Triticon Training Programs

TriTiCon Provides training in Clinical Development, primarily focused on systems used in clinical trials and Clinical Data Management. Our training program is comprised of a series of individual modules, organized in themes, to provide full flexibility so you can tailor the training to suit your needs.

The training is available as “mix & match” (select any combination of modules) or as pre-defined courses (defined set of modules for different objectives and target audiences). The “mix & match” option is available as self-service (eLearning), whilst the pre-defined courses has both a self-service and instructor lead option. Read more on the About Training page.




  • Clinical development stages, objectives and outcomes
  • The basics of clinical trial design and statistics
  • Clinical data collection & the role of clinical data
  •  Clinical development functions
  •  The role and objectives of clinical data management
  •  Clinical data management ABC
  • Set-up (planning, eCRF Set-up and UAT, handling of external data)
  • Conduct (data review and cleaning, status management)
  • Close out and delivery (database lock, data management deliveries, archiving)
  • Planning, start-up activities and timelines
  • Typical data management documents
  • eCRF design and set-up
  • ePRO / eCOA, handling of external data
  • System specifications and UAT
  • Data cleaning and query management
  • Data review and monitoring
  • Handling of external data, reconciliation
  • Residual data issues, protocol deviations
  • Status management
  • “Clean file” checkpoints
  • Database lock and release
  • Data management deliverables
  • Archiving and close out



  • Changes, trends and challenges in clinical data management, including topics like, distributed/virtual clinical trials, dynamic/adaptive trials, new types of data sources, sourcing and oversight, and from data management to data science.
  • Sourcing models (services and systems)
  • Sourcing options and key considerations for sourcing data management services and systems
  • Vendor contracting and oversight basics
  • Oversight in data management
  • Definitions of clinical data quality
  • Data quality risks management
  • Data quality planning and responsibilities.
  • Data quality monitoring, quality controls
  • Bias and fraud
  • Overview of industry standards
  • Standards management/governance
  • Standards in action. Getting standards to work in your favour and as an enabler rather than a constraint
  • The changing role of the data manager. Future responsibilities and key skills
  • Data management within the organization (from sponsor and CRO perspective)
  • Ownerships and responsibilities
  • Stakeholder and expectations management
  • The role of a department/team business plan.  Suggested components and considerations
  • Processes monitoring and continuous improvement methods



  • Overview of clinical systems (role, scope, key functionalities, handled data, users)
  • Typical data flow and data/information touch-points (related / redundant data)
  • The basics of system validation
  • Overview of clinical data sources and data flow
  • System  data/information “touch-points”
  • Data flow models and key considerations
  • Specific cases: SAE-data, lab-data, ePRO, IRT vs EDC
  • Consolidated data for medical monitoring, oversight and trial management
  • Basic and “2nd level” system modules
  • System and vendor categories
  • Key considerations and differentiators
  • Best practice for EDC/eCRF configurations and trial set-up
  • Introduction to patient/observer reported data (Validated instruments, regulatory requirements)
  • Set-up process and timelines, requirements for CTA/EC/IRB submissions, translations and instrument validity
  • Monitoring and compliance management
  • Technology and Vendor categories and considerations
  • Real life challenges and pit-falls
  • Set-up activities, best practice design, UAT
  • Data handling,  deviation handlings
  • Close out / archiving
  • System (and vendor) selection, recommended methodology/steps
  • System implementation, recommended approach and key considerations
  • System validation in practice



  •  Clinical systems choices and strategies – for your company needs
  •  System vs. service selection.
  •  Own versus trial-by-trial sourcing considerations
  • Definitions and regulatory requirements
  • The oversight process
  • Structuring and planning your oversight
  • Oversight conduct and documentation
  • Do’s and don’ts, practical recommendations
  • Definitions, regulatory requirements
  • Risk Management in practice: making regulatory requirements and business benefits meet
  • Suggested risk assessment areas, methods and processes
  • Navigating  the cross-functional world
  • The benefits and challenge of “responsibility splitting”
  • Leading specialists
  • Training and learning in the 2020’s

Download overview in pdf-format here


Pre-defined courses have self-service or instructor lead options (registration link below). Contact us for courses further tailored to your specific needs. Download course description in pdf format here .

Pre-defined Options

Questions? Just email us or use the contact form.