OrBiTo - translating mechanistic knowledge on absorption into predictive models
Amin Rostami-Hodjegan, PhD, FCP, FAAPS, FJSSX
University of Manchester & Simcyp Ltd, United Kingdom
OrBiTo is a new European project within the IMI programme in the area of oral biopharmaceutics tools that includes world leading scientists from nine European universities, one regulatory agency, one non-profit research organization, four SMEs together with scientists from twelve pharmaceutical companies.
The OrBiTo project will address key gaps in our knowledge of gastrointestinal (GI) drug absorption and deliver a framework for rational application of predictive biopharmaceutics tools for oral drug delivery. This will be achieved through novel prospective investigations to define new methodologies as well as refinement of existing tools.
Extensive validation of novel and existing biopharmaceutics tools will be performed using active pharmaceutical ingredient (API), formulations and supporting datasets from industry partners. A combination of high quality in vitro or in silico characterizations of API and formulations will be integrated into physiologically based in silico biopharmaceutics models capturing the full complexity of GI drug absorption. This approach gives an unparalleled opportunity to initiate a transformational change in industrial research and development to achieve model-based pharmaceutical product development in accordance with the Quality by Design concept. Benefits include an accelerated and more efficient drug candidate selection, formulation development process, particularly for challenging projects such as low solubility molecules (BCS II and IV), enhanced and modified-release formulations, as well as allowing optimization of clinical product performance for patient benefit. In addition, the tools emerging from OrBiTo are expected to significantly reduce demand for animal experiments in the future as well as reducing the number of human bioequivalence studies required to bridge formulations after manufacturing or composition changes.