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The Align Foundation

The Align Foundation

254 posts

The Align Foundation

@Align_Bio

Improving life science with programmable experiments. 🧬 🤖 Home of the Protein Engineering Tournament & Open Datasets Initiative

Joined January 2022

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The Align Foundation
@Align_Bio
19h
🧬 Proposal spotlight: predicting resistance before it emerges in a patient. When a patient turns from susceptible to resistant mid-treatment, is it new mutation or reinfection? We'd build a prospective, multi-site LMIC cohort (an ACORN extension) with paired WGS to predict it,
zenodo.org
Predicting treatment-emergent antimicrobial resistance at the patient level in LMICs
Resistance that emerges within a patient during treatment is clinically devastating but poorly predicted, and the evidence that it is foreseeable from routine infection histories comes almost...
The Align Foundation
@Align_Bio
Aug 25
🧬 Proposal spotlight: flagging antibiotic liver toxicity before synthesis. Toxicity models trained on typical drugs stumble on antibiotics. We'd build the first matched antibiotic dataset across liver cell lines and organoids, then predict hepatotoxicity and its mechanism from
zenodo.org
Closing the Antibiotic Discovery Gap: AI-Enabled Mechanistic Toxicity Prediction
Toxicity is a leading cause of antibiotic attrition, yet general-purpose toxicity prediction platforms perform poorly on antibacterial compounds, which occupy a distinct region of physicochemical...
The Align Foundation
@Align_Bio
Aug 20
🧬 Proposal spotlight: personalized antibiotic dosing for kids. Start by extending KidsCalc, a validated vancomycin dosing tool, beyond Australia. Then build a model predicting outcomes, toxicity, and resistance emergence, so dosing adapts to each child. The gap: the data
zenodo.org
Data to Dose: AI-Guided Validation of Paediatric Antibiotic Regimens and Their Link to Efficacy and...
Paediatric antibiotic dosing is largely extrapolated from adult pharmacokinetic data, and the model-informed dosing tools that improve on it, such as the KidsCalc vancomycin calculators, are develo...
The Align Foundation
@Align_Bio
Aug 18
🧬 Proposal spotlight: getting drugs into Gram-negatives. Their outer membrane is the problem: will a compound get in, and will it stay in? We'd build an LC-MS/MS accumulation dataset across E. coli, A. baumannii, and P. aeruginosa, using active learning to pick the most
zenodo.org
Predicting permeability and efflux of antibiotic compounds
Whether a compound penetrates Gram-negative bacteria and escapes efflux remains a major bottleneck in antibiotic discovery, and existing predictive rules and models are built largely from E. coli...
The Align Foundation
@Align_Bio
Aug 13
🧬 Proposal spotlight: predicting quantitative MIC straight from a genome. Resistance is shaped by genes, mutations, copy number, and epistasis. We'd build species-specific MIC-from-WGS models across ~10 WHO priority pathogens, on globally diverse isolates so predictions hold up
zenodo.org
Predicting Quantitative MIC from Whole Genome Sequencing
Machine-learning models that predict antimicrobial minimum inhibitory concentrations (MICs) from whole-genome sequencing (WGS) are currently built mostly for single species and trained on geographi...

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