Regulators
Related Publications
- A practical application of two in silico systems for identification of potentially mutagenic impurities
- A rationale for determining, testing, and controlling specific impurities in pharmaceuticals that possess potential for genotoxicity
- Addressing toxicity risk when designing and selecting compounds in early drug discovery
- An evaluation of in-house and off-the-shelf in silico models: Implications on guidance for mutagenicity assessment
- An Expert System To Predict the Forced Degradation of Organic Molecules
- An in Silico Method for Predicting Ames Activities of Primary Aromatic Amines
- Assessing Confidence in Predictions.wmv
- Biotransformation Pathways of Biocides and Pharmaceuticals in Freshwater Crustaceans
- Developing Structure-Activity Relationships for the Prediction of Hepatotoxicity
- Expert Systems - The Use of Expert Systems in Drug Design-Toxicity and Metabolism
- Food for thought - A toxicology ontology roadmap
- Nexus 2 - Improved functionality to assist in ICH M7 submission
- Evaluation Of A Statistics-based Ames Mutagenicity QSAR Model And Interpretation Of The Results Obtained
- It’s difficult, but important, to make negative predictions
- Benchmarking Assessment of Salmonella Mutagenicity QSAR Models for Potential Use Under ICH M7.pdf
- Why data sharing is important - a case study using proprietary mutagenicity and skin sensitisation data.pdf
- Undertaking Expert Review under ICH M7 - A Practical Guide
- Mutagenic impurities: predicting alerting structures using in silico tools
- Practical Implementation of (Q)SAR and Expert Review for Compliance with ICH M7 Guidelines
- Predicting the Purging of Impurities within an API Synthetic Pathway
- Summation of Toxicity Data in Vitic
- Skin Sensitisation - Negative Predictions, Validations and Integrated Testing Strategies
- Assessing confidence in predictions made by knowledge-based systems
- ICH M7 Classification Workflow
- Workbook: Expert Review of EC3 Predictions - a workshop
- Nothing to report? An in silico fragmentation methodology for making explicit negative predictions of skin sensitisation
- Using Sarah Nexus Effectively: Intuitive Model Building and Interpreting Confidence
- Alternatives to in vivo testing for plant protection products
- Negative Predictions for Skin Sensitisation 47th ICGM
- Manual and Computational Methods for the Evaluation of Statistical Predictions Based on Expert Analysis
- Sarah Nexus: The Statistical System for ICH M7
- Negative Predictions for Skin Sensitisation
- Expert Review of EC3 Predictions
- Expert Review of In Silico Predictions for Skin Sensitization Potency
- Drug Master File (DMF) Holders Preferred PGI Control Strategy Under ICH M7 in Support of Abbreviated New Drug Applications (ANDAs)
- Nexus 2.2: An Overview of Key New Features - Sarah Nexus
- Nexus 2.2: An Overview of Key New Features - Derek and Meteor Nexus
- EC3: Methodology Explained
- Strain profiles: Moving beyond binary Ames classification
- Addressing the Challenge of Making Negative Predictions for Skin Sensitisation
- Derek Nexus and the Prediction of Human Skin Sensitisation Potential: An Evaluation
- Sarah Nexus Strain Information
- In Silico Prediction of DILI - Extraction of Histopathology Data from Preclinical Toxicity Data Studies of the eTOX Database for new In SIlico Models of Hepatotoxicity
- Skin sensitisation - What place does in silico have within a defined approach?
- A Defined Approach to Skin Sensitisation: Integrating Derek Nexus with In Chemico/In Vitro Assays - A Summary
- Strain Profiles: Moving Beyond Binary Ames Classification - A Summary
- Addressing the Challenge of Making Negative Predictions for Skin Sensitisation - A Summary
- An Elemental Impurities Excipient Database: A Viable Tool for ICH Q3D Drug Product Risk Assessment
- ICH M7 Overview: Predicting, Assessing, and Controlling Mutagenic Impurities from Degradation
- ICH M7 Use Cases
- Improving Toxicity Predictions through knowledge and data sharing
- Perspectivas Regulatórias sobre a Qualificação de Produtos de Degradação e Impurezas
- Supporting Lhasa Members in a Regulatory Setting
- Mutagenicity Predictions using a Statistical System
- Mirabilis: Using Mirabilis to Support Purge Arguments Under ICH M7
- Making reliable negative predictions of human skin sensitisation using an in silico fragmentation approach
- Vitic - A Faster, More Efficient Searching Experience
- A pharma-wide approach to address the genotoxicity prediction of primary aromatic amines.
- Interpreting the Sensitivity and Equivocal Settings in Sarah Nexus
- Elemental Impurities Data Sharing Initiative
- A Defined Approach for Predicting Skin Sensitisation Hazard and Potency
- Enhancing the ICH M7 Workflow through Setaria
- Principles and procedures for handling out-of-domain and indeterminate results as part of ICH M7 recommended (Q)SAR analyses
- Important considerations for the validation of QSAR models for in vitro mutagenicity
- The Liability Load and how Lhasa Limited Focuses on Reducing it
- How To - Filtering Mass Defect
- Improving In Silico Predictions in Developmental and Reproductive Toxicology
- A Suggested ICH M7 Framework Using Lhasa Limited Products
- ICHQ3D Implementation: Use of published data driven risk assessments
- Draft Reflection Paper - Non-Genotoxic Impurities
- Q3D Regulatory Case Study
- In silico prediction of Mutagenicity
- Valsartan – Implications
- Managing Mutagenic Impurity Risks in Pharmaceutical Products
- (Q)SAR Evaluation of Drug Impurities from the US FDA Scientific Perspective
- Setting the basis for the mutagenicity assessment of new dyes: Application to the Max Weaver Dye Library
- 2019 Pharmaceutical Industry and Regulators Symposium Recording - Day 1, Part 1
- 2019 Pharmaceutical Industry and Regulators Symposium Recording - Day 1, Part 2
- 2019 Pharmaceutical Industry and Regulators Symposium Recording - Day 1, Part 3
- 2019 Pharmaceutical Industry and Regulators Symposium Recording - Day 1, Part 4
- 2019 Pharmaceutical Industry and Regulators Symposium Recording - Day 2, Part 1
- 2019 Pharmaceutical Industry and Regulators Symposium Recording - Day 2, Part 2
- 2019 Pharmaceutical Industry and Regulators Symposium Recording - Day 2, Part 3
- 2019 Pharmaceutical Industry and Regulators Symposium Recording - Day 2, Part 4
- ICH M7 - Risk assessment for mutagenic impurities and control strategies
- Zeneth: an in silico tool to aid identification of degradants
- How Zeneth fits into ICH Q3D
- Use of In Silico for Assessing Degradants
- Toxicity Evaluation of Degradation Products
- RDC53: Challenges on impurities qualification
- Toxicity Studies for Degradation Impurities - An Industry Perspective
- Current advances in skin sensitization in silico predictions and their use in a defined approach
- Mutagenicity assessment strategy for pharmaceutical intermediates to aid limit setting for occupational exposure
- Predicting skin sensitisation using a decision tree integrated testing strategy with an in silico model and in chemico/in vitro assays
- Utilising Adverse Outcome Pathways as a Framework to Organise Evidence and Support Carcinogenicity Risk Assessment
- Predicting the safety of medicines in pregnancy: A workshop report
- Comparing and combining in silico outcomes and in vitro mechanism-based assays to predict genotoxicity
- In silico workflow under ICH M7 - Recording
- Aiding and standardising expert review under ICH M7 - Recording
- In silico workflow under ICH M7
- Introduction to the Lhasa Carcinogenicity Database - Recording
- Lhasa's Carcinogenicity Database - Recording
- Who is using Vitic? Infographic
- Vitic Data Sharing Benefits
- Aiding and standardising expert review under ICH M7
- The Application of Adverse Outcome Pathways (AOPs) for Risk Assessment
- An Overview of Lhasa Limited Collaborative Data Sharing Initiatives
- Controlling a cohort - Understanding the risk of nitrosamines within drug substance synthesis (Webinar Presentation Slides)
- Do all nitrosamines pose a significant level of genotoxic risk? (Webinar Presentation Slides)
- Use of Mirabilis based purge calculations to understand Nitrosamine-related risk and control strategy options
- Pathways for N-nitroso compound formation: secondary amines and beyond
- Improvements to in silico predictivity after access to proprietary data
- Setaria Product Brochure
- ICH M7 Expert Review Workshop: Resolving common prediction scenarios using automated arguments in Nexus 2.3 (Webinar Presentation Slides)
- Mirabilis Purge Ratio Infographic
- Session 1 - Creating a DART AOP network to enable improved decision-making during risk assessments - Recording
- Potential impurities in drug substances: Compound-specific toxicology limits for 20 synthetic reagents and by-products, and a class-specific toxicology limit for alkyl bromides
- Session 3 - A pharmaceutical regulator’s view on the utility of adverse outcome pathways for carcinogenicity assessment - Slides
- Session 3 - A pharmaceutical regulator’s view on the utility of adverse outcome pathways for carcinogenicity assessment - Recording
- Session 4 - The growing network of genotoxicityAOPs - Slides
- Session 4 - The growing network of genotoxicity AOPs - Recording
- Session 4 - Combining knowledge and data on an AOP framework in order to take advantage of new and emerging methods In genotoxicity assessment - Slides
- Session 4 - Combining knowledge and data on an AOP framework in order to take advantage of new and emerging methods In genotoxicity assessment - Recording
- Are all nitrosamines concerning? A review of mutagenicity and carcinogenicity data
- 2020 Zeneth 8 webinar - Zeneth 8: A re-designed and improved forced degradation prediction system for organic compounds - Recording
- 2020 Zeneth 8 webinar - Zeneth 8: A re-designed and improved forced degradation prediction system for organic compounds - Slides
- Nexus ICH M7 Expert Review Support Functionality (an infographic)
- Development of an Adverse Outcome Pathway Network to Support an Integrated Approach to Testing and Assessment of Carcinogenic Risk
- 2019 Webinar Zeneth 8: A faster, more intuitive, degradation predictive system - Recording
- Bringing Together Scientific Disciplines for Collaborative Undertakings: A Vision for Advancing the Adverse Outcome Pathway Framework
- 2021 Webinar - An overview of Effiris 2.1; An enhanced qualitative model suite for anticipating and mitigating adverse drug reactions – Slides and recording
- Case study on the use of integrated approaches to testing and assessment for the prediction of a 90-day repeated dose toxicity study (OECD 408) for 2-Ethylbutyric acid using a read-across approach from other branched carboxylic acids.
- Systematic analysis of protein targets associated with adverse events of drugs from clinical trials and postmarketing reports
- Development of an Adverse Outcome Pathway Network to Support an Integrated Approach to Testing and Assessment of Carcinogenic Risk - SOT 2021 Presentation Slides
- Data Sharing Projects using Vitic [an infographic]
- In silico prediction of N-nitrosamine degradants in APIs that possess a secondary or tertiary amine functional group
- 1. Qualifying impurities and degradation products: Anvisa's experience and technical improvement - Maria Rodrigues (Slides)
- 1. Qualifying impurities and degradation products: Anvisa's experience and technical improvement - Maria Rodrigues (Video)
- 2. Risk assessment of potential mutagenic impurities in anti-hypertensive drug products approved in Brazil - Fernanda Waechter (Slides)
- 2. Risk assessment of potential mutagenic impurities in anti-hypertensive drug products approved in Brazil - Fernanda Waechter (Video)
- 3. Case studies on the qualification of impurities - Mariah Ultramari (Slides)
- 3. Case studies on the qualification of impurities - Mariah Ultramari (Video)
- A collaborative benchmarking study to evaluate the newly released Zeneth 8
- 2021 Webinar | Accessing vital sources of long-term carcinogenicity study data with Lhasa’s Carcinogenicity Database – An update and an overview - Recording
- 2021 Webinar | Accessing vital sources of long-term carcinogenicity study data with Lhasa’s Carcinogenicity Database – An update and an overview - Slides
