Due to an increased use of targeted therapies, greater uptake of branded drugs, and a rising incidence of breast cancer, the breast cancer therapeutics market will grow from $9.2 billion in 2013 to $13.1 billion by 2020, according to a new report from market research firm GBI Research.
The moderate growth represents a compound annual growth rate (CAGR) of 5.1%. The figures cover the eight major global geographic markets, consisting of the U.S., the U.K., France, Germany, Spain, Italy, Japan, and Canada.
Branded drugs will become more favored over this period, and market growth will also result from the launch of a number of premium-priced agents and a gradual increase in the use of targeted therapies, GBI analyst Saurabh Sharma said in a statement.
GBI said the breast cancer drug treatment pipeline is highly robust, with potential candidates in various phases of clinical development. Of the 612 active progressing pipeline molecules, 259 (42%) are in the preclinical stage of development, 100 (16%) are in phase I clinical trials, 130 (21%) are in phase II, and 52 (8%) are in phase III, according to the company.
A substantial number of active drug candidates are also in the discovery stage. The current pipeline of investigational agents also includes new combinations and targeted therapies, promising immunotherapies, and chemotherapy drug candidates, Sharma said.
![Overview of the study design. (A) The fully automated deep learning framework was developed to estimate body composition (BC) (defined as subcutaneous adipose tissue [SAT] in liters; visceral adipose tissue [VAT] in liters; skeletal muscle [SM] in liters; SM fat fraction [SMFF] as a percentage; and intramuscular adipose tissue [IMAT] in deciliters) from MRI. The fully automated framework comprised one model (model 1) to quantify different BC measures (SAT, VAT, SM, SMFF, and IMAT) as three-dimensional (3D) measures from whole-body MRI scans. The second model (model 2) was trained to identify standardized anatomic landmarks along the craniocaudal body axis (z coordinate field), which allowed for subdividing the whole-body measures into different subregions typically examined on clinical routine MRI scans (chest, abdomen, and pelvis). (B) BC was quantified from whole-body MRI in over 66,000 individuals from two large population-based cohort studies, the UK Biobank (UKB) (36,317 individuals) and the German National Cohort (NAKO) (30,291 individuals). Bar graphs show age distribution by sex and cohort. BMI = body mass index. (C) After the performance assessment of the fully automated framework, the change in BC measures, distributions, and profiles across age decades were investigated. Age-, sex-, and height-adjusted body composition reference curves were calculated and made publicly available in a web-based z-score calculator (https://circ-ml.github.io).](https://img.auntminnieeurope.com/mindful/smg/workspaces/default/uploads/2026/05/body-comp.XgAjTfPj1W.jpg?auto=format%2Ccompress&dpr=2&fit=crop&h=167&q=70&w=250)
