Harnessing Artificial Intelligence and Polypharmacology to Discover Pharmacotherapeutics for Substance Use Disorders (R41/R42 Clinical Trials Not Allowed)

Active
Yes
Status
Open
Release Date
January 29th, 2024
Open Date
June 25th, 2024
Due Date(s)
July 25th, 2024
Close Date
July 26th, 2024
Topic No.
RFA-DA-25-053

Topic

Harnessing Artificial Intelligence and Polypharmacology to Discover Pharmacotherapeutics for Substance Use Disorders (R41/R42 Clinical Trials Not Allowed)

Agency

Department of Health and Human ServicesNational Institutes of Health

Program

Type: STTRPhase: BOTHYear: 2024

Summary

The Department of Health and Human Services, specifically the National Institutes of Health, is seeking proposals for the topic of "Harnessing Artificial Intelligence and Polypharmacology to Discover Pharmacotherapeutics for Substance Use Disorders (R41/R42 Clinical Trials Not Allowed)". This solicitation aims to leverage AI/ML tools to identify pharmacotherapeutic development candidates with lower toxicity and higher efficacy to prevent or treat substance use disorders (SUDs). The goal is to streamline and enhance decision-making in drug discovery efforts for SUDs using AI/ML technologies. The research objectives include identifying and validating disease targets, screening potential compounds, developing assays to test candidate compounds, synthesizing novel compounds, and conducting in vitro and in vivo studies to assess efficacy and toxicity. This Small Business Technology Transfer (STTR) program is a phased program, with Phase I focused on establishing technical merit and feasibility, and Phase II aimed at advancing the technology towards commercialization. Successful projects are expected to attract strategic partners or investors for ultimate commercialization. Phase I and Fast Track applications are accepted, with Fast Track allowing Phase I and Phase II applications to be submitted and reviewed together for expedited award decisions. Milestones and deliverables must be clearly defined for Fast Track applications. The solicitation is currently open, with a release date of January 29, 2024, an open date of June 25, 2024, and a close date of July 26, 2024. More information can be found on the grants.gov website.

Description

Background:

Drug discovery and development is a high-cost, high-risk, and time-consuming endeavor where the failure rate of therapeutic candidates that enter clinical trials is 90%. Because of this, in recent years, artificial intelligence (AI), including machine learning (ML) technologies, has been embraced to reduce clinical failure rates and to speed up drug discovery. AI/ML technologies are used to identify novel targets, design new molecules, conduct virtual preclinical studies, and analyze preclinical and clinical data. Multiple AI/ML-discovered compounds have advanced into Phase II clinical trials.

While AI/ML is transforming drug discovery and promises to deliver new classes of medications, AI/ML-driven drug discovery for substance use disorders (SUDs) has lagged. A contributing reason is that the traditional drug discovery paradigm involves identifying highly potent and selective molecules that act on specific targets (i.e., enzymes and receptors) in a "one disease, one target, one molecule" model. Although single-target-based drug discovery has been successful in developing new medications for some indications, SUDs can be caused by complex mechanisms and, therefore, can be outside the traditional single-target-drug paradigm. Another complicating factor for SUDs is that polysubstance use is increasingly more common. Polysubstance use involves the intentional or unintentional co-use of two or more drugs, such as alcohol, tobacco, benzodiazepine, cannabis, cocaine, fentanyl, xylazine, or nitazene. Due to polysubstance use, individuals face a greater risk of toxicity from the drug combinations, leading to increased morbidity and mortality. For instance, drug poisoning deaths involving fentanyl and stimulants climbed from 0.6% in 2010 to 32.3% in 2021.

Polypharmacology is emerging as a new paradigm that can advance drug development for multifactorial diseases such as SUDs. Polypharmacology is the study of how drug molecules interact with multiple targets. In the context of this notice of funding opportunity (NOFO), polypharmacology is defined as a single drug acting on multiple targets of a unique disease pathway or multiple targets of multiple disease pathways. These molecules are multi-target directed ligands (MTDL). The concepts for polypharmacology and MTDL design are supported by several approved drugs that elicit their therapeutic effect through complex polypharmacology. Some key challenges in polypharmacology are identifying the target combination, predictions of the off-target toxicities, and the rational design of MTDLs, especially when the targets of interest are not phylogenetically or structurally related. Implementing a polypharmacology strategy in drug discovery relies on advances in computational approaches such as data mining, ligand-based analysis and virtual screening.

Since drug discovery is a multidimensional search and optimization process, artificial intelligence and machine learning (AI/ML) technologies trained in polypharmacology could significantly improve SUD discovery and development efforts. By unlocking insights from the network of drug-drug, protein-drug, and protein-protein interactions that drive substance use, AI/ML tools can efficiently evaluate and predict the effects of binding to multiple biological targets, thereby enhancing potential clinical efficacy ("beneficial polypharmacology"). AI/ML can also identify pathways and mechanisms leading to side effects caused by drug binding to unintended off-targets ("adverse polypharmacology"), thereby reducing unmanageable toxicity. Such AI/ML tools can identify the best targets, design effective MTDLs, and inform the in vitro and in vivo assays to characterize the effects of these ligands on targets and functions.

Research Objectives

The goal is to leverage AI/ML tools to identify pharmacotherapeutic development candidates with lower toxicity and higher efficacy to prevent or treat SUDs. Molecules may include new chemical entities, investigational compounds, and repurposed marketed medications. AI/ML tools can pinpoint the most promising targets, design effective ligands based on predicted drug-likeness, and guide in vitro and in vivo assays to assess the effects of these ligands on biological targets and functions.

Applicants should propose and conduct activities that use AI/ML tools to streamline, enhance decision-making, and accelerate the identification of SUD pharmacotherapeutics. Applications may aim to conduct the following process:

Identify and validate disease targets. Screen potential compounds to develop preliminary hits. Develop assays to test the activities of candidate compounds in vitro. Synthesize novel series of compounds; test efficacy and toxicities in vitro. Test pharmacokinetics and toxicity of selected compounds in relevant in vivo models on a non-GLP level. Conduct non-GLP in vivo toxicity and efficacy of lead compound; pharmacokinetic studies. Application Not Responsive to this NOFO

The following types of projects are not responsive to this NOFO and will not be reviewed:

Applications that pursue a single target. Applications solely focused on alcohol use disorders. Applications pursuing pain as a sole focus without addressing substance dependence and SUD. Applications that do not propose using computer-based approaches to augment drug discovery efforts. The Small Business Technology Transfer (STTR) program is a phased program.

An overall objective of the STTR program is to increase private sector commercialization of innovations derived from federally supported research and development.

The main objective of STTR Phase I is to establish the technical merit and feasibility of the proposed research and development efforts. In contrast, the STTR Phase II objective is to continue the R&D efforts to advance the technology toward ultimate commercialization.

Beyond the scope of this NOFO, it is anticipated and encouraged that the outcomes of successful STTR projects will help attract strategic partners or investors to support the ultimate commercialization of the technology as a publicly available product or service.

The following types of applications are accepted in response to this NOFO:

Phase I. The objective of Phase I is to establish the technical merit, feasibility, and commercial potential of the proposed R/R&D efforts and determine the quality of performance of the small business recipient organization before proceeding to Phase II.

Fast Track. The NIH Fast Track process allows Phase 1 and Phase II grant applications to be submitted and reviewed together. It expedites award decisions and funding of SBIR and STTR Phase II applications for scientifically meritorious projects that have high potential for commercialization. Importantly, before Fast Track Phase II can start, the National Institute on Drug Abuse (NIDA) conducts an administrative review and evaluates the achievement of the stated milestones. In addition to Approach and Investigator(s), Fast-Track milestones are assessed as Additional Review Criteria: Does the Phase I application specify milestones that should be achieved prior to initiating Phase II? Applicant’s failure to provide milestones and specific, measurable, achievable, relevant, and time-bound milestone deliverables may be sufficient reason for the peer review to exclude the application from the Fast Track review. Fast Track applicants must propose two separate sets of milestones and associated with the specific, measurable, achievable, relevant, and time-bound milestone deliverables, one set for Phase I and another set for Phase II. It is important to clearly state the go/no-go milestone decisions that will determine transition to Phase II. Failure to adequately address these criteria may negatively affect the application’s impact score. Based on peer review recommendations, NIDA Program Officer may negotiate the Phase I milestones with the Fast Track potential awardees before they are included in the terms of the award.

Similar Opportunities

Harnessing Artificial Intelligence and Polypharmacology to Discover Pharmacotherapeutics for Substance Use Disorders (R41/R42 Clinical Trials Not Allowed)
Department of Health and Human Services
The Department of Health and Human Services, specifically the National Institutes of Health, is seeking proposals for the topic of "Harnessing Artificial Intelligence and Polypharmacology to Discover Pharmacotherapeutics for Substance Use Disorders (R41/R42 Clinical Trials Not Allowed)". This solicitation aims to leverage AI/ML tools to identify pharmacotherapeutic development candidates with lower toxicity and higher efficacy for the prevention or treatment of substance use disorders (SUDs). The traditional drug discovery paradigm of single-target-based approaches has limitations in addressing the complex mechanisms and polysubstance use associated with SUDs. Polypharmacology, the study of how drug molecules interact with multiple targets, is emerging as a new paradigm for drug development in multifactorial diseases like SUDs. The use of AI/ML technologies trained in polypharmacology can enhance the discovery and development efforts for SUD pharmacotherapeutics by identifying the best targets, designing effective multi-target directed ligands (MTDLs), and predicting the effects of binding to multiple biological targets. The research objectives include identifying and validating disease targets, screening potential compounds, developing assays, synthesizing novel compounds, and conducting in vitro and in vivo studies. The Small Business Technology Transfer (STTR) program is a phased program, with Phase I focused on establishing technical merit and feasibility, and Phase II aimed at advancing the technology towards commercialization. The Fast Track option allows for the submission and review of Phase I and Phase II grant applications together, expediting the award decisions and funding for projects with high potential for commercialization.
Harnessing Artificial Intelligence and Polypharmacology to Discover Pharmacotherapeutics for Substance Use Disorders (R43/R44 Clinical Trials Not Allowed)
Department of Health and Human Services
The Department of Health and Human Services, specifically the National Institutes of Health, is seeking proposals for the topic of "Harnessing Artificial Intelligence and Polypharmacology to Discover Pharmacotherapeutics for Substance Use Disorders (R43/R44 Clinical Trials Not Allowed)". This solicitation aims to leverage AI/ML tools to identify pharmacotherapeutic development candidates with lower toxicity and higher efficacy for the prevention or treatment of substance use disorders (SUDs). The traditional drug discovery paradigm of single-target-based approaches has limitations in addressing the complex mechanisms and polysubstance use associated with SUDs. Polypharmacology, the study of how drug molecules interact with multiple targets, is emerging as a new paradigm for drug development in multifactorial diseases like SUDs. The use of AI/ML technologies trained in polypharmacology can enhance the identification of SUD pharmacotherapeutics by evaluating and predicting the effects of binding to multiple biological targets, reducing toxicity, and informing in vitro and in vivo assays. The research objectives include identifying and validating disease targets, screening potential compounds, developing assays, synthesizing novel compounds, and conducting toxicity and efficacy studies. The Small Business Innovation Research (SBIR) program offers Phase I and Phase II funding opportunities to establish technical merit, feasibility, and commercial potential. Successful SBIR projects are expected to attract strategic partners or investors for ultimate commercialization. Phase I, Fast Track, and Direct to Phase II applications are accepted in response to this solicitation. The application due date is July 25, 2024. For more information, visit the [solicitation agency website](https://grants.nih.gov/grants/guide/rfa-files/RFA-DA-25-054.html).
Harnessing Artificial Intelligence and Polypharmacology to Discover Pharmacotherapeutics for Substance Use Disorders (R43/R44 Clinical Trials Not Allowed)
Department of Health and Human Services
The Department of Health and Human Services, specifically the National Institutes of Health, is seeking proposals for the topic of "Harnessing Artificial Intelligence and Polypharmacology to Discover Pharmacotherapeutics for Substance Use Disorders (R43/R44 Clinical Trials Not Allowed)". This solicitation aims to leverage AI/ML tools to identify pharmacotherapeutic development candidates with lower toxicity and higher efficacy for the prevention or treatment of substance use disorders (SUDs). The traditional drug discovery paradigm of single-target-based approaches has limitations in addressing the complex mechanisms and polysubstance use associated with SUDs. Polypharmacology, the study of how drug molecules interact with multiple targets, is emerging as a new paradigm for drug development in multifactorial diseases like SUDs. The use of AI/ML technologies trained in polypharmacology can enhance the discovery and development efforts by identifying the best targets, designing effective multi-target directed ligands (MTDLs), and predicting the effects of binding to multiple biological targets. The research objectives include identifying and validating disease targets, screening potential compounds, developing assays, synthesizing novel compounds, and conducting in vitro and in vivo studies. The Small Business Innovation Research (SBIR) program offers Phase I and Phase II funding opportunities to support the technical merit, feasibility, and commercial potential of the proposed research. Successful SBIR projects are expected to attract strategic partners or investors for ultimate commercialization.
Developing Regulated Therapeutic and Diagnostic Solutions for Patients Affected by Opioid and/or Stimulants use Disorders (OUD/StUD) (R41/R42 Clinical Trial Optional)
Department of Health and Human Services
The Department of Health and Human Services, specifically the National Institutes of Health, is seeking proposals for the development of regulated therapeutic and diagnostic solutions for patients affected by opioid and/or stimulant use disorders (OUD/StUD). The current drug crisis surrounding these disorders has resulted in a significant number of deaths and an urgent need for comprehensive solutions. The solicitation is focused on the research and development of medical products regulated by the U.S. Food and Drug Administration (FDA), including pharmacotherapeutics and medical therapeutic and diagnostic devices. In the area of pharmacotherapeutics, the solicitation encourages the development of small or large molecule agents, biologics, natural products, longer-acting formulations of existing addiction medications, advanced drug delivery systems, and the development and characterization of biomarkers. Proposed activities may include target identification, assay development, lead optimization, preclinical studies, formulation development, and process development. The ultimate goal is to file an Investigational New Drug (IND) application and conduct clinical studies to support the filing of a New Drug Application (NDA) or a Biological License Application (BLA). In the area of medical therapeutic and diagnostic devices, the solicitation seeks research and development of imaging technologies, devices for diagnosing and reducing craving and withdrawal symptoms, therapeutic devices, devices for treating pediatric patients, in vitro diagnostic assays, digital therapeutics, devices for detecting and treating opioid-induced respiratory depression, and data science and cloud-based technologies. Proposed activities may include studies supporting an Investigational Device Exemption application, process development, non-clinical safety studies, clinical trials, and engagement with the FDA Center of Devices and Radiological Health. The goal is to successfully file an FDA premarket application for clearance/approval. The solicitation is open for applications and offers funding for Phase I, Phase II, and Fast Track projects. Phase I aims to establish the technical merit and feasibility of the proposed research, while Phase II continues the R&D efforts to advance the technology toward commercialization. Fast Track applications combine Phase I and Phase II into one application to reduce or eliminate the funding gap between phases. Small businesses that have received Phase I STTR awards are eligible to submit Phase II applications as "Renewal" applications.