BDDCS, the Rule of 5 and drugability
The Rule of 5 methodology appears to be as useful today in defining drugability as when it
was proposed, but recognizing that the database that we used includes only drugs that …
was proposed, but recognizing that the database that we used includes only drugs that …
In vitro to in vivo extrapolation for high throughput prioritization and decision making
SM Bell, X Chang, JF Wambaugh, DG Allen, M Bartels… - Toxicology in vitro, 2018 - Elsevier
In vitro chemical safety testing methods offer the potential for efficient and economical tools
to provide relevant assessments of human health risk. To realize this potential, methods are …
to provide relevant assessments of human health risk. To realize this potential, methods are …
The biopharmaceutics classification system (BCS) and the biopharmaceutics drug disposition classification system (BDDCS): beyond guidelines
A Charalabidis, M Sfouni, C Bergström… - International journal of …, 2019 - Elsevier
The recent impact of the Biopharmaceutics Classification System (BCS) and the
Biopharmaceutics Drug Disposition Classification System (BDDCS) on relevant scientific …
Biopharmaceutics Drug Disposition Classification System (BDDCS) on relevant scientific …
[HTML][HTML] Effective exposure of chemicals in in vitro cell systems: A review of chemical distribution models
Nominal effect concentrations from in vitro toxicity assays may lead to inaccurate estimations
of in vivo toxic doses because the nominal concentration poorly reflects the concentration at …
of in vivo toxic doses because the nominal concentration poorly reflects the concentration at …
A next-generation risk assessment case study for coumarin in cosmetic products
MT Baltazar, S Cable, PL Carmichael… - Toxicological …, 2020 - academic.oup.com
Abstract Next-Generation Risk Assessment is defined as an exposure-led, hypothesis-driven
risk assessment approach that integrates new approach methodologies (NAMs) to assure …
risk assessment approach that integrates new approach methodologies (NAMs) to assure …
The critical role of passive permeability in designing successful drugs
Passive permeability is a key property in drug disposition and delivery. It is critical for
gastrointestinal absorption, brain penetration, renal reabsorption, defining clearance …
gastrointestinal absorption, brain penetration, renal reabsorption, defining clearance …
Clearance in drug design: miniperspective
DA Smith, K Beaumont, TS Maurer… - Journal of Medicinal …, 2018 - ACS Publications
Due to its implications for both dose level and frequency, clearance rate is one of the most
important pharmacokinetic parameters to consider in the design of drug candidates …
important pharmacokinetic parameters to consider in the design of drug candidates …
Physiologically‐based pharmacokinetic models for evaluating membrane transporter mediated drug–drug interactions: current capabilities, case studies, future …
KS Taskar, V Pilla Reddy, H Burt… - Clinical …, 2020 - Wiley Online Library
Physiologically‐based pharmacokinetic (PBPK) modeling has been extensively used to
quantitatively translate in vitro data and evaluate temporal effects from drug–drug …
quantitatively translate in vitro data and evaluate temporal effects from drug–drug …
Estimating human ADME properties, pharmacokinetic parameters and likely clinical dose in drug discovery
AJ Lucas, JL Sproston, P Barton… - Expert opinion on drug …, 2019 - Taylor & Francis
Introduction: Prediction of human absorption, distribution, metabolism, and excretion
(ADME) properties, therapeutic dose and exposure has become an integral part of …
(ADME) properties, therapeutic dose and exposure has become an integral part of …
Evaluation of the success of high-throughput physiologically based pharmacokinetic (HT-PBPK) modeling predictions to inform early drug discovery
Minimizing in vitro and in vivo testing in early drug discovery with the use of physiologically
based pharmacokinetic (PBPK) modeling and machine learning (ML) approaches has the …
based pharmacokinetic (PBPK) modeling and machine learning (ML) approaches has the …