An understanding of the complex pathologies involved in patients with neurodegenerative diseases is integral to the identification of biomarkers and potential treatment methods for individuals who suffer from Alzheimer’s, Parkinson’s, and ALS. Here, we look at the development of dedicated biomarker strategies for helping to combat neurodegeneration.

Simon Gao of Genentech discusses his background in clinical imaging and the impact that AI-based approaches may have on biomarker discovery.

With a sensitivity many times greater than traditional ELISA methods, the Simoa® platform can measure brain biomarkers in blood, offering you another dimension of data from a readily available, non-invasive source.

Breakthroughs in the use of AI for biomarker prediction and validation of efficacy could shape future treatments for immunotherapies. In this case study, we look at its applications in validating lung cancer patient responses to treatment.

While the integration of AI in digital pathology will require a concerted push from those in the industry, the ability to rapidly process large amounts of tissue data with a high degree of accuracy makes it a potentially invaluable resource for diseases which are highly heterogeneous.

Milena Dumont Milutinovic, Senior Manager of Field Applications at Quanterix, walks through the company's ultrasensitive biomarker assay technology.

While constraints on the integration of NGS approaches in selection biomarker validation for new treatments still need ironing out, their benefits in assisting clinical trial progress are undeniable.

We explore some of the different applications of AI in biomarkers for cancer analysis, including in urology and the characterisation of prostate cancer.

With efforts already being made to apply artificial intelligence to imaging data for improved biomarker validation, AI is here to stay. However, to truly streamline drug development it needs to be implemented practically.