AmTrin ASAP Laboratories, which is a partnership between Amebis Limited and Trinity College Dublin (TCD), and which provides Accelerated Stability Assessment Programme (ASAP) and ASAP related services to the pharmaceutical industry, has been successfully unveiled by Professor Anne Marie Healy, head of the School of Pharmacy and Pharmaceutical Sciences at TCD and AMBER principal investigator. ASAP is an accelerated ageing process allowing faster and more accurate prediction of product shelf-life – 15 of the 20 largest global pharmaceutical companies are using the ASAP technique. AmTrin ASAP Laboratories is the first European service provider with dedicated ASAP laboratories for performing contract ASAP studies and researching new applications. The benefits of AmTrin’s services, in addition to faster shelf-life prediction time, include improved understanding of packaging, formulation and process choices and faster submissions into clinical trials for new drugs. An ASAP study can be performed, and the shelf life of a product determined, in as little as three weeks compared with the standard for ICH testing of two to six months. Prof Healy said: “AmTrin’s services for the pharmaceutical industry can set the shelf life for products including tablets, capsules, gels, creams and ointments. Companies can save both time and money by building an accurate stability prediction model for their products and AmTrin can support all ASAP requirements from protocol design to study conduct.” AmTrin combines the expertise from researchers at Amebis, AMBER and the School of Pharmacy and Pharmaceutical Sciences, TCD, with state-of-the-art equipment to refine and research new applications for the ASAP technique. The first stage involves exposing the test material to a range of environmental conditions. AmTrin employs the Amebis system to accurately measure the temperature and relative humidity test conditions. The aged test material is then analysed using a range of equipment and finally ASAP modelling software is used to build the prediction model.