Differentiate or die: Preclinical and early clinical assessment of differentiation potential via modeling

The need for differentiated drugs is more pressing than ever. Patients and physicians are more informed than ever about treatment choices and solicit comparative information. Regulators are advocating the standardization of active control/comparator arms in clinical trials. Payers have adapted health technology assessment decision trees balancing pharmacological differentiation with cost. Pharmaceutical companies face fierce competition from within-industry competitors racing to raise the efficacy/safety bar with better drugs and from generics and biosimilars competing on price. In a world where "good" is no longer "good enough" how does one assess the potential of a drug candidate at every step of pharmaceutical R&D?
Systems pharmacology is ideally suited for the task at hand: a knowledge- rather than data-driven integration and analysis of all available information (disease/target, preclinical/early clinical, alloclinical) within a quantitative framework that can be used to quantify uncertainty and benchmark the differentiation potential against a desired target efficacy/safety profile or against competitor drugs. The presentation will review the landscape that makes necessary this shift in R&D mentality and will discuss (masked) examples from UCB's internal modeling activities from candidate selection to proof of concept, their adaptation to the reality that is pharmaceutical R&D process, and their impact on decision making.