Expert Interview: How can we develop and industrialize chemical processes faster, smarter, and more sustainably?

In this expert video, Damla Torun, PhD, our HTE platform manager, shares how HTE transforms the early stages of chemical development and process optimization. By enabling rapid, parallel screening of reaction conditions, HTE helps chemists identify optimal pathways that meet industrial demands— cost-efficiency, sustainability, and speed.

Read the full interview below

How does High Throughput Experimentation (HTE) accelerate the early stages of chemical development and industrial process optimization?

“HTE significantly accelerates the early stages of chemical development and fine-tuning industrial process optimization by enabling rapid, parallel testing of multiple reaction conditions. By using miniaturized formats (96 well plates) and integrated liquid and solid handling robot, the platform allows running multiple reactions simultaneously. This significantly reduces the time required to explore chemical space so defining faster only the key parameters to deeper optimize the yield. This innovative approach provides valuable support to chemists in traditional laboratories, enabling them to advance their R&D and industrial support projects more efficiently.
The ability to evaluate multiple hypotheses concurrently significantly accelerates the design-test-learn cycle.

This methodology is particularly advantageous for:

• Reaction screening, yield comparison and parameters optimization
• Identification of conditions yielding optimal product formation
• Systematic investigation of continuous variables such as equivalents, concentrations, temperature, pressure…
• Evaluation of discrete parameters including catalyst precursors, ligands, and solvents,
• Improvement of yields and impurity profiles optimization and assessment of novel synthetic pathways.“

What are the main benefits of using HTE?

“The primary advantages include efficiency and speed, along with reduced use of reagents and substrates. Some substrates’ availability are often the limiting factor to do efficient and fast chemical development. HTE will also allow us to use more efficiently chemical and analytical resources as chemists will focus more on the design of the experiment and number of parameters to screen rather than doing the experiments themselves and then, they will focus on the interpretation of the results. HTE generates large datasets that can be leveraged to detect trends using statistical tools or machine learning. This enables faster and more confident identification of optimal conditions, reaction pathways, and at the end faster process optimization during the development or once the process has reached pilot or industrial stage.
This approach facilitates systematic exploration of multiple variables (e.g., catalysts, solvents, temperatures) and minimizes human error ensuring reproducibility. HTE allows for quick cycles of designing, testing, and learning, making it easier and faster to find the best conditions for a given experiment.
Finally, HTE is a powerful tool that generates high-quality data to train machine learning models, enabling faster optimization while reducing the number of required experiments without compromising information quality.”

Can you share a concrete example where HTE helped solve a catalyst screening or a process optimization challenge?

“Case study 1: Biocatalysis screening

One example is an enzyme screening project focused on the phosphorylation of a monosaccharide in one step (in order to be more sustainable than classical chemical process). The key objectives were to identify an enzyme with both high activity and selectivity, to optimize the reaction conditions for scalability and sustainability, and to avoid the use of heavy metals or harsh reagents.
Within the framework of automating the workflow from screening to optimization, the following strategy was implemented: an initial high-throughput screening of 2,200 clones, representing 22 enzyme variants, allowed the identification of 11 candidate enzymes. These candidates were subsequently validated by systematically challenging various reaction parameters, including temperature and substrate concentration. This validation step enabled the selection of 4 enzymes for further small-scale optimization experiments, investigating the effects of temperature, pH, and substrate-to-buffer concentration ratios. Ultimately, two enzymes were confirmed as optimal under these conditions. Subsequent traditional laboratory-scale studies identified one enzyme that demonstrated a significant increase in productivity, facilitating successful process scale-up. Today a ton scale process of the phosphorylated product is considered, with an enzyme impacting less than 10% on the overall cost.

Case study 2: Screening of Solvents for addressing an Industrial Hygiene Challenge

HTE technology can also be applied to address industrial hygiene challenges. For instance, processes involving CMR solvents now require strong justification. In a specific study case where the reaction occurs in an organic solvent/water mixture, two strategic approaches were adopted: replacing the CMR solvent with a greener alternative and investigating the effect of water on the reaction medium.
In addition to the CMR solvent, eight alternative solvents were screened under both strategies, resulting in a total of 18 reaction conditions. These reactions were analyzed using an LC-HRMS system to quantify the screening achieved through substitution, with the original CMR solvent serving as a reference point. This study led to the identification and confirmation of two viable alternative solvents. In collaboration with the project leader, the results were subsequently transferred to the traditional small reactor scale for process development using only one of the two identified solvents.”

How does HTE contribute to more sustainable R&D practices?

“HTE plays a key role in driving more sustainable and efficient R&D practices. It allows for precise dosing and automated handling, which significantly reduces the consumption of costly or rare raw materials. In addition, by enabling early optimization of parameters such as temperature profiles, it contributes to the development of more energy-efficient processes. HTE also helps streamline development by identifying optimal reaction conditions early on, reducing the need for iterative experimentation. Finally, its rapid screening capabilities make it possible to quickly rule out non-viable pathways, allowing teams to focus resources on the most promising solutions. Last but not least, HTE can support industrial plant to fine-tune existing processes in order to help savings few yield percentage and consequently decreasing wastes generated.”