Peregrine Pharmaceuticals has received a European patent for its In-Line labeling technology, used to link biological agents to labels for diagnostic and therapeutic applications.
The technology was developed for the production of radiolabeled anticancer antibodies, but is applicable to other agents as well, according to the Tustin, CA-based vendor. A study published in the July 2009 issue of the Journal of Nuclear Medicine found that In-line labeling can reduce the complexity and cost of producing radiolabeled cancer drugs, Peregrine said.
Related Reading
Peregrine reports healthy Q3 revenue, March 13, 2009
Peregrine mourns loss of chairman, December 11, 2008
Peregrine gains more time for compliance, October 23, 2008
Peregrine posts Q1 2009 results, September 10, 2008
Peregrine establishes Chinese subsidiary, sues CTL, January 12, 2007
Copyright © 2009 AuntMinnie.com










![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&fit=crop&h=112&q=70&w=112)





