Pipeline funnel and crowding index

Products by development stage for any of 69 targets, every modality class and every cancer, with the phase 2 and 3 studies registered for them. Below, a crowding index: active assets per 100,000 addressable patients a year, currently led by KIT, NTRK, BCR::ABL1 (Philadelphia chromosome).

TROP2 4 products in the corpus

Approved

Phase 3

Phase 2

Phase 1

Preclinical

Stopped

Registry phase 3

Registry phase 2

186

Recruiting

107

All registry studies

269

Registry counts are ClinicalTrials.gov phase 2 and 3 studies naming each product (fetched 2026-09-09); a combination study counts once per product it names, so sums overstate distinct trials.

Products by stage

Sacituzumab govitecan ADC135Approved
Datopotamab deruxtecan ADC39Approved
Sacituzumab tirumotecan ADC92Phase 3
AK146D1 Bispecific ADC3Phase 1

Crowding index by target

Show targets with at least active assets


KIT 1 cancer with incidence and prevalence data · partial: 1 without a GLOBOCAN estimate	10	0	2,029	1k (663 to 2k)	753.58*
NTRK 2 cancers with incidence and prevalence data · partial: 1 without a GLOBOCAN estimate	3	0	48	6k (493 to 12k)	47.66*
BCR::ABL1 (Philadelphia chromosome) 1 cancer with incidence and prevalence data	5	0	502	19k (8k to 29k)	26.65
FLT3 1 cancer with incidence and prevalence data	5	0	157	32k (21k to 44k)	15.49
ALK 1 cancer with incidence and prevalence data · partial: 1 without a GLOBOCAN estimate	7	1	302	57k (36k to 79k)	13.94*
KMT2A (MLL) rearrangement 2 cancers with incidence and prevalence data	2	0	1,563	15k (6k to 24k)	13.08
VEGF / VEGFR 1 cancer with incidence and prevalence data · partial: 2 without a GLOBOCAN estimate	13	2	8,111	136k (98k to 174k)	11.04*
RET 2 cancers with incidence and prevalence data	6	0	1,033	58k (27k to 89k)	10.36
FGFR2 2 cancers with incidence and prevalence data · partial: 1 without a GLOBOCAN estimate	4	2	693	62k (30k to 95k)	9.62*
BTK (Bruton tyrosine kinase) 1 cancer with incidence and prevalence data	4	2	663	84k (49k to 119k)	7.14
MET 3 cancers with incidence and prevalence data	5	0	348	91k (57k to 126k)	6.56
CDK4/6 1 cancer with incidence and prevalence data · partial: 1 without a GLOBOCAN estimate	3	1	546	68k (34k to 103k)	5.84*
Somatostatin receptor 2 1 cancer with incidence and prevalence data · partial: 1 without a GLOBOCAN estimate	4	2	174	127k (77k to 177k)	5.51*
Menin 2 cancers with incidence and prevalence data	2	0	19	38k (23k to 54k)	5.24
LAG-3 1 cancer with incidence and prevalence data	1	1	118	39k (25k to 53k)	5.13
BCMA 1 cancer with incidence and prevalence data	6	1	189	170k (152k to 188k)	4.12
AKT 2 cancers with incidence and prevalence data	3	0	640	77k (40k to 114k)	3.9
BRAF 4 cancers with incidence and prevalence data	7	0	1,021	182k (103k to 261k)	3.85
HER2 6 cancers with incidence and prevalence data · partial: 1 without a GLOBOCAN estimate	17	2	2,695	563k (333k to 793k)	3.37*
IDH1 / IDH2 2 cancers with incidence and prevalence data · partial: 1 without a GLOBOCAN estimate	4	0	92	130k (89k to 171k)	3.08*
PD-1 2 cancers with incidence and prevalence data	12	2	6,414	493k (248k to 738k)	2.84
Estrogen receptor (ERα) 2 cancers with incidence and prevalence data	11	1	2,222	443k (268k to 618k)	2.71
CD19 3 cancers with incidence and prevalence data	8	0	296	329k (220k to 438k)	2.43
Androgen receptor 2 cancers with incidence and prevalence data	7	1	1,009	338k (215k to 461k)	2.37
CD20 2 cancers with incidence and prevalence data	6	0	2,476	259k (178k to 341k)	2.31
CD123 1 cancer with incidence and prevalence data	2	0	16	87k (58k to 117k)	2.29
BRCA1 / BRCA2 (HRD) 5 cancers with incidence and prevalence data	3	0	450	144k (87k to 200k)	2.09
PIK3CA / PI3K-alpha 4 cancers with incidence and prevalence data	7	0	877	407k (251k to 563k)	1.72
Nectin-4 2 cancers with incidence and prevalence data	1	0	77	175k (102k to 249k)	1.71
PARP 4 cancers with incidence and prevalence data	4	0	621	251k (187k to 314k)	1.6
EGFR 4 cancers with incidence and prevalence data	16	3	3,173	1.4m (1.1m to 1.7m)	1.44
PSMA 2 cancers with incidence and prevalence data	4	2	108	421k (263k to 580k)	1.42
BCL-2 2 cancers with incidence and prevalence data · partial: 1 without a GLOBOCAN estimate	2	0	598	147k (86k to 208k)	1.36*
KRAS 5 cancers with incidence and prevalence data	4	2	104	1.2m (947k to 1.4m)	0.85
CD38 2 cancers with incidence and prevalence data	2	0	414	253k (201k to 305k)	0.79
Claudin 18.2 2 cancers with incidence and prevalence data	2	1	22	425k (268k to 582k)	0.71
PD-L1 5 cancers with incidence and prevalence data	4	0	1,622	832k (607k to 1.1m)	0.48
Folate receptor alpha 3 cancers with incidence and prevalence data	2	2	41	1.2m (951k to 1.5m)	0.33
HER3 3 cancers with incidence and prevalence data	2	2	395	1.5m (1.1m to 1.9m)	0.27
TROP2 5 cancers with incidence and prevalence data	2	1	269	1.7m (1.2m to 2.1m)	0.24
CD3	11	3	484	no incidence or prevalence data	n/a
JAK2	5	0	424	no incidence or prevalence data	n/a
ROS1	4	0	134	no incidence or prevalence data	n/a
CTLA-4	3	0	965	no incidence or prevalence data	n/a
Smoothened (hedgehog pathway)	3	0	100	no incidence or prevalence data	n/a
GD2 (disialoganglioside)	2	0	49	no incidence or prevalence data	n/a

* Partial population: one or more of the target’s cancers (sarcoma, GIST, neuroendocrine tumours, neuroblastoma) has no GLOBOCAN site estimate and is excluded from the denominator, so the index is inflated. Read those rows as “crowded in the cancers we can count”.

The crowding formula

crowding = active assets / (addressable patients per year / 100,000)

active assets     = corpus products aimed at the target, excluding
                    negative, withdrawn and historic
addressable/year  = sum over cancers with a prevalence figure of
                    GLOBOCAN incidence (world) x subtype share
                    x prevalence x first setting share, midpoint

The population term is the addressable population estimator run for the world with the broadest setting. Targets whose cancers have no GLOBOCAN estimate (sarcoma, neuroendocrine tumours) or no parseable prevalence get no index, not a zero.

What it does and does not say

A high index means many programmes per patient: TROP2, HER2 and PD-1 crowding is real and shows up here. It does not measure quality, differentiation or the odds any one asset wins, and it counts only what is in this corpus, so thinly covered targets look less crowded than they are. Registry study counts include combination trials under each product named, so they overstate distinct trials.

Statuses come from product records (checked on each product’s as of date); registry counts were fetched 2026-09-09.