Making better decisions during synthetic route design: leveraging prediction to achieve greenness-by-design

2019 ◽  
Vol 4 (9) ◽  
pp. 1595-1607 ◽  
Author(s):  
Jun Li ◽  
Martin D. Eastgate
Keyword(s):  
Conceptual Framework ◽  
Synthetic Route ◽  
Route Design

A conceptual framework for incorporating machine learned ligand prediction into predictive route comparisons, to enable greener chemistry outcomes.

Synthetic Route Design of AZD4635, an A2AR Antagonist

2019 ◽  
Vol 23 (7) ◽  
pp. 1407-1419 ◽  
Author(s):  
Mairi M. Littleson ◽  
Andrew D. Campbell ◽  
Adam Clarke ◽  
Mark Dow ◽  
Gareth Ensor ◽  
...  
Keyword(s):  
Synthetic Route ◽  
Route Design

Making Better Decisions During Synthetic Route Design: Leveraging Prediction to Achieve Greenness-by-Design

2019 ◽  
Author(s):  
Jun Li ◽  
Martin Eastgate
Keyword(s):  
Proof Of Concept ◽  
Synthetic Route ◽  
High Complexity ◽  
Route Design ◽  
Synthetic Routes ◽  
Catalyzed Reactions ◽  
Metal Catalyzed ◽  
Potential Efficiency

This paper expands our work predicting Process Mass Intensity (PMI), as a methodology for exploring the potential efficiency of proposed synthetic routes. In the present work, we integrate a method for predicting the PMI contributions of high complexity reagents, needed to enable certain transformations. We focus on ligands for metal catalyzed reactions - and develop an approach for predicting which ligands may function in CN couplings - as a proof of concept. We leverage this to enable the integration of the PMI contribution of the ligands into a predictions of a routes efficiency, enabling an understanding of the holistic impact of a route decision..

Development of Evaluation Model for Strategic Sites in Synthetic Route Design System AIPHOS

2008 ◽  
Vol 9 ◽  
pp. 81-91
Author(s):  
Akio Tanaka ◽  
Takashi Kawai ◽  
Tsutomu Matsumoto ◽  
Tetsuhiko Takabatake ◽  
Hideho Okamoto ◽  
...  
Keyword(s):  
Evaluation Model ◽  
Design System ◽  
Synthetic Route ◽  
Route Design

scholarly journals AI-Driven Synthetic Route Design with Retrosynthesis Knowledge

2020 ◽  
Author(s):  
Shoichi Ishida ◽  
Kei Terayama ◽  
Ryosuke Kojima ◽  
Kiyosei Takasu ◽  
Yasushi Okuno
Keyword(s):  
Deep Neural Networks ◽  
Data Driven ◽  
Machine Learning Techniques ◽  
Synthetic Route ◽  
Learning Techniques ◽  
Route Design ◽  
Human Interventions ◽  
Synthesis Planning ◽  
Retrosynthetic Analysis ◽  
Synthetic Routes

<div>Computer-aided synthesis planning (CASP) aims to assist chemists in performing retrosynthetic analysis for which they exploit their experiments, intuition, and knowledge. Recent breakthroughs in machine learning techniques, including deep neural networks, have significantly improved data-driven synthetic route designs without human interventions. However, such CASP applications are yet to incorporate retrosynthesis knowledge sufficiently into their algorithms to reflect chemists' way of thinking flexibly. In this study, we developed a hybrid CASP application of data-driven techniques and various retrosynthesis knowledge called "ReTReK" that integrates the knowledge as adjustable parameters into an evaluation for promising search directions. Experimental results showed that ReTReK successfully searched synthetic routes based on the specified retrosynthesis knowledge, and the results indicated that the synthetic routes searched with the knowledge were preferred to those without knowledge. The concept of integrating retrosynthesis knowledge as adjustable parameters into data-driven CASP applications is expected to contribute to further their development and spread them to chemists widely. </div>

Making Better Decisions During Synthetic Route Design: Leveraging Prediction to Achieve Greenness-by-Design

2019 ◽  
Author(s):  
Jun Li ◽  
Martin Eastgate
Keyword(s):  
Proof Of Concept ◽  
Synthetic Route ◽  
High Complexity ◽  
Route Design ◽  
Synthetic Routes ◽  
Catalyzed Reactions ◽  
Metal Catalyzed ◽  
Potential Efficiency

This paper expands our work predicting Process Mass Intensity (PMI), as a methodology for exploring the potential efficiency of proposed synthetic routes. In the present work, we integrate a method for predicting the PMI contributions of high complexity reagents, needed to enable certain transformations. We focus on ligands for metal catalyzed reactions - and develop an approach for predicting which ligands may function in CN couplings - as a proof of concept. We leverage this to enable the integration of the PMI contribution of the ligands into a predictions of a routes efficiency, enabling an understanding of the holistic impact of a route decision..

scholarly journals AI-Driven Synthetic Route Design with Retrosynthesis Knowledge

2020 ◽  
Author(s):  
Shoichi Ishida ◽  
Kei Terayama ◽  
Ryosuke Kojima ◽  
Kiyosei Takasu ◽  
Yasushi Okuno
Keyword(s):  
Deep Neural Networks ◽  
Data Driven ◽  
Machine Learning Techniques ◽  
Synthetic Route ◽  
Learning Techniques ◽  
Route Design ◽  
Human Interventions ◽  
Synthesis Planning ◽  
Retrosynthetic Analysis ◽  
Synthetic Routes

<div>Computer-aided synthesis planning (CASP) aims to assist chemists in performing retrosynthetic analysis for which they exploit their experiments, intuition, and knowledge. Recent breakthroughs in machine learning techniques, including deep neural networks, have significantly improved data-driven synthetic route designs without human interventions. However, such CASP applications are yet to incorporate retrosynthesis knowledge sufficiently into their algorithms to reflect chemists' way of thinking flexibly. In this study, we developed a hybrid CASP application of data-driven techniques and various retrosynthesis knowledge called "ReTReK" that integrates the knowledge as adjustable parameters into an evaluation for promising search directions. Experimental results showed that ReTReK successfully searched synthetic routes based on the specified retrosynthesis knowledge, and the results indicated that the synthetic routes searched with the knowledge were preferred to those without knowledge. The concept of integrating retrosynthesis knowledge as adjustable parameters into data-driven CASP applications is expected to contribute to further their development and spread them to chemists widely. </div>

Evaluating research in developmental disabilities: a conceptual framework for reviewing treatment outcomes

1999 ◽  
Vol 41 (1) ◽  
pp. 55-59 ◽  
Author(s):  
Charlene Butler ◽  
Henry Chambers ◽  
Murray Goldstein ◽  
Susan Harris ◽  
Judy Leach ◽  
...  
Keyword(s):  
Developmental Disabilities ◽  
Conceptual Framework ◽  
Treatment Outcomes

Understanding Why Older People Develop a Wish to Die

Crisis ◽  
2011 ◽  
Vol 32 (4) ◽  
pp. 204-216 ◽  
Author(s):  
M. L. Rurup ◽  
H. R. W. Pasman ◽  
J. Goedhart ◽  
D. J. H. Deeg ◽  
A. J. F. M. Kerkhof ◽  
...  
Keyword(s):  
Older People ◽  
Cohort Studies ◽  
Conceptual Framework ◽  
Life Events ◽  
Traumatic Life Events ◽  
Quantitative Studies ◽  
Wish To Die ◽  
Open Coding ◽  
Death Wishes ◽  
Depth Interviews

Background: Quantitative studies in several European countries showed that 10–20% of older people have or have had a wish to die. Aims: To improve our understanding of why some older people develop a wish to die. Methods: In-depth interviews with people with a wish to die (n = 31) were carried out. Through open coding and inductive analysis, we developed a conceptual framework to describe the development of death wishes. Respondents were selected from two cohort studies. Results: The wish to die had either been triggered suddenly after traumatic life events or had developed gradually after a life full of adversity, as a consequence of aging or illness, or after recurring depression. The respondents were in a situation they considered unacceptable, yet they felt they had no control to change their situation and thus progressively “gave up” trying. Recurring themes included being widowed, feeling lonely, being a victim, being dependent, and wanting to be useful. Developing thoughts about death as a positive thing or a release from problems seemed to them like a way to reclaim control. Conclusions: People who wish to die originally develop thoughts about death as a positive solution to life events or to an adverse situation, and eventually reach a balance of the wish to live and to die.

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