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

Primary targets: FGFR2 · FDA status: FDA Approved

Selectivity scorecard

MeasuredDerived
KISS
98.48
Gini
0.718
CATDS
0.032

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 Futibatinib. Strongest target: FGFR2 at 99.3% inhibition.

Accessible data table
RankTargetInhibition %Residual activity %
1FGFR299.3%0.7%
2FGFR399.0%1.0%
3FGFR199.0%1.0%
4FGFR497.9%2.1%
5RET97.7%2.3%
6BMX_ETK95.2%4.8%
7FGR81.5%18.5%
8JAK281.4%18.6%
9TRKC78.4%21.6%
10YES_YES170.3%29.7%
11TRKB65.5%34.5%
12JAK164.4%35.6%
13MKK760.4%39.6%
14ROS_ROS158.1%41.9%
15DDR156.4%43.6%
16CK1EPSILON54.8%45.2%
17ZAP7046.1%53.9%
18BLK42.6%57.4%
19FLT4_VEGFR341.8%58.2%
20FLT332.8%67.2%

Selectivity landscape

MeasuredDerived

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

Atlas insights for Futibatinib

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-target5%
Off-target95%
Ghost (2nd-order)0%
PathwayCompositionTotal |Π|
ADIPOGENESIS
999.27
ALLOGRAFT_REJECTION
3421.68
ANDROGEN_RESPONSE
761.52
ANGIOGENESIS
479.92
APICAL_JUNCTION
3408.81
APICAL_SURFACE
363.64
APOPTOSIS
2175.47
BILE_ACID_METABOLISM
335.92
CHOLESTEROL_HOMEOSTASIS
428.31
COAGULATION
197.40
COMPLEMENT
1655.54
DNA_REPAIR
671.77
E2F_TARGETS
1538.86
EPITHELIAL_MESENCHYMAL_TRANSITION
503.49
ESTROGEN_RESPONSE_EARLY
987.02
ESTROGEN_RESPONSE_LATE
1025.71
FATTY_ACID_METABOLISM
665.89
G2M_CHECKPOINT
1665.02
GLYCOLYSIS
1144.85
HEDGEHOG_SIGNALING
127.06
HEME_METABOLISM
701.82
HYPOXIA
1518.26
IL2_STAT5_SIGNALING
1132.66
IL6_JAK_STAT3_SIGNALING
3258.07
INFLAMMATORY_RESPONSE
1635.13
INTERFERON_ALPHA_RESPONSE
323.95
INTERFERON_GAMMA_RESPONSE
2891.01
KRAS_SIGNALING_DN
247.89
KRAS_SIGNALING_UP
985.66
MITOTIC_SPINDLE
1845.78
MTORC1_SIGNALING
1332.43
MYC_TARGETS_V1
979.47
MYC_TARGETS_V2
167.46
MYOGENESIS
960.01
NOTCH_SIGNALING
72.90
OXIDATIVE_PHOSPHORYLATION
1038.69
P53_PATHWAY
973.33
PANCREAS_BETA_CELLS
84.10
PEROXISOME
324.67
PI3K_AKT_MTOR_SIGNALING
4609.60
PROTEIN_SECRETION
988.90
REACTIVE_OXYGEN_SPECIES_PATHWAY
79.25
SPERMATOGENESIS
600.26
TGF_BETA_SIGNALING
687.70
TNFA_SIGNALING_VIA_NFKB
1561.11
UNFOLDED_PROTEIN_RESPONSE
522.11
UV_RESPONSE_DN
1561.60
UV_RESPONSE_UP
1162.35
WNT_BETA_CATENIN_SIGNALING
673.85
XENOBIOTIC_METABOLISM
775.86

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 = 3.05 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 = 0.809

SampleCancer typecos to ideal
EPT0291EPN0.809
SRR108999840.803
SRR233037520.802
TCGA-FD-A43X-01A-11R-A23W-070.793
aMVAC.P_005_TURBT_S2230.787

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