Inventiv Matrix

Biostatistician

Responsibilities

• Provide statistical supports for clinical study design such as sample size power calculation and generation of randomization schedule for clinical trials
• Assists senior biostatistician in writing statistical analysis plans (SAP) and SAS programming specifications (Tables/Listings/Figure shells) for clinical data analyses
• Provide statistical review of clinical trial documents such as protocol, case report form (CRF), data management plan (DMP), etc.
• Provide statistical guide for SAS programmers to conduct the clinical data analyses
• Perform independent programming validation for efficacy and safety results of clinical data analyses
• Provide statistical QC review of clinical data outputs before delivery to the clinical study team
• Provide statistical support for clinical study report (CSR) and technical support for publications under senior statistician supervision
• Working on variety of studies with Phases I-IV for exploring safety, efficacy and dosage of clinical trials data by extraction, Access and Managing clinical data from various clinical databases (INFORM, Medidata Rave, Oracle Clinical)
• PK/PD Dataset Production, reviewing specifications for Pharmacokinetics/Pharmacodynamics data file developed. further analysis was done for producing tables, graphs and analyses for all reporting events by including PK concentration parameters for a study
• Utilizing Response Evaluation Criteria in Solid Tumors (RECIST) guidelines (version 1.1) for the measurement of Target and Non target lesions in Oncology Studies
• Extensive use of NCI CTCAE 4.03 standard Document for coding the toxicity grades for lab tests and adverse events in new drug development and application process
• Extensive use of MedDRA and WHO-DRUG for coding the adverse events and concomitant Medication terms, CTCAE and RECIST in new drug development and application process
• Pooling of multiple studies datasets by Programming, which leads to development or manipulation or validation of Integrated Summaries of Efficacy (ISE) and Integrated Summaries Safety (ISS) and Generating the BIMO Listings for FDA submission as per the FDA request
• By utilizing of protocol defined Efficacy Endpoints in Tumor assessments like Overall Response, Progression-Free Survival, Time to Progression, Best Overall Response, Time to Treatment Failure for creating Efficacy outputs like Time to event analysis Kaplan-Mayer Plots, Tumor Reduction Waterfall Plots, Tumor Duration Swimmer Plots, Hazard Ratio Forest Plots and Spider Plots
• Using Statistical Models like regression model, ONE WAY ANNOVA, TWO WAY ANNOVA, general linear models, categorical data analysis, survival analysis, multivariate analysis, design of experiments, longitudinal data analysis, randomized trial designs, survey design and analysis for stratification and to find the regressions, linearity of data P-values, Confidence Intervals, Survival estimates in the efficacy analysis
• Development of SAS code for modeling data and directed the implementation of SAS/STAT procedures such as PROC LIFETEST, PROC LIFEREG, PROC PHREG, PROC REG and PROC GLM for Survival analysis, logistic regression analysis and other statistical analyses.

Qualifications

• PhD Degree or Master Degree in statistics or Equivalent, with statistics training
• Generally requires (0-2) years data analysis related experience
• Clinical data analysis experience plus
• Software skill and programming skill: Microsoft Office products, SAS, R, and other software as needed

SAS Programmer

Responsibilities

• Responsible for processing of clinical data required for analysis of clinical trials for Phases 1-4
• Proven experience developing macros from start to finish in a pharmaceutical or biotech company
• Develop SAS coding and table templates for preparing, processing and analyzing clinical data
• Generate and QC summary tables, data listings and graphs for in-house analyses of study data or publications using SAS standard coding practices
• Create/acquire tools to improve programming efficiency or quality validate work of other programmer/analysts
• Create/review programming plan, specifications for datasets and TLFs
• Establish monitoring of data transfers for ongoing trials to identify study conduct or data quality issues. Support data queries from other functional group (Biostatistics, Medical Writing, Clinical Development, Clinical Operations, Regulatory, and Pre-Clinical)
• Excellent knowledge of SAS programming and associated features and their applications in pharmaceuticals industry environment particularly in clinical trial data setting
• Strong understanding of clinical trial data and extremely hands on in data manipulations, analysis and reporting of analysis results
• Track record of generating new ideas and solutions to data analysis
• Excellent application development skills
• Excellent oral and written communication skills

- Data collection
- Data cleaning
- Data delivery
- Data reconciliation
- Database lock
- Data Management activity timelines

• Define the data management files, including but not limited to Data Management Plan (DMP), Data Validation Plan (DVP), SEC, DDT and related documents
• Lead the development, review, and finalization of data transfer requirements
• Serve as primary point of contact for query escalation
• Ensure high customer satisfaction by delivering on promises, meeting timelines, and providing excellent customer service at all times
• Conduct routine status meetings with Sponsor/CRO and internal teams. Provide agenda and meeting minutes to all attendees
• Communicate project status clearly with Sponsors and Project Management
• Other duties and responsibilities may be assigned as required

Qualifications

• Bachelor's Degree (or equivalent) in Health Sciences and 3+ years of relevant experience
• Relevant Experience: Clinical Research, Clinical Data Management, Clinical, Medical, or Master's Degree in a Health-related field and 2+ years of relevant experience
• Possess an understanding of database structure and computer storage in data management
• A basic knowledge of medical terminology, as well as knowledge of a scientific investigative methodologies and clinical research methodologies