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
PSI Introduction to Industry Training (ITIT) Course - 2026/2027
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.
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.
Our monthly webinar series allows attendees to gain practical knowledge and skills in open-source coding and tools, with a focus on applications in the pharmaceutical industry. This month’s session, “Graphics Basics,” will introduce the fundamentals of producing graphics using the ggplot2 package.
Connecting the False Discovery Rate to Shrunk Estimates
A 1 hour online event, that includes a presentation followed by Q&A.
This talk will explore the “replication crisis” in science, focusing on how testing large numbers of hypotheses can lead to false positive findings. It introduces key statistical approaches—False Discovery Rate (FDR) and shrinkage methods—to address this issue, and explains their conceptual foundations and connections. The session will also highlight how these tools can be understood within an empirical-Bayesian framework, linking significance testing with effect size estimation.
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 Book Club: The AI Con – Joint with ASA Book Club
The Guardian described the authors of this book as refreshingly sarcastic! What is sold to us as AI, they announce, is just "a bill of goods": "A few major well-placed players are poised to accumulate significant wealth by extracting value from other people's creative work, personal data, or labour, and replacing quality services with artificial facsimiles."
PSI Book Club: Another Door Opens – Book Club Special Event
This is a Book Club Special Event in response to the changes in our industry and as a supportive move to create community and connection for those navigating redundancy and uncertainty. Read the book in advance of the book club session then join the zoom call to discuss ideas. There will be breakout groups to connect with others, exchange experiences of how the book has helped, and offer support.
PSI Book Club: Change: How organisations achieve hard-to-image results in uncertain and volatile times
Organizations have to adapt to the transforming landscape of our industry to ensure they continue to be successful in the future. Many of us are feeling the impact of organizational change. By reading John P Kotter’s book we can understand about organizational change and learn how to thrive, rather than just survive, through change.
Change, by John P Kotter (and his team), is a summary of all that he has learned over his decades of research and leading change. His book describes why many current approaches to change are inadequate and explains why new solutions need to give people a voice and a role in a new, change-embracing organization.
Develop your understanding of organisational change and become empowered to be part of your organisation’s change, by reading Change by John P Kotter and joining the Sept-Dec 2025 book club. You will be invited to join facilitated discussions of the concepts and ideas and apply knowledge from the book in-between sessions.
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 networking event is aimed at statisticians that are new to the pharmaceutical industry who wish to meet colleagues from different companies and backgrounds.
A Lead Statistician builds and leads teams of statisticians and representatives from other functions and ensures the use of appropriate and efficient statistical analysis methods during development of Bayer products
As a Statistical Programmer II at ICON, you will play a vital role in the development, validation, and execution of statistical programs to support clinical trial analysis and reporting.
Leeds Clinical Trials Research Unit - Undergraduate Internships
The Internship is open to undergraduate students in the penultimate year of their undergraduate degree at a UK university, in a mathematical, statistical, or quantitative related field.
: We have an exciting opportunity for an Associate Director (AD), Statistical Programming, to join a passionate team within Advanced Quantitative Sciences- Development.
Novartis - Senior Principal Statistical Programmer
We have an exciting opportunity for a Senior Principal Statistical Programmer, to join a passionate team within Advanced Quantitative Sciences – Development.
Pierre Fabre - Clinical Development Safety Statistics Expert M/F
We are seeking a highly skilled and proactive Clinical Development Safety Statistics Expert to join our Biometry Department and the Biometry Leadership Team based in Toulouse (31, Oncopole) or Boulogne (92).
Pierre Fabre - Lead Statistician – Real World Evidence -CDI- M/F
Pierre Fabre Laboratories are hiring a highly skilled and experienced Lead Statistician – Real World Evidence (RWE) to join the Biometry Department, part of the Data Science & Biometry Department, based in Toulouse (Oncopôle) or Boulogne.
Pierre Fabre - Lead Statistician- Clinical Trials M/F
We are seeking a highly skilled and experienced Lead Statistician in Clinical Trials to join our Biometry Department based in Toulouse (31, Oncopole) or Boulogne (92).
Veramed - Manager/Senior Manager Statistics for Consultancy Team
An opportunity has arisen for a Statistician to join Veramed’s Statistical Consultancy Business Unit full time. The opportunity will be to provide statistical support to a variety of clients.
As a Senior Statistician, you will provide high-quality statistical support to one of our key-FSP clients. At Senior level you may also take on a supervisory role (e.g. line management and/or project management), depending on your experience and interest.
As a Senior Statistician at Viatris, you will take a leading role in designing clinical studies, guiding statistical strategy, and ensuring that statistical deliverables meet the highest scientific and regulatory standards.