The impact of AI in medical settings is far-reaching and potentially life-saving. At this point, AI-led custom telemedicine solutions are arguably non-negotiable for essential patient care. AI algorithms are also now a key element of diagnostic imaging and, in many cases, detect disease with more accuracy than trained professionals.
But, AI’s usage doesn’t end at the patient-facing side of modern healthcare. Predictive technologies are also playing a key role in current clinical trials. The benefits of this are tenfold, especially considering that convoluted trial and research processes have consistently delayed vital medical breakthroughs.
With AI onside, medical trials are faster and more concise than ever before. We’ll consider how that’s possible in this article.
Easier Cross-Trial Referencing
Thorough medical testing is a convoluted process in itself, let alone when researchers also have to manually research all previous trials relating to a specific compound. This job can take months in itself, but it’s something that well-implemented AI solutions stand to do in seconds.
Let’s say a researcher wants to study the potential uses of a compound like dihexa for memory support. A quick AI search could instantly reveal vital cross-trial information, such as the fact that dihexa has never previously been used in a human study due to safety fears around cancer progression.
Scientists are then better able to position more concise, informed studies of their own, which ensure consistent, more easily achievable outcomes that have never been replicated elsewhere. The ability to easily refer back to things like previous health risks experienced during trials with the same drugs can ensure that every team member is always fully informed about the need for key safety precautions at all times.
Simplified Drug Discovery
The discovery of new drugs and compounds typically requires a lifetime of work and is sometimes even passed from one professional to another after years of dedicated research.
AI isn’t an instantaneous route to drug discovery, but it does stand to significantly simplify key processes, such as predicting a drug’s efficacy or identifying potential targets for a drug in production. AI can also predict the molecular properties of any new drug at the trial stage, by providing screening processes in half the time.
During the later stages of drug discovery, AI can also assist in the synthesis of new drug molecules themselves, as well as optimizing and streamlining even sizable clinical trials.
Ensuring Adaptability
As drug trials progress, clinical researchers often need to change the parameters of their study, either based on safety concerns, or the emergence of evidence they couldn’t previously have foreseen. As well as eliminating as many of these variables as possible with more thorough upfront analysis, AI ensures the adaptability required to change study parameters quickly. For instance, AI can automatically modify study protocols, without the need for convoluted manual adjustment.
AI in medicine is already saving lives. By bringing this technology into their clinical research, medical professionals stand to uncover new chemical compounds and drug uses faster than ever before.
