Driving Innovation in Process Development | AIChE

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Innovation is one of several key aspects that differentiates good process development from great process development. Novel approaches to address the technical and managerial challenges that are presented by both research and commercialization projects throughout their lifecycles are often vital to ensuring the success of these projects. Developing new ways of designing, executing, or interpreting experiments, or new ways of implementing processes at scale, or new ways of collaborating cross-functionally are just some of the ways that innovative thinking fuels success and competitive advantage. In this session, we will discuss how innovative methods and ideas have progressed a variety of projects, and how challenges were overcome in implementing these innovative ideas.

Session Chairs:

  • Anne Mohan, Merck
  • Kil Ho Lee, Dow

Schedule:

TIME (EDT) PRESENTATION SPEAKER
11:00 AM Statistics & Machine Learning in Chemical Processes Flor Castillo, SABIC; Alexander Lapanowski, SABIC
11:30 AM Process Development and Scale-Up of a Photochemical Reaction for Drug Substance Intermediate Jonathan McMullen, Merck
12:00 PM Digital Process Design - using validated high-fidelity Digital Process Twins to accelerate innovation and manage risk Simon Leyland, Siemens Process Systems Engineering Inc.
12:15 PM RAPID Manufacturing Institute™ - Transforming the Process Industries through Consortium-Based Innovation William Grieco, RAPID; Ignasi Palou-Rivera, RAPID

Abstracts:

Statistics and Machine Learning in Chemical Processes

Flor Castillo, Alexander Lapanowski; SABIC Technology and Innovation

The role of data science and statistical methods are of fundamental importance in chemical processes in enabling researchers to efficiently investigate problems and accelerate discoveries. We present two important methods that have greatly assisted us in modeling chemical processes from product development to optimization and control: computer-generated optimal experimental designs and shrinkage methods for penalized regression. These methods represent a wide array of the data science and statistics field from data collection to predictive modeling. We illustrate the usefulness of these methods by detailing their use in our own projects within the chemical industry, thus supporting innovation and operational excellence.

Process Development and Scale-Up of a Photochemical Reaction for Drug Substance Intermediate

Jonathan P. McMullen, Cecilia Bottecchia, Francois Levesque, Stephen Dalby, Sean Dubina; Merck

Recent advances in light-emitting diode (LED) technology and development of visible-light photoredox catalysis have led to a resurgence of interest in photochemical transformations for drug substance development.  Photochemical approaches can streamline the manufacturing of active pharmaceutical ingredient (API) by providing reaction selectivity that cannot be achieved with traditional synthetic methods.  Despite the intrinsic synthetic value of these approaches, applications in the pharmaceutical industry have largely been focused in the early stages of drug development, with very few examples of photochemistry implemented beyond lab scale. 

This presentation will discuss various strategies that have been used to develop and scale up a photochemical bromination.  Small, benchtop experiments were used to identify the reaction mechanism and understand reaction sensitivities.  By establishing photon equivalence as the scaling factor, the bromination was scaled up to larger batch reactors and tech transferred to continuous flow reactors.  The process was scaled up to the kilo-scale with two different flow reactor configurations to understand the impact of reactor design on photochemical reaction performance before selecting a plug flow reactor for manufacturing.  To further understand the bromination reaction in a production environment, the process was explored at various residence times, irradiation levels, and temperatures in the pilot plant.  This data, along with kilo-scale process characterization investigations, enabled successful tech transfer of the process to manufacturing to produce metric tons of drug substance intermediate.

RAPID Manufacturing Institute™ - Transforming the Process Industries through Consortium-Based Innovation

William Grieco, RAPID; Ignasi Palou-Rivera, RAPID

The RAPID Manufacturing Institute™ is one of 16 current Manufacturing USA innovation institutes set up as public-private partnerships between the federal government and the private sector. RAPID is initially a $50 million five-year collaboration between the Department of Energy’s Advanced Manufacturing Office and AIChE to build a community around and drive research and development project in the areas of process intensification (PI) and modular process technologies. In the session, RAPID’s CEO Bill Grieco will describe how RAPID works to grow and educate our member community on these topics and offer some perspectives on the institute’s current and future consortium-based collaboration models. RAPID’s CTO Ignasi Palou-Rivera will describe several relevant process development and modeling projects that are helping to shape how new PI and modular technologies are deployed.