Improving the Delivery of Therapies in the Healthcare Market

Dataiku Company, Featured Kelci Miclaus

In the newly released Season 2 of the Dataiku web series AI&Us, Episode 3 explores how AI is reshaping patient health interactions and engagement. Through cutting-edge algorithms and predictive analytics, this episode showcases how AI empowers healthcare professionals to provide improved patient care through accelerated disease detection and diagnostics and personalized treatment plans.  This signals a major transformation in the connected ecosystem between life sciences organizations developing and delivering new therapies to the market, and the healthcare providers ensuring they reach the populations of patients in need.

The integration of AI into healthcare not only promises enriched patient experiences but also sets new standards for precision care. From providing comprehensive health insights to early cancer detection, AI is revolutionizing the healthcare landscape. We invite you to explore the capabilities of AI as showcased in the full video at the end of this post.

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This episode features insights from industry experts including Sahab Aslam (HealthTech Investor and AI Sector Lead at UC Berkeley), Funda Gunes (AI Health Researcher at Duke University), Georgia Kouyialis (Sr. Solutions Scientist of Health & Life Sciences at Dataiku), David West (CEO & Co-Founder of Proscia), Harini Gopalakrishnan (Field CTO, Lifescience at Snowflake), and Dr. Christopher E. Mason (Professor of Genomics, Physiology, and Biophysics), Ranjit Kumble (VP Data Science), Anubhav Srivastava (Associate Director, AI and ML), and Rory Kelleher (Global Head, Business Development for Healthcare and Life Sciences at NVIDIA). 

Equity in Therapeutic Access and Outcomes

Bringing new medicines to market is complex. Once approved, the focus shifts to ensuring they reach those most in need. Healthcare organizations have begun to analyze social determinants of health to ensure social factors that may contribute to need are incorporated into care plans and therapeutic access. AI and machine learning now enable the ability to pinpoint the immediate needs of specific localities, physician offices, or patient segments. Collaborating closely with medical communities, healthcare providers tailor interventions, revolutionizing disease treatment through precision medicine and diagnostic tests.

All of these things do factor in a person's health and well-being. Can we bring all the data points together and personalize the solution for patients … I think that's where the AI is going to come in.
-Sahab Aslam, HealthTech Investor and AI Sector Lead at UC Berkeley

However, the promise of AI also brings its set of challenges, particularly concerning ethical data usage and patient privacy. Rich Caruana's study at Microsoft underscores the potential biases in predictive modeling, revealing instances where asthma patients were incorrectly assessed as lower risk due to the oversight of intensive care treatments. This emphasizes how predictive models could misjudge patient risk without proper consideration, highlighting the critical need for high-quality, unbiased data and robust data governance.

What could be done is really spending a lot of time creating high-quality data, removing bias as much as possible, and then developing more simpler models that clinicians can understand.

-Funda Gunes, AI Health Researcher at Duke University

Enhanced Diagnostics Through Integrated Data Analysis

Technological advancements, such as those from companies like NVIDIA and Proscia, have transformed our ability to manage and analyze extensive medical datasets. Through seamless integration of digital pathology with advanced genomic and tissue imaging technologies, healthcare providers now conduct intricate tissue analyses, enabling earlier disease detection, precise medical assessments, and more personalized treatment approaches. Additionally, AI integration allows for pneumonia detection from chest X-rays, although human validation remains essential before communicating diagnoses to patients.

What we can do with some of the new GPUs from NVIDIA is actually take these large scale compute challenges that used to be very difficult and now take, for example, a complex, multidimensional image of cancer that has thousands and thousands of layers and do machine learning to tease out which kinds of cells are present by the tumor. 

-Dr. Christopher E. Mason, Professor of Genomics, Physiology, and Biophysics

Data science teams play a pivotal role in leveraging AI to drive significant progress throughout the drug development lifecycle. Their efforts focus on identifying common analytical patterns, facilitating the development of efficient tools and accelerators that benefit the entire healthcare ecosystem. A key insight from enterprise collaboration is recognizing shared methodologies and information usage across seemingly disparate departments and applications. This realization enables the creation of accessible and efficient accelerators, highlighting the invaluable synergy of enterprise collaboration.

In the commercial side of the organization, for example, from the earliest discovery of medicines, to their development, to the launch and commercialization of our assets. So literally everywhere, all along the product lifecycle, there are opportunities for AI and ML to drive real value for the organization.

-Danny Kinney, Data Science Leader at a Global Pharmaceutical Organization

Patient Engagement

The profound impact of AI in healthcare extends beyond pharmaceutical companies and medical professionals, significantly enhancing patient experiences worldwide. As patients increasingly expect proactive and personalized care, AI emerges as a useful tool in helping them feel informed, comfortable, and confident in their treatment and health decisions. Through innovative technologies like intelligent avatars and chatbots, individuals can engage in informed conversations tailored to their unique health journeys.

This episode of AI&Us exemplifies how AI is not only meeting but exceeding these expectations, promising a future where healthcare is more personalized, accessible, and effective than ever before. Discover more about AI's transformative role in healthcare by watching the full episode:

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