Announcement of Requirements and Registration for the National Center for Advancing Translational Sciences ASPIRE Design Challenge 3: Predictive Algorithms for Translational Innovation in Pain, Opioid Use Disorder and Overdose

Summary of NCATS ASPIRE Design Challenges

The National Center for Advancing Translational Sciences (NCATS), part of the National Institutes of Health (NIH), is inviting novel design solutions for A Specialized Platform for Innovative Research Exploration (NCATS ASPIRE) Design Challenges as part of the NCATS ASPIRE Program. The goal of the NCATS ASPIRE Design Challenges is to reward and spur innovative and catalytic approaches toward solving the opioid crisis through development of (1) novel chemistries, (2) data mining and analysis tools and technologies, and (3) biological assays that will revolutionize discovery, development and pre-clinical testing of next-generation, safer and non-addictive analgesics to treat pain, as well as new treatments for opioid use disorder (OUD) and overdose. The first phase of these prize competitions is implemented through a suite of concurrent companion Design Challenges that comprises separate Challenges for each of four areas — chemistry database, electronic laboratory knowledge portal for synthetic chemistry, algorithms and biological assays — and an additional Challenge for a combined solution to at least two Challenge areas. At this stage, innovators are expected to submit designs, not final products or prototypes.

NCATS envisions following these Design Challenges with a follow-on but distinct final Reduction-to-Practice Challenge, which will aim to invoke further scientific and technological development of the model system. Winners of the Design Challenges will be invited to present their designs so that, in the envisioned follow-up Reduction-to-Practice Challenge, an open competition, teams will be able to form multidisciplinary collaborations to advance and integrate the most feasible and promising approaches to the multiple Challenges into a single integrative platform. Innovators will be invited to demonstrate final solutions.

The NCATS ASPIRE Design Challenges are part of NIH’s Helping to End Addiction Long-term (HEAL) initiative to speed scientific solutions to the national opioid public health crisis. The NIH HEAL Initiative will bolster research across NIH to (1) improve treatment for opioid misuse and addiction and (2) enhance pain management. More information about the HEAL Initiative is available at https://www.nih.gov/research-training/medical-research-initiatives/heal-initiative.

NCATS refers to participants in the NCATS ASPIRE Design Challenges as “innovators,” because all solutions will require highly innovative approaches to achieve success. Innovators should clearly state how and why the proposed solution would provide significant advances over currently available tools. Innovators may choose to compete in one or more individual Challenges to address a single area (Challenges 1-4) or propose a combined solution for at least two Challenge areas (Challenge 5).

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Summary of NCATS ASPIRE Challenge 3: Predictive Algorithms for Translational Innovation in Pain, Opioid Use Disorder and Overdose

predictive algorithms

Challenge 3 aims to address the need for open source, advanced machine learning algorithms that would facilitate the discovery of novel, efficacious and non-addictive analgesics and/or treatments for drug abuse. This Challenge requires submission of only a detailed description of the design of the algorithms, not the final working versions. While initially the innovators can use their own training sets to demonstrate functionality of an algorithm, in the envisioned follow-on Reduction-to-Practice stage, the algorithm will be expected to incorporate and analyze data generated from Challenges 1, 2 and 4.

Evaluation criteria that reviewers will be asked to address are specified below.

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Dates and Deadlines

Solutions must be submitted to Challenge.gov by NOON Eastern Time on May 31, 2019. 

The Challenge begins: December 31, 2018 
Submission period: December 31, 2018-May 31, 2019
Judging period: June 17, 2019-August 2, 2019
Winners announced: August 2019

For further information send an email to NCATSASPIREChallenge@mail.nih.gov

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The IC’s Statutory Authority to Conduct the Challenge 

The general purpose of NCATS is to coordinate and develop resources that leverage basic research in support of translational science and to develop partnerships and work cooperatively to foster synergy in ways that do not create duplication, redundancy and competition with industry activities (42 USC 287(a)). In order to fulfill its mission, NCATS supports projects that will transform the translational process so that new treatments and cures for diseases can be delivered to patients faster by understanding the translational process in order to create a basis for more science-driven, predictive and effective intervention development for the prevention and treatment of all diseases. NCATS is also conducting this Challenge under the America Creating Opportunities to Meaningfully Promote Excellence in Technology, Education, and Science (COMPETES) Reauthorization Act of 2010, 15 U.S.C. 3719. In line with these authorities, this Challenge(s) will lead to innovative designs for developing technology to revolutionize discovery, development and pre-clinical testing of new and safer treatments of pain, opioid use disorder (OUD), and overdose; the result will be generalizable tools that will be widely available to fill longstanding gaps that have impeded the marriage of basic and translational sciences.

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Subject of the Challenge Competition

Challenge 3Predictive Algorithms for Translational Innovation in Pain, Opioid Use Disorder and Overdose. This Challenge aims to reward and spur innovative solutions to the development of machine learning algorithms that would aid the discovery of novel analgesics and/or treatments for opioid addiction and overdoses. For example, an algorithm can be developed to identify side groups and/or include ratio of bond types or atom types in a molecule in order to identify signatures that are less likely to trigger addiction. This Challenge requires submission of only a detailed description of the design of the algorithms, not the final working versions. The ultimate goal is to utilize the data from Challenge 1 and Challenge 2 during the envisioned Reduction-to-Practice Challenge to provide proof-of-concept and design, synthesize, optimize and test novel compounds that are less likely to trigger addiction or are able to treat addiction/overdose. Optimized novel small-molecule leads would be tested for their bioactivity using physiologically relevant models developed in Challenge 4 in order to provide proof-of-concept for therapeutic hypotheses to treat pain, addiction and overdose.

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Concurrent Companion NCATS ASPIRE Design Challenges

NCATS has recently explored the development of A Specialized Platform for Innovative Research Exploration (ASPIRE) to aid in the discovery and development of novel and effective treatments while at the same time making the process faster and more cost-effective. The NCATS ASPIRE Program aims to develop and integrate automated synthetic chemistry, biological screening and artificial intelligence approaches in order to significantly advance our understanding of the relationship between chemical and biological space and enable further access into biologically relevant chemical space. The platform will utilize currently available knowledge to develop innovative algorithms and predict and synthetize novel structures capable of interacting with specific targets; enable small-scale synthesis of the predicted molecules; and incorporate in-line, rapid biological testing of the molecules. Any new data obtained through this process would then be fed back into the system to further improve design, synthesis and biological characteristics of molecules.

Over 25 million people in the United States experience pain every day (2012 National Health Interview Survey data) and need safe, addiction-free treatments to alleviate their suffering. This clinical demand is of tremendous importance given that overprescribing of opioids for managing acute and chronic pain has fueled the current epidemic of opioid use disorder and overdose deaths, and the effectiveness of opioids for long-term pain management is being questioned. Safe, effective and non-addictive drugs (small molecules and biologics) to treat pain, mitigate addiction and reverse overdose are key to addressing the opioid crisis. Given failures and limitations of previous drug development efforts, drugs that recognize novel targets, have novel structures and can be identified in human-based, physiologically relevant in vitro systems are needed. To advance the NCATS ASPIRE Program and reward and spur innovative solutions to the development of new drugs for pain, addiction and overdose, NCATS is issuing this Challenge and concurrent companion Challenges to highly collaborative innovators interested in designing novel approaches that would lead to efficacious and non-addictive pain treatments and/or novel treatments for addiction and overdose.

The ultimate goal of the NCATS ASPIRE Program is development of a platform that a wide spectrum of scientists can use to advance their translational science relevant to development and pre-clinical testing of new and safer treatments of pain, opioid use disorder (OUD) and overdose. Furthermore, it is essential that the approaches described and proposed here are applicable to any translational problem.

Challenge 1: Integrated Chemistry Database for Translational Innovation in Pain, Opioid Use Disorder and Overdose rewards and spurs innovative solutions to the design of an open-source, controlled-access database that incorporates all currently available chemical, biological and clinical data of known opioid- and non-opioid-based analgesics, drugs of abuse and drugs used to treat drug abuse.

Challenge 2: Electronic Synthetic Chemistry Portal for Translational Innovation in Pain, Opioid Use Disorder and Overdose rewards and spurs innovative solutions to the design of a next-generation open-source electronic lab notebook (eLN) that collects, organizes and analyzes data relevant to the chemical synthesis and analyses of known opioid- and non-opioid-based analgesics, drugs of abuse and molecules used to treat drug abuse into an electronic laboratory knowledge portal for synthetic chemistry (electronic synthetic chemistry portal; eSCP).

Challenge 4: Biological Assays for Translational Innovation in Pain, Opioid Use Disorder and Overdose rewards and spurs innovative solutions to the design of novel, physiologically relevant biological assays that accurately replicate the safety profile and effectiveness of existing drugs to treat addiction and/or overdose and that can be reliably used in predictive risk assessments of new analgesics or drugs to treat addiction and/or overdose and/or be able to anticipate the degree of addictiveness of an analgesic prior to clinical testing.

Challenge 5: Integrated Solution for Translational Innovation in Pain, Opioid Use Disorder and Overdose rewards and spurs the design of innovative, comprehensive solutions to the opioid crisis through innovative approaches that integrate solutions to at least two Challenge areas (Challenges 1-4: Integrated Chemistry Database, Electronic Synthetic Chemistry Portal, Predictive Algorithms and Biological Assays, respectively) into a single platform.

Note: Each component of Challenge 5 (above) is also available as an individual Challenge at Challenge.gov.

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Registration Process for Innovators

Innovators may access the registration and submission platform in one of the following ways:

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The Prize

Amount of the Prize; Award-Approving Official. 

The total prize purse is $500,000. Up to five (5) winners will be selected. NIH reserves the right to cancel, suspend and/or modify this Challenge at any time through amendment to this notice. In addition, NIH reserves the right to not award any prizes if no solutions are deemed worthy. The Award Approving Official will be Christopher P. Austin, M.D., Director of the National Center for Advancing Translational Sciences (NCATS).

Payment of the Prize. Prizes awarded under this competition will be paid by electronic funds transfer and may be subject to federal income taxes. HHS/NIH will comply with the Internal Revenue Service withholding and reporting requirements, where applicable.

Matching Requirement. A for-profit private entity solver (innovator) receiving a prize under this Challenge must match funds or provide documented in-kind contributions at a rate of not less than 50% of the total federally awarded amount, as stipulated by Public Law 115-141, the Consolidated Appropriations Act of 2018. Such a winner(s) will be required to demonstrate that matching funds and/or in-kind contributions were committed to achieve the winning solution. Such a winner(s) must identify the source and amount of funds used to meet the matching requirement or describe how the value for in-kind contributions was determined.

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Evaluation and Winner Selection

Basis upon Which Winners Will Be Selected. A panel of federal and non-federal reviewers, with expertise directly relevant to the Challenge, will evaluate the solutions based on feasibility and ability to achieve the criteria listed below. The solutions and evaluation statements from the technical panel will then be reviewed by federal employees serving as judges, who will select the Challenge winners, subject to the final decision by the Award Approving Official. The NCATS will provide feedback from the technical experts and judges to the winners and non-winners on their respective submissions.

The points assigned to each set of evaluation criteria are guidelines from NCATS to suggest which scientific milestones are of emphasis and interest to the Center. All winners are highly encouraged to participate in future NCATS ASPIRE Reduction-to-Practice Challenges that NCATS is planning. 

Only complete submissions will be reviewed.

Submission Requirements and Template

Instructions for submission: Please format the proposal using the Submission Template and submit it to Challenge.gov as a PDF. Brief instructions on the submission process can be found below. Detailed instructions are provided in the submission template.

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Basis upon Which Submissions Will Be Evaluated

Challenge 3. Predictive Algorithms for Translational Innovation in Pain, Opioid Use Disorder and Overdose. This Challenge aims to reward and spur innovative solutions to the development machine learning algorithms that would aid the discovery of novel analgesics and/or treatments for opioid addiction and overdoses. For example, an algorithm can be developed to identify side groups and/or include ratio of bond types or atom types in a molecule in order to identify signatures that are less likely to trigger addiction. The ultimate goal is to utilize the data from Challenge 1 and Challenge 2 during the envisioned Reduction-to-Practice Challenge to provide proof-of-concept and design, synthesize, optimize and test novel compounds that are less likely to trigger addiction or are able to treat addiction/overdose. Optimized novel small-molecule leads would be tested for their bioactivity using physiologically relevant models developed in Challenge 4 in order to provide proof-of-concept for therapeutic hypotheses to treat pain, addiction and overdose.

Judging criteria:

Evaluation Criterion 1: Impact and Innovation (20 points)

  • Did the team identify potential roadblocks and suggest additional expertise that would be utilized to facilitate resolution of roadblocks to implementation?
  • Given that innovation is considered using a groundbreaking or paradigm-shifting approach or using existing approaches in an innovative way, to what degree is the proposed design innovative, creative and original?
  • To what extent is the proposed approach feasible, and how high is its likelihood to succeed?
  • Has the innovator or team of innovators demonstrated that appropriate expertise was utilized during development of the design?
  • Have the innovators established their own initial training datasets that can be used to demonstrate the algorithms’ functionality on the set?
  • Does the training data set include structurally diverse compounds?
  • To what extent have the innovators demonstrated why/how the proposed solution can outperform existing algorithms?
  • How well has the proposed solution demonstrated its ability to provide critical information necessary for the development of novel treatments and therapies for pain, drug addiction and/or overdose?

Evaluation Criterion 2: Algorithm Design Functionality and Implementation (20 points)

  • How well are the algorithms documented for completing a task on a training set and making predictions on a new set of compounds? (Are the steps precisely stated)?
  • To what extent are the algorithms implemented with open source codes/packages or commercial software packages?
  • Have the innovators designed a web portal or tool/platform that is accessible to research community to run the proposed algorithms and generate predictions on their compounds of interest?
  • How well have the innovators explained how their algorithms meet the criteria of precision, uniqueness, finiteness, definiteness, input, output and effectiveness?
  • How well can the algorithms identify structural and/or functional similarities in a diverse set of molecules?
  • How well can the algorithms identify specific signatures that may be associated with addiction?
  • How well can the algorithms compare the mechanism of action between multiple drugs and identify structural/functional similarities between them?
  • How successful are the algorithms in identifying structurally diverse drugs with similar pharmacological effect?
  • To what degree can the algorithms provide additional context for drug activity that can be used to identify or anticipate off-target effects?

Evaluation Criterion 3: Record of Innovation (10 points)

  • How well have the innovators demonstrated experience with creating solutions that:
    • Connect across multiple computational modeling and simulation tools and frameworks;
    • Evaluate and adjust models based on new data, as the data becomes available; and
    • Evaluate and adjust models based on the successes or failures of predicting phenomena observed in humans and, where biologically justified, in animals?

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