Blog: AI-based Solutions Power High-tech Future in the Life Sciences

From high-profile, high-tech applications to behind-the-scenes insights and efficiencies, the impact of artificial intelligence (AI) and machine learning has been profound — even transformative.
Nagesh Jadhav
Nagesh Jadhav // Photo courtesy of Stefanini Group

From high-profile, high-tech applications to behind-the-scenes insights and efficiencies, the impact of artificial intelligence (AI) and machine learning has been profound — even transformative.

AI-powered advances have shaped almost every industry, from marketing and manufacturing, to engineering and environmental sciences.

One of the most exciting new areas for AI innovation is in the life sciences space, where pharmaceutical, health care, and biotech companies have utilized AI and machine learning to develop and bring to market new drugs, identify and deploy new therapies and diagnostic tools, and reshape patient care fundamentals.

Recognizing the ways AI technology is impacting an evolving life sciences sector — and appreciating the challenges and opportunities that come with implementation and continued innovation — is an important step in understanding the increasingly convergent future of technology in medicine.

A Virtual Revolution
At a time when the tragic and tumultuous impact of a global pandemic has introduced formidable new hurdles for drug development and clinical trials, the importance of medical innovation is clearer than ever. Even as pharmaceutical companies and health care organizations, driven by a new sense of crisis-driven urgency, work to develop new drugs and evaluate potential therapeutic solutions, seven in 10 drug trials have had to be halted due to health concerns and logistical challenges.

That’s on top of the complexities of existing structural inefficiencies that plague the process: coordinating various systems, products, and vendors; navigating inefficient manual processes, and managing large volumes of complex data to facilitate necessary access, analytics, and reporting.

The good news is, AI-powered solutions are demonstrating an ability to reimagine drug trial processes and protocols, making it possible for health care institutions and pharmaceutical companies to radically overhaul the way they conduct, monitor, and review clinical trials.

By adopting the digital data collection and virtual trials solutions, data from connected devices, analytics, and AI, life science companies have the ability to conduct patient-centric smart, hybrid, and virtual trials that sidestep logistical and health challenges and deliver meaningful insights and better outcomes.

A Prescription for Breakthroughs
AI is having a significant impact in helping develop new treatments and therapies in clinical settings, as well. Machine learning makes it possible to parse extraordinarily large amounts of patient data to target promising new therapies.

Pharma companies are using the processing power of AI-based technologies to identify promising pharmacological profiles for R&D. Bayer and Merck and Co. received the FDA’s Breakthrough Device Designation for AI-powered software leading to a breakthrough in accurately diagnosing CTEPH, a serious and often misdiagnosed pulmonary condition.

One of the most exciting areas of AI-driven innovation in the life sciences is in the field of personalized medicine and customized treatments and therapies. 3-D printed drugs, an exploding global market projected to reach an eye-opening $437 million+ dollars by 2025, offers the potential for multiple drugs to be delivered through a single pill, for drug design based on group preferences, and, perhaps most exciting, for customization of medicines (content, dosage amount) based on individual patient physiology.

The result is that drugs are easier for the body to absorb and consequently more effective. New genomic breakthroughs are unlocking the possibility of getting treatments modified to an individual’s unique DNA profile, and digital body sensors implanted into the body can gather and transmit real-time health data to enhance care, monitor trials and treatments, and improve outcomes.

Dollars and Sense
Drug discovery and research process is an enormously expensive proposition. Only 14 percent of drugs pass clinical trials, and the median cost of bringing a drug to market approaches a staggering $1 billion (and often soars much higher). This is why the new efficiencies and cost-saving power of AI technology has the potential to make a dramatic impact on the industry.

AI solutions can recognize patterns and have the potential to identify promising solutions with previously unthinkable speed and efficiency. Consequently, drugs can be developed and brought to market faster and more affordably than ever before, and life science organizations can dedicate resources to promising new drugs, therapies, and treatment programs.

Social Listening
An underappreciated factor in the AI value equation is in the field of social listening — monitoring social media channels for relevant brand and product mentions and sentiment, competitor activity, and other valuable information. Social listening can identify consumer needs, help screen for patient identification and selection for trials and therapies, monitor disease prevalence or symptoms, and track patient engagement and retention over time.

Today, life science companies faced with the formidable challenges of a global pandemic and a costly and competitive marketplace have access to an exciting suite of emerging AI-driven solutions. From R&D to customized medicines and personalized treatments to detailed monitoring and engagement, AI tech is diagnosing a healthy and prosperous future for these essential industries.

Nagesh Jadhav is director of digital transformation and innovation in the health care and life sciences practice at Stefanini Group, which operates its U.S. headquarters in Southfield. Nagesh has more than 10 years of experience improving patient experience and engagement and getting faster and better care to patients through technologies like automation, AIOps, DevOps, data science, cloud solutions, and services. He can be contacted at