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

Primary targets: EGFR, ERBB2_HER2, ERBB4_HER4 · FDA status: FDA Approved

Selectivity scorecard

MeasuredDerived
KISS
98.50
Gini
0.709
CATDS
0.020

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 Afatinib. Strongest target: ERBB4_HER4 at 100.0% inhibition.

Accessible data table
RankTargetInhibition %Residual activity %
1ERBB4_HER4100.0%0.0%
2EGFR100.0%0.0%
3ERBB2_HER298.9%1.1%
4BLK96.8%3.2%
5TXK93.0%7.0%
6EPHA693.0%7.0%
7BTK88.6%11.4%
8DDR187.5%12.5%
9LCK83.5%16.4%
10C_MER82.8%17.2%
11LYN78.7%21.3%
12P38A_MAPK1478.1%21.9%
13IRAK172.1%27.9%
14ABL167.1%32.9%
15HCK66.5%33.5%
16C_MET65.7%34.3%
17DYRK262.6%37.4%
18PEAK159.8%40.2%
19FGR59.2%40.8%
20ITK58.7%41.3%

Selectivity landscape

MeasuredDerived

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

Atlas insights for Afatinib

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
1973.02
ALLOGRAFT_REJECTION
7007.21
ANDROGEN_RESPONSE
1489.93
ANGIOGENESIS
1139.15
APICAL_JUNCTION
6861.03
APICAL_SURFACE
645.30
APOPTOSIS
5118.75
BILE_ACID_METABOLISM
759.65
CHOLESTEROL_HOMEOSTASIS
1119.55
COAGULATION
735.61
COMPLEMENT
4273.72
DNA_REPAIR
1716.00
E2F_TARGETS
3286.68
EPITHELIAL_MESENCHYMAL_TRANSITION
1588.46
ESTROGEN_RESPONSE_EARLY
2177.97
ESTROGEN_RESPONSE_LATE
2154.03
FATTY_ACID_METABOLISM
537.06
G2M_CHECKPOINT
3162.63
GLYCOLYSIS
2096.77
HEDGEHOG_SIGNALING
890.04
HEME_METABOLISM
1404.86
HYPOXIA
3257.16
IL2_STAT5_SIGNALING
2444.18
IL6_JAK_STAT3_SIGNALING
3577.80
INFLAMMATORY_RESPONSE
3936.83
INTERFERON_ALPHA_RESPONSE
642.70
INTERFERON_GAMMA_RESPONSE
4825.33
KRAS_SIGNALING_DN
710.51
KRAS_SIGNALING_UP
2729.41
MITOTIC_SPINDLE
4868.24
MTORC1_SIGNALING
2983.34
MYC_TARGETS_V1
2312.72
MYC_TARGETS_V2
457.28
MYOGENESIS
2413.94
NOTCH_SIGNALING
311.65
OXIDATIVE_PHOSPHORYLATION
951.74
P53_PATHWAY
2912.78
PANCREAS_BETA_CELLS
255.82
PEROXISOME
845.03
PI3K_AKT_MTOR_SIGNALING
6298.78
PROTEIN_SECRETION
1503.15
REACTIVE_OXYGEN_SPECIES_PATHWAY
470.07
SPERMATOGENESIS
985.46
TGF_BETA_SIGNALING
1356.07
TNFA_SIGNALING_VIA_NFKB
3441.26
UNFOLDED_PROTEIN_RESPONSE
799.51
UV_RESPONSE_DN
3159.56
UV_RESPONSE_UP
2749.54
WNT_BETA_CATENIN_SIGNALING
1543.47
XENOBIOTIC_METABOLISM
1505.81

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 = 3.11 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 = 0.845

SampleCancer typecos to ideal
EPT0291EPN0.845
SRR233037520.839
SRR108999840.830
TCGA-CF-A5U8-01A-11R-A28M-070.828
aMVAC.P_005_TURBT_S2230.826

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