Use of Lhasa Limited Products for the In Silico Prediction of Drug Toxicity

Ponting, David J.; Burns, Michael J.; Foster, R.; Hemingway, Rachel; Kocks, Grace; Macmillan, Donna S.; Shannon-Little, Andrew L.; Tennant, Rachael E.; Tidmarsh, Jessica R; Yeo, David J.

doi:10.1007/978-1-0716-1960-5_17

Cited by 13 publications

(10 citation statements)

References 65 publications

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“…Moreover, this approach was used in the development of the ICH M7 guideline for control of mutagenic impurities in pharmaceuticals; since mutagenesis is the critical first step in the carcinogenic activity for the majority of relevant structures, for control of carcinogenic hazard due to impurities it has been deemed sufficient. Following assessment of an impurity, using either Ames and/or rodent carcinogenicity assay data or an in silico prediction of the Ames mutagenicity, a classification is assigned based on the hazard identified. , Following hazard identification, the guideline stipulates that a control strategy must be implemented for each impurity. This requires calculation of an acceptable intake (AI) either as a linear extrapolation from carcinogenicity data, if available for the impurity, or a TTC of 1.5 μg/day, which may be adjusted based on length of exposure to provide a less than lifetime (LTL) limit. , It is specifically noted in the guideline that this TTC limit may not be applied to chemicals in the CoC (aflatoxin-like, alkyl azoxy, N -nitroso), which instead require a compound-specific risk assessment.…”

Section: Development Of the Ttc Concept And The Cohort Of Concernmentioning

confidence: 99%

“…The Lhasa Limited software platform Nexus contains the expert-rule-based system Derek Nexus and the statistical QSAR system Sarah Nexus . Containing both models in a single platform has facilitated the implementation of a powerful set of tools to support the classification of impurities under ICH M7 through an integrated workflow.…”

Section: Implications For (Quantitative) Structure–activity Relations...mentioning

confidence: 99%

“…Following assessment of an impurity, using either Ames and/or rodent carcinogenicity assay data or an in silico prediction of the Ames mutagenicity, a classification is assigned based on the hazard identified. 1,11 Following hazard identification, the guideline stipulates that a control strategy must be implemented for each impurity. This requires calculation of an acceptable intake (AI) either as a linear extrapolation from carcinogenicity data, if available for the impurity, or a TTC of 1.5 μg/day, which may be adjusted based on length of exposure to provide a less than lifetime (LTL) limit.…”

Section: Cohort Of Concernmentioning

confidence: 99%

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Drawing a Line: Where Might the Cohort of Concern End?

Ponting

Foster

2023

Org. Process Res. Dev.

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The definitions of the chemical classes in the Cohort of Concern (CoC) by Kroes and co-workers are based on broad structural alerts, in particular for N-nitroso compounds�for which the alert consists essentially of the N−N�O substructure without further refinement. Recent pharmaceutical recalls have focused on the presence of dialkyl N-nitrosamine impurities, some of which are exceptionally potent carcinogens�2 orders of magnitude more potent than the pharmaceutical Threshold of Toxicological Concern (TTC), 1.5 μg/day. However, the class of "N-nitroso compounds" is potentially significantly broader. This Perspective looks at the N-nitroso compounds that are at the edges of the cohort, where changes in mechanism, metabolic activation potential, stability, or indeed toxicity data lead to questions about whether these compounds should be classed as CoC. The critical mechanism of action, metabolic α-hydroxylation leading to a diazonium ion, is presented, along with the pathways by which Nnitroso compounds that are not dialkyl N-nitrosamines can lead to comparable DNA adducts.

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Section: Development Of the Ttc Concept And The Cohort Of Concernmentioning

confidence: 99%

Section: Implications For (Quantitative) Structure–activity Relations...mentioning

confidence: 99%

Section: Cohort Of Concernmentioning

confidence: 99%

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Drawing a Line: Where Might the Cohort of Concern End?

Ponting

Foster

2023

Org. Process Res. Dev.

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“…The data used herein was curated from sources that provide detailed information on the experimentally observed SoMs for substrates of human SULTs. The dataset was initially curated by Lhasa Limited to support Meteor Nexus , but has been expanded for this work. Since the model is intended to distinguish the experimentally observed SoMs from all potential SoMs, the molecules included in the dataset have two or more potential SoMs, out of which at least one is experimentally observed.…”

Section: Experimental Datamentioning

confidence: 99%

“…The data used herein was curated from sources that provide detailed information on the experimentally observed SoMs for substrates of human SULTs. The dataset was initially curated by Lhasa Limited 52 to support Meteor Nexus 53,54 potential SoMs, the molecules included in the dataset have two or more potential SoMs, out of which at least one is experimentally observed. Any experiments run with unphysiological substrate concentrations were rejected; the highest accepted concentration was 100 μM or less.…”

Section: ■ Experimental Datamentioning

confidence: 99%

Predicting Regioselectivity of Cytosolic Sulfotransferase Metabolism for Drugs

Öeren,

Kaempf,

Ponting

et al. 2023

J. Chem. Inf. Model.

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Cytosolic sulfotransferases (SULTs) are a family of enzymes responsible for the sulfation of small endogenous and exogenous compounds. SULTs contribute to the conjugation phase of metabolism and share substrates with the uridine 5′diphospho-glucuronosyltransferase (UGT) family of enzymes. UGTs are considered to be the most important enzymes in the conjugation phase, and SULTs are an auxiliary enzyme system to them. Understanding how the regioselectivity of SULTs differs from that of UGTs is essential from the perspective of developing novel drug candidates. We present a general ligand-based SULT model trained and tested using high-quality experimental regioselectivity data. The current study suggests that, unlike other metabolic enzymes in the modification and conjugation phases, the SULT regioselectivity is not strongly influenced by the activation energy of the rate-limiting step of the catalysis. Instead, the prominent role is played by the substrate binding site of SULT. Thus, the model is trained only on steric and orientation descriptors, which mimic the binding pocket of SULT. The resulting classification model, which predicts whether a site is metabolized, achieved a Cohen's kappa of 0.71.

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Development and validation of stability indicating assay method for mitapivat: Identification of novel hydrolytic, photolytic, and oxidative forced degradation products employing quadrupole‐time of flight mass spectrometry

Bagul,

Patil,

Mane

et al. 2024

J of Separation Science

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Mitapivat is a novel, first‐in‐class orally active pyruvate kinase activator approved by the US Food and Drug Administration in 2022 for the treatment of hemolytic anemia. There is no literature available regarding the identification of degradation impurities of mitapivat. The present study deals with the degradation behavior of mitapivat under various stress conditions such as hydrolytic, photolytic, thermal, and oxidative stress. The multivariate analysis found that the independent variables, that is, molarity, temperature, and time, are interacting with each other to affect the degradation of mitapivat. A specific, accurate, and precise high‐performance liquid chromatographic (HPLC) method was developed to separate mitapivat from its degradation products. The separation was achieved on the C‐18 column (250 mm × 4.6 mm × 5 µm) using the combination of 0.1% formic acid buffer and acetonitrile in gradient elution profile. The method was validated as per the International Council for Harmonization of Technical Requirements for Pharmaceuticals for Human Use Q2(R2) guideline. LC‐electrospray ionization‐Quadrupole‐time of flight was employed to identify degradation products. A total of seven novel degradation products of mitapivat were identified based on tandem mass spectrometry and accurate mass measurement. In‐silico toxicity of mitapivat and its degradation products was qualitatively evaluated by the DEREK toxicity prediction tool.

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Use of Lhasa Limited Products for the In Silico Prediction of Drug Toxicity

Cited by 13 publications

References 65 publications

Drawing a Line: Where Might the Cohort of Concern End?

Drawing a Line: Where Might the Cohort of Concern End?

Predicting Regioselectivity of Cytosolic Sulfotransferase Metabolism for Drugs

Development and validation of stability indicating assay method for mitapivat: Identification of novel hydrolytic, photolytic, and oxidative forced degradation products employing quadrupole‐time of flight mass spectrometry

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