Breaking News

Tufts Report Reveals Use of New Methods to Boost Clinical Success

April 15, 2014

New approaches aim to predict clinical success

Drug companies and their development partners are employing new models and methods aimed at improving clinical success rates, according to the April R&D management report from Tufts Center for the Study of Drug Development.

"The research-based drug industry is racing to boost its research pipelines, as existing patents expire and development times continue to lengthen," said Tufts CSDD director Kenneth I Kaitin. "Drug companies are exploring new approaches to product development that focus on increasing the probability of clinical success and speeding time to market."

One approach, summarized in the report, focuses on statistical models that help predict clinical success. For example, a R&D team created a simple algorithmic model called the Approved New Drug Index (ANDI) that predicts which oncology products emerging from Phase II testing are likely to receive marketing approval. The team concluded that, compared to the prevailing industry metric, the data support assigning a much higher probability of success to oncology drugs with top ANDI scores of 7 and 8, and much lower probabilities of success to those with scores of 0 to 4.
Other points summarized in the report include: a shift in approach to decision making that favors data-driven models; more rigorous use of risk-adjusted value calculations earlier in clinical development to improve decision making on how to structure clinical trials; as well as advances in development of personal genomic information that offers significant potential to transform clinical trials.

blog comments powered by Disqus
  • Elemental Impurity Testing

    Elemental Impurity Testing

    Dr. Andrew Fussell, PANalytical ||January 28, 2016
    Advances in elemental impurity testing aid compliance with new USP requirements

  • Fit-For-Purpose Assay Development in Bioanalysis

    Fit-For-Purpose Assay Development in Bioanalysis

    Franklin Spriggs, Ligand Binding Assay Group Leader; Ashley Brant, Program Manager, AIT Bioscience||January 28, 2016
    The success of bioanalytical studies relies on the selection of the most suitable analytical method but the timeline of method development and types of analyses involved vary greatly.

  • Optimizing Collaboration Effectiveness in Alliance Partnerships

    Optimizing Collaboration Effectiveness in Alliance Partnerships

    Mary Jo Lamberti, Phil Birch, Ranjana Chakravarthy, Ken Getz, Tufts CSDD||January 28, 2016