Skip to the main content

Original scientific paper

https://doi.org/10.5562/cca4190

AI-Enabled Drug Candidates and the Evolving Role of CROs

Adrijana Vinter ; Selvita Ltd., Prilaz baruna Filipovića 29, 10000 Zagreb, Croatia *

* Corresponding author.


Full text: english pdf 1.832 Kb

page P1-P8

downloads: 1.297

cite


Abstract

The integration of artificial intelligence (AI) into early-stage pharmaceutical research is fundamentally reshaping the landscape of drug discovery. From generative chemistry and predictive modelling to phenotypic screening and target identification, AI is accelerating timelines, reducing attrition, and enabling a new class of clinical candidates. This paradigm shift has significant implications for contract research organizations (CROs), which are evolving from traditional service providers into strategic partners in data-driven discovery. In this paper, we examine the rise of AI-native drug candidates, analyse their journey from code to clinic, and explore how contract research organizations (CROs) are adapting their infrastructure, capabilities, and business models to remain competitive. Through case studies of companies, the transformative potential of CRO–AI biotech collaborations is illustrated. Also addressed were the regulatory, ethical, and operational challenges facing CROs, and a forward-looking perspective was provided on how they can capture value in an AI-enabled future.

Keywords

artificial intelligence; drug discovery; contract research organizations; AI-designed drug candidates; generative models; CRO–Biotech collaboration; machine learning; pharmaceutical innovation

Hrčak ID:

343391

URI

https://hrcak.srce.hr/343391

Publication date:

17.1.2026.

Visits: 1.821 *