Drug-Drug Interactions

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ScreenShot: A Foundation Model for Few-Shot Combination Drug Screening
Aug 12, 2026Antoine de Mathelin, Christopher Tosh, Wesley TanseyDrug-Drug Interactions Clinical Prediction
Computational Oncology Memorial Sloan Kettering Cancer Center New York, NY 10065
GRAIN: Molecules Are Not the Right Granularity -- Active-Ingredient Modeling for Safe Medication Recommendation
Jul 30, 2026Juao Fan, Jinhan Li, Shengxin ZhuMedication Leaflet Drug-Drug Interactions
Guangdong Provincial Key Laboratory of Interdisciplinary Research and Application for Data Science, Beijing Normal–Hong Kong Baptist University, Zhuhai, China
Trivial Prompt Reframing Bypasses Safety Guardrails in Googleś MedGemma-4B
Jul 9, 2026Avi-ad Avraam BuskilaLarge Language Model Safety Attack-Success Rate
Department of Information Science and Applied Artificial Intelligence, Bar-Ilan University, Ramat Gan, Israel
Asymmetric Focal Loss Improves Graph Neural Network Prediction of Drug-Drug Interactions
Jul 8, 2026Faranak Hatami, Mousa MoradiAbsorption, Distribution, Metabolism, And Excretion Drug-Drug Interactions
Department of Chemistry, University of Illinois Chicago, Chicago, IL 60607, USA · Harvard Ophthalmology AI Lab, Schepens Eye Research Institute of Massachusetts Eye and Ear, Harvard Medical School, Boston, MA, USA
Optimizing Large Language Models for Causality Assessment in Pharmacovigilance: Developing a Performance Metric as Objective for Bayesian Hyperparameter Optimization
Jul 4, 2026Nicole Sonne Heckmann, Arnault-Quentin Vermillet, Søren Norlin Mølgaard +4Causal Reasoning Agreement
Department of Drug Design and Pharmacology, University of Copenhagen, Copenhagen, Denmark. · Safety Operations, Novo Nordisk, Søborg, Denmark. · Clinical Development Centre Denmark, Novo Nordisk, Søborg, Denmark. +1
CoFEND: A Cross-Modal Fusion End-to-End Network for Cold-Start Drug-Drug Interaction Prediction
Jul 3, 2026Di Wu, Hongyi Sun, Haichao Xu +3Drug-Drug Interactions Absorption, Distribution, Metabolism, And Excretion
DDIAgents: Mechanism-Conditioned Context Flow for Drug-Drug Interaction Prediction
Jun 30, 2026Zhenqian Shen, Yu Liu, Xiaoyi Fu +1Drug-Drug Interactions Mixture-Of-Agents
Department of Electronic Engineering, Tsinghua University Beijing, China · Institute of Biomedical Engineering, University of Oxford Oxford, United Kingdom · Division of Emerging Interdisciplinary Areas, Hong Kong University of Science and Technology Hong Kong, China
The Critical Role of Model Selection in Causal Inference: A Comparative Analysis of Classification Models within the InferBERT Framework for Pharmacovigilance
Jun 15, 2026Csaba Kiss, Roland Molontay, Gabriele PergolaCausal Inferences Model Selection
Department of Stochastics, Institute of Mathematics, Budapest University of Technology and Economics, Műegyetem rkp. 3., Budapest, H-1111, Hungary · Institute of Biostatistics and Network Science, Semmelweis University, Üllői út 26., Budapest, H-1085, Hungary · Department of Computer Science, University of Warwick, Coventry, CV4 7AL, UK
Applicability Condition Extraction for Therapeutic Drug-Disease Relations
Jun 12, 2026Guanting Luo, Noriki Nishida, Yuji Matsumoto +1Drug-Drug Interactions Biomedical Text
1The University of Osaka · 2RIKEN · 4Tohoku University +1
MARD: Mirror-Augmented Reasoning Distillation for Mechanism-Level Drug-Drug Interaction Prediction
Jun 10, 2026Mohammadreza Riyazat, Vian Lelo, Rameen Jafri +2Drug-Drug Interactions Pharmacokinetics
University of Guelph, Canada · York University, Canada · Vector Institute, Canada
Unsupervised Pattern Analysis in Japanese Veterinary Toxicology: A Regulatory-Compliant Framework for Cross-Species Risk Assessment
Jun 4, 2026Yukiko Kawakami, Mohammad Shirazi, Ryo Shimizuwa +3Drug-Drug Interactions Toxicity
Tohoku University Graduate School of Medicine, Sendai, Japan · Amirkabir University of Technology, Tehran, Iran · Tohoku University Graduate School of Pharmaceutical Sciences, Sendai, Japan
UniD $^3$ : A Knowledge Graph-Enhanced RAG Framework for Drug-Disease Discovery and Reasoning
May 31, 2026Qing Wang, Tianshi Liu, Minghao Zhou +5Biomedical Knowledge Graph Drug-Drug Interactions
Department of Health Outcomes and Biomedical Informatics, University of Florida, Florida, USA · Department of Hematology, H. Lee Moffitt Cancer Center and Research Institute, Florida, USA · Center for Bioinformatics and Computational Biology, Houston Methodist Research Institute, Houston, TX, USA +2
From Detection to Mechanism: Cross-Attention Graph Neural Networks Enable Drug-Drug Interaction Type Prediction An Ablation Study with Acetylsalicylic Acid Validation
May 27, 2026Juergen DietrichDrug-Drug Interactions Graph Neural Networks
Hypergraph Pattern Machine: Compositional Tokenization for Higher-Order Interactions
May 15, 2026Kyrie Zhao, Zehong Wang, Tianyi Ma +5Hypergraphs Drug-Drug Interactions
University of Notre Dame · Stanford University · Yale University +2
AIM-DDI: A Model-Agnostic Multimodal Integration Module for Drug-Drug Interaction Prediction
May 14, 2026Yerin Park, Sangseon LeeDrug-Drug Interactions
Department of Artificial Intelligence, Inha University
A Non-Destructive Methodological Framework for Modernizing Legacy Clinical Reporting Systems for AI-Driven Pharmacoinformatics: A SAS Case Study
May 13, 2026Jaime YanMedical Report Generation Drug-Drug Interactions
Harrisburg University of Science and Technology, Harrisburg, PA, USA
LLM-Guided Monte Carlo Tree Search over Knowledge Graphs: Composing Mechanistic Explanations for Drug-Disease Pairs
May 10, 2026Rishabh Jakhar, Michel Dumontier, Remzi CelebiReasoning Graphs Knowledge Graphs
Institute of Data Science, Department of Advanced Computing Sciences, Maastricht University, The Netherlands
Drug Synergy Prediction via Residual Graph Isomorphism Networks and Attention Mechanisms
Apr 23, 2026Jiyan Song, Wenyang Wang, Chengcheng Yan +2Drug-Drug Interactions Synergy
College of Sciences, Shihezi University, 221 North 4th Road, Shihezi, 832003, Xinjiang, China · School of Mathematics and Computational Science, Xiangtan University, North 2nd Ring Road, Xiangtan, 411105, Hunan, China
RexDrug: Reliable Multi-Drug Combination Extraction through Reasoning-Enhanced LLMs
Mar 9, 2026Zhijun Wang, Ling Luo, Dinghao Pan +4Drug-Drug Interactions Relation Extraction
School of Computer Science and Technology, Dalian University of Technology, No.2 Linggong Road, Ganjingzi District, Liaoning 116024, China · Cancer Hospital of Dalian University of Technology, Liaoning Cancer Hospital & Institute, No.44 Xiaoheyan Road, Dadong District, Liaoning 110042, China
From Literature to Hypotheses: An AI Co-Scientist System for Biomarker-Guided Drug Combination Hypothesis Generation
Feb 28, 2026Raneen Younis, Suvinava Basak, Lukas Chavez +1Hypothesis-Driven Model Expansion Drug-Drug Interactions
Peter L. Reichertz Institute for Medical Informatics (PLRI), Hannover Medical School · Lower Saxony Center for Artificial Intelligence and Causal Methods in Medicine (CAIMed) · Sanford Burnham Prebys (SBP) Medical Discovery Institute
Multimodal AI predicts clinical outcomes of drug combinations from preclinical data
Mar 4, 2025Yepeng Huang, Xiaorui Su, Varun Ullanat +10Drug-Drug Interactions Clinical Prediction
Department of Biomedical Informatics, Harvard Medical School, Boston, MA · Program in Biological and Biomedical Sciences, Harvard Medical School, Boston, MA · Harvard College, Cambridge, MA +8
DrugAgent: Reliable Multi-Agent Integration of Conflicting Biomedical Evidence for Drug-Target Interaction Assessment
Aug 23, 2024Yoshitaka Inoue, Tianci Song, Xinling Wang +3Drug-Drug Interactions Drug Discovery
Department of Computer Science and Engineering, University of Minnesota, Minneapolis, MN, USA · Computational Biology Branch, National Library of Medicine, Bethesda, MD, USA · Khoury College of Computer Sciences, Northeastern University, Arlington, VA, USA +2

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ScreenShot: A Foundation Model for Few-Shot Combination Drug Screening

Antoine de Mathelin, Christopher Tosh, Wesley Tansey

Computational Oncology Memorial Sloan Kettering Cancer Center New York, NY 10065

Drug-Drug Interactions Clinical Prediction Combinations Foundation Model

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Treating patients with combinations of drugs reduces the risk of resistance to any individual drug. Finding effective combinations is difficult because the large search space makes combinatorial screens prohibitively expensive, time consuming, and often technically infeasible. Predictive models can fill this gap, yet existing methods typically require molecular profiling of each sample and per-cohort training, limiting their applicability when time and tissue are scarce. To address this challenge, we introduce ScreenShot, a hierarchical transformer pretrained on 40 drug screening datasets covering 3,700 drugs and 6,000 biological samples, whose architecture mirrors the nested structure of screening data. Given a few-shot context of observations from a new patient, ScreenShot predicts the response of the sample to combination therapies through in-context learning, operating directly on functional measurements with no fine-tuning and no molecular profiling. On four held-out datasets, ScreenShot outperforms all baselines in both prediction accuracy and identification of selectively effective treatments. ScreenShot's internal representations are directly useful for experimental design: we use them to drive a weighted k-means++ active learning strategy that selects which experiments to run, achieving the same hit detection as uniform screening with a third of the budget. Source code and interactive dashboard: https://github.com/tansey-lab/screenshot.

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