In vivo models and decision trees for formulation development in early drug development: A review of current practices and recommendations for biopharmaceutical development
- PMID: 31233862
- DOI: 10.1016/j.ejpb.2019.06.010
In vivo models and decision trees for formulation development in early drug development: A review of current practices and recommendations for biopharmaceutical development
Abstract
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.
Copyright © 2019 Elsevier B.V. All rights reserved.
Similar articles
-
Preclinical Bioavailability Strategy for Decisions on Clinical Drug Formulation Development: An In Depth Analysis.Mol Pharm. 2018 Jul 2;15(7):2633-2645. doi: 10.1021/acs.molpharmaceut.8b00172. Epub 2018 Jun 11. Mol Pharm. 2018. PMID: 29799758
-
In vitro models for the prediction of in vivo performance of oral dosage forms.Eur J Pharm Sci. 2014 Jun 16;57:342-66. doi: 10.1016/j.ejps.2013.08.024. Epub 2013 Aug 27. Eur J Pharm Sci. 2014. PMID: 23988843 Review.
-
Leveraging Oral Drug Development to a Next Level: Impact of the IMI-Funded OrBiTo Project on Patient Healthcare.Front Med (Lausanne). 2021 Mar 5;8:480706. doi: 10.3389/fmed.2021.480706. eCollection 2021. Front Med (Lausanne). 2021. PMID: 33748152 Free PMC article. Review.
-
Oral biopharmaceutics tools - time for a new initiative - an introduction to the IMI project OrBiTo.Eur J Pharm Sci. 2014 Jun 16;57:292-9. doi: 10.1016/j.ejps.2013.10.012. Epub 2013 Nov 1. Eur J Pharm Sci. 2014. PMID: 24189462 Review.
-
PBPK models for the prediction of in vivo performance of oral dosage forms.Eur J Pharm Sci. 2014 Jun 16;57:300-21. doi: 10.1016/j.ejps.2013.09.008. Epub 2013 Sep 21. Eur J Pharm Sci. 2014. PMID: 24060672 Review.
Cited by
-
New Cellular Models to Support Preclinical Studies on ICAM-1-Targeted Drug Delivery.J Drug Deliv Sci Technol. 2024 Nov;101(Pt A):106170. doi: 10.1016/j.jddst.2024.106170. Epub 2024 Sep 10. J Drug Deliv Sci Technol. 2024. PMID: 39669707
-
One and Two-Step In Vitro-In Vivo Correlations Based on USP IV Dynamic Dissolution Applied to Four Sodium Montelukast Products.Pharmaceutics. 2021 May 11;13(5):690. doi: 10.3390/pharmaceutics13050690. Pharmaceutics. 2021. PMID: 34064700 Free PMC article.
-
Stability of Protein Pharmaceuticals: Recent Advances.Pharm Res. 2024 Jul;41(7):1301-1367. doi: 10.1007/s11095-024-03726-x. Epub 2024 Jun 27. Pharm Res. 2024. PMID: 38937372 Review.
Publication types
MeSH terms
Substances
LinkOut - more resources
Full Text Sources