Molecular Fingerprinting by Single Cell Clone Analysis in Adverse Drug Reaction (ADR) Assessment

Anjan K Banerjee1

  • 1Medical Safety Solutions Ltd, Courtfield House, 21 Church Street, Market Deeping, Cambs PE6, 8AN UK.

Current Drug Safety
|July 28, 2021
PubMed

Insights

Single-cell RNA sequencing (scRNA-seq) offers a new way to understand adverse drug reactions (ADRs) by identifying specific cell clones. This molecular fingerprinting can improve drug safety and targeted treatments.

Area of Science:

  • Pharmacogenomics
  • Molecular Biology
  • Drug Safety

Background:

  • Adverse drug reactions (ADRs) causality is often based on epidemiology and signal detection.
  • Mechanistic evidence at the cellular level is less frequently utilized.
  • Individual patients can have distinct cell clones within organs, influencing ADR susceptibility.

Purpose of the Study:

  • To explore the application of single-cell RNA sequencing (scRNA-seq) for molecularly fingerprinting ADRs.
  • To distinguish between cell clones with differing susceptibilities to ADRs.
  • To propose a framework for ADR assessment using scRNA-seq and discuss regulatory implications.

Main Methods:

  • Utilizing single-cell RNA sequencing (scRNA-seq) techniques.
  • Molecularly fingerprinting ADRs by identifying Directly Expressed Genes (DEGs) within specific cell clones.
  • Applying scRNA-seq to biopsied/sampled tissues such as skin, liver, kidney, blood, and stem cells.

Main Results:

  • scRNA-seq enables molecular fingerprinting of serious ADRs, particularly in skin.
  • Identification of overexpressed DEGs within specific clones offers potential for targeted therapies.
  • scRNA-seq provides a molecular basis for screening therapeutic candidates for ADRs.

Conclusions:

  • scRNA-seq offers a novel approach to understanding ADR mechanisms at a single-cell level.
  • This technology can enhance pharmacovigilance and risk minimization strategies for medications.
  • Further considerations include cost-effectiveness, ADR frequency/severity, and population differences.