TY - JOUR
T1 - In vivo models and decision trees for formulation development in early drug development
T2 - A review of current practices and recommendations for biopharmaceutical development
AU - Zane, P.
AU - Gieschen, H.
AU - Kersten, E.
AU - Mathias, N.
AU - Ollier, C.
AU - Johansson, P.
AU - Van den Bergh, A.
AU - Van Hemelryck, S.
AU - Reichel, A.
AU - Rotgeri, A.
AU - Schäfer, K.
AU - Müllertz, A.
AU - Langguth, P.
PY - 2019
Y1 - 2019
N2 - The ability to predict new chemical entity performance using in vivo animal models has been under investigation for more than two decades. Pharmaceutical companies use their own strategies to make decisions on the most appropriate formulation starting early in development. In this paper the biopharmaceutical decision trees available in four EFPIA partners (Bayer, Boehringer Ingelheim, Bristol Meyers Squibb and Janssen) were discussed by 7 companies of which 4 had no decision tree currently defined. The strengths, weaknesses and opportunities for improvement are discussed for each decision tree. Both pharmacokineticists and preformulation scientists at the drug discovery & development interface responsible for lead optimization and candidate selection contributed to an overall picture of how formulation decisions are progressed. A small data set containing compound information from the database designed for the IMI funded OrBiTo project is examined for interrelationships between measured physicochemical, dissolution and relative bioavailability parameters. In vivo behavior of the drug substance and its formulation in First in human (FIH) studies cannot always be well predicted from in vitro and/or in silico tools alone at the time of selection of a new chemical entity (NCE). Early identification of the risks, challenges and strategies to prepare for formulations that provide sufficient preclinical exposure in animal toxicology studies and in FIH clinical trials is needed and represents an essential part of the IMI funded OrBiTo project. This article offers a perspective on the use of in vivo models and biopharmaceutical decision trees in the development of new oral drug products.
AB - The ability to predict new chemical entity performance using in vivo animal models has been under investigation for more than two decades. Pharmaceutical companies use their own strategies to make decisions on the most appropriate formulation starting early in development. In this paper the biopharmaceutical decision trees available in four EFPIA partners (Bayer, Boehringer Ingelheim, Bristol Meyers Squibb and Janssen) were discussed by 7 companies of which 4 had no decision tree currently defined. The strengths, weaknesses and opportunities for improvement are discussed for each decision tree. Both pharmacokineticists and preformulation scientists at the drug discovery & development interface responsible for lead optimization and candidate selection contributed to an overall picture of how formulation decisions are progressed. A small data set containing compound information from the database designed for the IMI funded OrBiTo project is examined for interrelationships between measured physicochemical, dissolution and relative bioavailability parameters. In vivo behavior of the drug substance and its formulation in First in human (FIH) studies cannot always be well predicted from in vitro and/or in silico tools alone at the time of selection of a new chemical entity (NCE). Early identification of the risks, challenges and strategies to prepare for formulations that provide sufficient preclinical exposure in animal toxicology studies and in FIH clinical trials is needed and represents an essential part of the IMI funded OrBiTo project. This article offers a perspective on the use of in vivo models and biopharmaceutical decision trees in the development of new oral drug products.
U2 - 10.1016/j.ejpb.2019.06.010
DO - 10.1016/j.ejpb.2019.06.010
M3 - Journal article
C2 - 31233862
AN - SCOPUS:85068157441
VL - 142
SP - 222
EP - 231
JO - European Journal of Pharmaceutics and Biopharmaceutics
JF - European Journal of Pharmaceutics and Biopharmaceutics
SN - 0939-6411
ER -