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

Primary targets: RET · FDA status: FDA Approved

Selectivity scorecard

MeasuredDerived
KISS
96.72
Gini
0.635
CATDS
0.013

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 Selpercatinib. Strongest target: RET at 100.0% inhibition.

Accessible data table
RankTargetInhibition %Residual activity %
1RET100.0%0.0%
2FLT4_VEGFR398.9%1.1%
3C_KIT98.7%1.3%
4FLT1_VEGFR196.2%3.8%
5FLT396.1%3.9%
6KDR_VEGFR295.9%4.1%
7FGFR295.0%5.0%
8JAK293.8%6.2%
9EPHB193.6%6.4%
10EPHA693.0%7.0%
11FMS92.8%7.2%
12DDR292.2%7.8%
13AURORA_C90.4%9.6%
14PLK4_SAK89.2%10.8%
15FGFR187.4%12.6%
16LCK87.3%12.7%
17FGFR386.6%13.4%
18LYN86.4%13.6%
19CHK286.3%13.7%
20AURORA_B86.1%13.9%

Selectivity landscape

MeasuredDerived

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

Atlas insights for Selpercatinib

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
2785.31
ALLOGRAFT_REJECTION
8179.99
ANDROGEN_RESPONSE
1574.36
ANGIOGENESIS
1414.60
APICAL_JUNCTION
8730.56
APICAL_SURFACE
861.56
APOPTOSIS
6494.21
BILE_ACID_METABOLISM
882.64
CHOLESTEROL_HOMEOSTASIS
1041.86
COAGULATION
1138.60
COMPLEMENT
4804.29
DNA_REPAIR
1835.53
E2F_TARGETS
4349.33
EPITHELIAL_MESENCHYMAL_TRANSITION
1807.27
ESTROGEN_RESPONSE_EARLY
2836.51
ESTROGEN_RESPONSE_LATE
3172.24
FATTY_ACID_METABOLISM
887.94
G2M_CHECKPOINT
4735.17
GLYCOLYSIS
2743.76
HEDGEHOG_SIGNALING
1093.11
HEME_METABOLISM
2214.39
HYPOXIA
4141.03
IL2_STAT5_SIGNALING
3126.65
IL6_JAK_STAT3_SIGNALING
5809.79
INFLAMMATORY_RESPONSE
4404.01
INTERFERON_ALPHA_RESPONSE
757.65
INTERFERON_GAMMA_RESPONSE
6280.04
KRAS_SIGNALING_DN
670.28
KRAS_SIGNALING_UP
3181.05
MITOTIC_SPINDLE
5660.25
MTORC1_SIGNALING
3666.55
MYC_TARGETS_V1
2919.59
MYC_TARGETS_V2
620.72
MYOGENESIS
2791.32
NOTCH_SIGNALING
259.13
OXIDATIVE_PHOSPHORYLATION
1521.45
P53_PATHWAY
3543.54
PANCREAS_BETA_CELLS
434.07
PEROXISOME
1088.23
PI3K_AKT_MTOR_SIGNALING
9011.44
PROTEIN_SECRETION
1776.13
REACTIVE_OXYGEN_SPECIES_PATHWAY
513.63
SPERMATOGENESIS
1403.29
TGF_BETA_SIGNALING
2010.50
TNFA_SIGNALING_VIA_NFKB
4462.51
UNFOLDED_PROTEIN_RESPONSE
1365.51
UV_RESPONSE_DN
4630.46
UV_RESPONSE_UP
3087.00
WNT_BETA_CATENIN_SIGNALING
1746.30
XENOBIOTIC_METABOLISM
1725.22

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 = 3.10 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 = 0.842

SampleCancer typecos to ideal
EPT0291EPN0.842
SRR233037520.837
SRR108999840.826
aMVAC.P_005_TURBT_S2230.825
TCGA-CF-A5U8-01A-11R-A28M-070.824

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