NeurIPS 2025 Workshop on AI Virtual Cells and Instruments: A New Era in Drug Discovery and Development

Accepted papers (41)

Fetched from OpenReview (v2) on 2026-06-10.

1. A Scalable Latent Diffusion Model for Single-Cell Gene Expression Data

   Giovanni Palla, Sudarshan Babu, Payam Dibaeinia, Donghui Li, Aly A Khan, Theofanis Karaletsos, Jakub M. Tomczak

2. Active Causal Hypothesis Testing for AI-Guided Drug Target Discovery

   David Scott Lewis, Enrique Zueco

3. BEACON: Bayesian Contrastive Learning for Single-Cell Gene Regulatory Inference

   Yunwei Zhao, Ankit Bhardwaj, Lakshmi Subramanian

4. Beyond Atoms: Evaluating Electron Density Representation for 3D Molecular Learning

   Patricia Adriana Suriana, Joshua A Rackers, Ewa Nowara, Pedro O. Pinheiro, Vishnu Sresht, John M Nicoludis

5. Chem42∗: a Family of chemical Language Models for Target-aware Ligand Generation

   Maryam Nadeem, Aahan Singh, Engin Tekin, Nancy A. ElNaker, Mohammad Amaan Sayeed, Natalia Vassilieva, Boulbaba Ben Amor

6. Constrained Molecular Generation with Discrete Diffusion for Drug Discovery

   Michael Cardei, Jacob K Christopher, Bhavya Kailkhura, Thomas Hartvigsen, Ferdinando Fioretto

7. Context-aware geometric deep learning for RNA sequence design

   Parth Bibekar, Lucien F. Krapp, Matteo Dal Peraro

8. Cross-Species Graph Neural Network for Translating Animal Disease Resistance to Human Drug Targets

   Deek Guruge, Michelle M Li, Natalie DeForest, Phil McNamara, Manashvi Borad, Linda B. Goodman

9. D-Flow: Multi-modality Flow Matching for D-peptide Design

   Fang Wu, Shuting Jin, Xiangru Tang, Junlin Xu, James Zou, Mark Gerstein

10. DiffDAG: Diffusion DAG Models for modeling Gene Perturbations

    Shiv Shankar

11. Domain Knowledge Infused Conditional Generative Models for Accelerating Drug Discovery

    Bing Xu Hu, Jong-Hoon Park, Anita Layton, Young-Rae Cho, Sun Sun, Helen Hong Chen

12. Early Prediction of Overall Survival in Oncology Trials Using Tumor Dynamic Neural-ODE

    Gengbo Liu, Victor Poon, Omid Bazgir, Phyllis Chan, Kenta Yoshida, Chanu Pascal

13. FocusMR: An Attention-Based Single-Cell Mendelian Randomization Framework to Map Cellular Contexts at Candidate Genes

    Martin Meinel, Jan P. Engelmann, Michael Patrick Menden, Theofanis Karaletsos, Francesco Paolo Casale

14. FragmentGPT: A Unified GPT Model for Fragment Growing, Linking, and Merging in Molecular Design

    Xuefeng Liu, Songhao Jiang, Qinan Huang, Tinson Xu, Ian Foster, Mengdi Wang, Hening Lin, Rick Stevens

15. Gene42: Long-Range Genomic Foundation Model With Dense Attention

    Kirill Vishniakov, Boulbaba Ben Amor, Engin Tekin, Nancy A. ElNaker, Karthik Viswanathan, Aleksandr Medvedev, Aahan Singh, Maryam Nadeem, Mohammad Amaan Sayeed, Praveenkumar Kanithi, Tiago Magalhaes, Natalia Vassilieva, Dwarikanath Mahapatra, Marco AF Pimentel, Shadab Khan

16. GRASP: Graph Reasoning Agents for Systems Pharmacology with Human-in-the-Loop

    Omid Bazgir, Mohammad Jafarnejad, Vineeth Manthapuri, Ilia Rattsev

17. High-Throughput Protein Perturbation Screens with AI-Designed Degraders

    Lin Zhao, Aastha Pal, Tong Chen, Pranam Chatterjee

18. HyperDiffusionFields (HyDiF): Diffusion-Guided Hypernetworks for Learning Implicit Molecular Neural Fields

    Sudarshan Babu, Phillip Lo, Xiao Zhang, Aadi Srivastava, Ali Davariashtiyani, Jason Perera, Michael Maire, Aly A Khan

19. ImmuneNet: Composition-Aware Quantification of Adaptive Lymphocytes in High-Grade Serous Ovarian Cancer

    Jaelyn S. Liang

20. Improving Classification of Cell Types in Acute Myeloid Leukemia with Self-guided Masking Technique

    Amirreza Naziri, Arash Asgari, Eleftherios Sachlos, Aijun An, Laleh Seyyed-Kalantari

21. Label-free biochemical imaging of neural organoids via deep learning-enhanced Raman microspectroscopy

    Dimitar Georgiev, Ruoxiao Xie, Daniel Reumann, Xiaoyu Zhao, Álvaro Fernández-Galiana, Mauricio Barahona, Molly M. Stevens

22. Learning from B Cell Evolution: Adaptive Multi-Expert Diffusion for Antibody Design via Online Optimization

    Peng Qiu, Hanqi Feng, Yiran Tao, Meng-Chun Zhang, You Fan, Jingtao Xu, Barnabas Poczos

23. LLM-Integrated Representative Path Selection for Context-Aware Drug Repurposing on Biomedical Knowledge Graphs

    Haerin Song, Dongmin Bang, Bonil Koo, Sun Kim, Sangseon Lee

24. LLMs as Virtual Instruments for Drug Formulation

    Michael Craig, Gary Tom, Pauric Bannigan, Christine Allen, Riley Hickman

25. MoAgent: A Hypothesis-Driven Multi-Agent Framework for Drug Mechanism of Action Discovery

    Jun Hyeong Kim, Seokhyun Moon, Seonghwan Kim, Junhyeok Jeon, Taein Kim, Jisu Seo, Songmi Kim, Woo Youn Kim

26. Mol-SGCL: Molecular Substructure-Guided Contrastive Learning for Out-of-Distribution Generalization

    Andrew Zhou, Yasha Ektefaie, Maha Farhat

27. Monte Carlo Tree Diffusion with Multiple Experts for Protein Design

    Xuefeng Liu, Mingxuan Cao, Songhao Jiang, Xiao Luo, Xiaotian Duan, Mengdi Wang, Tobin R. Sosnick, Jinbo Xu, Rick L. Stevens

28. OligoGym: Curated Datasets and Benchmarks for Oligonucleotide Drug Discovery

    Rachapun Rotrattanadumrong, Carlo De Donno

29. PatchDNA: A Flexible and Biologically-Informed Alternative to Tokenization for DNA

    Alice Del Vecchio, Chantriolnt-Andreas Kapourani, Abdullah M Athar, Agnieszka Dobrowolska, Andrew Anighoro, Benjamin Tenmann, Lindsay Edwards, Cristian Regep

30. Patient-level prediction from single-cell data using attention-based multiple instance learning with regulatory priors

    Kristin C. Y. Tsui, Kameron B. Rodrigues, Xianghao Zhan, Yiyun Chen, Kelvin C. Mo, Crystal L. Mackall, David B Miklos, Olivier Gevaert, Zinaida Good

31. Perturbation-aware representation learning for in vivo genetic screens

    Florian Hugi, Tanmay Tanna, Randall J Platt, Gunnar Ratsch

32. Predicting cellular responses to perturbation across diverse contexts with State

    Abhinav Adduri, Dhruv Gautam, Beatrice Bevilacqua, Alishba Imran, Rohan Shah, Mohsen Naghipourfar, Noam Teyssier, Rajesh Ilango, Sanjay Nagaraj, Chiara Ricci-Tam, Chris Carpenter, Vishvak Subramanyam, Aidan Winters, Mingze Dong, Sravya Tirukkovalur, Jeremy Sullivan, Brian Plosky, Basak Eraslan, Nick Youngblut, Jure Leskovec, Luke Gilbert, Silvana Konermann, Patrick D Hsu, Alexander Dobin, Dave Burke, Hani Goodarzi, Yusuf H Roohani

33. Probing Functional Plasticity in Peptide–Protein Interaction with Minimal Data

    Pouriya Bayat, Spencer Perkins, Sebastian Clancy, Sahil Swapnesh Patel, Richard Fei Yin, Krištof Bozovičar, Idorenyin IWE, Serena Singh, Sepehr Bayat, Vivian White, Matthew Xie, Sean Palter, Mohammad Simchi, Ilan Yaniv Zeisler, Keith Pardee

34. Prot42 : a Novel Family of Protein Language Models for Target-aware Protein Binder Generation

    Mohammad Amaan Sayeed, Engin Tekin, Maryam Nadeem, Nance A. Elnaker, Aahan Singh, Natalia Vassilieva, Boulbaba Ben Amor

35. rbio1 - training scientific reasoning LLMs with biological world models as soft verifiers

    Ana-Maria Istrate, fausto milletari, Fabrizio Castrotorres, Jakub M. Tomczak, Michaela Torkar, Donghui Li, Theofanis Karaletsos

36. Refine Drugs, Don’t Complete Them: Uniform-Source Discrete Flows for Fragment-Based Drug Discovery

    Benno Kaech, Luis Wyss, Karsten Borgwardt, Gianvito Grasso

37. SigSpace: an LLM-based agent for drug response signature interpretation

    Rohit Khurana, Ishita Mangla, Giovanni Palla, Siddhant Sanghi, Daniele Merico

38. Smiles2Dock: a large-scale dataset for ML-based docking score prediction using AlphaFold structures

    Thomas Le Menestrel, Manuel Rivas Cruz

39. Toward a Coherent Virtual Cell Model: Probing Biological World-Model Coherence in Transcriptomic Foundation Models

    Noa Moriel, Yishai Shimoni, Michal Rosen-Zvi, Michael Danziger

40. Virtual Cells as Causal World Models: A Perspective on Evaluation

    Tiffany Callahan, Zane Beckwith, Thomas Merth, Constantijn van der Poel, Adam Lewis, Pablo Lemos

41. Why Pool When You Can Flow? Active Learning with GFlowNets

    Renfei Zhang, Mohit Pandey, Artem Cherkasov, Martin Ester