Learning Center
Every Clinical SP Bootcamp part as an interactive lesson — concept scenes, checkpoint quizzes with graded answers, and hands-on exercises built on a simulated oncology study. Each lesson pairs with its source article and saves your progress locally in this browser. No account, no tracking, works on a phone, fully readable without JavaScript.
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21
lessons live
245
scenes
40 · ~7.5h
quizzes · study time
Built by the NDA statistical programming lead behind an FDA-approved product · series archived on Zenodo · companion research cited at PharmaSUG 2026 · 7 lessons with video companions
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AI-narrated video companions for the lessons — same content, spoken over the slides. Paired articles embed their video today; lesson-page video slots light up as the new pipeline publishes them.
Start Here
2/2 live
Orient yourself: the full learning path, and how to read the two documents that drive everything downstream.
A systematic path into clinical statistical programming: CDISC fundamentals, modern SCE workflow, and where AI agents fit — every part with runnable takeaways.
ready 12 scenes 2 quizzes hands-on ▶ video read the article ~22 min
Turn a protocol and SAP into a programmer's work list: endpoints, populations, windowing, dates, and query discipline for what the documents leave silent.
ready 11 scenes 2 quizzes hands-on companion article forthcoming ~20 min
SDTM
3/3 live
The CDISC tabulation model — domains, variable patterns, controlled terminology, and mapping specifications.
SDTM domains explained: domain classes, the topic-timing-qualifier variable pattern, USUBJID, controlled terminology, SUPPQUAL, and a day-one reading order.
ready 12 scenes 2 quizzes hands-on read the article ~22 min
A worked SDTM AE domain mapping example: MedDRA coding, serious flags, partial ISO dates, AESEQ derivation, SUPPAE, and CORE validation triage from a mock raw extract.
ready 12 scenes 2 quizzes hands-on read the article ~22 min
How to write an SDTM mapping specification: column anatomy, a row-by-row VS domain walk, hygiene rules, and how specs become define-XML and machine-usable code.
ready 12 scenes 2 quizzes hands-on read the article ~22 min
ADaM
6/6 live
Analysis datasets: ADSL, BDS, OCCDS, time-to-event, and the derivations reviewers check first.
How ADSL is built: deriving treatment dates and population flags from DM/EX/DS/SV, the one-row-per-subject rule, and the QC checks that catch real discrepancies.
ready 10 scenes 2 quizzes hands-on ▶ video read the article ~19 min
The BDS skeleton behind ADaM analysis datasets: PARAM/PARAMCD/AVAL, baseline flags, change from baseline, and how ADVS and ADLB are built visit by visit.
ready 11 scenes 2 quizzes hands-on ▶ video read the article ~20 min
ADAE from the OCCDS side: one row per event, the AE-to-ADSL merge, treatment-emergent flags driven by TRT01SDT, serious flags, and the QC defects reviewers catch.
ready 12 scenes 2 quizzes hands-on ▶ video read the article ~22 min
ADTTE step by step: event and censoring definitions from the SAP, the censoring date cascade, CNSR semantics, partial dates at the event, and QC listings per subject.
ready 12 scenes 2 quizzes hands-on read the article ~22 min
Visit windowing, baseline flags, and LOCF decide whether BDS datasets are right: anchor rules, ABLFL derivation, DTYPE discipline, and defect patterns reviewers find.
ready 12 scenes 2 quizzes hands-on companion article forthcoming ~22 min
ADRS turns RECIST 1.1 assessments into analysis data: TU-TR-RS traceability, overall response per timepoint, best overall response, PD dates, and PDS hand-off to ADTTE.
ready 11 scenes 2 quizzes hands-on companion article forthcoming ~20 min
TLF
2/2 live
Tables, listings and figures — from mock shell to the RTF output that actually ships.
How clinical TLF outputs ship: reading mock shells, PROC REPORT tables and listings, RTF conventions, and the four-pass QC order that catches defects cheapest first.
ready 12 scenes 2 quizzes hands-on ▶ video read the article ~22 min
SAS macros for clinical TLF: the driver pattern over a metadata table, parameter discipline, %local hygiene, and MPRINT debugging for classic macro failures.
ready 12 scenes 2 quizzes hands-on companion article forthcoming ~22 min
SCE & Modern Workflow
4/4 live
The modern toolchain: computing environments, Git in a GxP world, pipelines as code, and AI inside the boundary.
What a statistical computing environment is for in clinical trials, why desktop SAS and shared drives failed audits, and how cloud SCE workflow changes day one.
ready 12 scenes 2 quizzes hands-on ▶ video read the article ~22 min
Why filename-versioned SAS programs are an audit-trail liability, the minimum Git vocabulary a clinical programmer needs, and how branch-per-output maps to QC.
ready 12 scenes 2 quizzes hands-on read the article ~23 min
How to turn the SDTM-to-ADaM-to-TLF chain into pipeline as code: explicit dependencies, pinned environments, hash-verified outputs, and stage-level failure isolation.
ready 12 scenes 1 quizzes hands-on read the article ~21 min
The governance question sponsors actually ask about LLMs, how GAMP 5 and CSA risk-based assurance frame AI-assisted programming, and where human accountability sits.
ready 12 scenes 2 quizzes hands-on companion article forthcoming ~22 min
Submission
1/1 live
Define-XML and the Reviewer’s Guide — what regulators open first, and how programmers shape it.
Define-XML 2.1 and the ADRG from the programming side: element-by-element metadata, spec-driven generation, and the defects to sweep before the package ships.
ready 12 scenes 2 quizzes hands-on companion article forthcoming ~22 min
Statistics
1/1 live
The inference layer: p-values and tests you must be able to explain out loud, in plain language.
The tests a clinical SAS programmer must explain: p-values, confidence intervals, Wilcoxon, Fisher, MMRM, log-rank, multiplicity, and the QC craft behind every cell.
ready 12 scenes 1 quizzes hands-on companion article forthcoming ~21 min
Career
2/2 live
What interviews actually ask, and a realistic 2026 roadmap into the role.
How clinical SAS interviews actually work: four rounds from SAS mechanics to GxP habits, real-format questions, and the signals strong answers contain.
ready 10 scenes 2 quizzes hands-on ▶ video read the article ~19 min
What the job is, who gets hired, and how to train for it: a realistic 2026 guide to becoming a clinical statistical programmer, from SAS base to AI-assisted practice.
ready 12 scenes 2 quizzes hands-on read the article ~22 min
Same honesty rule as the interactive explainers: teaching schematics and illustrative values, never presented as measured study data. Registry regenerated by learn-center/scripts/build-registry.mjs.
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