Clinical trials continue to experience high attrition rates, with lack of efficacy being one of the leading causes of failure. However, in many cases, these failures do not reflect a lack of drug efficacy, but rather limitations in translational biomarker strategies and selection of disease-relevant pharmacodynamic (PD) biomarkers, suboptimal dose selection, or inadequate patient stratification.

To address this challenge, the pharmaceutical industry is increasingly adopting Model-Informed Drug Development (MIDD), an approach strongly encouraged by regulatory agencies to enhance development efficiency, reduce costs, accelerate timelines and support evidence-based decision-making throughout the drug development process.

At Evotec, multidisciplinary teams leverage mechanistic modelling approaches including pharmacokinetic/pharmacodynamic (PK/PD) modelling and Quantitative Systems Pharmacology (QSP) to quantitatively characterise and bridge the gap between drug exposure, biomarker response and clinical outcome. Particular emphasis is placed on identifying and validating disease-relevant PD biomarkers, ensuring that measured biological responses are informative for the intended therapeutic mechanism and clinical hypothesis.

By integrating how drugs interact with complex biological systems, these model-informed approaches optimise dose selection, strengthen translational biomarker strategies and enable patient stratification. Together, these capabilities support robust, data-driven decision-making across the development continuum, ultimately increasing the probability of clinical success.

Q&A with the speakers follows the presentation.

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