By Andrew Lacy
Thanks to recent breakthroughs in medical imaging, biochemical and genetic research, and AI-enabled analytics, a wave of new biomarkers are now changing the ways we think about a wide range of illnesses, from new challenges like COVID-19 to longstanding health concerns such as immune disorders and gastrointestinal ailments.
The resultant flood of data can create challenges for physicians — but in the long run, novel biomarkers will give us powerful new clinical weapons as we fight for our patients' health.
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In some cases, biomarkers can offer entirely new pathways to prevention or treatment. It was recently found that babies with high levels of heavy metals in their teeth are more likely to develop Crohn's disease, for instance — a remarkable environmental factor that could make it easier to encourage healthier behaviors in mothers or caregivers. Similarly, lupus sufferers can increasingly look forward to customized treatments as doctors begin to use novel biomarkers found in blood or urine to monitor their disease's progression and response to clinical interventions.
Of course, novel biomarkers are especially important when we're tackling novel diseases, and the COVID-19 pandemic has driven important new research in this area. Some researchers have identified specific proteins that can indicate an increased likelihood of serious disease, helping healthcare professionals to triage patients and identify suitable candidates for antibody therapies and other new interventions that can't be offered to every single infected patient.
The possibility of forecasting a patient's death with 90% accuracy up to 10 days in advance might sound like something lifted from the pages of a science fiction novel. Still, the reality is that overburdened clinicians are already having to make judgment calls of this sort on a daily basis. In a world where doctors already need to make difficult choices about which patients get oxygen, ventilators, antibody therapies, or other potentially scarce resources, we should at least ensure we're equipping them to make smart, well-informed decisions along the way.
The power of AI
Making sense of biomarkers isn't always as simple as running an assay and getting a straightforward, yes-or-no result. Often, especially in the world of medical imaging, human judgement and professional experience play a huge role in parsing out the clinically useful signals amidst the noise. In such areas, improved analysis of existing data can be as important as finding novel markers. Machine learning tools and neural networks are now able to distinguish COVID-19 infections from community-acquired pneumonia with about 90% accuracy based on CT scans, for instance, and can also help imaging specialists to diagnose cancers and other illnesses earlier in their progression.