Dataset Information

Evaluation of the Relevance of DILI Predictive Hypotheses in Early Drug Development: Review of In Vitro Methodologies vs BDDCS Classification.

ABSTRACT: Drug-induced liver injury (DILI) is a major safety concern; it occurs frequently; it is idiosyncratic; it cannot be adequately predicted; and a multitude of underlying mechanisms has been postulated. A number of experimental approaches to predict human DILI have been proposed utilizing in vitro screening such as inhibition of mitochondrial function, hepatobiliary transporter inhibition, reactive metabolite formation with and without covalent binding, and cellular health, but they have achieved only minimal success. Several studies have shown total administered dose alone or in combination with drug lipophilicity to be correlated with a higher risk of DILI. However, it would be best to have a predictive DILI methodology early in drug development, long before the clinical dose is known. Here we discuss the extent to which Biopharmaceutics Drug Disposition Classification System (BDDCS) defining characteristics, independent of knowing actual drug pharmacokinetics/pharmacodynamics and dose, can be used to evaluate prior published predictive proposals. Our results show that BDDCS Class 2 drugs exhibit the highest DILI severity, and that all of the short-lived published methodologies evaluated here, except when daily dose is known, do not yield markedly better predictions than BDDCS. The assertion that extensively metabolized compounds are at higher risk of developing DILI is confirmed, but can be enhanced by differentiating BDDCS Class 2 from Class 1 drugs.

Conclusion

Our published analyses suggest that comparison of proposed DILI prediction methodologies with BDDCS classification is a useful tool to evaluate the potential reliability of newly proposed algorithms, although BDDCS classification itself is not sufficiently predictive. Almost all of the predictive DILI metrics do no better than just avoiding BDDCS Class 2 drugs, although some early data with microliver platforms enabling long-enduring metabolic competency show promising results.

SUBMITTER: Chan R

PROVIDER: S-EPMC5959290 | biostudies-literature | 2018 May

REPOSITORIES: biostudies-literature

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Evaluation of the Relevance of DILI Predictive Hypotheses in Early Drug Development: Review of In Vitro Methodologies vs BDDCS Classification.

Chan Rosa R Benet Leslie Z LZ

Toxicology research 20180418 3

Drug-induced liver injury (DILI) is a major safety concern; it occurs frequently; it is idiosyncratic; it cannot be adequately predicted; and a multitude of underlying mechanisms has been postulated. A number of experimental approaches to predict human DILI have been proposed utilizing in vitro screening such as inhibition of mitochondrial function, hepatobiliary transporter inhibition, reactive metabolite formation with and without covalent binding, and cellular health, but they have ach ...[more]

PMID: 29785262

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Project description:Drug-induced liver injury (DILI) is a leading cause of drug failure in clinical trials and a major reason for drug withdrawals. DILI has been shown to be dependent on both daily dose and extent of hepatic metabolism. Yet, early in drug development daily dose is unknown. Here, we perform a comprehensive analysis of the published hypotheses that attempt to predict DILI, including a new analysis of the Biopharmaceutics Drug Disposition Classification System (BDDCS) in evaluating the severity of DILI warnings in drug labels approved by the FDA and the withdrawal status due to adverse drug reactions (ADRs). Our analysis confirms that higher doses ≥50 mg/day lead to increased DILI potential, but this property alone is not sufficient to predict the DILI potential. We evaluate prior attempts to categorize DILI such as Rule of 2, BSEP inhibition, and measures of key mechanisms of toxicity compared to BDDCS classification. Our results show that BDDCS Class 2 drugs exhibit the highest DILI severity and that all of the published methodologies evaluated here, except when daily dose is known, do not yield markedly better predictions than BDDCS. The assertion that extensive metabolized compounds are at higher risk of developing DILI is confirmed but can be enhanced by differentiating BDDCS Class 2 from Class 1 drugs. We do not propose that the BDDCS classification, which does not require knowledge of the clinical dose, is sufficiently predictive/accurate of DILI potential for new molecular entities but suggest that comparison of proposed DILI prediction methodologies with BDDCS classification is a useful tool to evaluate the potential reliability of newly proposed algorithms.ConclusionThe most successful approaches to predict DILI potential all include a measure of dose, yet there is a quantifiable uncertainty associated with the predicted dose early in drug development. Here, we compare the possibility of predicting DILI potential using the BDDCS classification versus previously published methods and note that many hypothesized predictive DILI metrics do no better than just avoiding BDDCS Class 2 drugs.

Project description:Drug-induced liver injury (DILI) is a type of bizarre adverse drug reaction (ADR) damaging liver (L-ADR) which may lead to substantial hospitalizations and mortality. Due to the general low incidence, detection of L-ADR remains an unsolved public health challenge. Therefore, we used the data of 6.673 million of ADR reports from January 1st, 2012 to December 31st, 2016 in China National ADR Monitoring System to establish a new database of L-ADR reports for future investigation. Results showed that totally 114,357 ADR reports were retrieved by keywords searching of liver-related injuries from the original heterogeneous system. By cleaning and standardizing the data fields by the dictionary of synonyms and English translation, we resulted 94,593 ADR records reported to liver injury and then created a new database ready for computer mining. The reporting status of L-ADR showed a persistent 1.62-fold change over the past five years. The national population-adjusted reporting numbers of L-ADR manifested an upward trend with age increasing and more evident in men. The annual reporting rate of L-ADR in age group over 80 years old strikingly exceeded the annual DILI incidence rate in general population, despite known underreporting situation in spontaneous ADR reporting system. The percentage of herbal and traditional medicines (H/TM) L-ADR reports in the whole number was 4.5%, while 80.60% of the H/TM reports were new findings. There was great geographical disparity of reported agents, i.e. more cardiovascular and antineoplastic agents were reported in higher socio-demographic index (SDI) regions and more antimicrobials, especially antitubercular agents, were reported in lower SDI regions. In conclusion, this study presented a large-scale, unbiased, unified, and computer-minable L-ADR database for further investigation. Age-, sex- and SDI-related risks of L-ADR incidence warrant to emphasize the precise pharmacovigilance policies within China or other regions in the world.

Dataset Information

Evaluation of the Relevance of DILI Predictive Hypotheses in Early Drug Development: Review of In Vitro Methodologies vs BDDCS Classification.

Conclusion

Publications

Evaluation of the Relevance of DILI Predictive Hypotheses in Early Drug Development: Review of <i>In Vitro</i> Methodologies <i>vs</i> BDDCS Classification.

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