What’s the next step in big data and AI?

Listen to this article on the DDW Podcast: Big data and AI are all the rage. But, beyond these buzzwords and the quantity of data, what’s next for these powerful tools? Troy Groetken of intellectual property and technology law firm McAndrews, Held & Malloy tells Lu Rahman how pharma companies can take this data from where it currently stands (drug design and development) to a more clinical level. Troy Groetken says that data has the ability to create personalised, predictive and preventative medicine tailored to individual patients and identified patient groups/populations. He has 25 years’ legal experience in intellectual property (IP) and more than 25 years’ experience in the pharmaceutical, biotechnological, and chemical fields. As a registered US patent attorney, Groetken is known globally as a ‘go-to’ intellectual property attorney for Fortune 500 clients on complex and cutting-edge IP matters and on strategic global patent portfolio development, implementation, and enforcement. “I love innovation and working with incredible minds in the pharmaceutical and life science fields who create amazing new technologies and methods of treatment,” says Groetken. His work provides insight into AI and big data in relation to pharma and drug discovery– now and in the future. “AI and big data are now commonly involved with drug discovery and development. The next phase, however, is the utilisation of AI and big data as to precision therapy. In doing so, AI and big data can be used to assess treatment modalities, especially in the clinical trial dynamic currently, to better tailor those treatments to patient demographics (particular genders, ethnicities, age, co-morbidities, and so many additional variables),” he says. According to Groetken the overall goal is to better understand the incredible amount of data that is generated from clinical activities and to use that data “to better design treatments for individual patients and patient groups by improving results, reducing side effects, among other outcomes.” Key opportunties Drug development companies are always keen to uncover new market opportunities and Groetken is clear about the ways they can maximise on those created by AI and data. His advice? Up front collection and controlling your data! He adds: “The better dataset that can be developed short-and long-term allows for maximum AI utilisation of that data. Better data helps to prevent garbage-in-and-garbage-out when AI is applied. As a result, better technologies and treatments are developed. Further, improved intellectual property can be obtained as well. From an ROI perspective, AI and big data is definitely the new frontier for many pharmaceutical and life science companies.” So what advice would he suggest for pharma and life sciences companies looking to take current data (ie drug design and development) to a more clinical level? “For a pharmaceutical company to take advantage of AI and big data, a well-constructed team of professionals is needed. Today's standard team will also include software engineers, AI and big data specialists to help design clinical programs that collect patient outcomes and then model new and improved therapies. Investment will be significant and ongoing for companies who wish to develop within this arena. However, the rewards of such investment could be substantial,” he says. Groetken sees many opportunities to utilise big data and AI in pharma. In therapeutics he says AI and big data already allow for high throughput outcomes to identify pharmaceutical and life science candidates with potential value. In clinical trials he sees the opportunity for improved data collection and patient/patient group modelling to enhance therapy development at an accelerated pace. “AI and big data allow for enhanced modelling analysis in a real time environment to determine ways to improve the therapeutic outcomes, reduce negative outcomes, and assess if a particular approach should be continued or discontinued,” he says. “The main barriers to using AI and big data in a more precision-therapy-manner are ownership, use constraints, regulatory constraints and privacy. As data are generated, who owns it? The patient? The clinical facility? The company paying for the clinical trial?” He believes we need to take all these owners into account and the data needs to be treated accordingly bearing each owner in mind: “Additionally, as AI uses that initial data and may interact with the internet to cross consider further data, who owns those resultant outcomes?” Groetken believes we need to consider cross-ownership concerns of coming led data by the AI mechanism and raises some key questions. “Does this lead to patent infringement concerns? Does this also lead to other legal ownership and misappropriation concerns? Alternatively, a number of concerns are raised if only one source ‘owns’ the data or AI mechanism. If so, what about governmental interests? What about access by others to move the data and AI resultant outcomes forward in their own creative ways? Isn’t the whole point of data and AI to accelerate innovation? Yet, ownership and ROI are always factors that must be considered as well,” he says. He adds that a new balance has to be considered between the investment and return on investment that must be capitalised for big data and AI and the public needs to use and access that same data, AI mechanism and resultant outcomes once AI is applied to that big data. “Attorneys are addressing these various issues and trying to draft improved legal documentation to address these ownership and related issues,” he says, adding that the ‘how’ has to be answered as well. “If data is generated, how will it be utilised with the AI mechanism? Is the patient, patient population, clinician, clinical facility, company, governmental entity in agreement on how such data will be implemented with AI?” he asks. This then interacts with privacy concerns. “How will the privacy of the patient be maintained? How will resultant information be kept in a manner that allows for innovation and precision therapy development, while ensuring patient/patient populations privacy,” Groetken states and says that this is not easily achieved when the overall goal of precision therapy is to tailor therapies to a particular patient/ patient population, which will inevitably already have various identifiers, characteristics and the like. “Here are a number of considerations for attorneys working in the pharmaceutical and life science fields,” he says. Regulatory issues Finally, current regulatory frameworks are a barrier to the AI and big data process and progress. According to Groetken such frameworks are built upon methodologies that do not involve AI. “As a result,” he says, “many regulatory schemas are being reviewed and analyses being done as to how AI can be evaluated and validated. Again, if the AI dynamics change (as they can during the drug development and precision therapy development process), what are the impacts to the safety and efficacy analysis from a regulatory perspective for the therapy being developed?” He says that the analysis and review may not always involve clinicians but a much larger team involving software engineers and the like, which is a new landscape for regulatory bodies. “As a result, regulatory bodies such as the FDA are trying to adapt their processes for drug and medical device reviews when AI and big data is involved in the development of those products and treatments,” says Groetken. The global view Groetken says that countries that have a well-developed pharma/life science systems in combination with AI systems have a significant advantage and head start. “Thus, the United States, Europe, Japan, among others would appear to have a significant leg up on the competition since each system already has mechanisms in place that they can bring to bear upon precision therapy development with AI and big data. Already, we are seeing significant investment in these countries and regions regarding AI and big data for drug and therapy development.” Volume 23 - Issue 3, Summer 2022 About the author Troy Groetken has around 25 years’ legal experience in the intellectual property (IP) field and more than 25 years’ technical experience in the pharmaceutical, biotechnological, and chemical fields. He is recognised in the IAM Patent 1000: The World’s Leading Patent Professionals, and has been listed as one of the Best Lawyers in America since 2012. As a registered US patent attorney, Groetken is known globally as a ‘go-to’ intellectual property attorney for Fortune 500 clients and others on complex and cutting-edge IP matters, and on strategic global patent portfolio development, implementation, and enforcement.