Harnessing data analytics to propel drug discovery and development in 2025

As the pharma landscape evolves, data analytics will be at the forefront of drug discovery and development, transforming traditional methods. By leveraging data-driven insights, companies can expedite R&D, optimise clinical trials, and personalise treatments, bringing life-saving therapies to market more efficiently, explains Biju Davis, SVP, Engineering, Model N

- Biju Davis

In 2025, pharmaceutical innovation is in a race against time-each day lost in drug development could mean lives unaltered or unextended. As the demand for quicker, more precise medical solutions intensifies, data analytics has emerged not just as a powerful tool but as a lifeline, reshaping the way we discover, test, and deliver lifesaving treatments. With costs soaring up to $2 billion and development spanning more than a decade, as detailed by a Deloitte 2023 report, the stakes have never been higher, and the role of data-driven insights has never been clearer.

The rising need for data-driven insights in pharma

Globally, healthcare generates approximately 80 per cent of the world's data, with the volume expected to grow at a compound annual growth rate (CAGR) of 36 per cent through 2025. India's biotechnology sector has grown to over $130 billion in 2024 and is projected to reach $300 billion by 2030. The significant growth highlights the immense potential in harnessing data analytics to optimise drug discovery, particularly as clinical trials and R&D investments expand to meet both domestic and global demand. This surge in patient health data, clinical research findings, and real-world evidence presents unprecedented opportunities for breakthroughs, but it also underscores the limitations of traditional methods.

Data analytics solutions, through predictive models and deep learning, enable pharma companies to leverage this wealth of information, offering visibility into emerging health trends, patient outcomes, and clinical success indicators. The insights derived reveal critical details about disease progression, treatment efficacy, and demographic-specific responses, allowing researchers to make well-informed, real-time decisions. Data analytics, thus, has become central to producing the insights necessary to thrive in today's high-stakes pharma landscape.