QSP modelling predicts pharmacodynamic range of a drug

Published: 27-Jul-2018

Certara experts highlight quantitative systems pharmacology’s role in first-in-human clinical trials

Certara, specialist in model-informed drug development, regulatory science, market access and real-world evidence services, has described the important role that quantitative systems pharmacology (QSP) can play in defining dosing criteria for first-in-human (FIH) clinical trials.1

QSP combines computational modelling and experimental methods to examine the mechanistic relationships between a drug, the biological system and the disease process.

QSP integrates quantitative drug data with knowledge of the drug’s mechsanism of action. It facilitates the evaluation of complex, heterogeneous diseases such as cancer, immunological, metabolic and central nervous system diseases that require multiple therapies.

Understanding mechanistic pharmacodynamics is a major challenge in drug development and one that QSP is ideally positioned to address. Although it is a relatively new technology, QSP is already being recognised by industry and global regulatory agencies as a valuable, scientific approach that can increase understanding of disease biology, improve target selection, and help to ensure drug safety and efficacy in clinical trials.

“We are proposing that QSP be used in the efficient design of FIH clinical trials to help determine the starting dose and subsequent dose escalations and ensure the best possible protection for human subjects,” said Professor Piet van der Graaf, PharmD, PhD, Certara Vice President, QSP.

“If FIH doses are estimated only on the basis of preclinical data, without including mechanistic model-based approaches such as QSP, investigators are not making the best use of all the available data.”

Certara’s QSP approach builds upon the EMA FIH guidance, which went into effect early in 2018 and puts more emphasis on the better use of preclinical data to guide rational dose selection in FIH studies.2,3 This EMA guideline was issued in response to the tragic outcome of the fatty acid amide hydrolase (FAAH) inhibitor BIAL 10-2474 FIH trial in 2016.

“We had a QSP model that could have been used to improve understanding of BIAL 10-2474’s pharmacodynamic range and set stopping criteria well below the (fatal) highest dose tested,” said Professor van der Graaf. “We are working to increase awareness of these valuable QSP tools to help prevent similar tragedies from occurring."

Certara is routinely employing its QSP model to support clinical trial designs for a variety of mechanisms and indications.4 QSP models, which are modular in format, can be updated and extended whenever new biological insights become available. Certara has also developed unique methods to develop simpler versions of QSP models to inform pharmacometric applications in clinical development.

The EMA stated: “Mechanistic models leading to further refinement of the predictions from standard preclinical procedures and the use of additional drug-specific or mechanistic data or considerations are encouraged. Relevant models holding the potential to better reflect a substance’s effects in human tissues and potentially improve safety of trial participants will be supported by EMA.”

Certara has already established two QSP Consortia during the past 2 years, in partnership with leading biopharmaceutical companies, to develop an Immunogenicity and an Immuno-oncology Simulator, respectively. Modelled after Certara’s highly successful, Simcyp Consortium, QSP Consortia members are working together in a pre-competitive environment to advance development of these important new simulators.


  1. van der Graaf, P. & Benson, N. The role of quantitative systems pharmacology (QSP) in the design of first-in-human trials. Clin. Pharmacol. Ther. (2018) https://doi.org/10.1002/cpt.1145.
  2. EMA Guideline on strategies to identify and mitigate risks for first-in-human and early clinical trials with investigational medicinal products (http://www.ema.europa.eu/ema/index.jsp?curl=pages/regulation/general/general_content_001001.jsp&mid=WC0b01ac0580029570).
  3. Benson, N. et al. A systems pharmacology perspective on the clinical development of fatty acid amide hydrolase inhibitors for pain. CPT Pharmacometrics Syst. Pharmacol. 3, e91 (2014). https://doi.org/10.1038/psp.2013.72.
  4. Matsuura, T., Walker, M., Karmani, D., Benson, N. & van der Graaf, P.H. Clinical validation of a quantitative systems pharmacology (QSP) model for nerve-growth-factor (NGF) therapies. PAGE 27, Abstr 8465 (2018). www.page-meeting.org/?abstract=8465.

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