Summary
It was incredible! Within 41 days of identifying, isolating and fully sequencing the Covid-19 virus, pharmaceutical company Moderna* had delivered a vaccine candidate. To top this, the company did all of this in January and February 2020 – a full month before lockdowns began in most parts of the world.¹ It was thanks to a mixture of Artificial Intelligence (AI) algorithms and advanced analytics that this feat was achieved. But why should it not surprise us?
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The AI trend in biotech has been decades in the making
The concept of AI has been around for centuries but didn’t get sufficient traction until Alan Turing had the idea of using computers to stimulate intelligent behaviour and critical thinking. From then, it gradually advanced to formation of increasingly complex algorithms such as ML (machine learning), DL (deep learning) and computer vision. Despite the period of reduced funding for AI between the 1970s and 2000, collaboration between the pioneers in the field continued and expanded particularly in AIM (Artificial Intelligence in Medicine). At that point, AI was already sufficiently advanced to enable physicians to share information about specific diseases, their potential causes and patient information, with various systems such as CASNET or MYCIN being able to generate the appropriate treatment recommendation. The development of the above-mentioned algorithms made all of this happen.2
Then, in 2003, the first human genome was sequenced. It was an incredible achievement and took 13 years and USD 3 billion to get there.3 Fast-forward to 2021 and this same process now costs less than USD 1,000 to achieve.
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The pace of technological progress we are seeing in biotech is breathtaking. A side effect of this has been an explosion of data in biotech. It has got to a stage where AI and advanced algorithms are needed to continue this incredible scientific progress. In many ways, this is already happening. |
AI is making what is extraordinary, seem almost ordinary
AI is now being used widely in biotech. According to the Genetic Engineering & Biotechnology News, it is already being used for "drug target identification, drug screening, image screening and predictive modelling.It is also being used to comb through scientific literature and manage huge amounts of critical clinical trial data that is now produced".4
How were Covid-19 vaccines developed so fast?
AI has become a valuable commodity
AI is needed to help discover new medicines quicker than ever before. It is giving the biotech industry an edge by being able to process data and simulate outcomes at breathtaking speed.
Drug development that once took decades to achieve can be dramatically shortened. The billions spent on clinical trials, could be saved through virtual simulations.
What AI does is make better use of patient data. It is able to simulate chemical interactions and predict how patients will react based on their genomics and medical history. It is giving the medical community a real edge in the fight against many diseases that still afflict the human race. It is also not just a technology anymore – it is a commodity – and it is a commodity that science can no longer live without.
AI needs data to thrive
The conditions need to be right for AI to thrive, which is timely because we are now generating a huge amount of data.
According to research produced by IDC, the global data sphere will grow from 33 zettabytes of data in 2018 to 275 zettabytes by 2025. To put this into perspective, it would take 1.8 billion years to download 275 zettabytes with an average high-speed internet connection.9
This huge dataset is the reason why AI is doing so well and being embraced by the biotech industry. Patient information, including genetic information and electronic health records on medical histories and allergies, can now be used for new applications in medicine that were impossible before. A great example of this is personalised medicine.
Medicine will become personalised and tailored
The most significant advances in medicine that we will see is likely to be personalised and precision medicine. Here, AI will perform an important role.
If medicine can be personalised to the genetics and health conditions of the patient, the side effects could be dramatically reduced and the treatment would be more effective. This could lead to huge benefits for patients suffering from diseases such as cancer and HIV. Unpredictable and destructive cocktails of drugs would no longer be administered, which would improve the quality of life for the patient and their chances of survival.
Companies such as Johnson & Johnson* and Pfizer* are already using IBM Watson to analyse patient data and
recommend better treatment
When it comes to oncology, IBM Watson is able to analyse the meaning and context of both structured and unstructured data in clinical notes and reports that might be important for selecting the right treatment. By combining data from a patient's file with clinical expertise, external research and data, the best treatment for the patient can be selected.11
IBM has also launched Medical Sieve, a cognitive medical assistant with analytical reasoning capabilities and a range of clinical knowledge. It is being used in clinical decision-making in radiology and cardiology, and can analyse radiology images to spot and detect problems faster and more reliably.12
Personalised and precision medicine will need a myriad of disruptive technologies to work on a scale that is cost effective and practical. The boom in data in the information age, coupled with the advances being made in AI, could therefore be a real game changer.
AI is making its presence felt in biotech, in ways that were unimaginable a decade ago. This is arguably just the beginning. The investment potential is therefore, immense.
Allianz Global Artificial Intelligence
Artificial intelligence has been transforming our lives and disrupting industries for years and yet we are only at the beginning of this vast structural trend. Our Allianz Global Artificial Intelligence fund offers investors global and diversified exposure to the Artificial Intelligence theme. It is not built to be a technology fund.
The fund invests across the full market capitalisation. However, our focus is on mid-cap and large-cap instead of primarily on mega-cap companies. Most importantly, we are investing along the full value chain from technology companies that develop infrastructure and enable the application of AI, to the companies across many sectors and industries adopting AI in their products, solutions and business processes. Artificial Intelligence will disrupt every industry in the future and so offers plenty of diverse investment opportunities for those with the right knowledge and expertise.
Our portfolio management team is based in San Francisco, providing them unique access to many of the key players in this space. This results in a continuous dialogue with both established players and start-ups, plus a better understanding of how AI is developing and proliferating. In addition, the Allianz Global Investors Global Research platform provides a global, cross-sector perspective. With a comprehensive understanding of the underlying technology and businesses, our team is best placed to understand the opportunities that Artificial Intelligence presents for all areas of the global economy.
Disruption from
AI
has only just
started
- AI is rapidly developing and is here to stay
- Annual investment into AI has grown 6x globally between 2015 and 201913
- AI is changing business models and traditional ways of operating
- It has the potential to accelerate human learning and productivity
- AI could contribute USD15.7tn to the global economy by 203014
Long-term growth opportunities
- Regardles of economic climate, countries recognise that future prosperity depends on investments in innovation
- AI will be the disruptive wave that will help modernise industries and drive economic growth
- Investors can participate in the secular growth opportunities of AI with the aim of enhancing returns
Diverse universe of innovative companies
- Our research platform, analyses >1,000 innovative companies
- We look for businesses that
stand to benefit from the:
- Deployment of AI infrastructure;
- Development of AI software and applications;
- Adoption of AI in key business processes;
- We have constructed a diversified portfolio of 40-100 holdings in companies that meet our investment criteria
* Securities mentioned in this document are for illustrative purposes only and do not constitute a recommendation or solicitation to buy or sell any particular security. These securities will not necessarily be comprised in the portfolio by the time this document is disclosed or at any other subsequent date.
References
1 Kelly, M. (2020, November 24). Lessons from Moderna: Leverage the Power of Artificial Intelligence. Stern Speakers. https://sternspeakers.com/news/lessons-from-modernaleverage-the-power-of-artificial-intelligence/
2 https://www.giejournal.org/article/S0016-5107(20)34466-7/pdf
3 Vella, H. (2019, January 2). The Institution of Engineering and Technology. Engineering and Technology. https://eandt.theiet.org/content/articles/2017/05/beating-cancersooner-with-data-and-artificial-intelligence/
4 Shaffer, C. (2020, April 16). Artificial Intelligence Is Helping Biotech Get Real. GEN - Genetic Engineering and Biotechnology News. https://www.genengnews.com/insights/trends-for-2020/artificial-intelligence-is-helping-biotech-get-real/
5 Terry, M. (2019, June 18). Sanofi and Google Partner on Digital Health and Real-World Evidence Analysis. BioSpace. https://www.biospace.com/article/google-and-sanofito-found-a-virtual-innovation-lab/
6 CB Insights. (2020, June 26). Big Tech Is Coming For Pharma. CB Insights Research. https://www.cbinsights.com/research/google-big-tech-pharma/
7 Novartis. https://www.novartis.com/news/novartis-and-microsoft-announce-collaboration-transform-medicine-artificial-intelligence
8 Hale, C. (2020, March 13). IBM Watson Health to tap EBSCO’s DynaMed libraries for a combined AI drug information suite. FierceBiotech. https://www.fiercebiotech.com/medtech/ibm-watson-health-to-tap-ebsco-s-dynamed-libraries-for-a-combined-ai-drug-information-suite
9 Payne, A. (2020, September 22). The role of AI in advancing personalized healthcare. TechRadar. https://www.techradar.com/news/the-role-of-ai-in-advancingpersonalized-healthcare
10 Johnson & Johnson to IBM: ‘Watson, come here. I want you.’ (2014, October 11). Fortune. https://fortune.com/2014/10/09/johnson-and-johnson-ibm-watson-new-drugs/
11 Motzer RJ, Barrios CH, Kim TM, et al. Piloting IBM Watson Oncology within Memorial Sloan Kettering’s regional network. J Clin Oncol [Internet]. 2014;32(25):2765–2772.
12 Syeda-Mahmood T, Walach E, Beymer D, et al. Medical sieve: a cognitive assistant for radiologists and cardiologists. Proc SPIE - Prog Biomed Opt Imaging [Internet].
2016;9785.
13 “Cyber-Risk Oversight Handbook For Corporate Boards,” OAS.13 “Cyber-Risk Oversight Handbook For Corporate Boards,” OAS.
14 Chenxi Wang, “Corporate Boards Are Snatching Up Cybersecurity Talents,” Forbes, August 2019.Available: https://www.forbes.com/sites/chenxiwang/2019/08/30/corporate-boards-are-snatching-up-cybersecurity-talents/#615246a479f5
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