Literature DB >> 33737635

Performance of preclinical models in predicting drug-induced liver injury in humans: a systematic review.

Hubert Dirven1, Gunn E Vist2, Sricharan Bandhakavi3, Jyotsna Mehta4, Seneca E Fitch5, Pandora Pound6, Rebecca Ram6, Breanne Kincaid7, Cathalijn H C Leenaars8, Minjun Chen9, Robert A Wright10, Katya Tsaioun11.   

Abstract

Drug-induced liver injury (DILI) causes one in three market withdrawals due to adverse drug reactions, causing preventable human suffering and massive financial loss. We applied evidence-based methods to investigate the role of preclinical studies in predicting human DILI using two anti-diabetic drugs from the same class, but with different toxicological profiles: troglitazone (withdrawn from US market due to DILI) and rosiglitazone (remains on US market). Evidence Stream 1: A systematic literature review of in vivo studies on rosiglitazone or troglitazone was conducted (PROSPERO registration CRD42018112353). Evidence Stream 2: in vitro data on troglitazone and rosiglitazone were retrieved from the US EPA ToxCast database. Evidence Stream 3: troglitazone- and rosiglitazone-related DILI cases were retrieved from WHO Vigibase. All three evidence stream analyses were conducted according to evidence-based methodologies and performed according to pre-registered protocols. Evidence Stream 1: 9288 references were identified, with 42 studies included in analysis. No reported biomarker for either drug indicated a strong hazard signal in either preclinical animal or human studies. All included studies had substantial limitations, resulting in "low" or "very low" certainty in findings. Evidence Stream 2: Troglitazone was active in twice as many in vitro assays (129) as rosiglitazone (60), indicating a strong signal for more off-target effects. Evidence Stream 3: We observed a fivefold difference in both all adverse events and liver-related adverse events reported, and an eightfold difference in fatalities for troglitazone, compared to rosiglitazone. In summary, published animal and human trials failed to predict troglitazone's potential to cause severe liver injury in a wider patient population, while in vitro data showed marked differences in the two drugs' off-target activities, offering a new paradigm for reducing drug attrition in late development and in the market. This investigation concludes that death and disability due to adverse drug reactions may be prevented if mechanistic information is deployed at early stages of drug development by pharmaceutical companies and is considered by regulators as a part of regulatory submissions.

Entities:  

Year:  2021        PMID: 33737635     DOI: 10.1038/s41598-021-85708-2

Source DB:  PubMed          Journal:  Sci Rep        ISSN: 2045-2322            Impact factor:   4.379


  38 in total

Review 1.  Are animal models as good as we think?

Authors:  R J Wall; M Shani
Journal:  Theriogenology       Date:  2007-11-07       Impact factor: 2.740

Review 2.  The third dimension bridges the gap between cell culture and live tissue.

Authors:  Francesco Pampaloni; Emmanuel G Reynaud; Ernst H K Stelzer
Journal:  Nat Rev Mol Cell Biol       Date:  2007-10       Impact factor: 94.444

Review 3.  An analysis of the attrition of drug candidates from four major pharmaceutical companies.

Authors:  Michael J Waring; John Arrowsmith; Andrew R Leach; Paul D Leeson; Sam Mandrell; Robert M Owen; Garry Pairaudeau; William D Pennie; Stephen D Pickett; Jibo Wang; Owen Wallace; Alex Weir
Journal:  Nat Rev Drug Discov       Date:  2015-06-19       Impact factor: 84.694

4.  Phase II and phase III failures: 2013-2015.

Authors:  Richard K Harrison
Journal:  Nat Rev Drug Discov       Date:  2016-11-04       Impact factor: 84.694

5.  Preclinical research: Make mouse studies work.

Authors:  Steve Perrin
Journal:  Nature       Date:  2014-03-27       Impact factor: 49.962

Review 6.  3D cell culture systems: advantages and applications.

Authors:  Maddaly Ravi; V Paramesh; S R Kaviya; E Anuradha; F D Paul Solomon
Journal:  J Cell Physiol       Date:  2015-01       Impact factor: 6.384

Review 7.  Cardionomics: a new integrative approach for screening cardiotoxicity of drug candidates.

Authors:  Judith K Gwathmey; Katya Tsaioun; Roger J Hajjar
Journal:  Expert Opin Drug Metab Toxicol       Date:  2009-06       Impact factor: 4.481

8.  Of mice and men: bridging the translational disconnect in CNS drug discovery.

Authors:  Hugo Geerts
Journal:  CNS Drugs       Date:  2009-11       Impact factor: 5.749

9.  Estimated Research and Development Investment Needed to Bring a New Medicine to Market, 2009-2018.

Authors:  Olivier J Wouters; Martin McKee; Jeroen Luyten
Journal:  JAMA       Date:  2020-03-03       Impact factor: 157.335

Review 10.  Epidemiology of adverse drug reactions in Europe: a review of recent observational studies.

Authors:  Jacoline C Bouvy; Marie L De Bruin; Marc A Koopmanschap
Journal:  Drug Saf       Date:  2015-05       Impact factor: 5.606

View more
  2 in total

Review 1.  Engineering complexity in human tissue models of cancer.

Authors:  Kacey Ronaldson-Bouchard; Ilaria Baldassarri; Daniel Naveed Tavakol; Pamela L Graney; Maria Samaritano; Elisa Cimetta; Gordana Vunjak-Novakovic
Journal:  Adv Drug Deliv Rev       Date:  2022-03-09       Impact factor: 17.873

Review 2.  Probabilistic risk assessment - the keystone for the future of toxicology.

Authors:  Alexandra Maertens; Emily Golden; Thomas H Luechtefeld; Sebastian Hoffmann; Katya Tsaioun; Thomas Hartung
Journal:  ALTEX       Date:  2022       Impact factor: 6.250

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.