The Need for Human Exposure Projection in the Interpretation of Preclinical<i>In Vitro</i>and<i>In Vivo</i>ADME Tox Data

Poulin, Patrick

doi:10.1002/9781119053248.ch6

Cited by 3 publications

(2 citation statements)

References 123 publications

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“…Results of quantitative hepatocyte-based in vitro-to-in vivo extrapolations continue to improve (Poulin, 2016;Tetsuka et al, 2017). In vitro strategies for liver toxicity testing have experienced concurrent advances (Soldatow et al, 2013) aided by increasing knowledge about factors that limit accuracy (LeCluyse et al, 2012;Fraczek et al, 2013;Godoy et al, 2013;Vellonen et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

A Model Mechanism-Based Explanation of an In Vitro-In Vivo Disconnect for Improving Extrapolation and Translation

Smith

Ropella

et al. 2018

J Pharmacol Exp Ther

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An improved understanding of in vivo-to-in vitro hepatocyte changes is crucial to interpreting in vitro data correctly and further improving hepatocyte-based in vitro-to-in vivo extrapolations to human targets. We demonstrate using virtual experiments as a means of helping to untangle plausible causes of inaccurate extrapolations. We start with virtual mice that use biomimetic software livers. Previously, using these mice, we discovered model mechanisms that enabled achieving quantitative validation targets while also providing plausible causal explanations for temporal characteristics of acetaminophen hepatotoxicity. We isolated virtual hepatocytes, created a virtual culture, and then conducted dose-response experiments in both culture and mice. We expected to see differences between the two dose-response curves but were somewhat surprised that they crossed because it evidenced that simulated acetaminophen metabolism and toxicity are different for virtual culture and mouse contexts even though individual hepatocyte mechanisms were unchanged. Differences in dose-response curves provide a virtual example of an in vivo-to-in vitro disconnect. We use detailed results of experiments to explain this disconnect. Individual hepatocytes contribute differently to system-level phenomena. In liver, hepatocytes are exposed to acetaminophen sequentially. Relative production of the reactive acetaminophen metabolite is largest (smallest) in pericentral (periportal) hepatocytes. Because that sequential exposure is absent in culture, hepatocytes from different lobular locations do not respond the same. A virtual culture-to-mouse translation can stand as a scientifically challengeable hypothesis explaining an in vivo-to-in vitro disconnect. It provides a framework to develop more reliable interpretations of in vitro observations, which then may be used to improve extrapolations.

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Section: Introductionmentioning

confidence: 99%

A Model Mechanism-Based Explanation of an In Vitro-In Vivo Disconnect for Improving Extrapolation and Translation

Smith

Ropella

et al. 2018

J Pharmacol Exp Ther

View full text Add to dashboard Cite

show abstract

“…Results of quantitative hepatocyte-based in vitro-to-in vivo extrapolations continue to improve [Tetsuka et al, 2017, Poulin et al, 2016. In vitro strategies for liver toxicity testing have experienced concurrent advances [Soldatow et al, 2013] aided by increasing knowledge about factors that limit accuracy [Vellonen et al, 2014, Godoy et al, 2013, LeCluyse et al, 2012.…”

Section: Introductionmentioning

confidence: 99%

A Model Mechanism Based Explanation of an In Vitro-In Vivo Disconnect for Improving Extrapolation and Translation

Smith

Ropella

et al. 2017

Preprint

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An improved understanding of in vivo-to-in vitro hepatocyte changes is crucial to interpreting in vitro data correctly and further improving hepatocyte-based in vitro-to-in vivo extrapolations to human targets. We demonstrate using virtual experiments as a means to help untangle plausible causes of inaccurate extrapolations. We start with virtual mice that have biomimetic software livers. Earlier, using those mice, we discovered model mechanisms that enabled achieving quantitative validation targets while also providing plausible causal explanations for temporal characteristics of acetaminophen hepatotoxicity. We isolated virtual hepatocytes, created a virtual culture, and then conducted dose-response experiments in both culture and mice. We expected the two dose-response curves to be displaced. We were surprised that they crossed because it evidenced that simulated acetaminophen metabolism and toxicity are different for virtual culture and mouse contexts even though individual hepatocyte mechanisms were unchanged. Crossing dose-response curves is a virtual example of an in vivo-to-in vitro disconnect. We use detailed results of experiments to explain the disconnect. Individual hepatocytes contribute differently to system level phenomena. In liver, hepatocytes are exposed to acetaminophen sequentially. Relative production of the reactive acetaminophen metabolite is largest (smallest) in pericentral (periportal) hepatocytes. Because that sequential exposure is absent in culture, hepatocytes from different lobular locations do not respond the same. A virtual Culture-to-Mouse translation can stand as a scientifically challengeable theory explaining an in vitro-in vivo disconnect. It provides a framework to develop more reliable interpretations of in vitro observations, which then may be used to improve extrapolations.AbbreviationsaHPCanalog hepatocyteAPAPacetaminophenCVCentral VeinSSsinusoidal segmentNAPQIN-acetyl-p-benzoquinone iminemitoDmitochondrial damage productsnonMDnon-mitochondrial damage products

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Structure Alerts

Norman¹

2021

Burger's Medicinal Chemistry and Drug Discovery

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Structure alerts are classes of chemicals, functional groups, or substructures that, when present in drugs or drug candidates, have been linked to preclinical toxicity and/or adverse drug reactions (ADRs) in humans. The assignment of structure alerts, which includes a wide variety of structural types, has mostly emerged from retrospective analyses of drug or drug candidates that have demonstrated toxicity. Some compounds are inherently toxic, while others containing structure alerts manifest toxicity due to metabolism and formation of reactive metabolites. In many cases, the mechanisms associated with toxicity have been hypothesized to be the result of covalent binding of a drug or metabolite to endogenous nucleophiles in proteins and nucleic acids. Strategies to mitigate toxicity due to structure alerts have generally focused on avoidance and/or replacement of the structure alert. However, as many safe and successful drugs contain structure alerts, there is no industry‐wide alignment on which should always be avoided or replaced. It has been demonstrated that ADRs are more likely to occur in higher dose drugs (>100 mg) and more lipophilic drugs (LogP >3). The inclusion of structure alerts in drug candidates that have these liabilities may increase the risk of toxicity.

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The Need for Human Exposure Projection in the Interpretation of PreclinicalIn VitroandIn VivoADME Tox Data

Cited by 3 publications

References 123 publications

A Model Mechanism-Based Explanation of an In Vitro-In Vivo Disconnect for Improving Extrapolation and Translation

A Model Mechanism-Based Explanation of an In Vitro-In Vivo Disconnect for Improving Extrapolation and Translation

A Model Mechanism Based Explanation of an In Vitro-In Vivo Disconnect for Improving Extrapolation and Translation

Structure Alerts

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