Patents by Inventor Reza Firouzbakht

Reza Firouzbakht has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • System for predictive analytics using real-world pharmaceutical transactions
    Patent number: 8140377
    Abstract: A system for predictive analytics using real-world pharmaceutical transactions includes a computer having a processor and memory, a data collection component configured to aggregate data for a plurality of pharmaceutical transactions, and a data reduction module configured to eliminate non-compliant transactions to generate a reduced transaction data set. An analysis module applies multiple linear regression analysis to a portion of the reduced transaction data set to identify key regression variables that correlate with an excess total return to shareholders. The analysis module also applies logistic regression analysis to a portion of the reduced transaction data set to identify key regression variables that correlate with an increased probability of regulatory agency approval. A report generator provides a graphical output of the identified key regression variables and a probability value corresponding to a likelihood of regulatory agency approval.
    Type: Grant
    Filed: July 14, 2008
    Date of Patent: March 20, 2012
    Assignee: Accenture Global Services Limited
    Inventors: Reza Firouzbakht, Elizabeth O. Coulton, Henry Lai, Tigran Markaryan
  • SYSTEM FOR PREDICTIVE ANALYTICS USING REAL-WORLD PHARMACEUTICAL TRANSACTIONS
    Publication number: 20090276287
    Abstract: A system for predictive analytics using real-world pharmaceutical transactions includes a computer having a processor and memory, a data collection component configured to aggregate data for a plurality of pharmaceutical transactions, and a data reduction module configured to eliminate non-compliant transactions to generate a reduced transaction data set. An analysis module applies multiple linear regression analysis to a portion of the reduced transaction data set to identify key regression variables that correlate with an excess total return to shareholders. The analysis module also applies logistic regression analysis to a portion of the reduced transaction data set to identify key regression variables that correlate with an increased probability of regulatory agency approval. A report generator provides a graphical output of the identified key regression variables and a probability value corresponding to a likelihood of regulatory agency approval.
    Type: Application
    Filed: July 14, 2008
    Publication date: November 5, 2009
    Inventors: Reza Firouzbakht, Elizabeth O. Coulton, Henry Lai, Tigran Markaryan