[HTML][HTML] Enhancing preclinical drug discovery with artificial intelligence

RSK Vijayan, J Kihlberg, JB Cross, V Poongavanam - Drug discovery today, 2022 - Elsevier
Artificial intelligence (AI) is becoming an integral part of drug discovery. It has the potential to
deliver across the drug discovery and development value chain, starting from target …

The rise of continuous flow biocatalysis–fundamentals, very recent developments and future perspectives

P De Santis, LE Meyer, S Kara - Reaction Chemistry & Engineering, 2020 - pubs.rsc.org
Biocatalysis community has witnessed a drastic increase in the number of studies for the use
of enzymes in continuously operated flow reactors. This significant interest arose from the …

[HTML][HTML] Machine learning in chemical engineering: strengths, weaknesses, opportunities, and threats

MR Dobbelaere, PP Plehiers, R Van de Vijver… - Engineering, 2021 - Elsevier
Chemical engineers rely on models for design, research, and daily decision-making, often
with potentially large financial and safety implications. Previous efforts a few decades ago to …

[HTML][HTML] Intensification strategies for improving the performance of photocatalytic processes: A review

DSM Constantino, MM Dias, AMT Silva, JL Faria… - Journal of Cleaner …, 2022 - Elsevier
Green and efficient technologies are one of the biggest challenges in Chemical
Engineering. Photocatalysis has been reported as one of the most promising eco-friendly …

Towards 4th industrial revolution efficient and sustainable continuous flow manufacturing of active pharmaceutical ingredients

CR Sagandira, S Nqeketo, K Mhlana, T Sonti… - Reaction Chemistry & …, 2022 - pubs.rsc.org
Continuous flow chemistry has opened a new paradigm in both the laboratory and
pharmaceutical industry. This review details the recently reported literature on continuous …

Artificial Intelligence Methods and Models for Retro-Biosynthesis: A Sco** Review

G Gricourt, P Meyer, T Duigou, JL Faulon - ACS Synthetic Biology, 2024 - ACS Publications
Retrosynthesis aims to efficiently plan the synthesis of desirable chemicals by strategically
breaking down molecules into readily available building block compounds. Having a long …

Revisiting the Paradigm of Reaction Optimization in Flow with a Priori Computational Reaction Intelligence

P Bianchi, JCM Monbaliu - Angewandte Chemie, 2024 - Wiley Online Library
The use of micro/meso‐fluidic reactors has resulted in both new scenarios for chemistry and
new requirements for chemists. Through flow chemistry, large‐scale reactions can be …

Speeding up turbulent reactive flow simulation via a deep artificial neural network: A methodology study

Y Ouyang, LA Vandewalle, L Chen, PP Plehiers… - Chemical Engineering …, 2022 - Elsevier
Turbulent reactive flow simulation often requires accounting for turbulence-chemistry
interactions and the sub-grid phenomena. Their complexity leads to a trade-off between …

A simulation study on NOx reduction efficiency in SCR catalysts utilizing a modern C3-CNN algorithm

P Han, X Shen, B Shen - Fuel, 2024 - Elsevier
Abstract The simulation of De-NOx system by selective catalytic reduction (SCR) catalyst is
very important in industrial application, however, the simulation is always highly time …

Exploring optimal reaction conditions guided by graph neural networks and Bayesian optimization

Y Kwon, D Lee, JW Kim, YS Choi, S Kim - ACS omega, 2022 - ACS Publications
The optimization of organic reaction conditions to obtain the target product in high yield is
crucial to avoid expensive and time-consuming chemical experiments. Advancements in …