Prediction of ADMET Properties

Norinder, Ulf; Bergström, Christel A S

doi:10.1002/cmdc.200600155

Cited by 214 publications

(68 citation statements)

References 74 publications

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“…While the field of in silico modeling for ADME applications has not yet realized its full potential in support of pharmaceutical research, it seems likely that this approach also will mature in the coming years, enabling predictions of the most relevant pharmacokinetic, metabolic, and, potentially, toxicity end points (53,54). Similarly, methods to predict the susceptibility of a new chemical entity toward metabolic activation will provide guidance to medicinal chemists engaged in drug discovery programs, although it seems unlikely that in silico techniques will replace well-established in Vitro or in ViVo experimental approaches in the foreseeable future.…”

Section: Drug Metabolism In the Future: What Lies Ahead?mentioning

confidence: 99%

Metabolism and Toxicity of Drugs. Two Decades of Progress in Industrial Drug Metabolism

Baillie

2007

Chem. Res. Toxicol.

184

116

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The science of drug metabolism and pharmacokinetics (DMPK) has developed significantly over the past 20 years, and its functional role in today's pharmaceutical industry has matured to the point where DMPK has become an indispensable discipline in support of drug discovery and development. While contributions to the lead optimization phase of discovery efforts have been particularly noteworthy in helping to select only the best drug candidates for entry into development, it should be recognized that the scope of DMPK spans the continuum of discovery through clinical evaluation and even into the post-marketing phase; as such, the breadth of DMPK's involvement is almost unique in contemporary pharmaceutical research. This perspective summarizes notable advances in the field, many of which have been made possible by technological developments in areas such as molecular biology, genetics, and bioanalytical chemistry, and highlights the critical nature of key partnerships between Drug Metabolism, Medicinal Chemistry, and Safety Assessment groups in attempting to advance drug candidates with a low potential for causing adverse events in humans. Finally, some speculative predictions are made of the future role of DMPK in pharmaceutical research, where current advances in our mechanistic understanding of the molecular processes that control the absorption, disposition, metabolism, elimination, and toxicity of drugs and their biotransformation products will combine to further enhance the impact of DMPK in drug discovery and development.

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Section: Drug Metabolism In the Future: What Lies Ahead?mentioning

confidence: 99%

Metabolism and Toxicity of Drugs. Two Decades of Progress in Industrial Drug Metabolism

Baillie

2007

Chem. Res. Toxicol.

184

116

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“…Previous reports have focused on prediction methods that utilize animal pharmacokinetic data (Caldwell et al, 2004;Ward and Smith, 2004a,b;Jolivette and Ward, 2005;Evans et al, 2006;Mahmood et al, 2006;Martinez et al, 2006;Tang and Mayersohn, 2006;Fagerholm, 2007;McGinnity et al, 2007) and in vitro data (Obach et al, 1997;Lombardo et al, 2002Lombardo et al, , 2004Nestorov et al, 2002;Riley et al, 2005;Grime and Riley, 2006). Recently, the availability of computational chemistry methodologies has increased, and these have been applied to the prediction of human pharmacokinetics and/or general absorption-distribution-metabolism-excretion-toxicology properties (Cruciani et al, 2005;Ghafourian et al, 2006;Gleeson et al, 2006;Lombardo et al, 2006;Gleeson, 2007;Gunturi and Narayanan, 2007;Norinder and Bergstroem, 2007). The construction of effective models not only requires sound computational tools but, very importantly, databases that have been carefully assembled.…”

mentioning

confidence: 99%

Trend Analysis of a Database of Intravenous Pharmacokinetic Parameters in Humans for 670 Drug Compounds

Obach

Lombardo²,

Waters³

2008

Drug Metab Dispos

358

304

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ABSTRACT:We present herein a compilation and trend analysis of human i.v. pharmacokinetic data on 670 drugs representing, to our knowledge, the largest publicly available set of human clinical pharmacokinetic data. This data set provides the drug metabolism scientist with a robust and accurate resource suitable for a number of applications, including in silico modeling, in vitro-in vivo scaling, and physiologically based pharmacokinetic approaches. Clearance, volume of distribution at steady state, mean residence time, and terminal phase half-life were obtained or derived from original references exclusively from studies utilizing i.v. administration. Plasma protein binding data were collected from other sources to supplement these pharmacokinetic data. These parameters were analyzed concurrently with a range of simple physicochemical descriptors, and resultant trends and patterns within the data are presented. Our findings with this much expanded data set were consistent with earlier described notions of trends between physicochemical properties and pharmacokinetic behavior. These observations and analyses, along with the large database of human pharmacokinetic data, should enable future efforts aimed toward developing quantitative structure-pharmacokinetic relationships and improving our understanding of the relationship between fundamental chemical characteristics and drug disposition.The prediction of human pharmacokinetics for new compounds has become an important process in drug research. Previous reports have focused on prediction methods that utilize animal pharmacokinetic data (Caldwell et al

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“…The computational tools are still rather limited, but a genotoxic metabolite of a non-genotoxic mother compound, for example, would strongly affect TTC values in the current use. A number of reviews on metabolic prediction tools are available (Boobis et al, 2002;Kulkarni et al, 2005;Norinder and Bergström, 2006;Mostrag-Szlichtyng and Worth, 2010;Tsaioun et al, 2016 An especially interesting combination is the one of TTC with read-across or (Q)SAR, especially as both are fast and not costly. Establishing a probability of hazard using these in silico tools as discussed above can synergize with TTC ( Fig.…”

Section: Discussionmentioning

confidence: 99%

Thresholds of Toxicological Concern – Setting a threshold for testing below which there is little concern

Hartung

2017

ALTEX

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Prediction of ADMET Properties

Cited by 214 publications

References 74 publications

Metabolism and Toxicity of Drugs. Two Decades of Progress in Industrial Drug Metabolism

Metabolism and Toxicity of Drugs. Two Decades of Progress in Industrial Drug Metabolism

Trend Analysis of a Database of Intravenous Pharmacokinetic Parameters in Humans for 670 Drug Compounds

Thresholds of Toxicological Concern – Setting a threshold for testing below which there is little concern

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