The Biopharmaceutical industry has big ambitions to accelerate the move towards industry 4.0. In this white paper we explore some of the major bottlenecks in the development lifecycle and the current barriers to effective digital transformation. We conclude by exploring the role effective BioPharmaceutical Lifecycle Management BPLM platforms will play in accelerating time to market for vaccines and therapies.
The global events surrounding the 2020 SARS-CoV-2 pandemic have put a renewed focus on the time and cost of bringing new therapeutics and vaccines to patients. Recent research highlighted that the average cost to develop a new drug sits at $1.3 Billion.1 With timelines ranging from 8 to 16 years and attrition rates that can be as high as 88%, it is clear that the current state of biopharma drug development is a barrier to the timely and cost-effective treatment of disease.
Development of cutting-edge biological medicines is underpinned by complex processes, but despite innovations in process science (enhanced product titers, the application of single-use technologies, the shift to continuous and semi-continuous manufacturing) the biopharmaceutical industry has so far failed to reap the benefits of digital transformation. According to research by pharmamanufacturing.com, in excess of 60% of biopharma organizations are still managing many of their critical steps with paper and Microsoft Office, while struggling to integrate the expanding ecosystem of equipment and data. This working method is long established. But in the digital age wasting 30–40% of time on basic data administration and documentation. We are entering the age of industrialized biology. A new world in which those who embrace efficiency, agility and smart ways to unlock the potential of their data will emerge as industry leaders.
Biopharma 4.0 is a bold vision, with smart factories and process automation, driven by real time data to constantly ensure quality and efficiency. The journey towards the vision starts with improved process understanding and characterization (ICH Q10/ QbD). This is supported by technology advances like high throughput process development (HTPD) as well as advances in data sciences that enable in-silico process development. Increases in data from equipment, instruments and sensors at all process scales quickly highlight the fragility of a lifecycle managed with paper records and silos of data, especially when contextualized data is the rocket fuel needed to drive speed and innovation.