Artificial intelegance.pptx
- 1. Pratibhatai Pawar College Of Pharmacy, Shrirampur. Artificial Intelligence in the Pharmaceutical Industry- An Overview of Innovations. Presented By- Mr. Sonawane Tejas Sanjay . Roll No.- 0087 Course- B. pharmacy (Final year) Guided by- Asst. Prof. Vishal Gaikwad . Department of pharmaceutics . 1
- 2. ļ¶ Content : ļµ Introduction ļµ Historical Background ļµ IBM Research Uses Advanced Computing to Accelerate Therapeutic and Biomarker Discovery ļµ How Is Artificial Intelegance accelerating drug Discovery ļµ The Challenges and Opportunities of Using Artificial Intelligence to Manage Chronic Conditions. ļµ Artificial Intelligence Statistics ļµ Impact of Artificial Intelligence in the Pharmaceutical industry: How is AI transforming the pharmaceutical industry? ļµ Artificial Intelligence Could Be the Key to Longevity ļµ AI for Pharmaceutical Market Analysis 2022 In-depth Research Studies on Products, Countries, Companies and Industry Segmentation by 2030 ļµ The Future of AI in the Pharmaceutical Industry ļµ Annexure ļµ Reference 2
- 3. ļ¶ Introduction : ļµ Artificial Intelligence (AI) is a rapidly growing technology that is used for a wide range of applications across industries. Small, mid-sized, mid-sized, and multinational companies are using AI technology and enhancing their capabilities to work smart in this digital sphere. Like retail, e-commerce, and manufacturing sectors, AI is gaining prominence across healthcare and pharma sectors. Leveraging the power of this modern Artificial Intelligence in Pharma Industry, the companies are finding innovative ways to resolve some of the significant issues that the pharma sector is facing today. Yes. AIpowered apps using machine learning, deep learning, predictive analytics, and big data have brought a radical shift in the paradigm of pharma. Artificial intelligence in Pharmaceutical Industry has the potential to promote innovation, while at the same time increasing productivity and providing better results. In addition, Artificial Intelligence in Pharma Industry offers a value proposition to the companies by creating new and latest business models. 3
- 4. ļ¶ Historical Background : Year Comment 1943 AI was done By Warren McCulloch and walter pits. They propose G model of Artificial Neurons . 1949 Donald Hebb demonstrated an undating Rule for connection strength Between Neurons and that Rules Called Hebbian learning 1950 Alan Turing publishes āComputing Machinery and Intelligenceāand he proposed test called as Turing Test. 1955 Allen Newell and Herbert A. Simon Created āFirst artificial Intelligence programā and named as āāLogic Theoristā. 1956 The word āArtificial IntelligenceāFirstly adopted by John McCarthy at the Dartmouth conference. 1966 Joseph Weizebaun created first Chatbot named as ELIZA. 1972 First Intelligent Humoid Robot was built in Japan and named as WABOT -1. 1980 First National conference of the American Association of Artificial Intelligence Was held at Stanford University. 2002 AI entered in form of Roomba a Vaccum Cleaner. 2006 Facebook ,twitter and Netflix Started Using AI. 2012 Google has launched an Android App features āāGoogle Nowāā. 2014 Chabot āEugene Gootman an ā Won completion in āāTuring Testāā. 2018 āāProject Debater āāfrom IBM debated with two Master Debates . Google has Demonstrated an AI program āāDuplex āāwhich was a virtual assistant. 4
- 5. IBM Research Uses Advanced Computing to Accelerate Therapeutic and Biomarker Discovery Over the past decade, artificial intelligence (AI) has emerged as an engine of discovery by helping to unlock information from large repositories of previously inaccessible data. The cloud has expanded computer capacity exponentially by creating a global network of remote and distributed computing resources. ļµ Improving the Drug Discovery Value Chain ļµ optimized Modeling of Nmes ļµ Drug Repurposing from Real-World Data ļµ Enhanced Clinical-Trial Design ļµ Revolution in Pharmaceutical R&D ļµ Better Accuracy in Epidemic Prediction 5
- 6. How Is Artificial Intelegance accelerating drug Discovery : ļµ Artificial Intelligence has the potential to transform the drug discovery process. It can make it more efficient and more effective, thus benefiting all parties involved - from companies developing new drugs to patients in desperate need of viable treatments. The health and biotech sector is becoming increasingly rich in data, and these large datasets require advanced analytical methods that can help understand the relationships within the data. However, the lack of advanced technologies limits the drug discovery process, making it a time-consuming and expensive task. ļµ AI can be used in many stages of the drug discovery process. Some examples include: ļµ ā¢ AI virtual high-throughput screening, ļµ ā¢ Predicting target protein structure with AI, ļµ ā¢ Predicting bioactivity with AI, ļµ ā¢ Toxicity prediction with AI, and more. 7
- 7. The Challenges and Opportunities of Using Artificial Intelligence to Manage Chronic Conditions. ļµ The United States, approximately 60% of the adult population is living with one or more chronic condition, from heart disease and asthma through to Alzheimerās, kidney disease, and diabetes.1 This is putting a significant burden on healthcare systems in terms of their ability to deliver care and the cost of managing these illnesses. In the U.S. alone, almost three quarters of healthcare spend is linked to chronic conditions or associated complications. ļµ Artificial Intelligence Needs Quality Data ļµ Regulations Need to Evolve ļµ Data Must Be Protected 7
- 8. Artificial Intelligence Companies Leading the Way in the Pharmaceutical Industry ļµ Artificial intelligence (AI) continues to play a significant role in addressing many of the core challenges currently faced by the pharmaceutical industry. As seen on Pharmaceutical Technologyās artificial intelligence deal tracker pharma sector deals involving pharma companies using artificial intelligence over the past nine quarters continues to be led by large corporations in the industry. As well as leading pharma companies using AI for an increasing number of applications and innovations, AI is becoming ubiquitous across society. ļµ Industry investment: pharmaceuticals companies using AI ļµ Discover the top pharma AI companies ļµ Smart robotic surgery ļµ Optimisation of clinical trials 8
- 9. AI Driven Innovation in the Pharma Sector AI Jobs Insights in the Pharma Sector 9 Artificial Intelligence Statistics
- 10. Impact of Artificial Intelligence in the Pharmaceutical industry: How is AI transforming the pharmaceutical industry? ļµ The pharmaceutical industry has long relied on cutting-edge tools and technologies to help deliver safe, reliable drugs to market. With the recent pandemic, on the surface, although it may seem that the challenge faced by the pharmaceutical industry is just about the race against time to find a viable vaccine, it is the digital technologies and tools that helped them achieve this historical victory. This is where Artificial intelligence in the pharmaceutical industry has been playing a critical role. Over the last five years, the use of Artificial Intelligence in the pharmaceutical industry has redefined how scientists develop new drugs, tackle the disease, and more. 10
- 11. Artificial Intelligence Could Be the Key to Longevity: ļµ What if we could generate novel molecules to target any disease, overnight, ready for clinical trials? Imagine leveraging machine learning to accomplish with 50 people what the pharmaceutical industry can barely do with an army of 5,000. Itās a multibillion-dollar opportunity that can help billions. The worldwide pharmaceutical market, one of the slowest monolithic industries to adapt, surpassed $1.1 trillion in 2016. In 2018, the top 10 pharmaceutical companies alone are projected to generate over $355 billion in revenue. At the same time, it currently costs more than $2.5 billion (sometimes up to $12 billion) and takes over 10 years to bring a new drug to market 11
- 12. AI for Pharmaceutical Market Analysis 2022 In-depth Research Studies on Products, Countries, Companies and Industry Segmentation by 2030 . ļµ . In 2019, the global artificial intelligence market in medicines was estimated at $XXXX billion and is anticipated to hit $XXXX billion from 2020 to 2030 at a CAGR of 49.8%.. The global AI for Pharmaceutical market is expected to grow significantly in the future, owing to rising demand for the product, increased awareness of the product, and major expenditures to improve product efficiency and close the demand-supply gap in the market. According to Fatpos Global, the major components are āAI for Pharmaceutical Market Insights, Size, Opportunities, Share, Growth, Emerging Trends, Forecast to 2031.ā The report includes a variety of in-depth research studies on various aspects of the global AI for Pharmaceutical market. Itās a praiseworthy effort to give a true, transparent picture of the current and future state of the global AI for Pharmaceutical market, based on trustworthy data and extremely exact figures 12
- 13. The Future of AI in the Pharmaceutical Industry ļµ Artificial Intelligence plays an important role in the pharmaceutical industry and the coming years there is simply no sign of the adoption of this cuttingedge technology slowing down. From making healthcare process automated to help in drug discovery, AI with machine learning can bring revolution in this industry. More companies should start adopting this technology to make R&D approaches and patient care better. 13
- 14. ļ¶ Reference : 1. Born, J. et al. J. Chem. Inf. Model. 62, 240ā257 (2022). 2. Laifenfeld, D. et al. Front. Pharmacol. 12, 631584 (2021). 3. Mohan, A. et al. Mov. Disord. 37, 553ā562 (2022). 4. Harrer, S. et al. Trends Pharmacol Sci. 40, 577ā591 (2019). 5. Parikh, J. et al. J. Pharmacokinet. Pharmacodyn. 49, 51ā64 (2022). 6. Kashyap, A. et al. Trends Biotechnol. 40, 647ā676 (2021). 7. Norel, R. et al. npj Parkinsonās Dis. 6, 12 (2020). 14
- 15. ļ¶ Annexure:
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