Priyanka Kumari

About

I’m a postdoctoral researcher at Albert Einstein College of Medicine focused on understanding and treating neurodegenerative diseases, particularly Alzheimer’s and related dementias.
My work uses objective measures of memory impairment, along with machine learning and statistical modeling, to improve clinical trial design and identify more meaningful endpoints. I collaborate with multidisciplinary teams and work with large-scale longitudinal data across both observational studies and clinical trials.
My goal is to help bridge the gap between data and better clinical outcomes.

Employment

• Albert Einstein College of Medicine Postdoctoral Researcher
  2024 - Present
• University of Liege PhD student
  2018 - 2024

Education

• University of Liege PhD
  2020 - 2023

Projects & Funding

Projects & funding information is unavailable.

Publications (16)

• Stages of objective memory impairment (SOMI) as a predictor of clinical progression in the A4 study
  The Journal of Prevention of Alzheimer's Disease 2026 DOI: 10.1016/j.tjpad.2026.100641
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• A case study on N-nitrosamine investigation in a marketed drug: from analytical procedure validation to risk mitigation decision
  FRONTIERS IN ANALYTICAL SCIENCE 2026 DOI: 10.3389/FRANS.2026.1772719
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• A case study on N-nitrosamine investigation in a marketed drug: From analytical procedure validation to risk mitigation decision
  Ssrn 2025 DOI: 10.2139/ssrn.5538163
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• Recent progress in the synthesis of C-S bond via sulfonyl hydrazides
  Journal of Sulfur Chemistry 2025 DOI: 10.1080/17415993.2024.2420796
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• Transfer Learning Approach to Multitarget QSRR Modeling in RPLC
  Journal of Chemical Information and Modeling 2024 DOI: 10.1021/acs.jcim.4c00608
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• The Osteoblast Transcriptome in Developing Zebrafish Reveals Key Roles for Extracellular Matrix Proteins Col10a1a and Fbln1 in Skeletal Development and Homeostasis
  Biomolecules 2024 DOI: 10.3390/biom14020139
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• Uncertainty management for In Silico screening of reversed-phase liquid chromatography methods for small compounds
  JOURNAL OF PHARMACEUTICAL AND BIOMEDICAL ANALYSIS 2024 DOI: 10.1016/J.JPBA.2024.116373
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• A multi-target QSRR approach to model retention times of small molecules in RPLC
  Journal of Pharmaceutical and Biomedical Analysis 2023 DOI: 10.1016/j.jpba.2023.115690
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• Quantitative Structure Retention-Relationship Modeling: Towards an Innovative General-Purpose Strategy
  Molecules 2023 DOI: 10.3390/molecules28041696
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• A pharmaceutical-related molecules dataset for reversed-phase chromatography retention time prediction built on combining pH and gradient time conditions
  Data in Brief 2022 DOI: 10.1016/j.dib.2022.108017
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