Two experts in biosimilar intellectual property (IP) law break down the issues that digital health and precision medicine face with IP and the history of case law that has created the current landscape.
Precision medicine is changing the treatment landscape for countless patients, but with the transformational advances come a host of intellectual property (IP) issues that must be overcome to ensure the continued evolution of these life changing technologies. With a focus on digital health, we will discuss what precision medicine is and the IP hurdles it faces, such as patent subject matter eligibility, proving infringement, and software licensing.
What Is Precision Medicine?
Precision medicine is a term used to refer to treatment and prevention strategies tailored to groups of people based on genetic, environmental, and lifestyle factors, instead of using a one-size-fits-all approach. “Precision medicine” is often used interchangeably with the older term, “personalized medicine,” but is preferred by some because personalized medicine was often misconstrued as individualized treatments, not those developed for a group of people.
Targeted therapies are the foundation of precision medicine. They include cancer treatments that target proteins controlling cell growth. Many targeted therapies are small molecule drugs or monoclonal antibodies, which have targets inside and on the outside of cancer cells. Using these targets, the drugs can mark cells for destruction by the immune system, stop cancer cell growth signals, stop blood vessel growth, cause cancer cell death, prevent access to hormones necessary for cell growth, or carry toxins to the cancer cells. Targeted therapies differ from chemotherapy in that they act on specific molecular targets associated with cancer cells instead of targeting all rapidly dividing cells, and they often prevent cell growth (cytostatic) where chemotherapies kill cells (cytotoxic).
Along with targeted therapies, precision medicine may also utilize diagnostics. Diagnostics can perform a variety of functions, including identifying potential for disease, diagnosing disease, and identifying patients who may or may not benefit from a particular therapy. In precision medicine, diagnostics may be used to analyze a patient’s genome for mutations or measure protein expression or metabolites to guide treatment decisions.
What Are the Benefits of Precision Medicine?
While precision medicine is still in its early days, its development and use is increasing because of its therapeutic and cost saving benefits. Ineffective medications are a concern for health care, from both a patient and cost perspective. As of 2015, for every patient that was helped by the 10 highest grossing medications, between 3 and 24 patients received no benefit. In 2001, a study showed that the available cancer drugs were ineffective for 75% of patients. Taking an ineffective drug subjects the patient to side effects without a therapeutic benefit, and prolongs the time to receiving an effective treatment, time during which their disease could irreversibly progress. Spending money on ineffective treatments is problematic, with an estimated $2.5 billion per year wasted on ineffective rheumatoid arthritis treatments alone. It was estimated that US pharmaceutical spending was over $575 billion in 2021, and given the high level of ineffective treatments, the overall waste could amount to billions of dollars each year.
Precision medicines and new diagnostic tools hope to provide prevention strategies and treatments more tailored to each individual. Targeted research is increasing, with 61% of clinical trials for cancer treatments conducted in 2019 using biomarkers, compared to only 18% in 2000. Precision medicine approvals have also been on the rise, accounting for over 25% of drug approvals each year since 2015, and with over 42% of new drug approvals in 2018 being precision medicines.
As of 2020, there were 286 precision medicines on the market in the US. In addition, 24 new or expanded indications for in vitro diagnostic testing systems have been FDA-approved over the last 3 years that can inform targeted therapeutic decisions. The cost for sequencing a human genome has dropped from $100 million in 2001 to approximately $1000 in 2019, allowing for more frequent use of this technology and the potential to compile large databases of genetic information for analysis.
What Is the Role of Digital Health in Advancing Precision Medicine?
Digital health is facilitating advances in precision medicine by helping patients manage their diseases and collecting and analyzing data that leads to the development of new treatments and indications. Digital health includes technologies such as medical mobile apps and software, wearable devices, artificial intelligence (AI), and machine learning. Software and devices can be used by patients to collect data and manage their treatments.
For example, a patient with multiple sclerosis may be able to use a wearable device to track their steps and speed, and using a mobile app, compare their data to other patients and track their own data over time to monitor the progression of their disease.
In addition to benefiting the individual patient, the data collected can also be compiled and analyzed to optimize treatment or to develop new and more effective diagnostics and therapeutics. AI and machine learning can be used to analyze large data sets, such as patient genomes, to determine correlations between genetic mutations and drug efficacy, or determine which drugs may or may not work for a particular patient based on their individual characteristics.
IP Issues for Digital Health Inventions
With the advances in digital health come a variety of patenting and licensing opportunities, as well as legal challenges that must be considered. Patenting opportunities exist throughout the process of discovery, testing, and administration of precision medicines. In the area of digital health, patents may potentially cover tools for building databases, analyzing, and sharing medical data, computer programs, and ways of storing data like electronic health records. Patenting opportunities may also exist for discovery platforms for designing and engineering precision antibodies, methods of screening genomes to identify disease targets, modeling tools, and wearable devices. Patenting challenges will vary depending on the technology, but some of the particular pitfalls for precision medicine come from 35 U.S.C. § 101 patentable subject matter challenges, divided infringement issues, and open source software (OSS) licensing.
§ 101 Subject Matter Eligibility
The Supreme Court issued a series of cases from 2012 to 2014 that form the basis for applying § 101 patentable subject matter, including Mayo v. Prometheus, 132 S. Ct. 1289 (2012), Ass’n for Molecular Pathology v. Myriad Genetics, 132 S. Ct. 1794 (2013), and Alice Corp. Pty. Ltd. v. CLS Bank Int’l, 134 S. Ct. 2347 (2014).
In Mayo, the Court found diagnostic testing claims to be unpatentable laws of nature, explaining that claims that include laws of nature can be patentable if the claims apply the law of nature. The claims cannot preempt the entire use of the law of nature, and the additional elements added to the claim have to be significant. They cannot simply add steps that are well understood, routine, or conventional.
In Myriad, the Court found claims covering isolated gene sequences unpatentable because isolating naturally occurring DNA is not patentable subject matter, where creating DNA that is not naturally occurring is eligible.
In Alice, the Court found a computer system implementing intermediated settlement of financial obligations to be unpatentable, creating a 2-part test for subject matter eligibility. In Step 1, the court determines whether the claim is “directed to” a patent-ineligible concept (law of nature, natural phenomena, or abstract idea). If the answer is yes, then the court proceeds to Step 2. In Step 2, the court considers the elements of each claim both individually and as an “ordered combination” to determine whether the claim contains an “inventive concept” that transforms the claim into a patent-eligible application that is “sufficient to ensure that the patent in practice amounts to significantly more than a patent upon the [ineligible concept] itself.” Id. at 2355.
The cases since this trio have shown that obtaining patents on digital health inventions can be challenging, particularly given the inconsistent application of case law, but they give some guidance on the types of claims that may survive a § 101 challenge and should be considered when drafting claims covering computerized methods.
Smartgene Inc. v. Advanced Biological Laboratories, 555 F. App'x 950 (Fed. Cir. 2014) held that adding a computer to perform steps of a mental process routinely engaged in by doctors is not enough to transform an abstract mental process into patentable subject matter, finding that systems and methods for guiding the selection of a therapeutic treatment regimen for a patient with a known disease or condition using a computer to be ineligible as abstract. Claims directed to the abstract ideas of mathematical calculations and statistical modeling that included generic steps of implementing and processing calculations and storing the data without any practical application were found unpatentable despite claims of improved accuracy, because “different use of a mathematical calculation, even one that yields different or better results, does not render patent eligible subject matter.”
In re: Board of Trustees of the Leland Stanford Junior Univ., 991 F.3d 1245, 1251 (Fed. Cir. 2021). Combining 2 abstract ideas, such as machine learning technology using support vector machines (SVM) and recursive feature elimination (RFE) to process large sets of data (like human genomes), is still an abstract idea and not patent eligible, particularly if a non-abstract application is not identified. See Health Discovery Corp. v. Intel Corp., 2021 WL 6116891 (W.D. Tex. Dec. 27, 2021).
As an example of how courts distinguish between patentable and unpatentable subject matter, it’s interesting to look at a pair of related cases between CardioNet and InfoBionic. These cases suggest that if an actual device is developed using the abstract mathematical concepts as opposed to using a generic computer, the claims are more likely to be found patent eligible. See CardioNet, LLC v. InfoBionic, Inc., 955 F.3d 1358 (Fed. Cir. 2020) CardioNet, LLC v. InfoBionic, Inc., 2021 WL 5024388 (Fed. Cir. Oct. 29, 2021).
The court’s analysis hinged on whether the claims were “directed to” the computer/device or the mathematical concept that the computer/device was performing. Providing proof of using the device in a real world context was also helpful in conferring patent eligibility, as was describing the advantages offered by the claimed system or device in the specification. See CardioNet, 955 F.3d 1358.
Finally, in the CardioNet case finding patent eligibility, there was nothing in the record suggesting doctors were previously employing the techniques at issue. See id.
However, in the case finding ineligibility, the claims did not describe how a doctor decided when to turn on the claimed T wave filter, suggesting that doctors using conventional techniques, and automating known techniques using a computer would not be patent eligible. See CardioNet, 2021 WL 5024388.
Although employing AI as part of precision medicine may be part of a patented process, so far it has not been feasible to list that AI as an inventor on patents in the United States. See Thaler v. Hirshfeld, 558 F. Supp. 3d 238 (E.D. Va. 2021).
This is consistent with the findings of courts in the United Kingdom, the European Union, and recently Australia (which had previously found that AI could be listed as an inventor). South Africa has allowed AI inventors, but lacks substantive prosecution, so it is unclear if it will be upheld if challenged.
Since performing a mathematical concept on a generic computer and automating known techniques have been found ineligible, drafting claims for computerized methods and software related to precision medicine that are directed to discrete devices, and include specific process and operation steps, will give the best chances of patent eligibility under § 101. Describing the improvements over the prior technology and providing evidence of actual application in the specification will also be helpful in avoiding a § 101 challenge.
Trade secrets should also be considered to protect aspects of inventions that may be considered ineligible subject matter. For example, an isolated nucleotide sequence may be unpatentable under Myriad, but could possibly be protected as a trade secret if the company takes the necessary steps to keep the information secure.
Until 2016, trade secret misappropriation was governed by state law, with varying statutes of limitation, remedies, and definitions of what a trade secret is. In 2016, the Defend Trade Secrets Act (DTSA) was passed, creating a civil cause of action for trade secret owners to sue in federal court. The DTSA does not preempt state trade secret law, but provides an additional option of filing a case in federal court. It also provides uniform definitions of “trade secret” and “misappropriation” and remedies including civil seizure, injunction, payment of a reasonable royalty, and damages.
Another potential concern for precision medicine patents is enforcement. Because patents for precision medicine often require steps to be performed by more than one party, without a single party controlling the actions of all the parties, divided infringement can be an issue. In particular, this can be an issue for claims involving a diagnostic method followed by a treatment based on the outcome of the diagnostic test. This type of claim has shown to be subject matter eligible under § 101, but the diagnostic testing is often done by one party followed by a treatment decision made by a doctor, dividing the infringement between multiple unrelated parties. For digital health, this could be an issue if, for example, claims were directed to diagnostic testing through patients collecting data via a wearable device, followed by their doctor providing treatment based on the data collected.
Under the precedent of Akami Techs., Inc. v. Limelight Networks, Inc., 797 F.3d 1020, (Fed. Cir. 2015) (en banc), a party can be held responsible for the infringement of other partiesperforming the steps of a method claim to 2 situations:
Direction or control can be found when an alleged infringer conditions participation in an activity or receipt of a benefit upon performance of a step or steps of a patented method and establishes the manner or timing of that performance. Id. The level of cooperation or control necessary to prove divided infringement should be considered broadly, and “conditioning” participation is not limited to legal obligations or technical prerequisites, and does not require penalties for non-compliance. See Travel Sentry, Inc. v. Tropp, 877 F.3d 1370 (Fed. Cir. 2017).
Proving direct infringement when there are multiple actors may be easier in the generic drug context than for diagnostic testing methods followed by treatment decisions, because instructions in the Physician Prescribing Information and Patient Information can establish the necessary level of direction or control to prove treatment was conditioned on performance of other method steps, and can show specific intent to induce infringement. See Eli Lilly and Co. v. Teva Parenteral Medicines, Inc., 845 F.3d 1357 (Fed. Cir. 2017).
A laboratory report provided to a doctor by a diagnostic testing company has not been shown to provide the necessary specific intent to induce infringement of method steps requiring the performance of an assay followed by administering a drug. See Cleveland Clinic Found. v. True Health Diagnostics LLC, 859 F.3d 1352 (Fed. Cir. 2017). The Court here also noted that a “party that provides a service, but no ‘material or apparatus,’ cannot be liable for contributory infringement.”Id.
While the case law indicates that proving infringement of certain digital health patent claims may be challenging, it does leave open the possibility of proving infringement in some situations, such as if a doctor conditions a patient’s treatment on their collection of data using a device or mobile app, or if a diagnostic laboratory is affiliated with a doctor or hospital and their contracts provide the necessary level of direction or control to prove infringement.
Open-Source Software (OSS) Licensing
Precision Medicine may employ the use of computer programs and mobile device apps. Many of these programs and apps may be built on open-source software (OSS), which is a type of software that has source code that is open to anyone to review, modify, and improve.
This software can be used instead of closed source (also known as proprietary) software which has code that can only be modified by the company that owns it. While there are some types of free OSS, many are available pursuant to an OSS license that may have restrictions on distribution, particularly if a company is considering “white labeling” software (rebranding to appear as though it is a company’s own software) for its precision medicine process. Depending on the license, code modifications may need to be provided to others for free.
OSS comes with many advantages, such as being less expensive than proprietary software and being interoperable with various systems. However, OSS does have issues that precision medicine companies will need to consider when developing their software and applications. Since patient health data is often collected in precision medicine, privacy is important and is directly impacted by software security. This is a concern for both OSS and proprietary software, with some feeling that OSS may be safer because so many people are reviewing the code.
However, support for technical issues can be unreliable for OSS since it typically relies on the open source community and not a particular vendor. Enterprise grade OSS could be used to avoid this issue and remain HIPPA compliant because it requires enhanced testing, performance tuning, and is proactively examined for security flaws. Unlike other OSS that relies only on the open source community to fix technical issues, enterprise grade OSS typically has a security team that reviews the code and has processes for responding to issues and notifying users about the issues and how to fix them. OSS rarely comes with any warranty, liability, or infringement indemnity protection should there be any issues.
Depending on the technology, certification of the software may be necessary, for example to comply with FDA regulations or interoperability standards set by the CMS and the Office of the National Coordinator for Health Information Technology. While it is possible to have OSS certified, it may be more challenging than for closed source alternatives.
While precision medicine has the potential to change the lives of many patients and save our health care system significant costs by better avoiding ineffective treatments, companies developing these technologies have many issues to consider when developing, patenting, and licensing their technologies. Because of the complex and often inconsistent application of case law to precision medicine and digital health inventions, IP counsel should be consulted on how to best protect these discoveries.
 Schork, NJ. Personalized medicine: Time for one-person trials. Nature. 2015;520:609-611. doi:10.1038/520609a
 The personalized medicine report: 2020 - Opportunity, challenges, and the future. Personalized Medicine Coalition. Published 2020. https://www.personalizedmedicinecoalition.org/Userfiles/PMC-Corporate/file/PMC_The_Personalized_Medicine_Report_Opportunity_Challenges_and_the_Future.pdf
 Lagasse, J. Precision medicine has potential to reduce wasteful ineffective treatments, study says. Healthcare Finance. Published May 22, 2018. https://www.healthcarefinancenews.com/news/precision-medicine-has-potential-reduce-wasteful-ineffective-treatments-study-says
 Personalized medicine at FDA: The scope & significance of progress in 2021. Personalized Medicine Coalition. Published 2021. https://www.personalizedmedicinecoalition.org/Userfiles/PMC-Corporate/file/Personalized_Medicine_at_FDA_The_Scope_Significance_of_Progress_in_2021.pdf