Literature DB >> 24022346

Use of preclinical dog studies and absorption modeling to facilitate late stage formulation bridging for a BCS II drug candidate.

Filippos Kesisoglou.   

Abstract

Formulation changes are common during drug development either due to clinical or manufacturing considerations. These changes especially at later stages of drug development oftentimes raise questions on the potential impact of a new formulation on bioavailability. In this work, the preclinical assessment of formulation bridging risk for a Biopharmaceutics Classification System II development compound is presented. Early clinical studies were conducted using a liquid-filled capsule (LFC). To assess the feasibility of a conventional solid dosage form, an initial analysis was conducted using absorption modeling which indicated conventional formulation of micronized active pharmaceutical ingredient (API) could be a viable option. Subsequently, test formulations were prepared and tested in vivo in dogs. The solid formulations were able to match exposures of the LFC capsule in the dog model; in addition, a sensitivity to API PSD was observed in line with the modeling predictions. When tested in the clinic, the conventional solid formulation resulted in exposures of approximately 25% lower compared to the LFC on an equivalent dose basis; however, bridging with a small dose adjustment would be feasible. The outcome of the clinical study was better predicted by the modeling approach while the dog model appeared to somewhat overestimate absorption. Through the use of preclinical tools and modeling and simulation, a risk assessment around formulation bridging can be conducted and inform formulation decisions or subsequent clinical study designs.

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Year:  2014        PMID: 24022346      PMCID: PMC3909157          DOI: 10.1208/s12249-013-0030-6

Source DB:  PubMed          Journal:  AAPS PharmSciTech        ISSN: 1530-9932            Impact factor:   3.246


  14 in total

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Review 6.  Understanding the effect of API properties on bioavailability through absorption modeling.

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Review 10.  Predicting pharmacokinetics of drugs using physiologically based modeling--application to food effects.

Authors:  N Parrott; V Lukacova; G Fraczkiewicz; M B Bolger
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