Key Dates

Related Announcements

• PA-19-055 - NIH Research Project Grant (Parent R01 Clinical Trial Required)
• PA-19-056 - NIH Research Project Grant (Parent R01 Clinical Trial Not Allowed)
• PA-19-091 NIH Research Project Grant (Parent R01 Basic Experimental Studies with Humans Required)

Issued by

National Institute on Drug Abuse (NIDA)

Purpose

The purpose of this Notice is to inform potential applicants to the National Institute on Drug Abuse (NIDA) about a special interest in research project applications focusing on discovery, development and validation of drug addiction biomarkers, biosignatures and elucidation of substance use disorder biotypes, with an emphasis on machine learning and artificial intelligence ( AI) based analytical approaches. Of interest are applications that focus on generating new data, as well as those integrating existing datasets to search for neurobiological and neuroclinical patterns, also in combination with peripheral biomarkers, neuroimaging, neurophysiological data, gene expression and epigenetic data. This type of research could result in an ability to compose more neurobiologically homogenous patient populations deeply profiled for clinical trials participation, enable selection and stratification of patients in studies to more precisely assess signals of therapeutic efficacy, predict a response to a therapeutic and/or behavioral intervention, as well as discover genotype-phenotype neural correlates and connect those with the proximal and distal outcomes of substance use disorders.

?Background

There have been recent advances in information and analytic technologies and open-access human datasets and databases coupled with addiction neuroscience achievements in the area of addiction-relevant neuronal ensembles and the connectome. Therefore there is a new window of opportunity for the advancement of substance use disorder biomarkers and computational peripheral composite biomarkers, as biosignatures of the addiction process. This new research can lead to a broadening of scope for clinical drug development endpoints, helping to address treatment challenges related to treatment response and relapse prevention where preclinical models have not been shown to be predictive.

In the future, with the discovery and characterization of addiction biotypes, substance use disorders that are currently classified by a particular substance used in the DSM-5 could be rearranged according to biotypes to allow for a more precise and neurobiologically-based diagnosis and personalized treatment. Biotypes can be transdiagnostic and transcend diagnostic boundaries. This novel approach to substance use disorder categorization,using biotypes, could provide a range of new endpoints and potential indications. We especially encourage applications that will use Big Data analytics, utilize machine learning computational approaches for analyzing large and complex integrative datasets acquired from existing research datasets.

Big data analytic technologies could be applied to complex large multivariate datasets that contain, for example, neuroclinical characterizations of patients together with biologics and neuroimaging data, behavioral tasks performance, genetic and epigenetic, physiologic, metabolic and other types of data.

Research Objectives

NIDA encourages research applications aimed at discovery, development and validation of biomarkers and biosignatures that may include (in combination or alone) neurocircuitry pathways data, neurophysiological changes, phenotypical data (also in a combination with biologic or imaging markers), genetic and epigenetic changes, physiologic, metabolic, immunologic, hormonal and other peripheral markers. NIDA priorities also include projects that would lead to the elucidation of biotypes of substance use disorders. Research projects could also be focused on searching for genotype-phenotype correlations linking the genetic architecture of dimensional domains related to the addiction process with phenotypical features and with fMRI resting-state brain connectivity.

Examples of approaches that are encouraged include, but are not limited to:

• The process of identification or/and validation of biomarkers, biosignatures, including across several SUDs when using dimensional domain-focused approach. Biomarkers and biosignatures could represent composites of peripheral and central markers, combinations and correlations of several -omics data, molecular profiles with neuroimaging data (e.g., resting-state connectivity) connected with deeply phenotyped clinical profiles, behavioral and cognitive tasks profiles. The aims could be to identify patterns correlated with substance use disorders phenotypes using machine-learning, AI and other innovative statistic approaches related to big data analytics.
• Big data -based analysis of available human genomic, transcriptomic, epigenomic data integrated with neuroimaging,for example, gray matter volumetric data connected with phenotypes information (deep phenotyping) to elucidate overlapping and unique structural brain characteristics and correlate them with clinical profiles, as candidate biotypes, across the addiction spectrum.
• Drug use trajectories, treatment response and time to relapse predictive biomarkers identification that could be developed into validated gold standard instruments within the defined context of use.

Application and Submission Information

This notice applies to due dates on or after February 5, 2020 and subsequent receipt dates through May 7, 2023.

Submit applications for this initiative using one of the following funding opportunity announcements (FOAs) or any reissues of these announcement through the expiration date of this notice.

• PA-19-055 - NIH Research Project Grant (Parent R01 Clinical Trial Required)
• PA-19-056 - NIH Research Project Grant (Parent R01 Clinical Trial Not Allowed)
• PA-19-091 NIH Research Project Grant (Parent R01 Basic Experimental Studies with Humans Required)

All instructions in the SF424 (R&R) Application Guide and the funding opportunity announcement used for submission must be followed, with the following additions:

• For funding consideration, applicants must include NOT-DA-20-012 (without quotation marks) in the Agency Routing Identifier field (box 4B) of the SF424 R&R form. Applications without this information in box 4B will not be considered for this initiative.

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