The Irish life sciences sector has consistently been a leading producer of pharmaceuticals and biotechnology products and is now facing pressure to digitally transform its approach to Quality Risk Management (QRM). This dissertation has described how Big Data Analytics (BDA) can help in improving QRM to enable predictive modelling, real-time monitoring and data-driven decision-making under the systems of ICH Q9. A positivist philosophy, and deductive methodology were used to gather the primary data through an online survey of 109 industry professionals, 103 valid responses were used to analyse variables using descriptive and inferential statistics. The findings show that although more than 60 percent of the organisations have started implementing BDA, maturity level and integration is not high due to legacy systems, regulatory and complexity and skills gaps in the workforce. However, companies who have implemented BDA already see tremendous benefits such as reduced deviations, faster batch release, audit preparedness and reductions in cost. Statistical results identify digital maturity, good data governance and competency of the employees as key factors that facilitate success with BDAdriven QRM. The dissertation presents concluding comments and recommendations to the Irish life sciences organisations including a recommendation to the organisation regarding investment in digital infrastructure, skills, and well developed governance frameworks that would ensure that the organisation complies with the regulations as well as be competitive in the long-term. This study can contribute to the academic debate on the digital transformation within the life sciences sector and serve as a practical guide to industry leaders and policymakers interested in making the highly regulated Irish life science environment, including the pharmaceutical and bio sector, more competitive and compliant.