The life sciences industry is evolving rapidly, fueled by groundbreaking technologies such as artificial intelligence (AI) and significant advancements in genomics. These innovations have the potential to enhance our world in ways we're just beginning to understand.
While AI is changing the landscape of businesses across every sector, the life science industry is taking full advantage of it. In fact, AI is transforming how we understand, diagnose, and treat diseases, and how we conduct biomedical research.
From enhancing medical imaging diagnostics to personalizing treatment plans based on genetic profiles, AI is ushering in a new era of precision medicine. This convergence of AI and life sciences holds the promise of accelerating scientific discoveries, improving patient outcomes, and fundamentally reshaping the future of healthcare.
In this article, we list five such ways in which AI is driving progress in life sciences and showcases companies effectively incorporating these technologies.
1. Drug Design
Drug design is the process of creating new drugs or optimizing existing ones to improve their therapeutic properties. AI plays a crucial role in predicting how newly designed compounds will interact with biological targets, such as proteins or enzymes, and in optimizing their properties to enhance efficacy while minimizing side effects.
AI techniques can predict the 3D structure of target molecules and design molecules that fit precisely into them. Additionally, AI models predict how these molecules will behave in the human body, aiding in the development of safer and more effective treatments.
Companies like Schrödinger and Novartis use AI to accelerate the discovery of new drugs. They integrate physics-based methods with machine-learning techniques to assess and optimize chemical compounds efficiently before synthesis.
2. Clinical Trials
Finding and recruiting the right eligible patients manually for clinical trials typically takes a long time, often months or even years. And then monitoring the patient’s response to treatment and observing any potential side effects is time-consuming and expensive.
Drug developers use AI to identify eligible candidates who meet specific criteria, ranging from demographic details and medical history to DNA sequencing data. AI can also monitor patients in real-time, detecting adverse events or other issues that could impact trial outcomes.
This streamlines the process for clinicians and drug developers to select patients for each phase of clinical trials more efficiently.
IQVIA and Pfizer, two of the world's largest pharmaceutical companies, use AI to optimize and accelerate clinical trials.
3. Medical Imaging Analysis
AI-powered medical imaging allows doctors to provide not just more accurate diagnoses, but also personalized treatment options.
This can potentially eliminate the need for invasive diagnostics, like biopsies, typically required to confirm a diagnosis. As a result, it can improve patient outcomes and increase the efficiency of the healthcare system.
Nanox AI is one such company that uses AI to analyze medical images from radiology scans in real time, identifying potential abnormalities.
4. Predictive Analysis
AI can predict various factors concerning disease progression and patient outcomes. For example, it can identify individuals at risk of developing specific diseases or experiencing complications during treatment.
This sought-after technology can also predict the effectiveness of treatments for individual patients by considering factors like medical history, genetics, and lifestyle. Moreover, AI forecasts disease progression, aiding in treatment planning and enabling earlier interventions when beneficial.
Researchers in the UK have developed a simple blood test using artificial intelligence to predict Parkinson's disease years before symptoms begin.
5. Prosthetics
The integration of AI in prosthetic devices holds the potential to enhance functionality, improve control and customization, and provide a more natural user experience, benefiting millions worldwide with limb amputations, vision and hearing impairments, and dental prosthetic needs.
Atom Limbs, for instance, uses advanced sensors and machine learning techniques, where computers train themselves over time, to interpret electrical signals from the brain. These signals are then used to move and manipulate prosthetic limbs effectively.
As companies and researchers in the life sciences sector continue to innovate and explore new possibilities, it's almost evident that technologies like AI will introduce even more new applications, evolving the industry and enhancing patient outcomes in ways we're just starting to grasp.
Edited by Harshajit Sarmah
