plugin/skills/tooluniverse-drug-synergy/SKILL.md
Drug-combination synergy analysis — quantify whether two drugs together are synergistic, additive, or antagonistic using the standard reference models (Bliss independence, HSA / highest single agent, Loewe additivity, ZIP, and the Chou-Talalay Combination Index). Use when you have measured single-drug and combination effects (inhibition/viability) and need a synergy score. Explains which model to use, what data each one needs, and how to read the score. NOT for looking up pre-computed synergy in a database (use the SYNERGxDB tool / cell-line-profiling skill).
npx skillsauth add mims-harvard/tooluniverse tooluniverse-drug-synergyInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Decide whether a two-drug combination does more than expected (synergy), exactly as expected (additivity), or less (antagonism) — and pick the right reference model for the data you have.
"Synergy" only means something relative to a null model of additivity, and the models define additivity differently — so the first decision is which model, driven by what data you measured.
| You measured… | Use model | Tool | Input |
|---|---|---|---|
| Single effects of A, B, and A+B at one dose pair | Bliss | DrugSynergy_calculate_bliss | effect_a, effect_b, effect_combination (each a fraction 0–1) |
| Effects of A, B, A+B across several dose points | HSA | DrugSynergy_calculate_hsa | effects_a, effects_b, effects_combo (arrays) |
| Single-agent dose-response curves + one combination point | Loewe | DrugSynergy_calculate_loewe | doses_a_single/effects_a_single, doses_b_single/effects_b_single, dose_a_combo, dose_b_combo, effect_combo |
| Single-agent dose-response + combo point, want Chou-Talalay CI | Combination Index | DrugSynergy_calculate_ci | same as Loewe + assumption |
| A full dose × dose viability matrix | ZIP | DrugSynergy_calculate_zip | doses_a, doses_b, viability_matrix (% , 0–100) |
Effects must be on a consistent inhibition scale. Bliss/HSA/Loewe expect fractional inhibition
0–1(0 = no effect, 1 = complete kill). If your data is % viability, convert:inhibition = 1 − viability/100. ZIP takes the viability matrix in % directly. Mixing scales is the most common error.
| Model | Null (additive) expectation | Best when |
|---|---|---|
| Bliss independence | drugs act independently: E_exp = E_a + E_b − E_a·E_b | different mechanisms; quick single-point screen |
| HSA (highest single agent) | combo should beat the better single agent: E_exp = max(E_a, E_b) | conservative "does it beat monotherapy?" question |
| Loewe additivity | a drug combined with itself = additive (dose equivalence) | same/similar mechanism; needs dose-response |
| ZIP | combines Bliss + Loewe; potency shift of one drug's curve by the other | dose-matrix screens (the SynergyFinder default) |
| Chou-Talalay CI | CI<1 synergy, =1 additive, >1 antagonism (median-effect) | classic isobologram-style analysis with dose-response |
There is no single "correct" model — state which one you used. Bliss and Loewe genuinely disagree for some combinations (that's expected, not an error); reporting two models (e.g. Bliss + HSA, or Loewe + ZIP) is good practice.
# Bliss (single dose pair, fractional inhibition)
tu run DrugSynergy_calculate_bliss '{"operation":"calculate_bliss",
"effect_a":0.4,"effect_b":0.3,"effect_combination":0.7}'
# -> expected 0.58, bliss_synergy_score 0.12, "Strong synergy"
scripts/synergy_reference.py computes the Bliss, HSA, and Loewe-style expected combination effects side-by-side from one dose pair, so you can see at a glance whether the models agree before running the full tools.
For Bliss/HSA/Loewe/ZIP, the synergy score is (observed − expected) (often ×100):
| Score (fractional, ×100 scale) | Call | |---|---| | > +10 | synergy | | −10 to +10 | additive (no meaningful interaction) | | < −10 | antagonism |
For Combination Index (Chou-Talalay): CI < 1 = synergy, CI = 1 additive, CI > 1 antagonism (note the opposite direction — lower is more synergistic).
tooluniverse-dose-response — fit the single-agent IC50/EC50 curves that Loewe/CI/ZIP need.tooluniverse-cell-line-profiling — look up pre-computed combination synergy (SYNERGxDB).tooluniverse-drug-repurposing / tooluniverse-network-pharmacology — rationale for combinations.tools
Post-market safety surveillance and recall/adverse-event RETRIEVAL across the full spectrum of FDA-regulated products that are NOT covered by the drug-AE signal skills: medical devices, food / dietary supplements / cosmetics, veterinary drugs, and drug supply (shortages). Orchestrates openFDA endpoints (MAUDE device adverse events + device recalls + 510(k), CAERS food/supplement/ cosmetic adverse events, veterinary adverse events, drug shortages, and cross-product enforcement/recall reports). USE WHEN the user asks: "are there adverse events for [device / pacemaker / infusion pump / insulin pump]", "device recalls for [firm/product]", "supplement / vitamin / cosmetic adverse reactions", "is [drug] in shortage", "what injectables are on shortage", "veterinary / animal adverse events for [drug] in [dog/cat/horse]", "food recall for listeria", "MAUDE report for [device]", "CAERS reactions for [brand]". DO NOT USE for drug adverse-event SIGNAL detection or disproportionality (PRR / ROR / IC) or drug-AE association scoring — that is `tooluniverse-pharmacovigilance` / `tooluniverse-adverse-event-detection`. This skill is multi-product surveillance and retrieval, not drug-AE statistical signal mining.
tools
--- name: tooluniverse-phewas description: Cross-ancestry / cross-biobank phenome-wide association (PheWAS) and replication. Given ONE variant (rsID) or ONE gene, look up every phenotype it associates with across European/UK (UKB-TOPMed), Finnish (FinnGen), Japanese (BioBank Japan), and Taiwanese (TPMI) biobanks, plus exome-wide gene-burden PheWAS (Genebass), then judge whether an association replicates across ancestries or is population-specific. Use whenever the user asks "what else is this va
tools
Dereplicate a putative natural product and assign its chemical taxonomy. Use to answer "is [compound] a known natural product", "what microbe/organism produces [compound]", "what chemical class is [compound]", "dereplicate this metabolite (by formula/exact mass/InChIKey/SMILES)", or "classify this molecule into ChemOnt". Searches NPAtlas for known microbial natural products (producing organism + literature reference), assigns the ChemOnt kingdom→superclass→class→subclass hierarchy via ClassyFire, resolves systematic IUPAC names to structure via OPSIN, and cross-references identity in PubChem. NOT for general drug/compound identity or ADMET (use tooluniverse-chemical-compound-retrieval / tooluniverse-small-molecule-discovery) and NOT for metabolomics pathway/enrichment analysis (use tooluniverse-metabolomics skills).
tools
Genome-ASSEMBLY discovery, QC, and replicon mapping for any organism (bacteria, archaea, fungi, and beyond) using NCBI Datasets. Resolves an organism name or taxid to assemblies, picks the reference/representative or best-quality assembly, pulls assembly QC metrics (total length, contig/scaffold N50, contig count, GC%, assembly level, RefSeq category), enumerates chromosomes and plasmids via per-replicon sequence reports, and compares candidate assemblies on quality. Use for "what genomes are available for [organism]", "assembly stats / N50 / GC content for [GCF_/GCA_ accession]", "how many plasmids does [strain] have", "compare assemblies for [species]", "find the reference genome for [taxon]", "is this assembly Complete Genome or just contigs". NOT for gene-level orthology/synteny (use tooluniverse-comparative-genomics), plant gene structure (use tooluniverse-plant-genomics), de novo assembly from raw reads (no tool exists), or taxonomy-only name/lineage lookups.