Related Experiment Video

Updated: Aug 6, 2026

Dual CRISPR-Interference Strategy for Targeting Synthetic Lethal Interactions Between Non-Coding RNAs in Cancer Cells
07:23

Dual CRISPR-Interference Strategy for Targeting Synthetic Lethal Interactions Between Non-Coding RNAs in Cancer Cells

Published on: May 30, 2025

Reversing cancer cell behavior using AI-guided CRISPR and quantum nanobiology: a systems-based approach to epigenetic

Bakr Ahmed Taha1,2, Ali J Addie3, Adawiya J Haider4

  • 1Photonics Technology Lab, Department of Electrical, Electronic and Systems Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, UKM Bangi, Malaysia. dra@ukm.edu.my.

Gene Therapy
|July 16, 2026
PubMed

Insights

This study explores combining quantum biology, AI, and nanomaterials to enhance CRISPR gene editing for cancer therapy. The goal is to precisely reverse malignant phenotypes by improving delivery and targeting cancer genetics.

Area of Science:

  • Biophysics
  • Computational Biology
  • Nanomedicine

Background:

  • Cancer treatment is limited by tumor genetic complexity and phenotypic plasticity.
  • CRISPR-Cas gene editing faces challenges in specificity, off-target effects, and adapting to tumor heterogeneity.

Purpose of the Study:

  • To investigate integrating quantum biological processes, artificial intelligence (AI), and nanomaterials for advanced CRISPR gene editing.
  • To improve the precision and efficacy of gene editing in modulating or reversing malignant cancer phenotypes.

Main Methods:

  • Utilizing quantum machine learning (QML) to simulate quantum biological processes in DNA repair and enzyme activity.
  • Employing AI-powered optimization to guide CRISPR editing within oncogenic signaling networks for targeted phenotypic reversal.
  • Leveraging nanomaterials (graphene, gold nanoparticles, lipid vectors) for biocompatible delivery of CRISPR systems to the tumor microenvironment.

Main Results:

  • Hypothesized partial restoration of homeostatic gene-expression states in experimental cancer models.
  • Demonstrated a potential integrated strategy combining quantum-informed AI, CRISPR, and nanomaterial delivery.

Conclusions:

  • The proposed integrated strategy offers a novel approach beyond tumor suppression towards controlled modulation of malignant cell states.
  • Substantial preclinical and clinical validation is required to translate this approach into future cancer therapies.

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