- As in most industries, AI will play an increasingly larger role in pharmaceutical patents
- Some have pointed out the benefits of AI in pharma patents, including accelerating the development process for new drugs, reducing overall costs, and even identifying new potential treatments and discovering new drugs
- Others have pointed out the challenges of AI in pharma patents, in particular, the question of the patentability of an AI invention
- Like many questions involving AI, it seems that the laws and regulations in many fields will have to evolve to keep pace with this new technology
In this article:
As detailed in our article entitled AI and the Future of Patents, it seems certain that artificial intelligence (AI) will affect almost every industry in the world in the coming years. This includes the pharmaceutical industry in general and pharmaceutical patents in particular.
In this article, we will focus on how some see the future playing out in this domain and the role that AI may end up taking in the development of pharmaceutical patents.
When it comes to AI and pharma patents, there are two distinct outlooks—one positive and one negative.
Those in the positive camp point out that AI is already in use in the medical field and in medical imaging, in particular when it comes to diagnosing diseases. This is where Machine Learning (and specifically Deep Learning algorithms) has excelled, such as in the detection of lung cancer or strokes based on CT scans.
AI is also already being used in the pharmaceutical industry, in one of the most important—and costliest—areas: clinical trials.
A. AI in Pharma Clinical Trials
It has been estimated that every year, pharmaceutical companies spend tens of billions of dollars on clinical trials, with some estimates putting the total at 40 percent of all pharma research budgets. Obviously, this is a major investment, and as well all know, not all trials are a success.
This is where AI has come in, streamlining and accelerating this key section of the drug development process. In specific, AI has done the following for clinical trials:
- Helped to design and create better clinical trials by developing better protocols
- Made it easier to find patients to participate in the trials
- Enabled data from the trials to be gathered and shared in real-time
B. AI in Pharma Drug Discovery
At the same time, AI is proving to be effective in another key area of the development process: drug discovery.
Already, start-ups around the world are employing AI to comb through large sets of data and identify patterns that humans may have missed or simply been unable to do.
As the founder and CEO of one such start-up stated
We are turning the drug-discovery paradigm upside down by using patient-driven biology and data to derive more predictive hypotheses, rather than the traditional trial-and-error approach.
By feeding algorithms large amounts of data from a wide range of sources, including clinical trials, research papers, patient records, and patents, AI might then be able to identify and even suggest previously undiscovered combinations, for example, that may be effective in treating a certain disease.
As the proponents of AI like to say, this new technology will disrupt the traditional pharmaceutical field, making the drug discovery and development process faster, more economical, and more effective.
Here, however, is where the negative camp starts to chime in, in such articles as the provocatively entitled “AI Could Threaten Pharmaceutical Patents.”
Sure, they basically say, they agree that AI will be able to do many, if not most, of the things mentioned above (and it is already doing so in many cases). However, they point out, will any of these AI-led inventions be patentable?
A. Non-Human Inventor?
One argument states that in order to obtain a patent, the inventor of the product, design, technology, or compound must be human. This was certainly borne out in the recent Dabus case, which saw the European Patent Office reject the patent application by an AI-inventor.
So, if an AI were to formulate a completely new compound on its own (without any human assistance, much as Dabus did in inventing new products), would it be possible to obtain a patent for this? What if an AI just worked on part of the process? Should it be considered as a contributor and classified as one of the inventors? If so, could a patent be granted, in whole or in part, to a non-human?
B. Obvious or Non-Obvious? To Whom?
Another argument states focus on obviousness. In order to obtain a patent, a new invention must be novel and non-obvious, and the test for this is usually the PHOSITA standard. In other words, would the invention be considered “obvious” by a “person having ordinary skill in the art?” If so, the invention would fail the non-obvious test and a patent would not be allowed.
However, in the AI age, when everyone may soon have access to advanced AI and AI-powered tools, what is considered “ordinary skill” and what can be considered “obvious”? A Pharma Times article raised “the question of whether these new AI-assisted inventions are sufficiently non-obvious to merit patent protection”:
While such inventions may surpass what is obvious to a person having ordinary skill in the art, we may reach the point when these inventions cannot be said to be non-obvious to a person skilled in the art, and who has access to machine learning that collates, analyses, and draws conclusions at a rate beyond the capacity of any person.
Or what happens when an AI is better able to solve problems than a human? Could inventions that would be considered non-obvious to a human, but obvious to an AI, pass the obviousness test and receive a patent?
One thing is clear—AI is already being used in the pharmaceutical industry and this will likely only continue to increase, especially considering the savings (in both time and money) and other efficiencies it can provide, not to mention the advances in drug discovery that continue to be made.
So, if AI will remain firmly a part of the pharma industry (as it has in many other industries), it seems that the laws involving pharma patents will have to evolve and be updated.
Right now, we are just at the beginning of this process, and cases like the Dabus patent applications are pushing this issue (and the need for change) forward.
In fact, just recently, it was reported that “an AI system created by British company Exscienta has invented a drug molecule that is entering phase 1 human trials.” The company’s CEO called this a “key milestone in drug discovery” with “a direct use of AI in the creation of a new medicine.”
It will be interesting to observe how this issue of AI in pharma patents continues to develop since the outcome will have far-reaching effects not only on the pharma, patent, and AI fields but on the entire human race as well.