Artificial intelligence-created medicine to be used on humans for first time
A drug molecule “invented” by artificial intelligence (AI) will be used in human trials in a world first for machine learning in medicine. It was created by British start-up Exscientia and Japanese pharmaceutical firm Sumitomo Dainippon Pharma. The drug will be used to treat patients who have obsessive-compulsive disorder (OCD). Typically, drug development takes about five years to get to trial, but the AI drug took just 12 months. Exscienta chief executive Prof Andrew Hopkins described it as a “key milestone in drug discovery”.
Enabling AI-driven health advances without sacrificing patient privacy
There’s a lot of excitement at the intersection of artificial intelligence and health care. AI has already been used to improve disease treatment and detecIon, discover promising new drugs, identify links between genes and diseases, and more. By analyzing large datasets and finding patterns, virtually any new algorithm has the potential to help patients — AI researchers just need access to the right data to train and test those algorithms.
This robot doesn’t need any electronics
Engineers at the University of California San Diego have created a four-legged soft robot that doesn’t need any electronics to work. The robot only needs a constant source of pressurized air for all its functions, including its controls and locomotion systems. Soft robots are of particular interest because they easily adapt to their environment and operate safely near humans.
Most of them are powered by pressurized air and are controlled by electronic circuits, but this approach requires complex components like circuit boards, valves, and pumps, often outside the robot’s body; these components, which constitute the robot’s brains and nervous system, are typically bulky and expensive. By contrast, the UC San Diego robot is controlled by a light-weight, low-cost system of pneumatic circuits, made up of tubes and soft valves, which are built into the robot itself. The robot can walk on command or in response to signals it receives from the environment.
How to Safeguard AI Technology: Patents versus Trade Secrets
The article above describes a common difficulty of intellectual property (IP) claims for artificial intelligence (AI): patent claims for AI are often deemed to be no more than abstract ideas. The United States Patent and Trademark Office (USPTO) has established a number of specific categories of AI in order to distil its definition, but the overarching theme amongst these categories is that, if a human mind can accomplish a particular task, it is likely an abstract idea. Of course, AI is, by its nature, an attempt to replicate the human mind, albeit in perhaps a stylized or exaggerated fashion; thus, the difficulty of patenting this technology is readily apparent.
In addition to with patents, legal battles also remain with regard to trade secrets. Rather than engage in litigation to prove infringement, a company seeking to protect a trade secret must instead demonstrate that the secret was misappropriated and that it took reasonable measures to maintain confidentiality. The distinction between patents and trade secrets remains very important for companies: trade secret law undoubtedly offers protection where patents do not, and vice versa.
Fatima Alkaabi (18), inventor: The world needs girls to study AI
Fatima Alkaabi (18) is an inventor wants to encourage girls and women to study AI. Around the world, girls and women are underrepresented in STEM classes and jobs, particularly in AI; indeed, more than 80% of AI professors are men and only 22% of AI professionals are women. One of these female AI professionals is Fatima, whose inventions have earned her prizes such as the Abu Dhabi Award and first place in the United Arab Emirates (UAE) Robot Olympics. Importantly, she does not want to be the only young female inventor getting these opportunities. As Fatima herself puts it: “We need women to create things that fit our needs as a society, and without their contributions, many of our needs might be ignored or misrepresented.”
How SMEs can use IP to secure success in the new data-fuelled AI paradigm
As the next generation of data-driven analytics gets underway and the need to deliver value from AI system outputs becomes more urgent, smaller players are eyeing up their chance to stake a claim in this multi-billion dollar landscape, which so far has been dominated by Big Tech. The author of this article explains the need to enhance IP protection beyond contractual rights to build controls and safeguards. Robust contracting and reinforcing the human element as an operational step will help to secure ownership through IP rights. This new space offers rich pickings – particularly for smaller, more agile players. The prizes will go to those best able to manouvere through the shifting web of IP, data protection, new data laws, new data governance laws, and new regulation, to claim a piece of the new AI bounty.
Artificial Intelligence in the Life Sciences Industry — Strategies for IP Protection
AI technologies including machine learning, deep learning, and natural language processing can be harnessed to process vast data sets to identify new drug candidates, optimize drug dosing, match patients with drug trials and diagnose diseases. Recognizing this potential, global biopharma companies have invested heavily in AI technology—the AI in life sciences market was valued at USD 1092.44 million in 2019 and is expected to reach USD 3445.60 million by 2025. But what happens to the IPRs? Can AI be an IPR holder?
This article provides answers to important questions about (future) IP ownership:
- Life science companies utilizing AI can mitigate potential IP ownership issues by defining ownership of AI-related IP rights in employment, licensing, or purchase agreements.
- Aside from general contractual protections of IP, life sciences companies should consider what type of IP protection is appropriate for their AI-related inventions.
- If patent protection is more appropriate (e.g., where the requirement of secrecy for trade secret protection is hard or impossible to meet), the companies should adopt an “AI-Patent Playbook” as follows to obtain patent protection for AI-related inventions.
The strategies described in the article could be adopted to minimize the risks while still harnessing the powerful potential of AI technology.