Part I: Top of the line, back of the house
By Julie Dibble
Editor and Senior Writer
The omnipresence of artificial intelligence (AI) has industries across the board abuzz with its potential implications. And while many unknowns still loom—including impacts on data security, ethical regulation, and the job market—it is undeniable that AI has already proven its ability to create astonishing progress.
In healthcare, where precision meets pressure and time is always in short supply, one thing is certain: AI has officially entered the chat.
Predictive AI, which analyzes data and patterns to forecast outcomes, and generative AI, which produces original text, code, and other output, are reshaping what’s possible. Considering this, let’s take a look at 3 of the most exciting—and impactful—ways AI is rapidly transforming the industry.
Smarter, Faster Drug Discovery
Thanks to AI, byte-sized breakthroughs are happening in research labs across the globe. This technology is set to revolutionize the development of medications, providing a deeper understanding of diseases and enabling more precise targeting in how to treat them.
Historically, the development of drug therapies has been a painstaking, time-consuming, and extremely expensive process. Today, AI is changing the equation. Machine-learning algorithms used by AI can analyze vast amounts of data in mere moments, identifying patterns and predicting relationships between drug and disease at exponentially faster rates and with higher accuracy than was previously possible.
For example, AI’s application in understanding the cellular basis of disease is proving to be integral to developing targeted and novel therapies. Biotech companies have already used AI to predict the effects of new drugs on patients with Alzheimer’s disease, classify digital images of different cells or genes for targeted experimentation, and analyze how to make more affordable versions of existing small molecule drugs.
It’s worth noting that these new AI-fueled capabilities are now poised to optimize not only the development of new medications, but also the ways existing medications are repurposed for new therapeutic uses.
AI –> AE
A key component of drug development is the study of adverse events (AEs) that a therapy has during clinical trials, known as pharmacovigilance (PV). Though the price tag for the intensive assessment, analysis, reporting, and ultimately prevention of AEs has traditionally been sky-high, AI is making the PV process more efficient and accurate.
This efficiency has led to dramatic cost savings—and significant benefits to patients. Researchers, for example, have used the tech to run high-fidelity simulations digitally, negating the need to physically test compounds on human beings. Besides the inherent cost reduction, this practice has reduced the risk to human study participants prior to engaging in traditional testing methods.
When it comes to AEs, AI is also stepping into the proverbial lab coat to help scientists predict things like toxicity, bioactivity, and other molecular quirks long before a compound ever sees a petri dish. The benefits of this expanded role of technology in PV are only beginning to be understood.
Pinpoint Precision
Effective medical care isn’t one-size-fits-all. This recognition drives precision medicine, a rapidly growing approach that considers an individual’s genetics, environment, and lifestyle when evaluating their overall health and prognoses.
In serving this approach, AI isn’t just crunching numbers—it’s decoding the intricate language of biology and translating it into real-world clinical wisdom. Where once we saw noise in a sea of data, AI now spots the patterns, flags the outliers, and helps turn overwhelming complexity into actionable clarity.
Take genetics, for example. AI can sift through massive amounts of genetic code faster than you can say double helix, pinpointing markers that reveal a person’s health risks or likely treatment responses. That means faster screenings and therapies that are dialed into your DNA, not just your diagnosis.
In immunology, AI is flexing its muscles even further, modeling how your immune system might react to a new drug or therapy before it ever hits your bloodstream. It’s a game-changer for designing personalized immunotherapies that are not just effective but smarter and safer, especially in tricky terrain like autoimmune disease and cancer. Think of it as giving doctors a high-powered microscope for the future of care.
Reading the AI Tea Leaves
The varied types and applications of AI in the healthcare landscape are only in their infancy, and yet, we’re already seeing the enormous impact and possibilities they hold for the industry and the patients it serves. These technologies hold the promise of transforming data overload into actionable insights that propel patient care and innovation forward in truly meaningful ways. But as with any breakthrough, the magic lies not just in the tools but in how they’re wielded. In Part II of this series, we’ll examine some of the ways AI is reshaping how providers and patients interact in real time. Keep an eye out for the post, coming this November!
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Julie Dibble brings nearly 20 years of strategic and creative content development to her role on the Encompass team. While her expertise and experience span several industries and platforms, she primarily applies her skills in the realm of market access, policy, and the inner workings of the US healthcare landscape to a variety of projects for Encompass’s clients and partners.
