Proceedings: DIA 2018 Global Annual Meeting

The Future of PharmaTech and How to Harness AI

Sandra Blumenrath
DIA Science Writer


ew technologies, such as AI, blockchain, cloud computing, and “the internet of things,” are leaving their footprint on the entire healthcare ecosystem. Pharmaceutical and biotech companies have taken on these innovative technologies to provide solutions at various steps throughout the product lifecycle – from discovery and clinical trials to manufacturing, regulatory approval, pharmacovigilance, and market access. This new trend of applying technology to various R&D processes is generally referred to as “PharmaTech.”

Speakers at the “Future of PharmaTech” DIAmond session examined the concept of PharmaTech and how innovative technologies in drug development, such as artificial intelligence, are impacting the pharmaceutical and biotech industry today.

Key Takeaways

  • The Massachusetts Institute of Technology (MIT) is collaborating with representatives from the pharma industry to move from “wearables” to “invisibles” using wireless signals.
  • Within the pharma industry, there are attempts to use innovative technologies in diagnostics, therapeutics, and the discovery of new biomarkers as well as to generate reliable real word evidence.
  • For regulators, new technologies like cloud computing and blockchain offer opportunities not only for speedier reviews, but also for increased case-by-case flexibility, collaborations that rely on exchanging information in real time, and accepting and processing many different types of real world data.
  • Overall, PharmaTech enables us to focus on patient outcomes and think about how healthcare and clinical trials can be brought to the patient’s home.
  • Work is needed to create a landscape view of the various technologies that companies are using and experimenting with to help us learn which technologies can or cannot be used in certain contexts.

Sudip Parikh and Patrick Brady discuss key points raised during the DIAmond session on innovative technologies that are finding their way into the pharmaceutical and biotech industry.

At least thirteen of the top twenty pharma companies have made public pronouncements of some kind in 2017 about their collaborative work on artificial intelligence (AI) in the R&D space, partnering with either AI vendors or AI initiatives within their own company to transform current R&D models. And there are claims that no less than 66 percent of industry executives expect AI to become a groundbreaking force inside their company within the next two years.

What is PharmaTech and What Can It Do?

Innovative technologies, such as AI, blockchain, cloud computing, and machine learning can be applied across the healthcare product lifecycle. PharmaTech may be best explained as encompassing the various ways these new technologies can be leveraged to help companies complete different aspects of the work required within the pharma R&D space. Industry, academia, and regulators are each finding new opportunities for advancing existing technologies to ultimately provide patients with better and more user-friendly healthcare.

MIT, for example, is actively working with pharma companies and providers to provide a proper landscape view of both the opportunities and challenges associated with using new technologies in R&D. What’s more, the Institute is collaborating with representatives from the pharma industry on moving from “wearables” to “invisibles,” a move that intends to address issues with adherence and compliance as well as the additional overhead that may complicate clinical trials.

Invisibles involve a customized box in the patient’s home that, with the help of machine learning and AI algorithms, uses wireless signals in the patient’s surroundings to collect data on their motion and physiology, their interactions with others, and activities of daily living (or ADLs). With such invisible devices, a person’s gait, trajectories, falls, heart rate, breathing, sleep patterns, and health-related day-to-day activities can be monitored 24/7 without ever putting a wearable sensor on the patient or asking them to enter information into an electronic database system. RF-Pose and EQ-Radio are two research projects investigating the use of radio frequency signals to monitor movements and physiological features.

Dina Katabi, MIT

Henry Francis, FDA

Industry is Adapting to New Technologies

Within the pharma industry, there are innovations on multiple levels:

  • Screenings and diagnoses: Using machine learning to extract more valuable information from data that already exist, such as MRI images and mammograms.
  • Biomarkers: Generating new types of additional biomarkers based on physiological monitoring data, for example in central nervous system disorders.
  • Therapeutics: Pairing drugs with “companion” technologies that adjust drug dosage according to the patient’s treatment progression.
  • Real World Evidence: Analyzing data on post-market safety, usage, comorbidities, and other attributes that were not captured by clinical trials.

DIAmond Session Panelists
Patrick Brady (Moderator), Vice President of Regulatory Affairs, Bayer

Henry Francis, Director for Data Mining and Informatics Evaluation and Research, OTS, CDER, FDA

Dina Katabi, Professor, Massachusetts Institute of Technology (MIT)

Dave Myers, National Director, US Life Sciences, Microsoft

Sudip Parikh, Senior Vice President and Managing Director, DIA Americas

Impact on Regulatory Affairs

For regulators, such as the FDA, the potential for processing information more efficiently and facilitate collaborations with other regulators across the globe is a highly attractive feature of new technologies. Being able to deliver and innovate in real time is a major advantage that the FDA seeks to leverage in various areas. Examples mentioned during the session include:

  • A cloud-based foundation for a lot of FDA’s computational capabilities allows for increased flexibility when it’s most needed, such as in emergency situations.
  • FDA also uses the cloud to facilitate internal and external collaborations. Internally, FDA is a highly secured environment, and external collaboration can be very complicated. But with cloud configuration the FDA is now able to work with external capabilities using blockchain to exchange real-time information on health records for drug safety reporting.
  • The FDA is looking to develop the capability to accept real world data (RWD) with a computational architecture that can tackle not only the data but also the speed and form in which these data are submitted.
  • Because each review case has unique attributes, there has to be an infrastructure that is adaptable on a case-by-case basis. Cloud infrastructure increases flexibility and adaptability to the extent that new ideas can be explored within weeks rather than years, and new safety information can be evaluated at a fraction of the time.

What’s Next?

The traditional uses of new technologies include examples of companies ‘digitizing’ their operations, for example in-house activities related to compliance, tracking, and analysis. What’s new is the move towards enhancing patient care. These technological advancements enable us to think about how we bring care and clinical trials to the patient’s home with the ultimate goal of making patients better faster. But panelists agreed that, while the use of AI and other technologies in pharma is very positive, there has to be a meaningful interaction between experts and the technology to use it most effectively. Bringing the academic viewpoint into this conversation and multi-disciplinary thinking will be increasingly important as these trends move forward.