Digital Transformation - Life Science

The programme focuses on enhancing learners’ knowledge, skills and competencies associated with the concepts of the smart factory.

Students will also learn more about the evolution of life science manufacturing from a traditional reactive process to the emergence of Industry 4.0 and Pharma 4.0. This programme is delivered in partnership with Innopharma.

Why study Digital Transformation at Griffith College?
• Gain knowledge and insight to develop and implement a digital transformation strategy for your organisation
• Explore the technology that is driving the digital transformation and understand what it means for an organisation
• Harness the power of disruptive technologies to improve operational excellence and increase business value
• Analyse the impact of digital transformation on organisational structure and critical skills and competencies

Course Highlights
• Experienced academic and industry lecturers
• Designed and developed in conjunction with Microsoft
• Minimise disruption to your schedule with blended learning solutions
• Gain expertise in process digitisation, digitalisation, data management, data analytics and data visualisation
• Upskill for the thriving Irish life sciences industry.

Subjects taught

Course Modules
Advanced Manufacturing in the Smart Factory
Business Case Development
ECTS Credits: 5
• Business case development
• Business model canvas
• Risk analysis
• Solution selection
• Project management
• Change management and communications strategies

Quality Management in a Digital Age
ECTS Credits: 5
• Future definition of quality
• Lifecycle approach to pharma and medical device
• Quality by design (QBD)
• Quality metrics
• Regulatory guidance on quality

Big Data Acquisition and Management
ECTS Credits: 10
• Types of data
• Data sources
• Data pipeline models
• Data acquisition
• Business intelligence
• Data processing and preparation
• Data warehousing
• Hybrid architectures
• MES and data serving

Business Strategy and Change Management
ECTS Credits: 5
• Current challenges of the pharmaceutical industry
• Strategic thinking in the biopharma industry
• Leading change in the biopharma industry
• Maturity matrix
• Culture of innovation
• Corporate governance and business ethics

Operational Excellence - Lean Sigma 4.0
ECTS Credits: 5
• Origins of operational excellence
• Operational excellence implementation models
• Lean sigma implementation
• Design for six sigma
• Science of innovation
• Key performance indicators
• Quality function deployment

Analysis of Big Data
ECTS Credits: 10
• Big data analysis
• Descriptive analytics
• Diagnostic analytics
• Predictive analytics
• Prescriptive analytics
• Analytical applications

Research Methods
• Research process
• Literature review
• Research questions and hypotheses
• Ethical & GDPR considerations
• Quantitative and qualitative methods
• Project management

Visualisation and Storytelling with Data
ECTS Credits: 5
• Learners are equipped to effectively use computer-based data visualisation techniques and strategies to communicate information, encompassing critical analysis and evaluation of data, construction of datasets, presenting complex data in order to provide clear, effective, and engaging graphical information representations.

ECTS Credits: 30
• Dissertation selection
• Literature review
• Dissertation hypothesis
• Primary research methodologies
• Findings and analysis
• Discussions and recommendations
• Viva presentation

Entry requirements

This course is suitable for those who possess qualifications at NFQ Level 8 Honours degree with a 2.2 or higher in a Science, Manufacturing, Quality, Computation, Engineering or a related discipline. Recognition of Prior Learning will also be taken into account.

English Language
Griffith College is accepting the online Duolingo English Test (DET) as valid proof of English proficiency.

Application dates

How to Apply
Please apply online directly to Griffith College.


1 year full-time.
Timetables to be confirmed.

Enrolment dates

Intake Dates
We run two intakes for this course, commencing as follows:
Autumn: September*
Spring: February*

*subject to sufficient numbers.

Post Course Info

Academic Progression
Options will depend on the academic requirements and the career choice of the learner.

Career Progression
Potential roles for graduates of this course include:
• Digital Transformation
• Advanced Manufacturing
• Process Analytical Technologies
• Process Digitisation / Digitalisation
• Regulatory Affairs / Compliance
• Data Architecture & Analytics
• Operational Excellence

More details
  • Qualification letters


  • Qualifications

    Degree - Masters (Level 9 NFQ)

  • Attendance type

    Full time,Daytime

  • Apply to

    Course provider