Quantifying Biomedical Data to Advance Human Health
Quantbiomed is revolutionizing healthcare by quantifying biomedical data to improve clinical outcomes and advance human health. We develop cutting-edge tools integrating data science, bioinformatics, and medical insights for personalized medicine and efficient diagnostics. Committed to innovation and collaboration, we transform data into actionable knowledge for a healthier future.
Our Real World Data Approach
Leveraging AI and Real World Data (RWD) to analyze and transform complex biomedical data into actionable insights
Quantbiomed integrates the domains of Quantification, Biology, and Medicine to develop foundational models that advance the forefront of Precision Medicine. We are meticulously cultivating the world’s largest network of healthcare professionals, clinicians, biomedical scientists, and data scientists to deliver comprehensive, end-to-end R&D solutions on a global scale.
Our approach starts with identifying the research gap in clinical care, followed by AI-based insights generation using big biomedical data and subsequent validation in real-world datasets obtained through our clinician-patient networks.
Discoveries
Novel Subtyping of Type 2 Diabetes
Emerging research reveals novel subtypes within Type 2 Diabetes Mellitus (T2DM), each with unique genetic and metabolic characteristics. These subtypes influence disease progression and treatment responses, often overlooked by traditional classifications.
Building on this research, we are developing easy-to-use biomarkers to accurately identify T2DM subtypes, enabling precise and personalized treatment strategies.
Read more in BMJ open diabetes research & careAnti-tumour Cell Subsets in Solid Tumors
Advances in graph machine learning have enabled the discovery of novel cell subsets that play critical roles in dictating anti-tumour responses in solid cancers. By analyzing the complex cellular interactions within the tumour microenvironment, this approach identifies previously uncharacterized cell populations influencing immune activity and therapeutic outcomes.
Read more in Machine Learning with ApplicationsBiomarkers for Metabolic Aging
Using multi-omics analysis followed by clinical validation over 1000 samples and adipose tissues, we have discovered novel biomarkers that mark adipose ageing in the Indian population.
Read more in BMJ open diabetes research & careContact Us
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