Implantable drug delivery systems are a rapidly advancing field in healthcare. With ongoing research, innovation, and refinements, they have the potential to improve the lives of patients by offering more precise, targeted, and convenient drug delivery options across a range of medical conditions.
AI and Machine Learning Integration
Artificial intelligence (AI) and machine learning algorithms will be at the heart of drug delivery innovation. These technologies will analyse patient data, treatment outcomes, and drug responses to make real-time adjustments in drug delivery. For example, AI-powered insulin pumps will anticipate and prevent hypoglycaemic events in diabetes patients.
Much like personalised drug delivery, AI and ML is a powerful force in modern medicine. These technologies are driving drug discovery, optimizing drug delivery systems, and enhancing patient care through personalized treatment regimens. As they continue to evolve, AI and machine learning will play an increasingly vital role in improving the safety, efficacy, and precision of drug delivery across a wide range of medical conditions.
There are promising developments in this space such as Atomwise, a drug discovery company, who are employing AI to predict how existing drugs might be repurposed to treat new diseases. By simulating the interaction between drugs and target proteins, they have identified potential treatments for conditions like Ebola and multiple sclerosis.
Google’s DeepMind used machine learning to develop an AI system that can predict acute kidney injury up to 48 hours before it occurs. Early detection allows healthcare providers to take preventive measures.
It’s difficult to predict the rate of progress with AI, as it typically follows a logarithmic pattern, things can suddenly become possible on a month-to-month timescale, let alone a multi-decade timescale.