Digital innovation in doing what patients need next – Enabling speed, efficiency and culture in pharmaceutical technical development

ON THE CONVERGENCE OF BIOTECH AND TECHNOLOGY REVOLUTIONS
Since the discovery and introduction of first biopharmaceuticals in late 70s to early 80s, the biopharmaceutical industry has come a long way with many life-changing medicines available to patients. From insulin to recombinant proteins, then to monoclonal antibodies as dominant modalities, we are seeing more cell and gene therapies and other novel modalities coming to the mainstream. While the various modalities are being advanced, in parallel we also see advances in different and more intensified with reduced manufacturing footprint biopharmaceutical manufacturing/processing formats such as single-use technologies and continuous manufacturing. Of these developments, we have been experiencing the proliferation of data generation during the technical development and manufacturing of medicines. In the world of technology, we have witnessed the Industry 4.0 revolution (with 5th revolution is around the corner). This involved connected cyber and physical systems, a boom in industrial internet of things and sensory networks towards enabling Smart Manufacturing concepts harnessing the power of artificial intelligence in the form of machine learning/deep learning, process analytical technologies and process control/automation (1, 2). It was then natural to see the convergence of these two revolutions in the biopharmaceutical development and manufacturing (and for wider Operations, hence, sometimes it is also called as Pharma 4.0). We are adapting these powerful technologies such as data and digital, automation, IoT, computational modeling and advanced analytics in advancing molecules to make them into medicines. This convergence is very well suited into achieving the efficiency, fast-to-patients and robust process design objectives across the technical development value chain.

DATA AND DIGITAL STRATEGY ENABLING THE VISION
We are working on a three-tiered digital strategy to achieve our aspirations. These are (i) Seamless Flow of Data and Information, (ii), Insights from Advanced Analytics and Modeling, (iii), Establishing Digital Mindset and Upskilling of our workforce. One of the main focus areas in seamless data and information flow includes capturing the key data across the development activities following FAIR data principles, i.e., Findable, Accessible, Interoperable and Reusable (3). While capturing the scientific data the right way is critical with the right ontologies, and taxonomies in place, the advent of large language models (LLMs) also offer very enabling possibilities to make the data FAIR, which is a trend we will continue to explore how it will evolve in the near future.