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Building a tiered approach to in vitro predictive toxicity screening: a focus on assays with in vivo relevance.

McKim JM - Comb. Chem. High Throughput Screen. (2010)

Bottom Line: It is generally recognized that early evaluation of new drug candidates is necessary to improve the process.In vitro cytotoxicity assays have been used for decades as a tool to understand hypotheses driven questions regarding mechanisms of toxicity.This review will focus on the development of an in vitro toxicity screening strategy that is based on a tiered approach to data collection combined with data interpretation.

View Article: PubMed Central - PubMed

Affiliation: CeeTox Inc., 4717 Campus Dr., Kalamazoo, MI 49008, USA. jmckim@ceetox.com

ABSTRACT
One of the greatest challenges facing the pharmaceutical industry today is the failure of promising new drug candidates due to unanticipated adverse effects discovered during preclinical animal safety studies and clinical trials. Late stage attrition increases the time required to bring a new drug to market, inflates development costs, and represents a major source of inefficiency in the drug discovery/development process. It is generally recognized that early evaluation of new drug candidates is necessary to improve the process. Building in vitro data sets that can accurately predict adverse effects in vivo would allow compounds with high risk profiles to be deprioritized, while those that possess the requisite drug attributes and a lower risk profile are brought forward. In vitro cytotoxicity assays have been used for decades as a tool to understand hypotheses driven questions regarding mechanisms of toxicity. However, when used in a prospective manner, they have not been highly predictive of in vivo toxicity. Therefore, the issue may not be how to collect in vitro toxicity data, but rather how to translate in vitro toxicity data into meaningful in vivo effects. This review will focus on the development of an in vitro toxicity screening strategy that is based on a tiered approach to data collection combined with data interpretation.

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Related in: MedlinePlus

In vitro toxicity screening differentiates toxicity between drugs in the same class. The antifungal drugs ketoconazole, itraconazole, and fluconazole ll have a similar mode of action but were not developed at the same time. If the three molecules had been part of a single discovery program, in vitro toxicity screening could have provided important information regarding the relative safety of these drugs. To demonstrate this, all three drugs were evaluated in the rat hepatoma (H4IIE) cell line according to conditions described under Fig. (5). Under the conditions tested, ketoconazole showed the highest potential to produce toxicity, while fluconazole showed the lowest potential to produce toxicity. This interpretation is consistent with clinical observations. Values represent the mean of 4-5 wells. The coefficient of variation was between 10 and 15% across the assays. Standard error of the mean bars are not shown for clarity. Ctox = estimated plasma concentration at steady state where toxicity would be expected to occur in liver, kidney, bone marrow, or heart. ND = not determined.
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Figure 9: In vitro toxicity screening differentiates toxicity between drugs in the same class. The antifungal drugs ketoconazole, itraconazole, and fluconazole ll have a similar mode of action but were not developed at the same time. If the three molecules had been part of a single discovery program, in vitro toxicity screening could have provided important information regarding the relative safety of these drugs. To demonstrate this, all three drugs were evaluated in the rat hepatoma (H4IIE) cell line according to conditions described under Fig. (5). Under the conditions tested, ketoconazole showed the highest potential to produce toxicity, while fluconazole showed the lowest potential to produce toxicity. This interpretation is consistent with clinical observations. Values represent the mean of 4-5 wells. The coefficient of variation was between 10 and 15% across the assays. Standard error of the mean bars are not shown for clarity. Ctox = estimated plasma concentration at steady state where toxicity would be expected to occur in liver, kidney, bone marrow, or heart. ND = not determined.

Mentions: In another example, in vitro multi-parametric analysis was used to evaluate the relative toxicity of three antifungal drugs: ketoconazole, itraconazole, and fluconazole. Fluconazole has fewer structural similarities than ketoconazole and itraconazole (Fig.8). Although these drugs were developed and marketed at different times, it is useful to analyze the compounds as if they had been three new NCEs in late stage discovery and only two could be selected and brought forward into animal safety studies. In 1995 two of the molecules, ketoconazole and fluconazole, were evaluated in an in vitro primary hepatocyte system [55]. These experiments showed that ketoconazole was considerably more cytotoxic than fluconazole at therapeutically relevant exposure concentrations. Moreover, it was reported that one mechanism of ketoconazole toxicity was linked to mitochondrial toxicity [56]. The toxicity profiles shown in Fig. (9) compare all three antifungal drugs in the H4IIE cell model combined with concentration response, and multi-parametric analysis. Ketoconazole caused mitochondrial toxicity and reduced the rate of cell proliferation. Ketoconazole was the most cytotoxic, with fluconazole having the safest profile. The estimated blood concentration where toxicity would first be expected to occur (Ctox) is also shown in Fig. (9). The predicted toxicity value of 55 µM obtained from the in vitro model was in close agreement with actual rat and human pharmacokinetic and toxicity data. Remembering that the toxicity data should only be one piece of the information used to select candidates for development, it is useful to review the potency/efficacy data for the three drugs. For the endpoints of potency/efficacy selected, all three drugs were similar. An evaluation of ADME data relevant to toxicity such as CYP inhibition indicates that ketoconazole and itraconazole are potent inhibitors of CYP3A4, the enzyme responsible for a large portion of drug metabolism in humans. This means that co-administration of drugs that are metabolized primarily by CYP3A4 (simvastatin, lovastatin, terfenadine, midazolam) with ketoconazole or itraconazole can result in clinically significant drug-drug interactions (DDIs) [57]. In comparison, fluconazole is a weak inhibitor of CYP3A4 and would therefore have a lower risk for DDIs when co-administered with drugs metabolized by CYP3A4. However, this compound is a potent inhibitor of CYP2C9 and CYP2C19 [57, 58] and therefore drugs that are primarily metabolized by 2C9 (phenytoin, warfarin, sulfamethoxazole, losartan) and co-administered with fluconazole could also produce DDIs. If all of these drugs had been developed in the same project, the best molecules for continued development would have been itraconazole and fluconazole as they carry less risk of toxicity produced by the parent drug and lower potential for DDIs. Although there is reason for concern regarding potential DDIs with the antifungal compounds discussed here, this risk must be weighed against the risk of not having an effective treatment for systemic fungal infections.


Building a tiered approach to in vitro predictive toxicity screening: a focus on assays with in vivo relevance.

McKim JM - Comb. Chem. High Throughput Screen. (2010)

In vitro toxicity screening differentiates toxicity between drugs in the same class. The antifungal drugs ketoconazole, itraconazole, and fluconazole ll have a similar mode of action but were not developed at the same time. If the three molecules had been part of a single discovery program, in vitro toxicity screening could have provided important information regarding the relative safety of these drugs. To demonstrate this, all three drugs were evaluated in the rat hepatoma (H4IIE) cell line according to conditions described under Fig. (5). Under the conditions tested, ketoconazole showed the highest potential to produce toxicity, while fluconazole showed the lowest potential to produce toxicity. This interpretation is consistent with clinical observations. Values represent the mean of 4-5 wells. The coefficient of variation was between 10 and 15% across the assays. Standard error of the mean bars are not shown for clarity. Ctox = estimated plasma concentration at steady state where toxicity would be expected to occur in liver, kidney, bone marrow, or heart. ND = not determined.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2908937&req=5

Figure 9: In vitro toxicity screening differentiates toxicity between drugs in the same class. The antifungal drugs ketoconazole, itraconazole, and fluconazole ll have a similar mode of action but were not developed at the same time. If the three molecules had been part of a single discovery program, in vitro toxicity screening could have provided important information regarding the relative safety of these drugs. To demonstrate this, all three drugs were evaluated in the rat hepatoma (H4IIE) cell line according to conditions described under Fig. (5). Under the conditions tested, ketoconazole showed the highest potential to produce toxicity, while fluconazole showed the lowest potential to produce toxicity. This interpretation is consistent with clinical observations. Values represent the mean of 4-5 wells. The coefficient of variation was between 10 and 15% across the assays. Standard error of the mean bars are not shown for clarity. Ctox = estimated plasma concentration at steady state where toxicity would be expected to occur in liver, kidney, bone marrow, or heart. ND = not determined.
Mentions: In another example, in vitro multi-parametric analysis was used to evaluate the relative toxicity of three antifungal drugs: ketoconazole, itraconazole, and fluconazole. Fluconazole has fewer structural similarities than ketoconazole and itraconazole (Fig.8). Although these drugs were developed and marketed at different times, it is useful to analyze the compounds as if they had been three new NCEs in late stage discovery and only two could be selected and brought forward into animal safety studies. In 1995 two of the molecules, ketoconazole and fluconazole, were evaluated in an in vitro primary hepatocyte system [55]. These experiments showed that ketoconazole was considerably more cytotoxic than fluconazole at therapeutically relevant exposure concentrations. Moreover, it was reported that one mechanism of ketoconazole toxicity was linked to mitochondrial toxicity [56]. The toxicity profiles shown in Fig. (9) compare all three antifungal drugs in the H4IIE cell model combined with concentration response, and multi-parametric analysis. Ketoconazole caused mitochondrial toxicity and reduced the rate of cell proliferation. Ketoconazole was the most cytotoxic, with fluconazole having the safest profile. The estimated blood concentration where toxicity would first be expected to occur (Ctox) is also shown in Fig. (9). The predicted toxicity value of 55 µM obtained from the in vitro model was in close agreement with actual rat and human pharmacokinetic and toxicity data. Remembering that the toxicity data should only be one piece of the information used to select candidates for development, it is useful to review the potency/efficacy data for the three drugs. For the endpoints of potency/efficacy selected, all three drugs were similar. An evaluation of ADME data relevant to toxicity such as CYP inhibition indicates that ketoconazole and itraconazole are potent inhibitors of CYP3A4, the enzyme responsible for a large portion of drug metabolism in humans. This means that co-administration of drugs that are metabolized primarily by CYP3A4 (simvastatin, lovastatin, terfenadine, midazolam) with ketoconazole or itraconazole can result in clinically significant drug-drug interactions (DDIs) [57]. In comparison, fluconazole is a weak inhibitor of CYP3A4 and would therefore have a lower risk for DDIs when co-administered with drugs metabolized by CYP3A4. However, this compound is a potent inhibitor of CYP2C9 and CYP2C19 [57, 58] and therefore drugs that are primarily metabolized by 2C9 (phenytoin, warfarin, sulfamethoxazole, losartan) and co-administered with fluconazole could also produce DDIs. If all of these drugs had been developed in the same project, the best molecules for continued development would have been itraconazole and fluconazole as they carry less risk of toxicity produced by the parent drug and lower potential for DDIs. Although there is reason for concern regarding potential DDIs with the antifungal compounds discussed here, this risk must be weighed against the risk of not having an effective treatment for systemic fungal infections.

Bottom Line: It is generally recognized that early evaluation of new drug candidates is necessary to improve the process.In vitro cytotoxicity assays have been used for decades as a tool to understand hypotheses driven questions regarding mechanisms of toxicity.This review will focus on the development of an in vitro toxicity screening strategy that is based on a tiered approach to data collection combined with data interpretation.

View Article: PubMed Central - PubMed

Affiliation: CeeTox Inc., 4717 Campus Dr., Kalamazoo, MI 49008, USA. jmckim@ceetox.com

ABSTRACT
One of the greatest challenges facing the pharmaceutical industry today is the failure of promising new drug candidates due to unanticipated adverse effects discovered during preclinical animal safety studies and clinical trials. Late stage attrition increases the time required to bring a new drug to market, inflates development costs, and represents a major source of inefficiency in the drug discovery/development process. It is generally recognized that early evaluation of new drug candidates is necessary to improve the process. Building in vitro data sets that can accurately predict adverse effects in vivo would allow compounds with high risk profiles to be deprioritized, while those that possess the requisite drug attributes and a lower risk profile are brought forward. In vitro cytotoxicity assays have been used for decades as a tool to understand hypotheses driven questions regarding mechanisms of toxicity. However, when used in a prospective manner, they have not been highly predictive of in vivo toxicity. Therefore, the issue may not be how to collect in vitro toxicity data, but rather how to translate in vitro toxicity data into meaningful in vivo effects. This review will focus on the development of an in vitro toxicity screening strategy that is based on a tiered approach to data collection combined with data interpretation.

Show MeSH
Related in: MedlinePlus