[Ip-health] AI Patent Trolls Now on the Job for Drug Companies

Claire Cassedy claire.cassedy at keionline.org
Mon Feb 4 06:51:39 PST 2019


https://hackaday.com/2019/01/30/ai-patent-trolls-now-on-the-job-for-drug-companies/

AI Patent Trolls Now on the Job for Drug Companies

by: Dan Maloney
January 30, 2019

Love it or loathe it, the pharmaceutical industry is really good at
protecting its intellectual property. Drug companies pour billions into
discovering new drugs and bringing them to market, and they do whatever it
takes to make sure they have exclusive positions to profit from their
innovations for as long a possible. Patent applications are meticulously
crafted to keep the competition at bay for as long as possible, which is
why it often takes ages for cheaper generic versions of blockbuster
medications to hit the market, to the chagrin of patients, insurers, and
policymakers alike.

Drug companies now appear poised to benefit from the artificial
intelligence revolution to solidify their patent positions even further.
New computational methods are being employed to not only plan the synthesis
of new drugs, but to also find alternative pathways to the same end product
that might present a patent loophole. AI just might change the face of drug
development in the near future, and not necessarily for the better.

Many Paths to Progress

In most industries, a patent is a simple concept: come up with a new idea,
and if it proves to be novel, non-obvious, and useful, chances are good
that a patent will be granted that prevents anyone but the owner from
making, using, selling, or importing the covered invention for a certain
period of time. The rub to the patent process is that the application must
reveal everything about the invention publicly, which means that after the
exclusivity period has expired, anyone can profit from the original
inventor’s work.

Pharmaceuticals, though, are treated differently. Since it’s relatively
easy to reverse engineer a chemical compound using analytical chemistry
tools and methods, patents for drugs concentrate on the process used to
arrive at the desired endpoint. Most drugs are relatively simple organic
compounds whose creation is a long, complicated series of reactions.
They’ll often start with a couple of simple compounds, reacted together
under just the right conditions to yield an intermediate compound. That
product is then perhaps purified before being mixed with a fourth compound,
and the process continues. Functional groups are added or subtracted at
each step until the final compound is created in sufficient quantity and
quality.

Every step in the process is claimed in the process patent application so
that the resulting patent is as broad as possible. But it doesn’t stop
there. There may be more than one way to skin the synthetic cat, and every
single feasible alternative synthesis needs to be covered by the
application too. Chemists at pharmaceutical companies spend a lot of effort
looking for and plugging these potential patent loopholes.

AI to the Rescue

Both the design of the best, most commercially viable synthesis and the
search for loopholes are perfect applications for AI. Syntheses can be
broken down into well-defined steps governed by rules that an expert system
can rapidly churn through, searching for a path from a known starting point
to the desired product. Researchers at the Polish Academy of Sciences and
the Ulsan National Institute of Science and Technology in South Korea had
previously shown that an application called Chematica can autonomously
generate a synthetic plan for a group of seven well-known drugs from simple
starting materials. (Chematica was recently purchased by Merck and seems to
have been rebranded as Synthia.) Each plan was generated in about 20
minutes and verified by chemists, who followed the synthetic instructions
in the lab and came up with the right endpoints.

As a follow-up, the same team turned that process around, using Chematica
to search for “retrosynthetic” paths to three new endpoints. This time, the
products were blockbuster drugs with billions in sales and presumably
air-tight patent positions. The researchers gave Chematica some rules,
making certain key synthetic steps off-limits to the algorithm and forcing
it to find alternate ways to the same product. To their surprise, paths to
each of endpoints were discovered that successfully evaded the
patent-infringing steps.

The implications of this development are potentially far-reaching. In the
first instance, it seems like Chematica and similar tools will quickly
become an aid to the intuitive, creative process of designing an organic
synthesis. Such applications could also put a fair number of chemists out
of a job, when it can do in 20 minutes what a chemist might take weeks or
months to accomplish.

On the other hand, AI applications like these stand to stifle competition.
The more airtight the patent position for a drug, the longer the patent
owner can maintain a monopoly on that drug. Using AI to test for loopholes
around the synthetic process only solidifies the claims, making it less
likely that generic versions of a drug will reach the market in a timely
fashion.

Taken at face value, the use of AI to both explore new routes to drug
synthesis and find potential patent loopholes is a fascinating use of
technology. But like anything else, the devil is in the details, and when
such systems are inevitably put into widespread use, it’s likely that the
ones that end up paying the price of progress will be the consumers.


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