mlsanityData to 14 Oct 2026

scPPDM: A Diffusion Model for Single-Cell Drug-Response Prediction

arXiv 2510.11726 ↗First posted 8 Oct 2025q-bio.QM cs.LGcited by 6

On the map: Diffusion models → Flow matching, time series and science

Abstract (arXiv)

This paper introduces the Single-Cell Perturbation Prediction Diffusion Model (scPPDM), the first diffusion-based framework for single-cell drug-response prediction from scRNA-seq data. scPPDM couples two condition channels, pre-perturbation state and drug with dose, in a unified latent space via non-concatenative GD-Attn. During inference, factorized classifier-free guidance exposes two interpretable controls for state preservation and drug-response strength and maps dose to guidance magnitude for tunable intensity. Evaluated on the Tahoe-100M benchmark under two stringent regimes, unseen covariate combinations (UC) and unseen drugs (UD), scPPDM sets new state-of-the-art results across log fold-change recovery, delta correlations, explained variance, and DE-overlap. Representative gains include +36.11%/+34.21% on DEG logFC-Spearman/Pearson in UD over the second-best model. This control interface enables transparent what-if analyses and dose tuning, reducing experimental burden while preserving biological specificity.

Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). Placed in Flow matching, time series and science, one of 14 directions in Diffusion models. Builds on 14 of its 44 references that are in the map. First posted on arXiv 8 Oct 2025.

Builds on

14 of 44 references.

Closest ancestors · 1

Same direction, newest first

  1. 2024scDiffusion: conditional generation of high-quality single-cell data using diffusion model8 Jan

Other references · 13

  1. 2017Attention Is All You Needcited by 60,361
  2. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,863
  3. 2020A Simple Framework for Contrastive Learning of Visual Representationscited by 12,049
  4. 2020Denoising Diffusion Implicit Modelscited by 9,781
  5. 2020Score-Based Generative Modeling through Stochastic Differential Equationscited by 9,122
  6. 2018Representation Learning with Contrastive Predictive Codingcited by 7,777
  7. 2022Scalable Diffusion Models with Transformerscited by 6,054
  8. 2022Classifier-Free Diffusion Guidancecited by 5,847
  9. 2023Adding Conditional Control to Text-to-Image Diffusion Modelscited by 5,503
  10. 2017FiLM: Visual Reasoning with a General Conditioning Layercited by 2,333
  11. 2023T2I-Adapter: Learning Adapters to Dig out More Controllable Ability for Text-to-Image Diffusion Modelscited by 1,351
  12. 2022Compositional Visual Generation with Composable Diffusion Modelscited by 624
1 more
  1. 2022Predicting Cellular Responses to Novel Drug Perturbations at a Single-Cell Resolutioncited by 45

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 6.

6 papers.

  1. 2026STRAND: Sequence-Conditioned Transport for Single-Cell Perturbationscited by 4
  2. 2026OCOO-T : A Simple and Scalable Virtual Cell Model for Transcriptional Perturbation Response Predictioncited by 1
  3. 2026Stochastic Flow Map for Count Datacited by 1
  4. 2026AblateCell: A Reproduce-then-Ablate Agent for Virtual Cell Repositoriescited by 0
  5. 2026PhAME: Phenotype-Aware Molecular Editing via Latent Diffusioncited by 0
  6. 2026Modeling Cell-Cycle-Aware Single-Cell Drug Perturbation Responsescited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025Doloris: Dual Conditional Diffusion Implicit Bridges with Sparsity Masking Strategy for Unpaired Single-Cell Perturbation Estimation
  2. 2026scDFM: Distributional Flow Matching Model for Robust Single-Cell Perturbation Prediction
  3. 2026Genotype-Conditioned Molecular Generation via Evidence-Grounded Multi-Objective Latent Perturbation in Diffusion Models
  4. 2024scRDiT: Generating single-cell RNA-seq data by diffusion transformers and accelerating sampling
  5. 2026PerturbDiff: Functional Diffusion for Single-Cell Perturbation Modeling
  6. 2026Generalizable single-cell perturbation response prediction using energy-guided flow matching
  7. 2026Reading the Cell, Designing the Cure: Perturbation-Conditioned Molecular Diffusion for Function-Oriented Drug Design
  8. 2026Improving scDiffusion with Sparsity-Biased Classifier-Free Guidance