Priyaben Patel
*********@*****.***
Fremont, CA 415-***-****
PROFESSIONAL SUMMARY:
3.1 years of experience of SAS Programming and Data analysis in the Pharmaceutical Industry.
* **** ** ****rience in field project with UC San Diego in Pharmaceutical data analysis and SAS programming.
Thorough knowledge of clinical trials of Phases I, II and III within Infectious disease, dermatology and oncology therapeutic studies.
Very good programming experience in using all Base SAS, Advanced SAS and statistical procedures.
Extensive experience in preparation of SDTM datasets, analysis datasets (ADaM), tables, listings and graphs.
Very good experience in analyzing Case Report Forms (CRF), Clinical Data, Validation and Documentation.
Worked on FDA Submissions and have good knowledge of CDISC SDTM standards, ADaM standards, Code of Federal Regulation (21 CFR Part 11), ICH, GCP guidelines.
Base SAS certified for SAS9 and a SAS Certified Clinical Trials Programmer Using SAS9.
Very good understanding of each assigned protocol, critical tasks and milestones.
Met the study requirements in a timely manner. Identified, tracked, and resolved Data and TLFs queries.
Excellent communication, interpersonal skills with strong analytical and problem-solving skills.
Ability to learn quickly and take up new tasks and responsibilities.
PROFESSIONAL EXPERIENCE
SAS Programmer / Analyst (Volunteering work)
ClinBiometrics USA July 2018 – Sep 2018
Worked on SAS 9.3
Worked on Dermatology Therapeutic area.
Reviewed annotated CRF and gave comments on it.
•Reviewed specification for SDTM datasets.
•Prepared and validated SDTM datasets such as DM, AE, EX, CM, MH, CO, PE, VS, SC, SV, ZA etc. as per CDISC standards.
•Validated ADaM datasets such as ADSL, ADAE, ADEX, ADEFF, ADSEFF, ADIGA, ADVS as per CDISC standards and requirements of SAP.
•Participated in study meetings and provided input about complex variables.
Cognizant Technology Solutions - Mumbai, India. May 2011- March 2014
Data Analyst/SAS Programmer
Worked on SAS 9.1,9.2.
Worked on infection, oncology therapeutic studies.
Performed CRF review, Mock shell review for the assigned studies.
Did SDTM annotation of CRF.
Worked on Raw to SDTM data and SDTM to ADaM data Programming specification and Validation documents.
Developed Trial Design Datasets (TA TE TV TS TI).
Created SDTM datasets (Demographics, Exposure, Disposition, Adverse Events, Medical History, Physical Examination, Concomitant Medications, Vital Signs, etc.) as per CDISC standards.
Created reporting datasets (RDB/ADAM) like ADSL, ADRS, ADTTE, ADEFF, ADAE, ADEX, ADVS as per SAP and CDISC standards.
Worked collaboratively with Data management team and biostatistician to meet project deliverables and timelines for clinical data quality checking and reporting.
Ensured completeness, correctness and consistency of routine clinical data and data structure.
Programmed statistical summary tables, graphs, and subject data listings using SAS programming.
Validated Data and TLFs.
Converted Xml and CSV files into SAS datasets by using Proc import procedure, Libname and infile statements.
Used Output Delivery System (ODS) facility to direct SAS outputs to PDF files.
Worked on Define.xml file.
ACADEMIC EXPERIENCE
UCSD School of Extended Studies and Public Programs, Biostatistics 2016–2017
Project 1
Analyzed Lipid data and investigated the relationships between two cholesterol lowering drugs, lifestyle
information, and blood lipid levels by using SAS Enterprise guide 7.1
Summary
Analyzed characteristics of study population by descriptive statistics by using proc means, Proc Freq and proc univariate procedures.
Did hypothesis test and calculated confidence interval of two population means by using Proc Ttest
Did hypothesis test of two categorical variables by using Proc Freq.
Did correlation and regression analysis of the two continuous variables by using Proc Reg.
Created Report.
Project 2
Analyzed epidemiologic data that suggests that the use of non-steroidal anti-inflammatory drugs
(NSAIDS), including aspirin, is associated with a decreased risk of colorectal cancer by using SAS 9.3
Summary
Analyzed characteristics of study population by descriptive statistics by Proc Means and Proc Freq.
Calculated OR and its 95% confidence interval by using Proc Logistic.
Did analysis of confounding variables and fitted the model.
Created summary table and report.
EDUCATION
Biostatistics Certification, University of California, San Diego, CA 2017
CDISC Standards for Clinical Data, University of California, San Diego, CA 2016
Master of Science in Biostatistics, Maharaja Sayajirao University, Baroda, India 2011
Bachelor of Science in Microbiology, B.P. Baria Science Institute, Navsari, India 2009