Overview of drug discovery-01 overview of drug discovery

1. Speaker introduction

Tang Jian At present, it is the Montessori Institute of learning algorithms （Mila） Assistant professor of , The Institute focuses on deep learning and reinforcement learning , By the Turing prize winner Yoshua Bengio Leader , from 2017 year 12 Month begins . His research focuses on graphic representation learning 、 Graphical neural networks 、 Drug discovery and knowledge map . He was nominated as one of the first Canadians CIFAR AI chair （CIFAR AI Research Chair ）. He is a researcher at the University of Michigan and Carnegie Mellon University . He was a researcher at Microsoft Research Asia for two years . He won the ICML’14 Best paper award and WWW’16 The best thesis nomination for .
Faye Wong He is currently an associate professor of health informatics in the Department of Population Health Sciences, Weill Cornell School of medicine, Cornell University . His main research interest is data mining and its application in health data science . He published in the field of artificial intelligence and medicine 250 Many papers , To obtain the 12700 Multiple citations . His H The index is 56. His paper has won a prize in the top international conference on data mining and medical informatics 8 Best Paper Award . Dr. Wang is 2018 National Science Foundation career award （NSF CAREER Award） The winner of , The award is 2019 year IEEE International Conference on health informatics （ICI） The first research leadership award . Dr. Wang is a member of the American Medical Informatics Association （AMIA） Chairman of the working group on knowledge discovery and data mining .
Chengfeixiong Dr. is the lead researcher at the Cleveland Clinic Institute for genomic medicine .Cheng Doctor is working on developing computing and experimental network medicine technology , To promote the characterization of disease heterogeneity , So as to achieve the strategic goal of patient-centered coordination , So as to promote the development of innovative diagnosis and therapeutics . Dr. Zheng has won many awards , Include NIH Independent path award （K99/R00）、SCI Highly cited Thesis Award and Vanderbilt annual postdoctoral Honor Award .

2. Drug discovery process

Drug discovery ：12 - 15 year ,10 Million to 26 Billion dollars
The goal is / Hit and clue recognition –》 Preclinical study –》 Clinical stage 1/ Clinical stage 2/ Clinical stage 3–》FDA approval
（3---------------------------------6 year ） （5-------------------------------7 year ） （1-2 year ）
FDA: Us food and drug administration

3. The challenge of drug discovery

since 1993 New since FDA approval ： Drug evaluation and Research Committee （CDER） Approved new molecular entity （NME） And biological agent license application （BLA） The number of .2019 See table for new approvals in 1. Center for evaluation and research of biological agents (CBER) Approved products , Such as vaccines and gene therapy (CBER) Not included in this drug count ( See table 2).

4. The reasons for the failure of drug discovery

a.2013-2015 The reason for the failure ： business （6%）/ Security （24%）/ efficacy （52%）/ Strategy （15%）/ operating （3%）
b. Percentage of failures by treatment type ： oncology （32%） The central nervous system （17%） Musculoskeletal （13%） Infectious Diseases （5%） cardiovascular （7%） digestive tract （7%） metabolize （6%） other （13%）

5. The evolution of drug discovery and clinical trials


6. High success rate of precise drug discovery


7. Big help from big data

The right medicine , Appropriate dosage , The right person
8. Big data challenges faced by quasi genomics

Everything in you DNA How long is ？ 2*10^14 Power m, Equivalent to the distance from the earth to the moon 667 times

9.166 Billion small organic molecules

2020《 chemical 》 《 Chemical model 》

10 The human pharmaceutical genome

The power of gigabytes
Drug discovery and healthcare generate detailed data , This is critical to creating a learning health system for drug discovery and development . Innovative technologies and algorithms are needed …

13. Computers calculate drugs

14 Rethinking of drug design in the era of artificial intelligence

Design analysis test manufacture

15 Artificial intelligence / machine learning / Deep learning

Artificial intelligence （ machine learning （ Deep learning ）（ neural network ））

16 Machine learning tools and their applications in drug discovery

regression analysis methods Regression analysis method
classifier methods classification method
clustering methods Clustering method