Skip to main content
Menu
gated page cost effective hero
Article

When less is more: Cost-effective application of primary cell models in drug discovery through spheroid miniaturization

Using primary human cells cultured in 3D systems early in drug discovery provides greater physiological relevance than traditional cell lines, enabling more predictive assessments of efficacy and toxicity. However, cost and availability challenges have limited their broader adoption.

Revvity is part of the Nanoscale Drug Testing consortium which unites academia, pharmaceutical companies, and technology providers to improve the predictive power of preclinical research models. The consortium is pioneering methods to miniaturize 3D cell models into mini-spheroid systems, aiming to establish sustainable workflows that enable broader use of human-derived cells earlier in the discovery process.

In this expert interview, you’ll discover:

  • Insights from project leaders at Karolinska Institutet, AstraZeneca, and GSK
  • How miniaturization can overcome limitations of primary cells, including cost, availability, and scalability
  • The consortium’s strategic approach, including culturing methods, functional characterization, and cross-site validation
  • How Cell Painting is being used to capture multiparametric data, supporting large-scale, human-relevant screening workflows
  • Future plans to expand donor diversity for better global representation

For research use only. Not for use in diagnostic procedures.

To view the full content please answer a few questions

By submitting my personal data, I acknowledge
that Revivify and its affiliates (“Company”) will process my personal data provided above consistent with the Company’s Privacy Policy (available here and here)

CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.

Download Resource

When less is more: Cost-effective application of primary cell models in drug discovery through spheroid miniaturization

Revvity AI Assistant Beta