NeRD: a multichannel neural network to predict cellular response of drugs by integrating multidimensional data

Table 5 Case studies. Three largest cancer tissues (i.e., lung, skin, and pancreas) were screened from the predicted top 1% drug-cell line pairs, and then some drug-cell line pairs were screened from these tissues. We found that the predicted results of these drug-cell lines were consistent with those reported in the existing literature (i.e., Study)

Cell line	Cancer tissue	Drug name	Predicted IC50	Study
NCIH2122	Lung	Dasatinib	0.093358595	[65]
RERFLCAI	Lung	Dasatinib	0.124904478	[66]
NCIH1650	Lung	Bortezomib	0.046070208	[67]
NCIH322	Lung	Bortezomib	0.046246483	[11]
NCIH522	Lung	Ganetespib	0.074710398	[68]
SKMEL5	Skin	NVP-AUY922	0.038356718	[69]
UACC62	Skin	Piperazine	0.107990561	[70]
A2058	Skin	Piperazine	0.125350529	[71]
UACC62	Skin	Trametinib	0.063189984	[72]
WM1799	Skin	Trametinib	0.130639812	[73]
ASPC1	Pancreas	Dasatinib	0.120664515	[74]
PANC1005	Pancreas	Docetaxel	0.038846238	[75]
PATU8902	Pancreas	Docetaxel	0.041285745	[76]
SW1990	Pancreas	Docetaxel	0.049888730	[77]
HPAC	Pancreas	Ganetespib	0.070858083	[78]

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