analysis by ABE, RSABE, and the upper 90% limit test
- RSABE as recommended by the FDA approach
This workflow computes the SWR, a point estimate for the geometric mean ratio and computes the 95% upper confidence bound for the x2 distributed test statistic. The workflow will provide an assessment of whether RSABE is shown (point estimate within 0.8000 and 1.2500 and upper confidence bound ≤ 0.
- Average Bioequivalence
Using the FDA’s recommended model for replicated data, the ABE workflow tests the NTID criteria that the drug must still meet the usual 80.00% and 125.00% limits for ABE for the 90% confidence interval of the test-to-reference ratio for AUC and Cmax.
- Upper 90% criterion for ratio of Test to Reference Variability
To check the third criteria for NTIDs, this workflow computes the upper bound of a 90% confidence interval of the ratio σWT/σWR and tests whether the upper bound is less than or equal to 2.5.
- Final Tables
The workflow complies conclusions from the three criteria, and lists any subjects not used in the analyses due to missing observations.
The results of the project demonstrated that RSABE for NTIDs following the three criteria required by the FDA Guidance can be performed in Phoenix versions 6.4, 7.0, 8.0, and 8.1 using reusable template projects and workflows. The template projects require minimal input from the user in order to be used with any input dataset from a replicated 4-period crossover design.
The Phoenix template projects and executed examples for NTID can be downloaded for free through Certara University (106-FL). The course content also includes template projects for RSABE for highly variable drugs (HVD).
Making Sense of 6MWT Variability: Developing a Disease Progression Model for DMD Using Phoenix NLME
Duchenne Muscular Dystrophy (DMD) is a life-threatening, sex-linked, pediatric rare disease, primarily affecting boys. It is characterized by progressive muscle degeneration, weakness, and eventually functional loss. DMD is caused by a mutation in the dystrophin gene, a protein needed to maintain muscle integrity, and for improving signaling and growth in differentiation of the muscle tissue. DMD is diagnosed at four to five years of age. By twelve to fourteen, the patient loses the ability to walk. Ultimately, patients succumb to the disease in their mid-twenties due to complications including cardiomyopathy and impaired respiratory function.
Recent promising therapeutic advances, such as exon skipping therapies, stop codon-read-through, and gene therapies, have led to increased patient life expectancies. Corticosteroids are the standard for treating symptoms. However, more research is needed to better understand the mechanisms of muscle atrophy and defects to develop more efficacious therapies.
Because DMD is a pediatric disease, there is a developmental component to how children perform in the motor function tests, including the 6-minute walk test (6MWT). Younger subjects show some improvement in motor function over time. However, when the disease takes over, motor function declines. Hence, the 6MWT trajectory shows an “up and down” effect. The dependence on age is important to assess in drug trials because, otherwise, a drug effect may be missed or a false conclusion of efficacy may be derived.
In a recent webinar, Drs. Lora Hamuro (Bristol Myers Squibb) and Jogo Gobburo (University of Maryland) reviewed how a disease progression model, developed using Phoenix NLME, was used to better understand variability in the 6MWT. They sought to determine if a quantitative approach can discern drug effect, given the age-dependent variability. Can a disease progression model be leveraged to inform downstream trial design, examine drug effects, and then simulate potential drug effects in future trials?
Dr. Hamuro highlighted some of the inherent challenges of disease progression modeling. Although aggregate-level information on age, race and weight is available, the lack of detailed patient demographic information that drives variability, such as type of steroid treatment, and patient factors including dystrophin mutation, baseline cardiac and respiratory function, may hinder building a disease progression model.
Six structural models, with increasing complexity, were evaluated for their ability to accurately predict the training dataset and a novel dataset. A Linear Model with Simultaneous Estimation using Phoenix NLME was developed to bucket various forms of 6MWT variability. The model was a series of linear models that did not require a priori fix of age but rather could let the data speak for itself and estimate what this would be.
The disease progression linear model was shown to do a fairly good job of accounting for variability seen in the observed training datasets and for predicting 6MWT performance in the training datasets as well as a novel dataset.
To evaluate a drug for a clinical meaningful effect, a standard sample size calculation was performed to determine how many patients would be needed to detect a drug effect. If studying an aggregate age group, 160 subjects per trial arm would need to be recruited. This is not feasible for a rare disease such as DMD. But by using the disease progression model, a small, non-age stratified trial could detect a hypothetical drug effect using only 6 subjects per treatment arm. The model was shown to parse out the age dependence on variability and accurately predict the dose response for the hypothetical drug.
This approach highlighted the power of modeling and simulation (M&S) for rare disease drug development. It demonstrated how a quantitative platform can be used to simulate different drug trial scenarios to assess sources of patient variability and allow for much smaller drug trials to be conducted.
Want to learn more about Phoenix 8.1 and Certara Professional Certification? Check out our scientific webinar that provides an overview and a demo of all the new features in Phoenix 8.1, and an overview of the Certara Professional Certification, given by Nathan Teuscher, Venkateswari Muthukrishnan, and Ana Henry. Interested in getting Phoenix? Download now >
Tips of the Trade
Learn tips and guidance on how to streamline the process for validating new or upgraded software and to get a better understanding on common pitfalls and ways to avoid them. Learn More >
Following is a compendium of scientific articles and information to augment your knowledge on topics highlighted in this issue.
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Your source for all Certara information including case studies, white papers, blog posts, webinars, articles, posters, brochures, and press releases. Visit the Library >
Information from Certara on topics contained in this issue: