If you build global budgets, Japan is the country that doesn’t fit the template. No grid, no line-by-line check against your FMV tool. Just a cost per patient, a few institution fees, and a note that medical expenses will be billed separately. Here’s what a Japanese budget looks like, why it’s built that way, and where the switch to FMV really stands.
A practical introduction to Veeva Vault for clinical trial budget analysts, covering document lifecycles, workflows, version control, audit trails, and what to do when things go wrong. Based on experience working on Takeda studies.
A practical guide to clinical trial budgeting in Belgium, covering the regulatory timeline, site setup requirements, patient reimbursement, contracts, Power of Attorney, GDPR, withholding, and payment considerations for IGAs and budget developers.
A Start-up total that looks reasonable isn't the same as one that's been tested against the study. Here's how to benchmark Start-up requests from first principles, spot the line items that deserve a second look, and write payment terms that protect the sponsor if a site never activates.
Site fees are the least standardized, most inconsistently named part of any CTA and Start-up is where it gets worst. Here's how to break black-box start-up fees into specific, verifiable activities you can actually evaluate.
If you've built an observational study budget, you know it's one of the simpler builds you'll encounter - lean SOEs, no IP administration, no PK draws. But why do these studies exist at all, and why does a drug that just finished a multi-thousand-patient Phase III program need more data collected on it? This article breaks down the logic behind observational research, the different study types you'll encounter, and what it actually means for the work on your desk.
Observational studies are often misunderstood in clinical trial budgeting. This article explains how to scope observational and non-interventional study budgets correctly, what costs should always be included, when additional procedures need to be coded, and how to handle common edge cases that create confusion during budget build.
Why do sponsors use central labs instead of local site laboratories? This article explains the real reason behind the central lab model in clinical trials, how it improves data consistency across global studies, the operational burden it creates at the site level, and why it matters for clinical trial budgeting and contract negotiations.
Central vs. local lab assumptions are one of the fastest ways to either overbuild or underbuild a clinical trial budget. This article breaks down how to code each setup correctly, how mixed lab models should be handled, and which assumptions must be documented to avoid costly rework, sponsor pushback, and site payment issues.
Protocol amendments are an inevitable reality of clinical research, not a reflection of budgeting errors. This guide explores how to distinguish between simple and complex amendments, manage the impact on site contracts, and execute a methodical "Delta Analysis" to keep your study on track.
