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Positive Stats About PK/PD Modeling in the Pharmaceutical Industry

Pharmacokinetic/pharmacodynamic (PK/PD) modeling and simulation (M&S) is an important tool that can help researchers gain a better understanding of their drug’s efficacy— especially at the early stages of drug development. In this blog post, I’ll discuss some positive statistics uncovered in a recent IQ Consortium survey that examined the current landscape for preclinical PK/PD modeling and simulation in the pharmaceutical industry.

How was the survey conducted?

The mission of the International Consortium for Innovation and Quality in Pharmaceutical Development (IQ Consortium) is to support science-based standards and regulations for the global pharma industry. Its membership is composed of representatives from pharmaceutical and biotechnology companies. The survey was conducted in the fall of 2013 via an online questionnaire. It focused on five different areas:

  • Demographics: General characteristics of organizations and the composition of preclinical PK/PD modeling groups
  • Organizational structure: How these groups fit within the larger organizational structure
  • Operating logistics: Practical, operational aspects of preclinical PK/PD M&S groups
  • Applications: How companies are using information gleaned from PK/PD M&S
  • Impact/perspectives: How preclinical PK/PD M&S is perceived in organizations and its role in decision making

Demographic and organizational structure trends

Responses were received from 22 pharma companies ranging from small (fewer than 500 employees) to large (greater than 10,000 employees) organizations. The majority of the US-based companies reported having research programs for both small molecules and biologics; this reflects a general industry trend of having diversified portfolios. Companies tended to have more clinical modelers than preclinical modelers. The greater number of clinical modelers may be due to the history of PK/PD modeling originating in clinical groups with a more recent spread to preclinical research groups. The survey also assessed how preclinical PK/PD modelers are organized within companies. In general, preclinical PK/PD M&S appears to be a desired skill for members of DMPK groups, rather than a dedicated activity.


Operating logistics trends

This part of the survey was devoted to quantifying the timing and outsourcing of preclinical PK/PD M&S. It also included a question on the prevalence of use of various software packages. I am especially proud of these findings:

Applications, impact and perspectives on preclinical PK/PD M&S

With approximately 68% of surveyed companies using preclinical PK/PD analysis in all therapeutic areas, this is clearly a tool with broad applications. Indeed, 86% of companies reported that preclinical PK/PD analyses significantly impacted their approach to drug development. Finally, almost three quarters of companies indicate including preclinical PK/PD analysis in regulatory submissions. We can almost certainly expect that there will need to be continued recruitment and training of scientists to fully support the use of preclinical PK/PD M&S as a tool to better understand drug efficacy and increase the chances for regulatory approval. For more information, read the AAPS Journal article, “Preclinical Pharmacokinetic/Pharmacodynamic Modeling and Simulation in the Pharmaceutical Industry: An IQ Consortium Survey Examining the Current Landscape.”

Do you have the tools needed to support the preclinical group at your organization?

Humans have a distinct biochemistry, anatomy, and physiology compared to other animals. Predictions of a drug’s PK profile in humans based on animal PK data must account for these differences. Allometric scaling is used to predict differences in PK parameters based only on size.

Getting the dose right for FIM trials is critical. Allometric scaling calculations are performed frequently in preclinical groups as they study various drugs in different model organisms. Read this case study to learn about an application that automates FIM allometric scaling using preclinical PK data.

About the author

By: Suzanne Minton

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