Certara Pharmacology Scientist Post Vacancy – Apply Online
This role involves interpretation (analyzing and Quality control) of Clinical trials data across various therapeutic areas and actively contribute to the development of database products that support informed decision making at various stages of clinical development and post-approval phases using modelling and simulation approaches. This job necessitates a profound knowledge of pharmacology and clinical research, understanding of statistics, experience in development, quality management and change management process of clinical databases for conducting a systematic literature review and meta-analysis (pairwise, network and model-based meta-analysis), knowledge of Information science, a PICOS based Clinical/Medical literature search approaches
Job Title: Scientist, Quality Manager
Location: Secunderabad, Telangana, IN
Eligibility:
- Masters in Pharmacology or Pharmaceutics (with relevant experience), Pharma D, Clinical Practice, Masters in Public Health and Epidemiology. PhD in Pharmaceutical sciences, MD Pharmacology are eligible with minimal/no work experience
- Minimum 5-7 years of experience in the areas of Information science, Systematic Literature review, Health-economics and public health sectors, pharmaceutical industry experience preferred
- Strong knowledge of Pharmacology and clinical research is a must
- Knowledge of clinical development and post-approval phases, PICOS approach, trial designs, Pharma Industry data standards/ontologies
- Good Knowledge of statistics, data management tools like R is an added advantage
Skills & Abilities:
· Comfortable in a team environment and able to communicate with and collaborate with peer scientists
· Excellent interpersonal skills
· Excellent domain training skills
· Strong learning skills to be able to support databases in multiple disease areas
Responsibilities:
- Play a key role in the development of clinical database products in various therapeutic areas like Metabolic & CV, Neuroscience, Autoimmune, Oncology, Respiratory etc., with a very high quality that supports Meta-analysis (Pairwise, Network and Model-based meta-analysis)
- Analyze and Review or Quality control the information pertaining to
- Trial design, treatments, demographics and outcomes data (biomarker, clinical, safety and quality of life outcomes) for the full-time course from clinical literature (Journals, conference abstracts, Regulatory reviews etc.)
- The data extracted from graphs for outcomes reported on linear, logarithmic and semi-log scales with precision
- Perform the above consistently with very high quality, provide the required feedback and training to the data analysts & reviewers at L1/L2/L3 continuously thereby contributing to the enhancement of database quality and ensure the reduction of rework
- Involve in pilot and sample database products to evolve and validate the specifications, develop metadata lists thereby contributing to comprehensive processes
- Work in a team environment with lead consultant, peer data analysts, data reviewers, Team leader and Project Manager and actively contributing to the database rules, specifications and a comprehensive quality management system on a continuous basis to assure “first time correctness”
- Actively contribute to process implementation, identify process enhancements and ensure change management necessities
- Review and finalize the queries and special cases raised by the team to set up appropriate workflows and thereby monitor the change management process
- Conduct the literature search in multiple data sources using the search strategies developed by Team leader and cross verify the synonyms and related terms used as search terms
- Review the literature search results, identify the miss cases and share the analysis report basing which the PICOS based search algorithm shall be enhanced (by the lead consultant/Team leader/Project Manager) to include the specific terms resulting in the miss cases
- Work closely with Data analysts and Data reviewers and train them with specifications, data standards, checklists and recommend right ontologies for data consistency
- Consolidate the data from reviewers and ensure quality control by submitting relevant documents like checklists, error logs and Acceptance or Rejection report to Team leader
- Undergo relevant training programs (Statistics, R coding, Systematic literature review and Data analysis methods) and excel in these skill enhancement programs to grow in the organization ladder
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