Numbers of applications (NDA, ANDA) supported by PBPK modeling has increased significantly since 2008.
In Silico and in Vitro Simulations to Predict Idiosyncratic DILI: What is on the Horizon?
Multiple species: human, rat, mouse, and dog, Population variability, The three primary acinar zones of liver represented, Essential cellular processes represented to multiple scales in interacting submodels...
Assessing and Managing DILI Risk in Trials: A Consultant’s Perspective
DILI typically has drug-specific “signatures”: Hepatocellular, cholestatic, mixed (R-value), Latency “window,” Rate of progression, rate of resolution, Extra-hepatic manifestations (e.g. hypersensitivity signs)
How to Understand Aqueous Ionization and Its Influence on Key Physical Properties of Drugs
Part I “You Must Unlearn What You Have Learned”: Clearing Up Myths About Aqueous Ionization of Drugs
Validating property and metabolite predictions for some novel antimalarial compounds
Metabolite Assignment Considerations & Caveats: One compound can (and often does) give rise to two or more mass spectral (MS) peaks - but there should only be one HPLC peak per compound...
Developing PBPK for Ocular Delivery
Cooperation grant with the FDA (2014‐2019) a 4‐year funded collaborative project with the FDA Office of Generic Drugs on the development of mechanistic models for ocular delivery
Proprietary modeling platforms to support regulatory interactions: A vendor’s perspective
Proprietary modeling platforms are driving the vast majority of internal R&D activities at companies.
Assessing Effects of Sublingual BHV-0223 and Oral Riluzole on Liver Function Test Parameters
DILIsym is a mechanistic, mathematical model that has been constructed to support pharmaceutical risk assessment and decision making
Applying in silico-in vitro-in vivo Extrapolation (IS-IV-IVE) Techniques to Predict Exposure and Guide Risk Assessment
Applying IS-IV-IVE Techniques to Predict Exposure and Guide Risk Assessment
Game Changing: The Latest Developments in the Machine Learning/ PBPK/QST Modeling Space
Simulations Plus continues to lead in the areas of PBPK modeling to support regulatory submissions and alternatives to animal testing.
DILIsym 8A New Features for Predicting & Understand Drug-Induced Liver Injury
So how can DILIsym help my organization? Predict DILI liabilities beforehand and save $$$, Choose the lead candidate most likely to succeed from a DILI standpoint, Communicate with regulators on safety issues with information they have requested from others numerous times and from a platform they license (FDA) & keep patients safer.
An Update to the DILI-sim Initiative and the DILIsym Tool
Identifying Right Target, Right Drug, Right Dose and Right Patient
Use of a Quantitative Systems Pharmacology (QSP) Model to Predict Liver Toxicity in Simulated Populations
DILIsym is a mechanistic, mathematical model that has been constructed to support pharmaceutical risk assessment and decision making.
Mechanisms Underlying Species Differences in Hepatotoxicity
Quantitative Systems Toxicology (QST) modeling can explain and predict species differences in dose-dependent hepatotoxicity.
Assessing the Role of Intracellular Binding Protein in Drug-Induced Bile Acid Transporter Inhibition Using QuantiativeSystems Pharmacology (QSP) Modeling
DILIsym Is Used to Predict Bile-Acid Mediated Drug-Induced Liver Injury
HTPK: Conducting PK modeling and simulations at high speed
HTPK lightens the burden of collecting and preparing input variables for full blown PK simulations by using structure-based predictions.
Using in-silico Models to Integrate in-vitro Data to Support Virtual Trials for Cost Effective Drug Development
PBPK models allow incorporating different types of in vitro measurements into single platform to account for all processes affecting drug’s absorption, distribution and elimination.
Use of In Silico Mechanistic Models to Support Interspecies Extrapolation of Oral Bioavailability and Formulation Optimization: Model Example Using GastroPlus™
PBPK models provide unique platform to combine information from in vitro, in silico and animal assays for accurate prediction of complex drug behavior in vivo