ARTIFICIAL INTELLIGENCE IN PHARMACEATICALSseminar (2).pptx

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1. Artificial Intelligence in Drug Discovery and Development Presented by : 23011760-018

2. Journal name – DOI - https://doi.org/10.1016/j.drudis.2020.10.010 ARTICLE REFERRED

3. Introduction Use of AI in pharmaceutical sector AI: things to know AI : networks and tools Overview of AI approaches Conclusion OUTLOOK

4. Over the past few years, there has been a drastic increase in data digitalization in the pharmaceutical sector. Artificial Intelligence (AI) plays a pivotal role in drug discovery. In particular artificial neural networks such as deep neural networks or recurrent networks drive this area . Introduction

5. Drug discovery and development Drug repurposing Improving pharmaceutical productivity Activity predictions like : P hysicochemical properties ADMET properties QSAR Clinical trials, etc. Use of AI in pharmaceutical sector :

6. AI is being introduced in the medical field to keep a medical record in digital format and conduct patient checkup using smart technologies. It provides solutions, especially in targeted treatments, uniquely composed drugs and personalized therapies. AI is an innovative technology that helps to guide the surgeon during medication, treatment and operation. The main application of this technology is for better decision-making for complicated cases.

7. It can also help to track, detect, investigate and control the infection in the hospital. This technology develops and optimizes online patient appointment platforms. Assist in decision making. Determine the right therapy for a patient, including personalized medicines. Manage the clinical data generated and use it for future drug development. Thus, AI helps in reducing the human workload as well as achieving targets in a short period.

8. One tool developed is International Business Machine (IBM) Watson supercomputer (IBM, New York, USA ) in February 14, 2011 . It was designed to assist in the analysis of a patient’s medical information its correlation with a vast database resulting in suggesting treatment strategies for cancer. This system can also be used for the rapid detection of diseases. This was demonstrated by its ability to detect breast cancer. Example of use of AI:

9. ARTICLES PUBLISHED

10. AI in drug development

11. Comparison of Conventional drug discovery with Artificial Intelligence

12. Artificial intelligence (AI) empowered drug repurposing

13. Applications of artificial intelligence

14. AI is a technology based system involving various advanced tools and networks that can mimic human intelligence . Artificial intelligence is considered as intelligence demonstrated by machines . AI can handle large volumes of data with enhanced automation [2]. Artificial intelligence: Things to know

15. AI involves several method domains , such as reasoning, knowledge representation, solution search, and among them, a fundamental paradigm of machine learning (ML) . ML uses algorithms that can recognize patterns within a set of data that has been further classified. A subfield of the ML is deep learning (DL), which engages artificial neural networks (ANNs). AI: Networks and Tools

16. In particular, artificial neural networks, such as deep neural networks (DNN) or recurrent neural networks (RNN) drive the evolution of artificial intelligence. In pharmaceutical research, novel artificial intelligence technologies received wide interest . AI applications for early drug discovery has been widely increased .

17. Method domains of artificial intelligence (AI)

18. Artificial intelligence has received much attention recently and also has entered the field of drug discovery successfully. Many machine learning methods, such as QSAR methods, SVMs (Support vector machines) are well-established in the drug discovery process. The applicability of AI including physicochemical properties as well as biological activities, toxicity etc. Conclusion

19. The application of AI for drug discovery benefits strongly from open source implementations, which provide access to software libraries. Frequently used open source libraries are :

20. Leading pharmaceutical companies and their association with AI

21. With progress in these different areas, we can expect more and more automated drug discovery done by computers. L arge progress in robotics will accelerate this development. Nevertheless , artificial intelligence is far from being perfect.

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