Exclusive report: AI & Informatics: Drug discovery and development
11 August 2021
In this original report, find an in-depth analysis of AI and informatics within imaging, synthetic biology, drug screening and drug design. Featured interviews with experts from AstraZeneca, Auransa, PolarisQB and Chalmers University of Technology.
In this 63-page report, leading scientists and experts explore the key benefits of AI and informatics processes, revealing where the challenges lie for the implementation of AI and how they see the use of these technologies streamlining workflows in the future.
Also featured within this report are exclusive interviews with experts from AstraZeneca, Auransa, PolarisQB and Chalmers University of Technology.
Summary of Key Findings
- 57% of scientists use machine learning in imaging and data analysis
- 75% of drug screening experts believe AI technologies should be open-access and 79% believe its use will increase within drug screening
- 75% of researchers believe the uptake of AI will increase within drug design
- 100% of synthetic biologists report using neural networks for modelling, with 50% using machine learning algorithms
- 67% of drug design researchers predict that big pharma are most likely to use AI and machine learning in the future
- 71% of scientists use AI and machine learning to discover new chemical entities and for structure-based drug discovery
Download this original report to access the full survey results, in-depth analysis and market research to explore AI & Informatics in drug discovery and development.
AI and imaging – the current and future landscape
Dr Mishal Patel is Global Head of Imaging, AI & Data Analytics, R&D at AstraZeneca. Mishal undertook research at the Institute of Cancer Research before moving to the National Health Service. He joined AstraZeneca in 2018 and has led teams focusing on machine learning, real world evidence and imaging to aid better decision making in drug development.
Accelerating drug discovery through AI and informatics
Generating synthetic proteins
Associate Professor Aleksej Zelezniak graduated as a bioengineer at the Vilnius Gediminas Technical University. Obtaining a master’s degree in bioinformatics from the Technical University of Denmark and a PhD from EMBL in Heidelberg, he joined as an EMBO postdoctoral fellow in the Markus Ralser at the University of Cambridge and the Francis Crick Institute. Since 2017, he has led a research group at Chalmers University of Technology, Gothenburg, Sweden. The Zelezniak lab actively uses machine learning to study biological systems and for synthetic biology applications.