The depth and breadth of the impact of coronavirus is astonishing. Everyone and everything is impacted. Every institution has a role to play in managing the crisis, as evidenced by the Israeli Attorney General’s extraordinary authorization of a compulsory license to import a generic version of a patent-protected drug, Kaletra, in the rush to ensure access to needed drugs – irrespective of their patent protection. In fact, the Attorney General’s trailblazing decision resonated globally, with Kaletra’s manufacturer, AbbVie, waiving its patent rights for the drug across the world.
But the Israel Patent Office, another institution with a key role to play in defeating Covid-19, surely cannot be content at seeing its patenting processes circumvented as an answer to a problem. Rather the Patent Office processes should be adapted as part of the solution.
The Attorney General’s action is, arguably, an understandable course of action in the midst of a short-term crisis. However, it does not encourage innovation at a time when innovation is needed most. The outbreak of the coronavirus demonstrates the acute need for the Patent Office to think differently in terms of its role in supporting and protecting the kind of high-speed innovation that will help stop this, and future, crises.
The burden of delivering innovative treatments and solutions to patients as quickly as possible sits on the shoulders of the R&D community – and in the case of medical treatments the pharma, biotech and academic communities specifically. Patents are inseparable from the process of developing new and innovative treatments, and therefore, adapting the patent system is imperative in the coronavirus era (and beyond).
The R&D community is facing great challenges which directly impact patent filing. Pressure on research labs is immense – just in terms of the work needed to be done in the day to day management of increased testing and treatment of patients. Other, more innovative work, needed for getting experimental support for new inventions (i.e. cell-based assays) is delayed; pre-clinical trials are being significantly damaged as mice colonies, which are used as models for many diseases, are being depleted. Pharma companies are, by necessity, having to scale-down their drug development plans. With quarantines, isolation and public transport issues, clinical sites are being closed and patient recruitment and adherence to clinical study protocols is impaired.
All of the above will halt innovation and create a real gap in drug R&D. They are also particularly relevant to obtaining a patent for a new treatment. This is because the new treatment must be novel, or undisclosed (and non-obvious) prior to the filing of a patent application, but the patent applicant must also possess and enable the “invention” when the application is filed. For new treatments, showing possession and enablement have required at least some pre-clinical evidence that the treatment will be effective. These requirements delay the disclosure of a new treatment, including sharing information within the scientific community, until after the patent application has been filed. In fact, recently, in the midst of the coronavirus outbreak, China filed a patent application for a new treatment based on a small pilot patient study. It is unknown, but possible, that China felt it necessary to delay wider spread treatment, and the sharing of information among researchers, until it obtained positive results from the pilot study.
These problems mean that huge changes in thinking are urgently needed in order to keep the wheels of innovation turning. One answer can be found in the advancement in machine learning-led technologies and the ability to utilize massive amounts of human clinical data, to build computational disease models and other computational based biology and chemistry approaches. These breakthroughs now provide a unique opportunity to bring unprecedented accuracy and speed to drug and/or vaccine discovery and development.
Well established pioneers in the burgeoning field of data-driven computational disease modeling, offer a new fast track for obtaining proof of effectiveness. These platforms built on extensive public and proprietary human clinical data have had their methodologies peer-reviewed and widely published in the scientific literature. Such computational models based on human clinical data have shown their ability to deliver accurate and correct analysis of drug and disease modes of action. They have, in record time, identified novel disease targets, uncovered various biomarkers, helped repurpose drugs, expand indications and drive drug and target combination selection. Their results are being validated with increasing regularity and their uptake by industry is increasing exponentially.
It is precisely these kinds of technologies and human data integration that can bring the accuracy and speed necessary in crisis situations like we face today. They can save precious time, allow for rapid sharing of information in the scientific community and can speed-up drug discovery and development processes resulting in faster patient access to new treatments. Let’s not lose this opportunity to take advantage of this option to support and protect the innovation we desperately need.
This article was originally published by Globes, Israel business news – www.globes-online.com – on April 5, 2020