Research Use Only. KIRhub outputs are computational research artifacts. They are not validated for clinical decision-making, diagnosis, or treatment.

Primary targets: C_KIT, PDGFRA, PDGFRB · FDA status: FDA Approved

Selectivity scorecard

MeasuredDerived
KISS
92.95
Gini
0.674
CATDS
0.011

Computed from wild-type kinome inhibition at 1 μM. Gini reproduces the published values within tolerance; KISS and CATDS are computed but pending reconciliation with the paper's reference code.

Polypharmacology radar

MeasuredDerived

Top 20 strongest-inhibited wild-type kinases for Ripretinib. Strongest target: ARAF at 100.0% inhibition.

Accessible data table
RankTargetInhibition %Residual activity %
1ARAF100.0%0.0%
2BRAF100.0%0.0%
3RAF1100.0%0.0%
4C_KIT99.3%0.7%
5YSK4_MAP3K1998.7%1.3%
6ZAK_MLTK97.4%2.6%
7LCK97.2%2.8%
8FMS97.2%2.9%
9DDR196.9%3.1%
10EPHB196.5%3.5%
11TAOK2_TAO196.4%3.6%
12JAK196.0%4.0%
13LYN95.3%4.7%
14HIPK495.3%4.7%
15EPHA295.2%4.8%
16EPHB495.2%4.8%
17DDR294.8%5.2%
18MLK2_MAP3K1094.7%5.3%
19ABL2_ARG94.5%5.5%
20EPHA694.1%5.9%

Selectivity landscape

MeasuredDerived

Where Ripretinib sits in the 92-drug selectivity landscape (KISS vs Gini). The highlighted point is Ripretinib.

Atlas insights for Ripretinib

MeasuredReference

Pathway-space view of what this drug actually does, drawn from the Pathway Atlas.

On-target vs off-target shadow

DerivedMeasured

How much of this drug's pathway perturbation comes from primary targets vs polypharmacology vs 2nd-order propagation. When off-target dominates, the FDA label is the smallest description of the drug.

On-target0%
Off-target100%
Ghost (2nd-order)0%
PathwayCompositionTotal |Π|
ADIPOGENESIS
2941.43
ALLOGRAFT_REJECTION
9417.15
ANDROGEN_RESPONSE
1238.15
ANGIOGENESIS
1607.44
APICAL_JUNCTION
9777.97
APICAL_SURFACE
1109.96
APOPTOSIS
7132.72
BILE_ACID_METABOLISM
1028.51
CHOLESTEROL_HOMEOSTASIS
1310.42
COAGULATION
1268.72
COMPLEMENT
5523.99
DNA_REPAIR
1667.83
E2F_TARGETS
4305.52
EPITHELIAL_MESENCHYMAL_TRANSITION
1709.26
ESTROGEN_RESPONSE_EARLY
3264.37
ESTROGEN_RESPONSE_LATE
2958.36
FATTY_ACID_METABOLISM
917.66
G2M_CHECKPOINT
4574.00
GLYCOLYSIS
2533.90
HEDGEHOG_SIGNALING
1005.47
HEME_METABOLISM
2337.94
HYPOXIA
4262.22
IL2_STAT5_SIGNALING
3596.92
IL6_JAK_STAT3_SIGNALING
6306.72
INFLAMMATORY_RESPONSE
5274.88
INTERFERON_ALPHA_RESPONSE
1107.43
INTERFERON_GAMMA_RESPONSE
6701.24
KRAS_SIGNALING_DN
934.64
KRAS_SIGNALING_UP
3544.57
MITOTIC_SPINDLE
6003.15
MTORC1_SIGNALING
3745.63
MYC_TARGETS_V1
3249.62
MYC_TARGETS_V2
785.84
MYOGENESIS
2857.69
NOTCH_SIGNALING
195.17
OXIDATIVE_PHOSPHORYLATION
1650.04
P53_PATHWAY
3749.56
PANCREAS_BETA_CELLS
259.52
PEROXISOME
1004.05
PI3K_AKT_MTOR_SIGNALING
10043.40
PROTEIN_SECRETION
1986.10
REACTIVE_OXYGEN_SPECIES_PATHWAY
481.48
SPERMATOGENESIS
1614.95
TGF_BETA_SIGNALING
1885.12
TNFA_SIGNALING_VIA_NFKB
4574.28
UNFOLDED_PROTEIN_RESPONSE
1402.74
UV_RESPONSE_DN
5477.06
UV_RESPONSE_UP
3642.91
WNT_BETA_CATENIN_SIGNALING
1917.60
XENOBIOTIC_METABOLISM
1827.65

See this drug on the perturbation map →

Hallmarks-of-Cancer reach

DerivedReference

Projection onto the 10 canonical Hanahan & Weinberg hallmarks. Breadth = how many hallmarks this drug meaningfully perturbs.

ProliferationEvading apoptosisAngiogenesisInvasion / metastasisReplicative immortalityDeregulated metabolismImmune evasionGenome instabilityInflammationGrowth signaling

Breadth = 3.07 bits (max possible across 10 hallmarks = 3.32 bits). Multi-hallmark agent — broad polypharmacology.

Compare against the full catalog →

Anti-tumor matches — the "ideal patient" search

ModeledDerived

Top 5 real tumors closest to this drug's ideal patient (the tumor whose pathway state = −Π_d). Closest match cosine = 0.831

SampleCancer typecos to ideal
SRR233037520.831
EPT0291EPN0.830
SRR108999840.817
aMVAC.P_005_TURBT_S2230.814
TCGA-CF-A5U8-01A-11R-A28M-070.812

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