Matthew Clark, Scientific Services, R&D Solutions, Elsevier, Philadelphia, USA & Thomas Steger-Hartmann, Investigational Toxicology, Bayer AG, Berlin, Germany
Abstract:
Attrition of drug candidates in clinical trials due to safety issues still contributes to a significant part of project closures besides other reasons such as the lack of efficacy, PK issues or strategic reasons. While failure of a candidate during preclinical development is a reflection of the primary task of the functions involved in this phase (i.e. toxicology, safety pharmacology and DMPK), failures during the later clinical phases often raise the question whether the preclinical safety studies are sufficiently predictive for the human outcome. Due to the fact that the First-in-Man study requires pivotal animal studies normally performed in two species, the focus of analysis of the debated predictivity centers around these animal studies. After the seminal study from Olson et al. (2000) numerous publications have shown that animal toxicity studies are predictive to a certain extent and that the predictivity varies among endpoints, some of them such as hematological, gastrointestinal, and cardiovascular events being better predicted than others (e.g. cutaneous adverse events). Most of these analyses compared the preclinical – clinical correlation for a rather limited set of compounds (<150) or for specific field of indications. The authors will present the results of this purely statistical approach based on data available for 3290 compounds in the commercial database Pharmapendium. The work provides answers to the implication of an observation in an animal for human risk and more specifically to the question whether concordance, i.e. the translatability of an observation from animal to human is dependent on the animal species. The statistical methods and procedures will be described in detail.
Registration:
Registration has now closed.
Scientific Meetings
How Well do Toxicology Studies Predict Clinical Safety Outcome? – A Translational Safety Big Data Analysis
Matthew Clark, Scientific Services, R&D Solutions, Elsevier, Philadelphia, USA & Thomas Steger-Hartmann, Investigational Toxicology, Bayer AG, Berlin, Germany
Abstract:
Attrition of drug candidates in clinical trials due to safety issues still contributes to a significant part of project closures besides other reasons such as the lack of efficacy, PK issues or strategic reasons. While failure of a candidate during preclinical development is a reflection of the primary task of the functions involved in this phase (i.e. toxicology, safety pharmacology and DMPK), failures during the later clinical phases often raise the question whether the preclinical safety studies are sufficiently predictive for the human outcome. Due to the fact that the First-in-Man study requires pivotal animal studies normally performed in two species, the focus of analysis of the debated predictivity centers around these animal studies. After the seminal study from Olson et al. (2000) numerous publications have shown that animal toxicity studies are predictive to a certain extent and that the predictivity varies among endpoints, some of them such as hematological, gastrointestinal, and cardiovascular events being better predicted than others (e.g. cutaneous adverse events). Most of these analyses compared the preclinical – clinical correlation for a rather limited set of compounds (<150) or for specific field of indications. The authors will present the results of this purely statistical approach based on data available for 3290 compounds in the commercial database Pharmapendium. The work provides answers to the implication of an observation in an animal for human risk and more specifically to the question whether concordance, i.e. the translatability of an observation from animal to human is dependent on the animal species. The statistical methods and procedures will be described in detail.
Registration:
Registration has now closed.
Training Courses
How Well do Toxicology Studies Predict Clinical Safety Outcome? – A Translational Safety Big Data Analysis
Matthew Clark, Scientific Services, R&D Solutions, Elsevier, Philadelphia, USA & Thomas Steger-Hartmann, Investigational Toxicology, Bayer AG, Berlin, Germany
Abstract:
Attrition of drug candidates in clinical trials due to safety issues still contributes to a significant part of project closures besides other reasons such as the lack of efficacy, PK issues or strategic reasons. While failure of a candidate during preclinical development is a reflection of the primary task of the functions involved in this phase (i.e. toxicology, safety pharmacology and DMPK), failures during the later clinical phases often raise the question whether the preclinical safety studies are sufficiently predictive for the human outcome. Due to the fact that the First-in-Man study requires pivotal animal studies normally performed in two species, the focus of analysis of the debated predictivity centers around these animal studies. After the seminal study from Olson et al. (2000) numerous publications have shown that animal toxicity studies are predictive to a certain extent and that the predictivity varies among endpoints, some of them such as hematological, gastrointestinal, and cardiovascular events being better predicted than others (e.g. cutaneous adverse events). Most of these analyses compared the preclinical – clinical correlation for a rather limited set of compounds (<150) or for specific field of indications. The authors will present the results of this purely statistical approach based on data available for 3290 compounds in the commercial database Pharmapendium. The work provides answers to the implication of an observation in an animal for human risk and more specifically to the question whether concordance, i.e. the translatability of an observation from animal to human is dependent on the animal species. The statistical methods and procedures will be described in detail.
Registration:
Registration has now closed.
Journal Club
How Well do Toxicology Studies Predict Clinical Safety Outcome? – A Translational Safety Big Data Analysis
Matthew Clark, Scientific Services, R&D Solutions, Elsevier, Philadelphia, USA & Thomas Steger-Hartmann, Investigational Toxicology, Bayer AG, Berlin, Germany
Abstract:
Attrition of drug candidates in clinical trials due to safety issues still contributes to a significant part of project closures besides other reasons such as the lack of efficacy, PK issues or strategic reasons. While failure of a candidate during preclinical development is a reflection of the primary task of the functions involved in this phase (i.e. toxicology, safety pharmacology and DMPK), failures during the later clinical phases often raise the question whether the preclinical safety studies are sufficiently predictive for the human outcome. Due to the fact that the First-in-Man study requires pivotal animal studies normally performed in two species, the focus of analysis of the debated predictivity centers around these animal studies. After the seminal study from Olson et al. (2000) numerous publications have shown that animal toxicity studies are predictive to a certain extent and that the predictivity varies among endpoints, some of them such as hematological, gastrointestinal, and cardiovascular events being better predicted than others (e.g. cutaneous adverse events). Most of these analyses compared the preclinical – clinical correlation for a rather limited set of compounds (<150) or for specific field of indications. The authors will present the results of this purely statistical approach based on data available for 3290 compounds in the commercial database Pharmapendium. The work provides answers to the implication of an observation in an animal for human risk and more specifically to the question whether concordance, i.e. the translatability of an observation from animal to human is dependent on the animal species. The statistical methods and procedures will be described in detail.
Registration:
Registration has now closed.
Webinars
How Well do Toxicology Studies Predict Clinical Safety Outcome? – A Translational Safety Big Data Analysis
Matthew Clark, Scientific Services, R&D Solutions, Elsevier, Philadelphia, USA & Thomas Steger-Hartmann, Investigational Toxicology, Bayer AG, Berlin, Germany
Abstract:
Attrition of drug candidates in clinical trials due to safety issues still contributes to a significant part of project closures besides other reasons such as the lack of efficacy, PK issues or strategic reasons. While failure of a candidate during preclinical development is a reflection of the primary task of the functions involved in this phase (i.e. toxicology, safety pharmacology and DMPK), failures during the later clinical phases often raise the question whether the preclinical safety studies are sufficiently predictive for the human outcome. Due to the fact that the First-in-Man study requires pivotal animal studies normally performed in two species, the focus of analysis of the debated predictivity centers around these animal studies. After the seminal study from Olson et al. (2000) numerous publications have shown that animal toxicity studies are predictive to a certain extent and that the predictivity varies among endpoints, some of them such as hematological, gastrointestinal, and cardiovascular events being better predicted than others (e.g. cutaneous adverse events). Most of these analyses compared the preclinical – clinical correlation for a rather limited set of compounds (<150) or for specific field of indications. The authors will present the results of this purely statistical approach based on data available for 3290 compounds in the commercial database Pharmapendium. The work provides answers to the implication of an observation in an animal for human risk and more specifically to the question whether concordance, i.e. the translatability of an observation from animal to human is dependent on the animal species. The statistical methods and procedures will be described in detail.
Registration:
Registration has now closed.
Careers Meetings
How Well do Toxicology Studies Predict Clinical Safety Outcome? – A Translational Safety Big Data Analysis
Matthew Clark, Scientific Services, R&D Solutions, Elsevier, Philadelphia, USA & Thomas Steger-Hartmann, Investigational Toxicology, Bayer AG, Berlin, Germany
Abstract:
Attrition of drug candidates in clinical trials due to safety issues still contributes to a significant part of project closures besides other reasons such as the lack of efficacy, PK issues or strategic reasons. While failure of a candidate during preclinical development is a reflection of the primary task of the functions involved in this phase (i.e. toxicology, safety pharmacology and DMPK), failures during the later clinical phases often raise the question whether the preclinical safety studies are sufficiently predictive for the human outcome. Due to the fact that the First-in-Man study requires pivotal animal studies normally performed in two species, the focus of analysis of the debated predictivity centers around these animal studies. After the seminal study from Olson et al. (2000) numerous publications have shown that animal toxicity studies are predictive to a certain extent and that the predictivity varies among endpoints, some of them such as hematological, gastrointestinal, and cardiovascular events being better predicted than others (e.g. cutaneous adverse events). Most of these analyses compared the preclinical – clinical correlation for a rather limited set of compounds (<150) or for specific field of indications. The authors will present the results of this purely statistical approach based on data available for 3290 compounds in the commercial database Pharmapendium. The work provides answers to the implication of an observation in an animal for human risk and more specifically to the question whether concordance, i.e. the translatability of an observation from animal to human is dependent on the animal species. The statistical methods and procedures will be described in detail.
Registration:
Registration has now closed.
Upcoming Events
Joint PSI/EFSPI Visualisation SIG 'Wonderful Wednesday' Webinars
Our monthly webinar explores examples of innovative data visualisations relevant to our day to day work. Each month a new dataset is provided from a clinical trial or other relevant example, and participants are invited to submit a graphic that communicates interesting and relevant characteristics of the data.
PSI Webinar: Development of Gene Therapies: Strategic, Scientific, Regulatory and Access Considerations
This webinar will cover the history of cell/gene therapy, major regulatory advances, the role of quantitative scientists in drug development of these novel therapeutics, and discuss opportunities for innovation and product advancement.
This networking event is aimed at statisticians that are new to the pharmaceutical industry who wish to meet colleagues from different companies and backgrounds.
PSI Introduction to Industry Training (ITIT) Course - 2024/2025
An introductory course giving an overview of the pharmaceutical industry and the drug development process as a whole, aimed at those with 1-3 years' experience. It comprises of six 2-day sessions covering a range of topics including Research and Development, Toxicology, Data Management and the Role of a CRO, Clinical Trials, Reimbursement, and Marketing.
PSI Training Course: Regulatory Guidelines for Statisticians
This 2-day course is designed to provide a comprehensive understanding of the regulatory guidelines affecting statisticians in the pharmaceutical industry, including the latest updates in the field. The course will cover key International Council for Harmonisation (ICH) guidelines and other key regional regulatory agency documents.
Joint PSI/EFSPI Pre-Clinical SIG Webinar: Virtual Control Groups in Toxicity Studies
Lea Vaas will present how replacement of concurrent control animals by Virtual Control Groups (VCGs) in systemic toxicity studies may help in contributing to the 3R's principle of animal experimentation: Reduce, Refine, Replace.
This networking event is aimed at statisticians that are new to the pharmaceutical industry who wish to meet colleagues from different companies and backgrounds.
This apprenticeship role offers a unique opportunity to learn and work in a global healthcare consultancy company alongside a team of statisticians, psychometricians and programmers.
Statisticians in the Pharmaceutical Industry Executive Office: c/o MCI UK Ltd | Unit 24/22 South | Building 4000 | Langstone Park| Langstone Road | Havant | PO9 1SA | UK