Dr. Km. Saumya

Assistant Professor

Email: Email: Km.saumya@galgotiacollege.edu
Address: Galgotias College of Pharmacy, Plot no. 1, Knowledge Park -II, Greater Noida, G.B. Nagar, U.P. 201310
Academic Identity: ORCID ID: 0000-0002-9516-6948
Google Scholar Profile: https://scholar.google.co.in/citations?hl=en&user=5LQGabQAAAAJ

Research Interests

Biomarker discovery and validation for early detection and risk stratification of chronic diseases, particularly chronic kidney disease (CKD).
Application of machine learning and artificial intelligence in biomedical data analysis, disease phenotyping, and predictive modeling.
Clinical pharmacology and pharmacotherapy with emphasis on improving patient outcomes.
Pharmacoepidemiology and real-world evidence generation for clinical decision-making.
Translational research integrating clinical biomarkers, computational tools, and patient centered outcomes.
Pharmacoeconomics and health outcomes research in chronic disease management.

Experience

Academic

1.5 Years
Research

6 years

Publications

Integrating Novel Biomarkers and Machine Learning for Early Detection and Stratification of Chronic Kidney Disease.

Expertise

Dr. Km. Saumya is currently serving as an Assistant Professor at Galgotias College of Pharmacy, Greater Noida, Uttar Pradesh. She holds a Ph.D. in Pharmaceutical Medicine (Division of Pharmacology) from the School of Pharmaceutical Education and Research, Jamia Hamdard University, New Delhi. She completed her M. Pharm. in Pharmacy Practice from NIPER Hajipur with an excellent academic record and earned her B. Pharm. from Banasthali Vidyapith, Rajasthan. She has 1.5 years of academic experience and 6 years of research experience. Her doctoral research focused on the evaluation of novel biomarkers such as periostin and galectin-3 for early detection and risk stratification of chronic kidney disease (CKD) and the assessment of health-related quality of life in CKD patients. She was also awarded with the Sun Pharma Scholarship during her Ph.D. program. Her research interests include biomarker discovery, machine learning and artificial intelligence in biomedical data analysis, clinical pharmacology, pharmacoepidemiology, Pharmacoeconomics, and clinical research, with a focus on improving early diagnosis, disease prediction, and therapeutic outcomes in chronic diseases.

Faculty Details