Automation Open House | April 8, 2025

Presentations & Speakers

Musings on OSR Pressure Reactions and High-Throughput Reaction Screening

Brandon Orzolek Scientific Director of the Automated Synthesis Facility Scripps Research

Jason Chen Executive Director of Core Facilities and Professor of Chemistry Scripps Research

Abstract: Scripps Research has a Big Kahuna for reaction screening and a Junior with OSR for pressure reactions and was a partner with Unchained Labs in developing small volume inserts for the OSR. The OSR at Scripps Research is among the busiest in the world. It supports diverse projects for different research groups, including hydrogenations, carbonylations, and aerobic oxidations. The chemistry and automation capabilities of the lab are currently being expanded to support accessible, high-throughput reaction screening through library building using the existing Unchained Labs ecosystem. With the new development in workflow and infrastructure, the lab seeks to harmonize fully- to semi-automated workflows to enable synthetic chemistry in the academic environment.



Driving CMC Innovation with Automation: Insights from Genentech

Adam Childs Scientist III Genentech

Abstract: Automation has become a cornerstone of Chemistry, Manufacturing, and Controls (CMC) development, propelled by continuous advancements in robotics and analytical instrumentation. Robust workflows powered by automation can greatly reduce cycle times across various stages of CMC, enabling the efficient and timely delivery of life-saving medicines to patients. This work highlights how diverse automation workflows, developed using cutting-edge robotic platforms, are leveraged to accelerate the process and formulation development of small molecule drugs as well as emerging new modalities. These workflows range from multiple process workflows, including reaction, solubility, salt and polymorph, as well as scavenger screening to formulation screening. Additionally, insights into future trends within the field will be discussed as well. Overall, we believe that embracing automation not only increases efficiency and productivity but also holds the potential to revolutionize modern pharmaceutical CMC development.



Self-Driving HTE Labs for Synthetic Molecule Process Development

Adrian Ramirez Galilea Associate Director, HTE & Automation Takeda

Abstract: Takeda SMPD has significantly built up its high-throughput (HTE) and automation capabilities over the last few years around the Unchained Labs family of tools and devices that integrate well into a complete solution. Our ultimate vision is to design and implement self-driving labs (SDLs) to carry out self-optimizing workflows. Process development and optimization frequently involves exploring wide parameter spaces, making these iterative algorithm-guided SDLs ideal for such optimizations, especially if coupled with automated HTE synthesis platforms. As such, we herein present our vision for fully self-optimizing HTE workflows, with the ultimate goal of creating SDLs with workflows optimized for a variety of general applications needed in synthetic molecule drug development. To illustrate this process, case studies will be presented, highlighting both their successes, as well as the limitations of our current hardware and software tools.



Accelerating High-Throughput Research with the Big Kahuna

Jordan Mowbray Senior R&D Technologist The Dow Chemical Company

Abstract: High-Throughput research is a cornerstone for accelerating innovation at Dow and is integral for catalyst discovery and product development. Using the Big Kahuna Reactor, both olefin and epoxide polymerization chemistries have been validated. This flexibility highlights the ease in which external peripherals that are necessary to run these diverse reactions can be incorporated. The Big Kahuna also enables collection of high quality, reproducible data both from a process and polymer product standpoint increasing project efficiency and productivity. The reactor provides many advantages over its predecessor, the parallel pressure reactor (PPR). These advantages include the ability to run at a range of reaction volumes, including larger ones that may be necessary for certain downstream application testing and smaller ones when raw materials are precious. This talk will showcase how the Big Kahuna Reactor can be used for catalyst screening and material property studies at Dow through selected examples.



Leveraging Automation to Transform Protein Engineering

Daniel Yoo Scientific Associate Director, Protein Therapeutics Large Molecule Discovery & Research Data Science Amgen, Inc

Abstract: As biologic therapeutics continue to increase in complexity, high throughput tools for protein production are more important than ever. Platforms such as the Big Tuna are a key component of our HTP formulation workflows and enable us to rapidly screen candidates at scale. To maximize on the speed, throughput and accuracy of the Big Tuna, we have developed end-to-end automation solutions for samples handling and data management. These tools further advance the speed and quality of our biologics development pipeline.



Accelerating the Discovery of Liquid and Polymer Electrolytes Using High-Throughput Experimentation

Sawyer Cawthern Research Assistant Department of Chemistry, Massachusetts Institute of Technology

Jason Phong Research Assistant Department of Chemistry and Materials Science, Massachusetts Institute of Technology

Abstract: The advancement of next-generation energy storage systems is critical for achieving a sustainable energy future. In this pursuit, developing novel electrolytes is crucial for enabling more affordable, stable, and power-dense batteries. Here, we leverage the Big Kahuna high-throughput experimentation platform to automate the synthesis and characterization of both solid polymer and liquid electrolytes. This platform integrates temperature-dependent electrochemical impedance spectroscopy with in-situ thickness measurements, enabling rapid and reproducible measurement of ionic conductivity across diverse electrolyte formulations. This approach facilitates the creation of a unified reference database for poly(ethylene oxide)-based solid electrolytes as well as the screening of multi-component liquid electrolytes. Given the intrinsic conductivity limit of traditional solid polymer electrolytes, this platform also enables the investigation of alternative ion transport mechanisms through unexplored chemistries. Coupled with data-driven methods such as machine learning-based property prediction and Bayesian optimization, this high-throughput framework could further accelerate the discovery of electrolytes beyond the constraints of conventional experimental workflows.


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