Clinical Trial Data and IP
How better data can make a difference in clinical trials and lead to new IP
This week is JPM, the largest healthcare conference of the year in San Francisco. To celebrate, this week’s blog post is themed around clinical trials and written with the team at MiracleML.
Clinical trials, which is how pharmaceutical manufacturers generate proof that their drug works and receive FDA approval, are a major cost of the increase in drugs. The cost of clinical trials have gone up dramatically—so much so that instead of Moore’s Law, the pharmaceutical industry has “Eroom’s Law,” which is Moore’s Law backwards to signify exponentially increasing costs. It used to cost $10,000 per patient and is now over $500,000, and trials account for nearly 40% of pharmaceutical company budgets. At the same time, nearly 80% of all clinical trials are delayed, which can cost up to $8 million in costs and lost revenue per day, to say nothing of the potential for patent delays.
At the same time, clinical trials are essential. They are the gold standard for how we know whether treatments and diagnostics work. And they can also be part of a strong IP strategy. Companies often underestimate the importance of clinical trials in generating IP. And done the right way, well-run clinical trials can result in stronger IP, more IP, and better-protected IP. So this week at Nonobvious, especially in honor of JPM, we are going into a few best practices to improve clinical data and how that can lead to a better IP strategy.
More data, more patents
Clinical trials involve the public use of drugs with clinical trial participants, often in great numbers to achieve statistical significance and statistical power. Patents are subject to a public use bar, which can have significant variation by jurisdiction—for example, European patent law is stricter. However, most patent law regimes do recognize an experimental use exception to the public use bar.
The question is whether clinical trials count as a public use or an experimental use. Mintz, a leading law firm, put out an article examining this question in greater detail. You should read the full piece, but the bottom line is this: you must take care to operate your trials in a compliant fashion (most importantly, using NDAs for participants and not informing them of the invention, only the drug and dosage) but companies can almost certainly file for patents that are undergoing Phase I trials, very likely file under Phase II trials, and likely not file under Phase III trials, though there may be rare circumstances that would support such a filing. The main factor is that you cannot patent something that was known at the start of a trial. For example, in Helsinn v. Teva (855 F.3d 1356 (Fed. Cir. 2017), aff’d 139 S.Ct. 628 (2019)), the Helsinn Court implied that a change in formulation between Phase II and Phase III potentially could have potentially supported a new patent application; however, because the efficacy of the drug with the formulation and dosage at issue had been proven in Phase II, Phase III was too late to patent. Of course, there may be variation in other jurisdictions.
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There is also the matter of publications. There are various regulatory regimes, like securities laws for publicly traded companies, that may require the filing of public information, which would count as a public use for purposes of preempting an application. However, the earlier you file, the shorter your patent term relative to your approval period, even with patent term extension. What this means is that the better your data, the more subtle variations you can pick up on and test in later phases of the approval process, thus extending your patent life. Plus, it will give you more options to test, which can mean more patents for your patent thicket. You can also pursue continuations in part, but beware—the original patent is often filed long after the original application, so there are additional requirements to avoid a Bauman priority date or even a finding of unpatentability.
So what can you patent? New uses, new treatment regiments, new formulations, and more. If you are working on a new device or diagnostic and must invent a new part to fix a problem, or a new algorithm, those remain new inventions. Furthermore, one of the new frontiers that may not be explored until a later trial is a combination therapy (in fact, the NCI CTD Task Force recommendations for combination therapy Phase I design includes designing a Phase II). It is common to not investigate a combination therapy until the efficacy of the underlying innovative treatment is established, at least with a small sample size. Combination therapies can be deemed an “unexpected result” sufficient to allow a new patent; indeed, this is one of the hot new strategies to extend the patent life of a drug.
Exploiting this opportunity requires, of course, a very nimble data operation. For one thing, a bad data operation can impact the enablement and written description supporting a set of claims. Furthermore, there are some differences in how clinical data is prepared for regulatory filings vs patent filings. One of the most important is avoiding delays in filing, so being able to collate data and organize it quickly is essential for avoiding an invalidity finding. The firm Knobbe Martin published an article in the journal Pharmaceutical Patent Analyst that goes deeper into the use of experimental data and what type of data to include in the patent application, like including pharmacological data and excluding data relating to research methodologies. Also importantly, clinical trial data can sometimes be applied ex post to overcome an obviousness rejection and support unexpected advantageous results for new claims, dosages, formulations, combinations, and other potential bases for new patents. For more detail, check out the article; it is very helpful and well-written.
Apple won an appeal against Masimo at the Federal Circuit, upholding the invalidation of two patents at PTAB. Of note, neither of these two patents have any relevance to the patents at issue in the ITC proceeding. Masimo Corporation v. Apple Inc. , No. 22-1895 (Fed. Cir. 2024)
In 2023, Qualcomm and TSMC received more patents than IBM, bringing it to spot #2. IBM was the top recipient for more than twenty years, which it used as a recruitment strategy; now that it has abandoned that strategy, the top patenters are Samsung, which is one of the most innovative companies in the world, and Qualcomm, for which patents are integral to its strategy. (Axios)
PepsiCo won an appeal that would have limited sales of its Lays potato chips in India. (Reuters)
Also in India, the Indian High Court prohibited the sales of generic drugs from 6 manufacturers. This is a particularly important win for the rule of law because generics manufacturers are now a big part of the Indian pharmaceutical industry and a favored industry. A win for IP therefore comes in against a favored industry. (Times of India)
SCOTUS rejected cert for yet another PTAB challenge, this time from Intel attempting to argue that PTAB decisions to not review a patent cannot be appealed. (Reuters)
In a precedential decision, the Federal Circuit invalidated some claims for a PacBio patent based on the difference between “identifying” and “detecting” biomolecules based on the ordinary meaning standard. Pacific Biosciences of California, Inc. v. Personal Genomics Taiwan, Inc., No. 22-1410 (Fed. Cir. 2024).
Singular Computing, which is suing Google over a machine learning patent and alleging over $1.6 billion in damages, began oral arguments this week. There is a separate appeal carrying on at the Federal Circuit level to invalidate those very patents. (Boston Globe)
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