Study Design
“Clinical Strategy & Medical Writing”
Design conflicts surfaced early, the statistical framework aligned with what the data can realistically support, and a protocol that satisfies regulatory requirements within the actual budget and timeline.
Typical Deliverables
The Problem
A single study with 50 patients cannot simultaneously power a primary efficacy endpoint, a non-inferiority comparison, and three secondary objectives. The root cause is usually a disconnect between what the business wants to claim, what the study can realistically demonstrate, and what the regulatory pathway requires. These conflicts need to be identified before the first patient is enrolled.
The Approach
Every engagement starts at the intersection of clinical science, biostatistics, and regulatory strategy, with one question: what does the study need to prove, and what can the data realistically support?
From there, a clinical evidence strategy takes shape that aligns the study design with the regulatory pathway, the budget constraints, and the current state of the art in the therapeutic area — resulting in a protocol that is scientifically sound, statistically powered, and regulatory-ready.
Service Catalog
Clinical Research Strategy
Strategic assessment of the clinical evidence needed for regulatory approval: what questions must be answered, what data already exists, and what studies are needed. Claims are mapped to the evidence required to support them, identifying the most efficient path to market — a single pivotal trial, a literature-based approach, or a phased evidence-generation plan.
Study Design & Protocol Development
Full protocol development compliant with ISO 14155, from study rationale and objectives through endpoint selection, inclusion/exclusion criteria, visit schedules, and data collection plans — designed to be operationally feasible, statistically sound, and aligned with the regulatory submission strategy. Deliverables include the Clinical Investigation Plan (CIP), Investigator's Brochure (IB), and a Statistical Analysis Plan (SAP).
Sample Size Estimation & Statistical Analysis Plans
Rigorous sample size calculations based on the primary endpoint, expected effect size, and regulatory requirements. Complete Statistical Analysis Plans (SAPs) cover primary and secondary analyses, interim analyses if applicable, handling of missing data, sensitivity analyses, and subgroup analyses — all calculations performed in R with fully documented, reproducible code.
Independent Statistical Analysis
End-to-end statistical analysis of clinical study data using R/RStudio — from data cleaning and exploratory analysis through confirmatory hypothesis testing and final study reports. All analyses are fully reproducible with documented code, validated against the SAP, and presented in publication-ready tables and figures.
Study design decisions are only as good as the state-of-the-art baseline they rest on. Where the current evidence base hasn't been systematically established yet, a clinical evidence assessment typically comes first — the same PICO framework then carries through into the protocol's comparator and endpoint choices.
Regulatory Framework
All pre-market services are delivered in compliance with the applicable regulatory and normative framework:
- —EU Medical Device Regulation (EU) 2017/745 (MDR)
- —ISO 14155 — Clinical investigation of medical devices for human subjects
- —21 CFR 812 — Investigational Device Exemptions (FDA)
- —ICH E6(R2) — Good Clinical Practice
- —ICH E9 — Statistical Principles for Clinical Trials
- —MEDDEV 2.7/1 Rev. 4 — Clinical evaluation guidance
- —MDCG guidance documents (as applicable)
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