In-vitro assays for immuno-oncology drug efficacy assessment and screening for personalized cancer therapy: scopes

Md Marufur Rahman1,2, Greg Wells1, Juha K Rantala1,3

  • 1Sheffield Ex vivo Group, Division of Clinical Medicine, School of Medicine & Population Health, University of Sheffield, Sheffield, UK.

Abstract

Insights

Personalized cancer immunotherapy requires effective in-vitro assays for drug screening. This review compares platforms like organoids and cancer-on-a-chip, highlighting their potential for predicting treatment efficacy.

Area of Science:

  • Oncology
  • Immunology
  • Biotechnology

Background:

  • Immunotherapy has transformed cancer treatment but shows variable patient responses.
  • Tumor microenvironment complexity and patient heterogeneity necessitate personalized approaches.
  • In-vitro assays are crucial for assessing cancer drug efficacy and predicting treatment outcomes.

Purpose of the Study:

  • To review and comparatively analyze in-vitro platforms for personalized immunotherapy drug screening.
  • To evaluate the suitability, high-throughput capacity, and clinical translatability of different assays.
  • To discuss end-point analysis strategies for optimizing experimental design in immunotherapy efficacy prediction.

Main Methods:

  • Comparative analysis of various in-vitro assays (2D models, organoid co-cultures, cancer-on-a-chip).
  • Evaluation of assay construction strategies, advantages, and limitations.
  • Discussion of image-based assays and their potential and challenges.

Main Results:

  • In-vitro platforms offer diverse insights into personalized immunotherapy efficacy.
  • Image-based assays excel in capturing cellular details but face challenges like background noise and lengthy experiments.
  • Significant improvements and validation are needed for clinical application.

Conclusions:

  • Optimizing in-vitro assays is critical for advancing personalized immunotherapy.
  • Further research and clinical trials are essential to validate and refine these platforms for real-world use.
  • Standardized end-point analysis will enhance the predictive power of these assays.

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