tooluniverse-drug-synergy
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).
How do I install this agent skill?
npx skills add https://github.com/mims-harvard/tooluniverse --skill tooluniverse-drug-synergyIs this agent skill safe to install?
- Gen Agent Trust Hubpass
The skill provides tools for drug synergy analysis using standard reference models. No security risks were found; the use of subprocess in the testing script is limited to legitimate local unit testing of its own code.
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- Snykpass
Risk: LOW · No issues
What does this agent skill do?
Drug-Combination Synergy Analysis
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.
Step 0 — Pick the model by the data you have
| 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.
Step 1 — What each model's "additivity" means
| 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.
Step 2 — Run it
# 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.
Step 3 — Interpret the score
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).
- A positive Bliss/HSA score means the combination exceeds the additive expectation at that point.
- Synergy is often dose-dependent — a combination can be synergistic at one ratio and antagonistic at another; for a matrix, report the synergistic region, not one number.
Step 4 — Gotchas (state these)
- Scale mismatch (% viability vs fractional inhibition) — convert first (Step 0).
- Effects near 0 or 1 (ceiling). If both single agents already kill ~everything, the combo can't show synergy (no headroom) — Bliss/HSA saturate; interpret with care.
- ZIP/Loewe/CI need real dose-response with ≥3 non-zero, measurable-effect dose points per drug, or the Hill fit fails (the tools say so).
- Model disagreement is normal — don't shop for the model that gives "synergy"; pre-specify the model and report it.
- A synergy score is not efficacy — a strongly synergistic combination can still be weak overall; report the absolute combination effect too.
Honest limitations
- These are reference-model synergy scores, not statistical tests — for confidence, replicate and report variability across the dose matrix.
- Synergy in vitro does not guarantee clinical benefit (PK/PD, toxicity, scheduling all matter).
Related skills
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.
How can the creator link this skill?
Add the canonical catalog link to the repository README so users can inspect current installs and available audits. The publishing guide covers the complete discovery path.
<a href="https://skillzs.dev/skills/mims-harvard/tooluniverse/tooluniverse-drug-synergy">View tooluniverse-drug-synergy on skillZs</a>