Radiopharmaceutical firm Ion Beam Applications (IBA) and molecular imaging and therapy developer Aposense have agreed to exclusively collaborate on the commercialization of Aposense's ML-10 PET tracer for molecular imaging of apoptosis.
The deal expands upon a relationship established in August 2008, when the two firms signed an agreement for fluorine-18 (F-18) labeling and distribution of ML-10 by IBA for Aposense's multicenter clinical trials. Under the new long-term global agreement, IBA of Louvain-la-Neuve, Belgium, and Aposense of Petach-Tikva, Israel, will collaborate and jointly fund phase III trials and subsequent clinical development of ML-10.
Both firms will also jointly market and sell the agent, with IBA focusing primarily on the PET imaging and nuclear medicine market. Aposense will market ML-10 to the referring clinical specialist market, according to the vendors.
Aposense will manufacture the ML-10 precursor, and IBA will provide F-18 labeling and distribution of the final drug product to clinical sites throughout its global network of PET radiopharmacies, the companies said. Both firms will share in revenue and development costs. Specific financial terms were not disclosed.
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Aposense reports positive SNM talk, June 23, 2009
Aposense teams with GlaxoSmithKline, June 8, 2009
Aposense begins trial, December 15, 2008
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![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)
