Overhead view of a clinical data review session — a wide desk with printed CRF pages, a laptop screen showing tabular datasets, and a hand holding a pen annotating a data listing in natural window light from the left
Overhead view of a clinical data review session — a wide desk with printed CRF pages, a laptop screen showing tabular datasets, and a hand holding a pen annotating a data listing in natural window light from the left
— Clinical & Bioinformatics

From raw data to regulatory submission — one structured workflow.

CDM, clinical analytics, bioinformatics, and RWE are not separate capabilities here. They run as a single evidence chain — organized to meet sponsor and regulator requirements from the first data point.

Close-up of hands at a workstation reviewing a bioinformatics pipeline output on a wide monitor — sequence alignment rows visible on screen, natural overhead lab lighting, a printed protocol sheet on the desk beside the keyboard
Close-up of hands at a workstation reviewing a bioinformatics pipeline output on a wide monitor — sequence alignment rows visible on screen, natural overhead lab lighting, a printed protocol sheet on the desk beside the keyboard
/ Professional Services

Four disciplines. One submission-ready output.

Clinical Data Management

Database build, CRF design, data cleaning, and CDISC-compliant dataset delivery. Structured for audit-readiness at every stage of the trial lifecycle.

Clinical Data Analytics

Statistical programming, TLF generation, and SAS/R-based analysis support aligned to ICH E9 and sponsor SAPs. Output built for regulatory review, not internal dashboards.

Bioinformatics

Genomic pipeline design, variant annotation, and multi-omics data integration. Workflows documented to meet data integrity requirements for IND and BLA submissions.

Real World Evidence

RWD curation, RWE study design, and HEOR analytics using claims, EHR, and registry sources. Framed against regulatory-grade evidence standards, not just internal reporting.

▸ Industrial Training

Practitioners learn by doing the actual work.

Every program runs on production-grade data standards. Trainees leave with hands-on hours in the tools and workflows your organization already uses — not a certificate and a slide deck.

CDM & Data Standards

Statistical Programming

Bioinformatics Pipelines

RWE Study Design & Analytics

CDASH, SDTM, and ADaM mapping exercises on real trial data structures. EDC system workflows and data reconciliation practice included.

Hands-on SAS and R programming for clinical data analysis — TLF production, validation macros, and output review against mock SAPs.

NGS data processing, variant calling workflows, and annotation pipelines in Python and R. Documentation practice built into every module.

Study protocol development for RWD sources, comparative effectiveness analysis, and evidence dossier preparation aligned to FDA RWE guidance.

Your data has a regulatory destination. Let's map the route.

Whether you need a CDM team, a bioinformatics pipeline review, or a training program for incoming analysts — bring the scope and we'll size the engagement.