Website Katalyst Healthcares & Life Sciences
Katalyst Healthcares & Life Sciences
Company : Katalyst Healthcares & Life Sciences
Job Description:
The Sr. SAS Programmer provides PKPD programming aspects of pharmacokinetics, pharmacodynamics data management by timely completion and high quality of all required deliverables.
Responsibilities:
- Prepare data for state-of-the-art analysis, such as PPK, PKPD, exposure-response (efficacy or safety), and C-QTc, typically based on CDISC ADaM / SDTM datasets.
- Prepare data for state-of-the-art NCA analysis, such as ADPC, PP, and ADPP, including the creation of defined packages and reviewer guides.
- Write, maintain, and develop high-quality Programs and Macros (R, SAS) to facilitate the construction of analysis datasets and P21 validations.
- Interact with members of the multidisciplinary team to establish project timelines; computerized data validation checks and ad hoc requests.
- Design and implement statistical algorithms and code in conformance with defined programming processes and standard operating procedures.
- Conduct exploratory analyses of PKPD data in support of modeling analyses.
- Write statistical analysis plan and perform exposure-analysis on QTc as requested.
- Following completion of the project deliverables, you are responsible for the creation of an electronic submission package for future submission to regulatory agencies.
Requirements:
- BS, MSc, Master in Statistics, Mathematics, PhD, PharmD, or related fields.
- About 5 years' experience and expertise in PKPD programming and analysis, report writing, and regulatory drug submissions.
- General knowledge of clinical drug development and demonstrated knowledge of pharmacokinetics and pharmacology.
- Expertise in PK/PD programming with strong quantitative skills applied to develop PPK, PKPD, ER-efficacy, ER-safety, and C-QTc datasets.
- Expertise in software used for dataset construction (e.g. R, SAS).
- Strong track record of working in various therapeutic areas.
- Familiarity with regulatory requirements and trends with respect to data standards.