Continuous flow synthesis enabling reaction discovery
AI Alfano, J García-Lacuna, OM Griffiths, SV Ley… - Chemical …, 2024 - pubs.rsc.org
This article defines the role that continuous flow chemistry can have in new reaction
discovery, thereby creating molecular assembly opportunities beyond our current …
discovery, thereby creating molecular assembly opportunities beyond our current …
[HTML][HTML] Supervised machine learning in drug discovery and development: Algorithms, applications, challenges, and prospects
Drug discovery and development is a time-consuming process that involves identifying,
designing, and testing new drugs to address critical medical needs. In recent years, machine …
designing, and testing new drugs to address critical medical needs. In recent years, machine …
In Silico Prediction of Pharmaceutical Degradation Pathways: A Benchmarking Study Using the Software Program Zeneth
R Hemingway, SW Baertschi, D Benstead… - … Process Research & …, 2024 - ACS Publications
Zeneth, a software application for the prediction of chemical degradation of small organic
molecules, incorporates a knowledge base of rules to predict degradation pathways. In …
molecules, incorporates a knowledge base of rules to predict degradation pathways. In …
Chemistry in a graph: modern insights into commercial organic synthesis planning
C Avila, A West, AC Vicini, W Waddington… - Digital …, 2024 - pubs.rsc.org
Across the chemical sciences, synthesis planning is a key aspect for defining synthesis
routes, starting from idea generation, combining literature searches and laboratory …
routes, starting from idea generation, combining literature searches and laboratory …
Bayesian data-driven models for pharmaceutical process development
Highlights•Bayesian-based modeling quantifies uncertainty to enable faster decision-
making.•Applications include route and process invention, optimization, and …
making.•Applications include route and process invention, optimization, and …
Emerging Trends in Multi-Objective Optimization of Organic Synthesis Leveraging High-throughput Tools and Machine Learning Methods
PQ Velasco, K Hippalgaonkar, B Ramalingam - 2024 - chemrxiv.org
The discovery of optimal conditions of chemical reactions is a labor-intensive, time-
consuming task that requires exploring a high-dimensional parametric space. Historically …
consuming task that requires exploring a high-dimensional parametric space. Historically …
Accelerated end-to-end chemical synthesis development with large language models
Y Ruan, C Lu, N Xu, J Zhang, J Xuan, J Pan, Q Fang… - 2024 - chemrxiv.org
The rapid emergence of large language model (LLM) technology presents significant
opportunities to facilitate the development of synthetic reactions. In this work, we leveraged …
opportunities to facilitate the development of synthetic reactions. In this work, we leveraged …
Machine Learning-Guided Strategies for Reaction Condition Design and Optimization
This review surveys the recent advances and challenges in predicting and optimizing
reaction conditions using machine learning techniques. The paper emphasizes the …
reaction conditions using machine learning techniques. The paper emphasizes the …
[图书][B] Supramolecular Synthons in Crystal Engineering of Pharmaceutical Properties
AK Nangia - 2024 - books.google.com
This comprehensive resource skillfully consolidates crystal engineering, the design of
organic solids, and supramolecular synthons (ie, structural hydrogen bond units) to achieve …
organic solids, and supramolecular synthons (ie, structural hydrogen bond units) to achieve …