Certara® has announced that Clinical Pharmacology & Therapeutics has published its “Letter to the Editor” describing the important role that quantitative systems pharmacology (QSP) can play in defining dosing criteria for first-in-human (FIH) clinical trials, together with the European Medicines Agency’s (EMA’s) response.
QSP combines computational modeling 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 mechanism 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 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.
Certara has established two QSP Consortia during the past two years to develop an Immunogenicity and an Immuno-oncology Simulator, respectively.
Professor Piet van der Graaf, PharmD, PhD, Certara Vice President, QSP said, “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. 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.”
The European Medicines Agency said that it “welcomed the initiative shown” in Certara’s letter. 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.”