Language Interaction Network for Clinical Trial Approval Estimation

TL;DR

This paper introduces the Language Interaction Network (LINT), a novel text-based model for predicting clinical trial outcomes, especially for biologics, achieving high ROC-AUC scores across trial phases.

Contribution

LINT is a new approach that predicts trial success using only free-text descriptions, addressing challenges with biologics data and expanding beyond traditional molecular-based methods.

Findings

LINT achieved ROC-AUC scores of 0.770, 0.740, and 0.748 for phases I, II, and III.

The model effectively predicts outcomes for biologic interventions.

It demonstrates the potential of text-based models in clinical trial outcome prediction.

Abstract

Clinical trial outcome prediction seeks to estimate the likelihood that a clinical trial will successfully reach its intended endpoint. This process predominantly involves the development of machine learning models that utilize a variety of data sources such as descriptions of the clinical trials, characteristics of the drug molecules, and specific disease conditions being targeted. Accurate predictions of trial outcomes are crucial for optimizing trial planning and prioritizing investments in a drug portfolio. While previous research has largely concentrated on small-molecule drugs, there is a growing need to focus on biologics-a rapidly expanding category of therapeutic agents that often lack the well-defined molecular properties associated with traditional drugs. Additionally, applying conventional methods like graph neural networks to biologics data proves challenging due to their complex nature. To address these challenges, we introduce the Language Interaction Network (LINT), a novel approach that predicts trial outcomes using only the free-text descriptions of the trials. We have rigorously tested the effectiveness of LINT across three phases of clinical trials, where it achieved ROC-AUC scores of 0.770, 0.740, and 0.748 for phases I, II, and III, respectively, specifically concerning trials involving biologic interventions.