What is the difference between SDTM and ADaM datasets?

SDTM (Study Data Tabulation Model) organizes collected trial data into a standardized structure for submission. ADaM (Analysis Data Model) builds analysis-ready datasets derived from SDTM, traceable back to it, that support the analyses in the SAP. Regulators expect both, plus define.xml documenting them.

What software environments do you work in?

Primarily validated SAS environments, with R used where appropriate under the same validation and QC discipline. Programming follows double-programming or independent-review QC for critical outputs.

When should biostatistics be involved in a trial?

As early as protocol design. Endpoint choice, estimands, sample size, and randomization are statistical decisions that determine whether a trial can answer its question — correcting them later is costly or impossible.

Can ExcelStat provide an independent unblinded statistician?

Yes. We provide firewalled unblinded statistical support for DSMBs and interim analyses, with strict access controls that preserve the blinding of the sponsor and study team.

Can you take over programming from another vendor mid-study?

Yes. We run a structured transfer: specification and code review, gap assessment against CDISC conformance, and parallel-run verification before assuming delivery responsibility.

Division 06

Biostatistics & Statistical Programming

ExcelStat·Biostatistics

ExcelStat turns clinical data into submission-ready evidence: rigorous study design, defensible analysis plans, and CDISC-compliant deliverables built to regulatory submission standards.

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CDISC

Submission-Ready Standards

CDISCICH E9SDTM / ADaM

Statistical rigor from first protocol draft to final submission

The statistical decisions made at protocol stage determine whether a trial can succeed at submission stage. ExcelStat embeds biostatistical thinking across the study lifecycle, from endpoint selection and sample size through analysis, reporting, and regulatory defense.

Our statisticians and programmers work to CDISC standards and ICH E9 principles as a baseline, not an aspiration, delivering SDTM and ADaM datasets, define.xml, and TLF packages prepared to regulatory submission standards.

Design-Stage Impact: Statistical input where it matters most — endpoints, powering, and randomization considered early, not retrofitted.
CDISC as Baseline: SDTM/ADaM conformance and define.xml validated before delivery — submission-ready by construction.
Independence & Blinding: Firewalled statistical support for DSMBs and interim analyses that protects trial integrity.
Reproducible & Verified: Double-programming and independent QC on critical outputs, so results are verified, not sampled.
End-to-End Programming: One team across SDTM, ADaM, and TLFs — consistent specifications from raw data to final output.
Integrated With Regulatory: Statistical deliverables aligned with submission strategy alongside the ExcelRegX team.

What ExcelStat delivers

Biostatistics and statistical programming capability across design, conduct, analysis, and submission.

Sample size and power calculations
Randomization scheme design and generation
Endpoint selection and estimand definition (ICH E9(R1))
Adaptive and complex design consultation
Protocol statistical section authoring

How an ExcelStat engagement runs

A quality-gated statistical workflow from design consultation to submission handover.

01
Design Consultation
Endpoints, estimands, powering, and randomization strategy defined with your clinical team.
02
SAP & Shells
Analysis plan and mock TLF shells locked before unblinding — no post-hoc ambiguity.
03
CDISC Build
SDTM/ADaM specifications, programming, and conformance validation in parallel with study conduct.
04
Dry Runs & QC
Double-programming of critical outputs and dry runs on blinded data de-risk database lock.
05
Final Analysis & Delivery
Locked-database analysis, TLF delivery, CSR support, and submission-package handover.

Why sponsors choose ExcelStat

Statisticians at the table early: Design-stage involvement helps avoid the underpowered endpoints and analysis ambiguities that derail programs.
Double-programmed critical outputs: Independent parallel programming of primary results — accuracy verified, not sampled.
Conformance before delivery: Datasets ship validated with documented issue resolution, so your reviewers see clean packages.
Integrated with regulatory strategy: Working alongside ExcelRegX, statistical deliverables align with submission strategy from day one.
Estimand-led thinking: Analyses framed around clearly defined estimands per ICH E9(R1), not just isolated p-values.
Clean handovers, mid-study or fresh: Structured transfer and parallel-run verification when taking over programming from another vendor.

Who We Serve

The organizations ExcelStat supports

Pharmaceutical Companies
Biotechnology Companies
Generic & Biosimilar Manufacturers
Medical Device Companies
CROs
Academic Research Organizations

Questions, answered

The essentials sponsors ask before engaging ExcelStat. For anything more specific, our team is one conversation away.

Yes — SDTM and ADaM datasets, define.xml, and reviewer's guides, validated for conformance (for example, using Pinnacle 21) with documented resolution of any findings before delivery.