Applied Artificial Intelligence & How it's Transforming Life Sciences
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The document discusses the transformative impact of artificial intelligence (AI) in the life sciences sector, highlighting its applications in drug discovery, genomics analysis, and cancer diagnosis. It outlines major approaches to applying AI, including machine learning and deep learning, and notes a growing trend among large pharmaceutical companies to leverage AI technologies. Additionally, it presents case studies illustrating the efficacy of AI in accelerating genomic analysis and enhancing liquid biopsy diagnostics.
Applied Artificial Intelligence & How it's Transforming Life Sciences
- 1. How Artificial Intelligence is Transforming Life Sciences For more info, contact us: xeraya@xeraya.com Follow us: @xerayacapital www.xeraya.com Applied AI in Life Sciences 1 August 2021. © Xeraya Capital.
- 2. Applied AI in Life Sciences Contents Overview • AI, Simplified • Major Approaches in Life Sciences • Potential Applications • Big Pharma on AI • Case Study: Genomics Analysis • Case Study: Liquid Biopsy 2 August 2021. © Xeraya Capital.
- 3. Artificial Intelligence, Simplified AI is the ability of computer algorithms to approximate conclusions based solely on input data. Through machine learning and deep learning, these algorithms can recognize patterns in behavior and create their own logic. They do not require direct human input. Source: https://en.wikipedia.org/wiki/Artificial_intelligence_in_healthcare Credit: TRP, University 0f Toronto 3 August 2021. © Xeraya Capital. AI has significantly impacted various fields and is spreading out to different areas beyond informatics including life sciences.
- 4. History of Artificial Intelligence 4 Warren McCulloch & Walter Pitts develops the 1st mathematical and computer model of the biological neuron. 1943 1948 Norbert Wiener coins the term ‘cybernetics’ in his book, Cybernetics: Or Control and Communication in the Animal and the Machine. John Von Neumann & Alan Turing made the transition from computers to 19th century decimal logic (0 to 9) and machines to binary logic (Boolean algebra, 0 or 1), demonstrated the Universal Machine. 1950 Source: https://www.coe.int/en/web/artificial-intelligence/history-of-ai 1956 John McCarthy of MIT coins the term ‘AI’ in a conference at Dartmouth College. The 1st commercial microprocessor by Federico Faggin, Marcian (Ted) Hoff, Stanley Mazor, and Masatoshi Shima at Intel. 1971 1997 IBM’s Deep Blue beats Garry Kasparov. 2011 IBM’s AI, Watson wins against 2 Jeopardy champions. August 2021. © Xeraya Capital. 2016 Google’s AI, AlphaGo beats Lee Sedol in Go (or Weiqi).
- 5. AI in Healthcare Major Approaches & Applications 5 August 2021. © Xeraya Capital.
- 6. Impact of AI In Healthcare Source: https://www.datarevenue.com/en-blog/artificial-intelligence-in-medicine AI is enabling researchers to develop cures faster, doctors to deliver more personalized and effective care, and healthcare companies to reduce costs while increasing access to care. This is achieved through its ability to manage and process large amounts of clinical data. Credit: Shutterstock 6 August 2021. © Xeraya Capital.
- 7. 4 Major Approaches of Applying AI August 2021. © Xeraya Capital. 7 Source: https://www.lek.com/sites/default/files/insights/pdf-attachments/2060-AI-in-Life-Sciences.pdf Machine Learning – Analyze input data & repeatedly optimize methods based on output Deep Learning – Approach that utilizes logic structure like biological neural networks Natural Language Processing – Refined automatic speech recognition, actual dialogue interaction Robotics & IoT – Integration of devices to collect, combine & share information
- 8. Applications of AI in Healthcare Source: https://en.wikipedia.org/wiki/Artificial_intelligence_in_healthcare 8 August 2021. © Xeraya Capital. Drug Discovery R&D Radiology Disease Diagnosis Digital Health Psychiatry
- 9. Big Pharma on AI Major Approaches & Applications 9 August 2021. © Xeraya Capital.
- 10. AI is Trending with Big Pharma 10 August 2021. © Xeraya Capital. Source: https://www.lek.com/sites/default/files/insights/pdf-attachments/2060-AI-in-Life-Sciences.pdf According to L.E.K. Consulting, all the largest 10 pharmaceutical companies (by revenue) have either partnered with or acquired AI companies. Target discovery Drug discovery Development
- 11. Recent Market Trends for AI August 2021. © Xeraya Capital. 11 COVID-19 Driving Factors - Clinical trials’ revenue share of 24.5% - AI detected 17 of 25 COVID-19 patients (against professionals diagnosing them negative) - Microsoft invested $20m in COVID-19 research, data science - Grand View Research Software Solutions Dominate Largest revenue share in AI for healthcare by 40.6% Global Market Value of $6.7b in 2020 Health AI valued at $600m in 2014, est. 11x growth Expected to Reach $120.2b by 2028 Expand at CAGR of 41.8% from 2021 to 2028 Source: https://www.grandviewresearch.com/industry-analysis/artificial-intelligence-ai-healthcare-market
- 12. Case Studies AI-Powered Genomics Analysis & Liquid Biopsy 12 August 2021. © Xeraya Capital.
- 13. Congenica’s AI-powered Genomics Analysis Genomics is the collective characterization & quantification a person’s genome (a complete set of DNA is approximately 3.2 billion bases). By implementing AI, Congenica’s platform can reduce genomic interpretation time to under 30 minutes. Research outcomes can also be improved with a 30% higher analytical yield. Source: https://www.congenica.com/solutions/our-platform/ Credit: vectorfusionart, Shutterstock 13 August 2021. © Xeraya Capital. Without AI, genomic analysis can take more than 20 hours, even days. AI can power genomic medicine to research rare diseases, prenatal diagnosis, gene therapy and more.
- 14. Intervenn’s AI-powered Liquid Biopsy Source: https://intervenn.com/glyco/ Unlike standard biopsy, liquid biopsy is a form of diagnostic done on a sample of blood to detect cancer (either cells or pieces of DNA) in the bloodstream. Intervenn utilizes AI to analyze protein glycosylation (process of attaching sugar molecules to proteins, lipids & RNA) within the human body. 14 August 2021. © Xeraya Capital. Credit: Medical Laboratory Observer Glycans are complex, making glycoproteomics analytically & computationally challenging. Intervenn’s AI platform allows high-throughput glycoproteomic analysis for both medical researchers & healthcare providers.
- 15. • AI has significantly impacted various fields and is spreading out to different areas beyond informatics including life sciences. • AI has the potential to tackle one of the biggest problems medical researchers (and healthcare providers) face: the analysis of huge amounts of data. • From drug discovery and clinical research to diagnosing cancer and other rare diseases, AI has the potential to disrupt the way we view medicine, research, health, and well-being. Conclusion 15 August 2021. © Xeraya Capital.
- 16. By xeraya capital For more info, contact us: xeraya@xeraya.com Follow us: @xerayacapital www.xeraya.com 16 August 2021. © Xeraya Capital.