ST. LOUIS, Mo.—Certara's Pharsight Consulting Services hasdeveloped a mathematical model of tumor growth inhibition, which when combinedwith baseline prognostic factors, predicts treatment effect with bevacizumabfor patients with metastatic colorectal cancer. These results are now publishedonline in the Journal of ClinicalOncology.
In an accompanying editorial, Dr. Michael Maitland,assistant professor of medicine at the University of Chicago Medicine, and hisco-authors say they have identified time-to-tumor growth (TTG) as the "bestmetric to predict overall survival in metastatic colorectal cancer patientstreated in the study." They predict that "if TTG proves a robust endpoint inthis clinical setting, one advantage will be the reduced follow-up time neededfor each patient on trial, and consequently, trials with this endpoint wouldlikely have reduced costs and reach their conclusions sooner than moreconventional PFS-based studies."
The Certara researchers estimated several tumor-sizeresponse metrics using longitudinal tumor-size models and data from two PhaseIII clinical trials, which compared bevacizumab with chemotherapy versus chemotherapyalone as first-line therapy for colorectal cancer. Trial participants included923 Western and 203 Chinese patients. Baseline prognostic factors and thetumor-size metric estimates were assessed in multivariate models to predictoverall survival. Multiple simulations of the Phase III studies were used totest the models' predictive capabilities.
Time-to-tumor growth proved to be the best metric forpredicting overall survival. The proposed model worked equally well whenpredicting overall survival rates for the Western and Chinese patients, andcould be used to support drug development decisions in either population.
Dr. René Bruno, managing director of Certara's PharsightConsulting Services Europe and a senior author of the paper, says, "This approachof combining modeling with longitudinal tumor-size data may contribute toimproved design and analysis of more informative early-stage clinical studies(Phase Ib, II). It could also enable researchers to select the most promisingtreatments and reduce the high attrition rate in Phase III oncology studies."
Dr. Robert Powell, former senior advisor at Roche China, anda co-author of the paper, adds, "It is important to know whether patients in anew market (e.g., China, India,Brazil) will be similar to patients in the original U.S. or EU New DrugApplication (NDA). While pharmaceutical companies usually assume patients fromdifferent regions are the same, there is emerging evidence that they might bedifferent with regard to efficacy, safety and dose response. This type ofanalysis helps better define Chinese colon cancer response relative to Westernpatients. Roche performed this combined Chinese and U.S. NDA study analysis tolearn whether Chinese patients responded similarly to Western patients so theycan use this information to plan future trials. Likewise, knowing these resultswill be important to local regulatory agencies such as the China Food and DrugAdministration."
In his editorial, Maitland points out that "extensiveinvestment in oncology drug discovery and development during the past decadehas not been matched by similar innovation in clinical trial design during thesame period, especially with regard to endpoint evaluation." He notes thatalternative metrics to progression-free survival (PFS) for detecting thebeneficial effects of cancer therapies are now an active area of research."Innovations in clinical trial design could accelerate availability ofeffective new drugs and reduce the rate of failure in expensive late-phasedevelopment, and therefore reduce the overall costs of oncology drugdevelopment," he concludes.
Certara was formed by the acquisition and integration ofTripos, Simcyp and Pharsight Corp., and provides software and scientificconsulting services to improve productivity and decision-making in drugdiscovery and development. Each Certara family brand focuses on a key phasewithin the drug discovery and development process; combined, they offerscientific modeling, analysis and simulation capabilities that can enable thecross-disciplinary approaches necessary for translational science initiatives.
