Course: Hands On Clinical Reporting Using R
Modules:
Welcome to Hands On Clinical Reporting Using R!
Introduction Fundamentals, Phase 3 Clinical Trials - Protocol & SAP, Data Collection - Using CRFs and Other Means, CDISC SDTM and ADaM Standards, FDA(U.S.) Submission Package, Clinical Data Flow: From Raw Data to Final Outputs
Introduction SDTM, Context and Workflow, SDTM Data Mapping, Programming SDTM
Introduction, What is ADaM?, Subject-Level Analysis Dataset Structure (ADSL), Occurrence Data Structure (OCCDS), Basic Data Structure (BDS), The Vision, admiral and pharmaverse for ADaM Development, Storing and Using ADaM Metadata, Part 1 - Metacore Object, Part 2 - Metacore Object, Part 3 - Metacore Object, QCing and Exporting ADaM, Part 1 - ADSL demo, Part 2 - ADSL demo, Part 3 - ADSL demo, Module Review
Introduction to OCCDS and ADAE, ADAE Training Overview, What to expect going into Session 1, Adverse Events background, R Packages, Tools and Resources for this training., Getting started programming ADAE in R, Let's read in the source data, Converting blanks to values to NA, Merging in ADSL variables, Deriving Adverse Event Start datetime, Deriving Adverse Event End datetime, Relative days of an AE from first exposure to study drug, AE Durations, What to expect in Session 4, Last Dose datetime, How to check Last Dose datetime derivation, Severity and Causality, What will be covered in this Session?, Flagging Treatment-Emergent AEs, Treatment-Emergent Flag window, Flagging AE Occurence, What are Standard MedDRA Queries (SMQs) and Custom Queries (CQs)?, Deriving Standard MedDRA Queries (SMQs) and Custom Queries (CQs), What to expect in Session 6, Adding in ADSL variables, Deriving Analysis sequence, Reading in your ADaM specifications, Checking variables between your dataset and specifications, Dropping unneeded variables from your dataset, Ordering variables in your dataset, Sorting your dataset by the sort key per your specfications, Variable Length attributes, Variable Label attributes, Controlled-Terminology checks, Final XPT check and conversion, Module Review
Creating static TLGs for clinical reporting with R, Lesson 1: Introduction & Concepts, Basic concepts of TLGs, How to decide on which TLGs are needed?, Stages of TLG development, Introduction to NEST, Key packages for TLG development, Lesson 1 Overview, Introduction to Lesson 2, Introduction to the Tern package, Tern analyze functions, What is rtables?, Concept of rtables, Introduction to demonstrations, Demography table, Demography table walk-through, Demography table conclusion, Adverse Event table introduction, Adverse Event walk-through, Adverse Event Table conclusion, Response Table Introduction, Response table - preprocessing the data, Response table walk-through part 1, Response Table walk-through part 2, Response Table part 3, Response table walk-through part 4, Response Table walk-through conclusion, Lesson 2 conclusion, Introduction to TLG Catalog, Anatomy of TLG Catalog, Feedback to TLG Catalog, TLG Catalog Demo Part 1, TLG Catalog Demo Part 2, Lesson 3 Summary, More on NEST packages, Industry collaboration efforts
Motivation for Interactive Data Displays, Introduction, What is teal?, Teal demo, Teal key features, How does teal work?, Demo modules using teal.gallery, Using teal as a data scientist, Introduction, Teal installation guide, App development worflow, App project setup, First teal app, Filters in teal, Advanced filters, Introduction, Teal app development workflow, Data review modules, Loading data, Code reproducibility, Processing input data, Adding a demographics table module, Adding an adverse events table module, Adding a KM plot module, Build the full app, Module review
Conclusion