Data from: Single-cell perturbation atlas of PTB prevention candidate drugs

Preterm birth (PTB) is the leading cause of mortality in children under
five, yet effective preventive therapies are lacking. PTB’s multifactorial
nature, as well as the high cost and ethical challenges of pregnancy
clinical trials, hinder drug development efforts. Meanwhile, targeting
immune pathways that regulate labor timing is emerging as a promising
preventive strategy. We present Simulated Immune Modeling of Clinical
Outcomes (SIMCO), a prediction ensemble that integrates single-cell immune
perturbation modeling with outcome prediction to rapidly evaluate PTB
prevention candidate drugs. To train SIMCO, we generated a mass cytometry
perturbation atlas of 218 million leukocytes, capturing drug effects on
specific cell types and signaling pathways that differed between pregnant
and non-pregnant individuals. SIMCO accurately recapitulated the
single-cell modulation induced by nine repurposed candidate drugs. When
applied to an independent longitudinal pregnancy cohort, SIMCO simulated
each drug’s effect on gestational length, offering a scalable framework
for drug prioritization. Tetrahydrofolate, maprotiline, and the
combination of aspirin and lansoprazole emerged as top candidates for PTB
prevention, delaying labor onset in preterm samples by 9.2 (± 2.1), 9.2 (±
1.2), and 6.5 (± 1.8) days, respectively, primarily through enhanced mTOR
signaling in innate immune cells and attenuated JAK/STAT signaling in
naïve CD4⁺ T cells. This upload includes all raw .fcs files generated for
the single-cell perturbation atlas pre-gated into 28 cell types via manual
gating.