By Diagnostics World Team
January 7, 2025 | 2024 was full of innovative ideas and achievements. We spoke with industry experts and leaders about what to expect in the new year. In 2025, spatial biology is anticipated to help increase understanding of how disease mechanisms work, predicts Erez Podoly of Cleveland Diagnostics. “These advanced methods, such as spatial transcriptomics and immunohistochemistry, allow researchers to map protein distribution and cellular interactions within intact tissue, preserving the tissue's architecture. By identifying how cells communicate and behave within their microenvironment, spatial biology can reveal critical insights into the progression of diseases like cancer, neurodegenerative disorders, and cardiovascular diseases.”
As understanding of cell communication and interactions improve, combination therapeutics may take a front seat. “2025 will be monumental for neurodegenerative disease diagnostics and therapeutics,” predicts Russ Lebovitz of Amprion. “I anticipate personalized medicine and combination therapies for these diseases will be embraced, and the traditional silos separating Alzheimer's, Parkinson's, ALS, FTD, PSP, CBD, and MSA will begin to merge, driving extensive data sharing and crossover trials.”
Finally, the hype around artificial intelligence (AI) is expected to take on a more grounded approach, according to Niven R. Narain of BPGBio. “The industry is beginning to recognize that success lies not in generic AI applications but in purpose-built platforms anchored in a biology-first approach. This year, I anticipate significant advancements, with more AI-driven diagnostics progressing through late-stage clinical trials and some potentially reaching commercialization.”
Here are the full predictions and trends, including more information on the impact of AI/ML, spatial biology, antimicrobial resistance, and more. -- the Editors
Russ Lebovitz, MD, Ph.D., Cofounder & CEO, Amprion
2025 will be monumental for neurodegenerative disease diagnostics and therapeutics: I anticipate personalized medicine and combination therapies for these diseases will be embraced, and the traditional silos separating Alzheimer's, Parkinson's, ALS, FTD, PSP, CBD, and MSA will begin to merge, driving extensive data sharing and crossover trials. Parallel advances in fluid biomarkers, imaging biomarkers, digital biomarkers, and AI/ML analysis of the relationships between them will enable new insights that demonstrate significant overlaps between most neurodegenerative diseases. These insights will herald a new age of personalized medicine for neurodegenerative diseases in which clinical symptoms, imaging data, and digital biomarkers predict locations of damage, and the molecular biomarkers (both fluid and imaging-based) indicate specific neurotoxic mechanisms. The linking of biomarkers related to misfolded proteins, proteostasis, neuro-inflammation, autophagy, and mitochondrial damage will help pinpoint novel disease-causing mechanisms and provide new targets for disease-modifying therapies.
Niven R. Narain, Ph.D., President and CEO, BPGBio
In 2025, we are moving beyond the initial hype to a more grounded realization phase for AI-based diagnostics development: The industry is beginning to recognize that success lies not in generic AI applications but in purpose-built platforms anchored in a biology-first approach. This year, I anticipate significant advancements, with more AI-driven diagnostics progressing through late-stage clinical trials and some potentially reaching commercialization. The increasing availability of clinical data will further validate this approach, solidifying AI's role in delivering transformative precision diagnostics.
I anticipate 2025 to bring advancements in spatial biology, which will transform our understanding of disease mechanisms by enabling the analysis of tissue samples at the cellular and subcellular level, in their native spatial context: These advanced methods, such as spatial transcriptomics and immunohistochemistry, allow researchers to map protein distribution and cellular interactions within intact tissue, preserving the tissue's architecture. By identifying how cells communicate and behave within their microenvironment, spatial biology can reveal critical insights into the progression of diseases like cancer, neurodegenerative disorders, and cardiovascular diseases. Spatial biology not only impacts our understanding of disease mechanisms but will also lay the groundwork for developing early diagnostic biomarkers. By detecting subtle cellular changes before symptoms manifest, these technologies could lead to the creation of highly sensitive, targeted diagnostic tools, enabling earlier interventions and personalized treatment strategies for a range of conditions.
Quentin Blackford, President and CEO, iRhythm
Primary care will be the gateway to early detection and specialized care: With specialty care in the U.S. continuing to face an overload leading to long patient wait times for appointments, primary care will solidify its role as the gateway to early detection and specialized care, enabled by actionable insights from remote monitoring devices. These digital health tools powered by AI and integrated into existing workflows will empower primary care to identify conditions earlier, guide timely treatment, and reduce the burden on specialists. This shift will enhance care coordination, improve patient outcomes, and optimize resource allocation across the healthcare system.
Amanda Hemmerich, Pathologist, Director of Digital Pathology Innovation, IQVIA
Recently and into 2025, we are seeing a tremendous growth in the acceptance and use of digitized lab pathology solutions within clinical research: This interest in digital pathology via artificial intelligence/machine learning and other tech-enabled tools is strengthening as clinical trial sponsors invest heavily into oncology and related novel treatments and mechanisms of action, including cell and gene therapies and immunotherapies, and need to extend capabilities and expertise to better ensure viable treatments meet the unique needs of patients. In digitizing glass hematoxylin and eosin stain slides, pathologists can use AI/ML to extract more granular information from one sample, allowing for image analysis to support the interpretation and quantification of biomarkers and specific physio-pathological changes in tissues. It is through this in-depth image analysis that pathologists can secure and apply intricate insights to develop personalized care approaches for patients. As these digital solutions are further finessed, they will support expert pathologists to gain deeper relational context within tissue analysis, securing subtle insights that tangibly move the needle of progress in precision medicine and meet needs of sub-patient populations. We will see a continued increase in the use of digitized pathology solutions (e.g., scanners, high-resolution imaging tools, and AI-driven data management strategies), to help expert pathologists dive deep into insights from a single tissue sample.
Transformative companion diagnostics will be used increasingly to optimize cancer treatment by ensuring the right medicines are prescribed for the right patients: For example, tests to identify breast cancer patients who would benefit from antibody drug conjugates will maximise the potential of these next-generation targeted therapies.
Molecular testing will continue to be a valuable tool in the fight against antimicrobial resistance (AMR): While efforts to curb AMR often focus on antibiotic resistance, the burden of antifungal resistances continues to increase. Historically, culture-based methods have been used to assess antifungal susceptibility. However, molecular techniques—such as PCR—produce results up to four weeks earlier than culture. In the case of invasive fungal infections, time is of the essence, as delays in appropriate treatment are linked to increased mortality. We will see more movement towards the development and validation of multiplex PCR assays that can rapidly identify the most resistance-associated mutations in clinically relevant fungal species. This is particularly important given the limited number of antifungal drug classes available and the rising incidence of antifungal-resistant infections.