Mike Schultz will be presenting at ACHEMA 2024
Presentation topic: Navigating the Bumpy Road of Industrial Biotechnology Scale-up
We have seen a growth in products from Industrial Biotechnology, with commercial technologies emerging in areas such as:
• Fuels. Sustainable Aviation Fuel, Green Diesel, and Ethanol from low cost feedstocks
• Chemicals. Drop-in replacements for industrial chemicals such as propanediol and butanediol, made through biological routes instead of conventional petroleum based options
• Alternative routes for proteins, fats, and meat
• Materials for building projects, fabrics, electronics
The drivers for this growth include a focus on sustainability, and a drive to enable circularity through reuse of carbon and carbon-based products. Some technologies offer the potential to make use of a lower cost source of carbon, through use of waste feedstocks such as industrial gaseous emissions, biogas, end of life plastic, and waste biomass. In addition, in some cases the bioproduct is a better product than the petroleum-based version, coming with a cheaper, safer processing route and performance advantages over traditional materials.
The road we travel while commercializing new technologies like these is often bumpy, with many challenges along the way. In order to be successful we must address these challenges while also: 1) reducing technology risk 2) reducing time to market 3) optimizing/minimizing cost and 4) maximizing value.
These are often competing objectives, and usually reducing time to market and reducing risk win out. Of course, if the capital and operating cost are too high, then a new technology will not be successful, so these criteria cannot be ignored.
This presentation will provide guidelines and best practices for the scale-up and design of industrial bioprocessing technology, to reduce time, cost, and risk of commercialization. These guidelines include elements such as:
Creative Process Engineering: The flow scheme is developed, the material balance is estimated, and key process design decisions are identified to establish the best process flowsheet for the technology.
Modeling & Analysis: A good model can save time and resources in the lab. Coupled with the right analysis, the scale-up team can prioritize objectives in the lab, pilot, and demo units.
Experimental Data: The right data is needed to prove out breakthrough ideas, secure partners and investors, and develop engineering data for equipment design. Multi-scale data is critical to this effort, and with good planning, multiple assets and external resources can be leveraged.
The key benefits of this approach are:
• Prioritization of R&D to de-risk and optimize the new technology.
• Identification of cost reduction opportunities throughout the scale-up effort.
• Anticipation of process design needs as early as possible.
In this presentation, these concepts will be illustrated with real world examples from personal experience with scale-up of industrial bioprocessing projects.