Computational and Pharmacoinformatic Approaches to Oral Bioavailability Prediction

Cabrera‐Pérez, Miguel Ángel; González‐Álvarez, Isabel

doi:10.1002/9781118067598.ch33

Cited by 4 publications

(4 citation statements)

References 92 publications

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“…The three deep neural networks (DeepPharm-BA, DeepPharm-PPBR and DeepPharm-VDss&HL) were developed using the integrated transfer learning and multitask learning approach. Usually, a consensus model can take the advantages of various models. , The consensus model (DeepPharm model) took the optimal prediction for each of the four pharmacokinetic parameters from the three networks. The accuracies of the DeepPharm model are shown in Table .…”

Section: Resultsmentioning

confidence: 99%

“…Usually, a consensus model can take the advantages of various models. 20,72 The consensus model (DeepPharm model) took the optimal prediction for each of the four pharmacokinetic parameters from the three networks. The accuracies of the DeepPharm model are shown in Table 2.…”

Section: Resultsmentioning

confidence: 99%

“…The three deep neural networks (DeepPharm-BA, DeepPharm-PPBR and DeepPharm-VDss&HL) were developed using the integrated transfer learning and multitask learning approach. Usually, a consensus model can take the advantages of various models 20,72 Table 3 showed the DeepPharm model performance on the basis of the metric criteria using different benchmarks of 10%, 20% and 30%. When the benchmark was set to 20%, the accuracies of the DeepPharm model were more than 75% in VDss and HL prediction.…”

Section: Deeppharm Modelsmentioning

confidence: 99%

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An Integrated Transfer Learning and Multitask Learning Approach for Pharmacokinetic Parameter Prediction

Ye¹,

Yang

et al. 2018

Mol. Pharmaceutics

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Note: Zhuyifan Ye and Yilong Yang made equal contribution to the manuscript. ABSTRACT:Background: Pharmacokinetic evaluation is one of the key processes in drug discovery and development.However, current absorption, distribution, metabolism, excretion prediction models still have limited accuracy.Aim: This study aims to construct an integrated transfer learning and multitask learning approach for developing quantitative structure-activity relationship models to predict four human pharmacokinetic parameters. Methods:A pharmacokinetic dataset included 1104 U.S. FDA approved small molecule drugs. The dataset included four human pharmacokinetic parameter subsets (oral bioavailability, plasma protein binding rate, apparent volume of distribution at steady-state and elimination half-life). The pre-trained model was trained on over 30 million bioactivity data. An integrated transfer learning and multitask learning approach was established to enhance the model generalization. Results: The pharmacokinetic dataset was split into three parts (60:20:20) for training, validation and test by the improved Maximum Dissimilarity algorithm with the representative initial set selection algorithm and the weighted distance function. The multitask learning techniques enhanced the model predictive ability. The integrated transfer learning and multitask learning model demonstrated the best accuracies, because deep neural networks have the general feature extraction ability, transfer learning and multitask learning improved the model generalization. Conclusions:The integrated transfer learning and multitask learning approach with the improved dataset splitting algorithm was firstly introduced to predict the pharmacokinetic parameters. This method can be further employed in drug discovery and development.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

“…The three deep neural networks (DeepPharm-BA, DeepPharm-PPBR and DeepPharm-VDss&HL) were developed using the integrated transfer learning and multitask learning approach. Usually, a consensus model can take the advantages of various models 20,72 Table 3 showed the DeepPharm model performance on the basis of the metric criteria using different benchmarks of 10%, 20% and 30%. When the benchmark was set to 20%, the accuracies of the DeepPharm model were more than 75% in VDss and HL prediction.…”

Section: Deeppharm Modelsmentioning

confidence: 99%

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An Integrated Transfer Learning and Multitask Learning Approach for Pharmacokinetic Parameter Prediction

Ye¹,

Yang

et al. 2018

Mol. Pharmaceutics

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“…La Infección del Sitio Quirúrgico (ISQ) no solo es objeto de prevención postoperatoria, sino también de prevención preoperatoria y perioperatoria, y su aparición está en relación a factores asociados que favorecen la colonización de microorganismos dentro de la herida quirúrgica. (Cabrera González et al,2015); como aquellos derivados de las características generales del paciente, como aquellos derivados de las comorbilidades y como aquellos derivados del acto quirúrgico. Entre los factores asociados con el paciente encontramos a la Edad, Sexo, Índice de Masa Corporal y al Tabaquismo (Noailles et al,2016) y (María Barbero et al,2016).…”

Section: Introductionunclassified

Factores asociados a infección de sitio operatorio (ISO) en cirugía de fractura de cadera

Barrientos-Ramos

2023

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El objetivo general de la presente investigación fue analizar jurídicamente el déficit jurídico de la tenencia compartida de menores concebidos dentro del matrimonio civil. La investigación se desarrolló desde el paradigma cuantitativo, además se enmarcó desde un diseño documental-bibliográfico, mediante la indagación, recolección y análisis crítico documental y referencial bibliográfico, basándose en la exploración metódica, rigurosa y profunda de diversas fuentes tales como artículos, trabajos arbitrados, tesis, leyes, convenios. Se aplicó una encuesta a 23 padres usuarios del sistema judicial de la Universidad Católica de Cuenca Extensión Cañar, en el periodo 2017-2018. Se concluye que, es necesario considerar que la ley, al no contemplar la posibilidad de la guarda y custodia compartida como parte de las resoluciones emitidas por un juez o mediante acuerdo, de forma explícita en el CONA, y las regulaciones legales que derivan de ella (garantías de cumplimiento, control, tiempos de cumplimiento de procesos, entre otros aspectos).

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Dendrimers-Mediated Delivery of Phytoconstituents

Rai,

Medicherla,

Pooja

et al. 2024

Nanotechnology Based Delivery of Phytoconstituents and Cosmeceuticals

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Computational and Pharmacoinformatic Approaches to Oral Bioavailability Prediction

Cited by 4 publications

References 92 publications

An Integrated Transfer Learning and Multitask Learning Approach for Pharmacokinetic Parameter Prediction

An Integrated Transfer Learning and Multitask Learning Approach for Pharmacokinetic Parameter Prediction

Factores asociados a infección de sitio operatorio (ISO) en cirugía de fractura de cadera

Dendrimers-Mediated Delivery of Phytoconstituents

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