Peter ID Lee¹, Jens Stampe Sorensen², Eduard Porta², Jiaxiang Gai², Meng Xu², Feng Wang², Gunjan Gugale²

1. Associate Director, OCP, OTS, CDER, FDA
2. ORISE Fellow, OCP, OTS, CDER, FDA

PKView has been developed to automate the pharmacokinetic analyses of clinical pharmacology studies. These studies are typically conducted during the phase 1 and 2 of the clinical development process, and are pivotal for bioequivalence determination, dosing adjustment in special populations, safety evaluation with concurrent drug administration, and the investigations of many other intrinsic and extrinsic factors. The study design can vary widely depending on the study objectives and the pharmacokinetics and pharmacodynamics of the drug. The treatment scheme may range from crossover, to parallel, sequential, multiple-cohort and nested, with most studies examining multiple arms of patients. In addition, study observations can span from single visit to steady state and include the pharmacokinetics of parent drug, metabolite, and concurrent medications.

Automation of clinical study data analysis has been an ambitious project for us, due to the wide spectrum of data formats among different pharmaceutical companies and the large varieties of clinical study designs. Throughout the years, we have accumulated experiences with hundreds of NDA and BLA submissions and close to a thousand clinical studies. The recurrent scenarios (e.g., study designs, data formats, and analysis methodologies) observed from these past submissions have been categorized in a knowledgebase, with the corresponding solutions built into PKView.

The PKView platform consists of the following components

1. The data management module assists the user to load the study data in SDTM format.
2. The reporting module allows the user to generate various types analysis reports on a per study basis.
3. The meta-analysis module performs meta-analysis combing multiple studies.

1. Side-by-side comparison of Source vs Audit analysis outcomes
2. Standard cohort of tables and figures for typical clinical reports
3. Forest plot for drug labels
4. Study conduct integrity evaluation

For the complete list, please see Output_listing

1. Windows 7 pro, or Windows 10 pro
2. SAS 9.4

Please see PKView_Setup_Guide.

Please see Data_requirement, Screen_shots, and Trouble_shooting.

Wherever applied, the contents in this Software and its accompanied documentations reflect the views of the authors and should not be construed to represent FDA’s views or policies.

Please post any questions or comments under the "Issues" tab.