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Active Investigations

There are many active research projects accessing and applying shared ADNI data. Use the search above to find specific research focuses on the active ADNI investigations. This information is requested annually as a requirement for data access.

Principal Investigator  
Principal Investigator's Name: Joseph Heenan
Institution: IQVIA
Department: Analytics Center of Excellence
Country:
Proposed Analysis: The usage of machine learning to inform early stopping criteria for CNS studies. Specifically evaluating approaches ranging from posterior probability analysis (Thall & Simon, 1994) (Thall & Simon, Practical Bayesian guidelines for phase IIB clinical trials, 1994), (Sylvester, 1988), persuasion probability (Heitjan, 1997), and two-stage phase II trial designs (Tan & D, 2002).
Additional Investigators  
Investigator's Name: Cheng Qian
Proposed Analysis: The usage of machine learning to inform early stopping criteria for CNS studies. Specifically evaluating approaches ranging from posterior probability analysis (Thall & Simon, 1994) (Thall & Simon, Practical Bayesian guidelines for phase IIB clinical trials, 1994), (Sylvester, 1988), persuasion probability (Heitjan, 1997), and two-stage phase II trial designs (Tan & D, 2002).
Investigator's Name: Pagani Lucia
Proposed Analysis: The usage of machine learning to inform early stopping criteria for CNS studies. Specifically evaluating approaches ranging from posterior probability analysis (Thall & Simon, 1994) (Thall & Simon, Practical Bayesian guidelines for phase IIB clinical trials, 1994), (Sylvester, 1988), persuasion probability (Heitjan, 1997), and two-stage phase II trial designs (Tan & D, 2002).
Investigator's Name: Altynbek Isabekov
Proposed Analysis: The usage of machine learning to inform early stopping criteria for CNS studies. Specifically evaluating approaches ranging from posterior probability analysis (Thall & Simon, 1994) (Thall & Simon, Practical Bayesian guidelines for phase IIB clinical trials, 1994), (Sylvester, 1988), persuasion probability (Heitjan, 1997), and two-stage phase II trial designs (Tan & D, 2002).
Investigator's Name: Mikki Behnke
Proposed Analysis: The usage of machine learning to inform early stopping criteria for CNS studies. Specifically evaluating approaches ranging from posterior probability analysis (Thall & Simon, 1994) (Thall & Simon, Practical Bayesian guidelines for phase IIB clinical trials, 1994), (Sylvester, 1988), persuasion probability (Heitjan, 1997), and two-stage phase II trial designs (Tan & D, 2002).