This application proposes a network to stimulate and foster collaborations that have the potential to lead to new methodology for the development and evaluation of adaptive treatment strategies for chronic disorders. These strategies are individually tailored approaches to treatment that correspond to the adaptive nature of clinical practice. For example, in practice, patients suffering from chronic disorders such as substance abuse, mental illness and HIV infection are treated sequentially, where decisions to modify or change treatment over time are made based on the clinician's and patient's evaluation of ongoing response, burden and adherence. Both data analysis methods and experimental data collection methods for informing and evaluating adaptive treatment strategies are in their infancy. This issue can be viewed from the perspective of computer scientists and control engineers as a multi-stage decision problem; however there has been little interchange between clinicians involved in the management of these disorders, statisticians who work in data analysis and design and computer scientists. Input from all of these areas has the potential to jump-start the methodological development in a manner that will ensure that major challenges will be identified and addressed in the most appropriate fashion. This network includes computer scientists, psychiatrists, psychologists, engineers and statisticians. We will write a joint position paper identifying the major challenges and potential solutions and we will form small collaborative groups that will work to address these methodological challenges.

Agency
National Institute of Health (NIH)
Institute
National Institute on Drug Abuse (NIDA)
Type
Exploratory/Developmental Grants (R21)
Project #
5R21DA019800-02
Application #
6953254
Study Section
Special Emphasis Panel (ZCA1-SRRB-D (O1))
Program Officer
Chandler, Redonna
Project Start
2004-09-30
Project End
2007-07-31
Budget Start
2005-08-01
Budget End
2007-07-31
Support Year
2
Fiscal Year
2005
Total Cost
$108,920
Indirect Cost
Name
University of Michigan Ann Arbor
Department
Internal Medicine/Medicine
Type
Schools of Medicine
DUNS #
073133571
City
Ann Arbor
State
MI
Country
United States
Zip Code
48109
Panuccio, Gabriella; Guez, Arthur; Vincent, Robert et al. (2013) Adaptive control of epileptiform excitability in an in vitro model of limbic seizures. Exp Neurol 241:179-83
Shortreed, Susan M; Moodie, Erica E M (2012) Estimating the optimal dynamic antipsychotic treatment regime: Evidence from the sequential multiple assignment randomized CATIE Schizophrenia Study. J R Stat Soc Ser C Appl Stat 61:577-599
Bush, Keith; Panuccio, Gabriella; Avoli, Massimo et al. (2012) Evidence-based modeling of network discharge dynamics during periodic pacing to control epileptiform activity. J Neurosci Methods 204:318-25
Gunter, L; Zhu, J; Murphy, S A (2011) Variable Selection for Qualitative Interactions. Stat Methodol 1:42-55
Chakraborty, Bibhas; Murphy, Susan; Strecher, Victor (2010) Inference for non-regular parameters in optimal dynamic treatment regimes. Stat Methods Med Res 19:317-43
Fard, Mahdi Milani; Pineau, Joelle (2009) MDPs with Non-Deterministic Policies. Adv Neural Inf Process Syst 21:1065-1073
Pineau, Joelle; Bellemare, Marc G; Rush, A John et al. (2007) Constructing evidence-based treatment strategies using methods from computer science. Drug Alcohol Depend 88 Suppl 2:S52-60
Murphy, Susan A; Collins, L M; Rush, A John (2007) Customizing treatment to the patient: adaptive treatment strategies. Drug Alcohol Depend 88 Suppl 2:S1-3
Murphy, Susan A; Lynch, Kevin G; Oslin, David et al. (2007) Developing adaptive treatment strategies in substance abuse research. Drug Alcohol Depend 88 Suppl 2:S24-30
Murphy, Susan A; Oslin, David W; Rush, A John et al. (2007) Methodological challenges in constructing effective treatment sequences for chronic psychiatric disorders. Neuropsychopharmacology 32:257-62