SEIA Inc.

•SEIA Inc. established in 2010 with the sole purpose of providing customer driven statistical and data analytics.

•Since inception SEIA Inc. has grown exponentially on the backbone of client centric services and delivering results of exceptional quality and compliance.

•The growth of SEIA Inc. is achieved by it’s team consisting of highly motivated professionals obsessed with quality and driven by efficiency.

•SEIA Inc. has successfully collaborated with top Pharma / Biotech / Medical Device companies including Pfizer, J&J, Amgen, Medtronic, PPD, ICON, BMS, GSK.

Integrity:

•We are grateful for our success and equally aware of our failures, we own our achievements and lessons learnt as integrity is built in our process.

Quality:

•We believe in quality over quantity and strive for accuracy and consistency.

•Our process is continuously evolved to be more efficient than before, thus helping us work diligently without compromising on quality.

•Quality control methods utilized are Output Review, Cross check, Independent Programming, Code review, log check and others as applicable.

Time Management:

•Transparency in our process allows us to evaluate and manage our time effectively while maintaining quality in our deliverables.

•Open and clear communication is encouraged enabling focus on quality of outputs.

•Project and Time management techniques are deployed generating efficiency in the process and encouraging innovation thus creating a positive feedback loop.

•SDTM services include converting legacy datasets to SDTM standards and developing SDTM datasets for ongoing studies.

•Industry standards and guidance documents utilized when developing SDTM datasets are CDISC SDTM IG, SDTM controlled terminology and TAUG along with P21 validation.

•Client mapping standards take priority over CDISC SDTM standards where applicable.

SDTM Mapping Process:

•Annotate CRF per established annotation guidelines.

•Map raw datasets to SDTM domains and create custom domains where applicable.

•Program and Validate SDTM domains.

•Create and review Define.xml

•Create Study Reviewer’s guide and produce submission package.

•Industry standards and guidance documents utilized when developing ADaM datasets are CDISC ADaM IG, ADaM CT and ADaM OCCDS guide.

•The source datasets can be SDTM domains or raw datasets for legacy studies.

ADaM Mapping Process:

•Review SAP and TLF shells to determine analysis variables and dataset structure needed for efficient programming.

•Develop ADaM specifications by utilizing information from SDTM domains, SAP and TLF shells.

•Program and Validate ADaM datasets.

•Create and review Define.xml

•Create Study Reviewer’s guide and produce submission package.

TLF Programming involves support for various kind of analyses including Ad-hoc requests, Post-hoc and exploratory analyses, DSMC meetings, DSURs, Annual updates, ISS, ISE, Abstracts, Manuscripts, Posters, IB, Interim and Final analyses.

TLF Programming Process:

•TLFs are created per SAP and TLF shells.

•TLFs are validated by following client SOPs, guidelines and all applicable SEIA SOPs and best practices.

•TLF review involves cross checking for consistency across different outputs, quality process to ensure a deliverable accurately reflects its input data and specifications.