High-Throughput Screening (HTS) Platform for Discovery of Medications to Treat Alcohol Use Disorder (R43/R44 Clinical Trials Not Allowed)

Drug development is challenging, particularly for Central Nervous System (CNS) medications. It takes approximately 18 years to move a potential CNS medication from its initial discovery phase to the marketplace, often costing several billion dollars. The failure rate is high (only 8% of new CNS compounds entering Phase I studies will reach the market) and contributes to the high costs and slow rate of development. One way to improve the efficiency of the drug development process is to develop better screening models. Currently, a variety of animal models (i.e., rodent vertebrate and other higher order vertebrate) exist that reflect the different stages of the addiction cycle: binge-intoxication, withdrawal-negative affect, and preoccupation-anticipation. However, studies using these models can be somewhat lengthy and expensive and are generally only able to test one compound at a time. Given this current state, it is desirable to develop a HTS platform, including the use of new model cells, tissues, and organisms, to test multiple candidate compounds and drug combinations identified using new compound discovery approaches (e.g., Connectivity Maps and artificial intelligence [AI]). Recent HTS approaches use cell- and tissue-based model systems for screening compounds. This may include brain cells and organoids derived from induced pluripotent stem cells. Advances in three-dimension (3D) technology help to visualize the complex biology of the cell and isolated tissues/organoids. In addition, recent evidence suggests that small vertebrate and invertebrate model organisms have the potential to be used as models for HTS. These include zebrafish, Drosophila (fruit flies) and the nematode C. elegans (roundworms). These models preserve the complexity and architecture of intact cells, organs, and organisms and have proven useful in studying alcohol's mechanisms underlying withdrawal. The most promising compounds to run through these models can be identified using powerful methodological approaches such as the Connectivity Map approach; a methodology that compares the gene expression profile of compounds with that of a particular disorder. In addition, the development of AI in exploring different molecular networks within the brain could lead to many new candidate compounds. Narrowing those choices using HTS could save time and resources and lead to a more efficient drug development process. Purpose/Research Objectives The purpose of this NOFO is to develop in vivo and/or in vitro HTS platforms to identify potential compounds to treat for AUD. Potential screening platform models consist of small vertebrate and invertebrate organisms such as nematode C. elegans, zebrafish, and Drosophila (fruit flies) and cell- and tissue-based models. Models consisting of rodents and other higher order vertebrates are not considered responsive to this NOFO; however human derived cell- and tissue-based models are acceptable. The HTS models must be sensitive to alcohol and produce measurable changes within the model. Compounds are then evaluated for their ability to prevent these changes caused by alcohol. One important hurdle is to validate the model, showing that its assay(s) is predictive of clinical success in humans. Validation can be accomplished by showing the relationship between the compound efficacy in human trials and the predictiveness of the platform model. Examples of Phase I Activities: Development of a new or optimization of an existing screening platform (i.e., cell, tissue, or organism) that has the following qualities: Has assays that are sensitive to alcohol and produce reliable and reproducible changes within the model When applicable, incorporates AI into the prediction of alcohol-mediated changes within the model Tests at least one compound with a known clinical profile for the treatment of AUD in the platform. Compounds of choice should include at least one of the following: naltrexone, acamprosate, topiramate, gabapentin, and varenicline. Specifies the metrics that will be used to evaluate assay success Examples of Phase II Activities: Benchmarked performance of the developed system against existing data obtained from well-established in vivo animal model(s) and clinical model(s) Tests of multiple, additional compounds with known clinical profile in prototype system Compounds of choice include naltrexone, acamprosate, topiramate, gabapentin, and varenicline. Test at least one compound that has proven efficacious in animal studies but not in clinical trials Tests of additional promising compounds identified as promising for the treatment of AUD using novel approaches (e.g., Connectivity Mapping; and NIH Library of Integrated Network-Based Cellular Signatures (LINCS)) for treatment of AUD Validate the additional promising compound in a well-established animal model to evaluate the performance of the screening platform. Commercialization Potential A validated HTS platform would allow drug developers and researchers to quickly identify and develop compounds to treat AUD. This platform would be of considerable value to pharmaceutical companies and research scientists in discovering new compounds. This platform could also have the potential to be used in screening compounds for other medical and psychiatric disorders. This will be particularly valuable as AI is advanced, undoubtedly producing perhaps thousands of compounds to be tested for the treatment of AUD as well as other medical disorders.