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

Primary targets: JAK1 · FDA status: FDA Approved

Selectivity scorecard

MeasuredDerived
KISS
97.98
Gini
0.663
CATDS
0.016

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 Upadacitinib. Strongest target: RAF1 at 99.9% inhibition.

Accessible data table
RankTargetInhibition %Residual activity %
1RAF199.9%0.1%
2JAK298.3%1.7%
3JAK397.5%2.5%
4JAK197.3%2.6%
5TYK297.1%2.9%
6YSK4_MAP3K1993.4%6.6%
7STK38L_NDR291.2%8.8%
8STK38_NDR190.8%9.2%
9PKCA84.7%15.3%
10PKCB283.3%16.7%
11C_KIT82.9%17.1%
12PKCD78.1%21.9%
13AURORA_A76.7%23.3%
14PKCG75.3%24.7%
15LRRK273.3%26.7%
16TRKC70.0%30.0%
17FLT369.7%30.4%
18TAOK2_TAO167.7%32.3%
19DDR267.4%32.6%
20ARAF64.9%35.1%

Selectivity landscape

MeasuredDerived

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

Atlas insights for Upadacitinib

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-target6%
Off-target94%
Ghost (2nd-order)0%
PathwayCompositionTotal |Π|
ADIPOGENESIS
1846.57
ALLOGRAFT_REJECTION
5346.35
ANDROGEN_RESPONSE
957.37
ANGIOGENESIS
842.55
APICAL_JUNCTION
5341.41
APICAL_SURFACE
602.33
APOPTOSIS
4209.58
BILE_ACID_METABOLISM
552.78
CHOLESTEROL_HOMEOSTASIS
594.95
COAGULATION
506.97
COMPLEMENT
2842.06
DNA_REPAIR
837.50
E2F_TARGETS
2748.47
EPITHELIAL_MESENCHYMAL_TRANSITION
1390.06
ESTROGEN_RESPONSE_EARLY
2393.61
ESTROGEN_RESPONSE_LATE
2187.31
FATTY_ACID_METABOLISM
453.34
G2M_CHECKPOINT
2637.04
GLYCOLYSIS
1611.71
HEDGEHOG_SIGNALING
606.84
HEME_METABOLISM
1353.54
HYPOXIA
2132.18
IL2_STAT5_SIGNALING
2103.35
IL6_JAK_STAT3_SIGNALING
4219.72
INFLAMMATORY_RESPONSE
3571.02
INTERFERON_ALPHA_RESPONSE
786.68
INTERFERON_GAMMA_RESPONSE
4411.04
KRAS_SIGNALING_DN
661.72
KRAS_SIGNALING_UP
1893.93
MITOTIC_SPINDLE
3150.30
MTORC1_SIGNALING
1942.48
MYC_TARGETS_V1
1808.90
MYC_TARGETS_V2
453.86
MYOGENESIS
2125.29
NOTCH_SIGNALING
47.67
OXIDATIVE_PHOSPHORYLATION
883.19
P53_PATHWAY
1811.43
PANCREAS_BETA_CELLS
88.94
PEROXISOME
681.99
PI3K_AKT_MTOR_SIGNALING
5706.03
PROTEIN_SECRETION
1506.37
REACTIVE_OXYGEN_SPECIES_PATHWAY
153.54
SPERMATOGENESIS
1167.90
TGF_BETA_SIGNALING
1042.88
TNFA_SIGNALING_VIA_NFKB
2997.87
UNFOLDED_PROTEIN_RESPONSE
1009.43
UV_RESPONSE_DN
3208.45
UV_RESPONSE_UP
2256.17
WNT_BETA_CATENIN_SIGNALING
1273.14
XENOBIOTIC_METABOLISM
915.79

See this drug on the perturbation map →

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 = 0.838

SampleCancer typecos to ideal
SRR233037520.838
EPT0291EPN0.835
TCGA-CF-A5U8-01A-11R-A28M-070.823
SRR108999840.823
aMVAC.P_005_TURBT_S2230.822

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