Why is the commercialization of biopharmaceutical products still so slow?
The industry still needs a lot of experiments, technical expertise, time, and costs to define the right design space, hence how to properly the process control strategy to predictively ensure product quality.
Project teams are still encountering surprises when scaling up the commercialization process: the control strategy, which was defined in process characterization, did not hold its promise to cover scale-up effects.
Many organizations struggle with evidencing sound science-based chemistry, manufacturing, and controls (CMC) process understanding to file flexible operating ranges and holistic control strategies, because the relationship between inputs (process parameters and raw material attributes) and outputs (Key Performance Indicators and Critical Quality Attributes) is complex.
Companies still need fire brigades of subject matter experts to fight against out-of-specification results to find the root cause and save the batch, because data at not governed properly and knowledge is not extracted holistically from the data.
These components cover the main difficulties of commercialization, experienced during the product life cycle. So why this hassle? Basically, the industry must realize that it still faces missing data governance and low process understanding, while aiming for commercializing complex products and processes.
Which methods can help?
Organizations need more platform methodologies to solve the above-mentioned difficulties of commercialization. ISPE can play a central role in creating awareness through sessions provided in this track and finally help the industry to get faster to the market, streamline validation approaches, and achieve lower production costs.
This track will include very impactful contributions from reputed industry leaders.
In "API-Lean Tactic to Accelerate Process Commercialization," Lenora Dieyi, representing GlaxoSmithKline (GSK), will provide a case study highlighting a methodology that will help with the evaluation and selection of new technology platforms. The goal of this methodology is to help organizations move toward the acceleration of technology transfer and the commercialization of a portfolio of similarly behaving products.
Miheala Simianu of SmartSkin Technologies will take the stage with a presentation titled, "Core Digital DP Knowledge and Speed to Commercialization." Simianu’s discourse will emphasize the transformative potential of digital technologies in expediting the journey from development to commercialization.
Peter Blennerhassett, representing Blynksolve, will introduce attendees to a new concept during his presentation, "Unified Knowledge Space - A Novel Lifecycle Enabler." Blennerhassett’s presentation will underscore the importance of integrating knowledge management systems throughout the product lifecycle.
Sebastian Scheler, of Innerspace GmbH, will delve into the realm of risk management with his presentation, "Autogenerated Risk Profiles to Accelerate Process Design." Scheler's discourse will shed light on how data science and automated workflows can expedite the identification and mitigation of risks in process design.
Finally, Thomas Zahel, representing Körber Pharma Austria, will demonstrate how companies can accelerate commercialization while minimizing risks and costs, using end-to-end digital twins in a real-time context, allowing for real-time release.
The common denominator to accelerate commercialization
What do all those contributions have in common? They show novel approaches and use cases focusing on:
- How process simulation, modeling, and self-learning systems can reduce experimental efforts in process development and accelerate facility and operational readiness
- How to predict the success of technology transfer using holistic data management and data science tools
- How to provide a robust control strategy using end-to-end approaches and for integrated continuous biomanufacturing (ICB)
- How proactive lifecycle management planning can reduce development cycles and accelerate the introduction of the process into the commercial facility
The common denominator across these areas is data science. Executives must understand that the commercialization of biopharmaceuticals is a digital business. Furthermore, the digital aspects go beyond proper data housekeeping ensuring data integrity: teams need to leverage the value of data along the ISPE data maturity model.
Please join the ISPE community in attending the 2024 ISPE Biotechnology Conference to learn and contribute to good practices on how to accelerate commercialization, time-to-market, and progress through the product lifecycle. Get familiar with state-of-the-art digital enablers and digital twins to predict process outcomes and achieve a robust control strategy.
Exchange solutions for the final steps of the data maturity model, hence self-adapting capabilities, real-time architectures along AI, and automated workflows.
Why did the authors not write this blog post (other can the first paragraph) with ChatGPT? Because AI can only summarize and combine what has already been invented by human beings. As this track covers novel concepts and innovative ideas regarding product lifecycle strategies, only the conference’s interactive discussion between humans will advance them.
Please join ISPE and pave the future for successful and accelerated commercialization of novel drugs for patients.
Register Now!